Regenerative Medicine Market Present Scenario And The Growth Prospects 2030 – openPR

The World Health Organization (WHO) estimates that non-communicable diseases (NCDs), such as cardiovascular diseases (CVDs), cancer, diabetes, and respiratory diseases, account for around 71% of global deaths, annually. As per the organization, CVDs, cancer, respiratory diseases, and diabetes cause 17.9 million, 9.3 million, 4.1 million, and 1.5 million human deaths, respectively, each year. Furthermore, the United Nations (UN) states that approximately 3,000-5,000 children are born with chromosome disorder, globally. Thus, the surging prevalence of chronic ailments and genetic disorders is creating a huge requirement for regenerative medicines, worldwide.

Moreover, the rising technological advancements in the medical industry will also help the regenerative medicine market progress at a healthy CAGR, of 16.3%, during 2020-2030. According to P&S Intelligence, the market was valued at $8,186.9 million in 2019 and it is expected to generate $39,012.0 million revenue by 2030. Major biotech and pharma companies are making hefty investments in technological developments to provide more effective gene therapies. The advent of 3D bioprinting is one of the prime examples of technological advancements in regenerative medicine.

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At present, governments across the world are focusing on implementing policy changes to accelerate research activities in the establishment of regenerative medicine as a novel medical discipline. For instance, the Regenerative Medicine Innovation Project (RMIP), established under the 21st Century Cures Act, aims to facilitate clinical research in the field of adult stem cells in the U.S. Under this initiative, the National Institutes of Health (NIH) works in coordination with the U.S. Food and Drug Administration (FDA).

Stem and somatic cell therapies, viral and non-viral gene therapies, and cell-based tissue engineered products are being offered by Smith & Nephew plc, Allergan plc, Integra LifeSciences Holdings Corporation, Organogenesis Holdings Inc., Stryker Corporation, Takeda Pharmaceutical Company Limited, Novartis AG, Vericel Corporation, and Amgen Inc. for patients suffering from chronic ailments and genetic disorders. In the coming years, cell therapy will be adopted at the highest rate due to the soaring number of clinical trials including several cell therapy techniques.

Currently, companies offering regenerative medicines are engaging in product launches and approvals to cater to a greater number of patients. For instance, in October 2020, Novartis AG received the marketing authorization for the Foundation for Biomedical Research and Innovation (FBRI) at Kobe from the Ministry of Health, Labour and Welfare of Japan. With this approval, the company will produce and supply commercial Kymriah (tisagenlecleucel) in the nation. This move makes FBRI the first and only approved commercial production unit for chimeric antigen receptor T (CAR-T) cell therapy in Asia.

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Geographically, North America led the regenerative medicine market in the recent past, and it is also expected to maintain its position in the foreseeable future. This can be owed to the increasing advancements in the field of tissue engineering, rising number of stem cell banks, escalating healthcare spending, and surging reliance on stem cell therapy for chronic disease treatment. Whereas, Asia-Pacific (APAC) will adopt regenerative medicines at the highest rate in the upcoming years, due to the rising prevalence of chronic diseases, flourishing medical tourism industry, and escalating public and private funding in research organizations.

Thus, the surging incidence of chronic diseases and genetic disorders and the increasing technological advancements in the medical sector will fuel the administration of regenerative medicines, worldwide.

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P&S Intelligence provides market research and consulting services to a vast array of industries across the world. As an enterprising research and consulting company, P&S believes in providing thorough insights on the ever-changing market scenario, to empower companies to make informed decisions and base their business strategies with astuteness. P&S keeps the interest of its clients at heart, which is why the insights we provide are both honest and accurate. Our long list of satisfied clients includes entry-level firms as well as multi-million-dollar businesses and government agencies.

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The combined signatures of the tumour microenvironment and … – Nature.com

Landscape of the genetic variation of NMRGs in GC

Figure1 presents the workflow of the study. Herein, 97 NMRGs were evaluated to explore their roles in GC. First, 97 NMRGs in GC were examined for copy number variations (CNVs) and somatic mutations (Supplementary Fig.1A), with mutations identified in 161 of the 433 samples (37.18%). DPYD and XDH showed the highest mutation rate (5%) followed by CAD, AMPD3 and AK9 (4%). Furthermore, ENTPD8, ENTPD2, DNPH1, UCK1AK8 and AK1 exhibited higher frequencies of CNV amplification, whereas DCTD, IMPDH1, CDA, DPYD and AK6 exhibited higher probabilities of CNV deletions (Supplementary Fig.1B). Supplementary Fig.1C shows the chromosomal positions of the aforementioned CNVs. To determine the relationship between genetic variation and NMRG expression, we also compared the expression levels of 97 NMRGs between normal and tumour samples. A total of 77 genes were differentially expressed (Supplementary Fig.1D).

The flow chart of the study design.

To further explore the potential association between NM and GC, fresh serum samples, consisting of 33 patients with GC and 27 healthy volunteers, were collected for metabolomic analysis. Using the limma package in R, a total of 18 differentially expressed nucleotide metabolites were identified. Among them, 1-Methyladenosine, 1-Methylguanosine, 7-Methylguanine, Allantoic acid, Cytidine, Dihydrothymine, Inosine, N2, N2-Dimethylguanosine, Pseudouridine, Uracil, Ureidopropionic acid, Uric acid and Xanthine were downregulated, whereas 5-Methylthioadenosine, 5-Methyluridine (Ribothymidine), Allantoin, N6-Methyladenosine and Uridine were upregulated in GC samples. These findings highlighted the metabolic reprogramming of NM in patients with GC (Supplementary Fig.2).

To construct an NM prognostic model, we first performed a univariate Cox survival analysis on 77 differentially expressed NMRGs, of which six were statistically significant (Supplementary Table S3). Additionally, the prognostic significance of the six genes was validated using KM analysis (Supplementary Fig.3A). Furthermore, a heatmap of the expression of the six genes in tumour and normal tissues was also drawn (Fig.2A). We then subjected the six genes to multivariate cox analysis (Fig.2B) and correlation coefficients were calculated to construct a model (Supplementary Table S4). The NM score was calculated for each patient, and the patients were classified into high and low score groups based on the median value. The KM curve showed that the high-risk patients had a worse prognosis (Fig.2C). Regarding the TME prognostic model, a high infiltration of activated CD4 memory-activated T cells, CD8 T cells and activated dendritic cells (DCs) were observed to be associated with a better prognosis for patients with GC (Supplementary Fig.3B). Similarly, these cells were subjected to multivariate cox analysis (Fig.2D) and correlation coefficients were calculated to construct a model (Supplementary Table S5). The KM curve showed that high-TME score samples had a better survival prognosis than those with low-TME scores (Fig.2E). GSEA revealed that the high NM score group was mainly enriched in cancer-related and classical oncogenic pathways, while the high TME score group was mainly enriched in immune-related pathways. (Supplementary Fig.3C,D).

Construction of the NM- and TME-related prognostic model. (A) Expression levels of the six model genes. (B) Multivariate cox regression analysis of NM model genes. (C) KaplanMeier (KM) curves of NM-related prognostic model. (D) Multivariate cox regression analysis of three TME cells. (E) KM curves of TME-related prognostic model. NM nucleotide metabolism, TME tumour microenvironment.

First, we investigated the correlation between the six NM model genes and the three TME cells. We found that T cells CD8 were negatively correlated with UPP1, ENTPD2, NT5E and positively correlated with DPYS and AK1; T cells CD4 memory activated were negatively correlated with AK5, ENTPD2, NT5E, DPYS, AK1; dendritic cells were negatively correlated with AK5, ENTPD2, DPYS, and positively correlated with UPP1 (Fig.3A). To further explore their association, we downloaded single-cell data from the GEO database, comprising 10 GC samples. The clustering and annotated results are presented in Fig.3B. Subsequently, we calculated the NM scores in different cell types and found that the NM scores were significantly higher in monocytes and endothelial cells than in B cells, T cells, CD8+ T cells, epithelial, macrophages, Tregs and mast cells (Fig.3C,D). Based on the NM score, monocytes and endothelial cells were divided into low NM score, medium NM score and high NM score monocytes and endothelial cells for cell communication analysis. The monocytes and endothelial cells with low NM scores had more abundant communication with other immune cells (Fig.3EH). Therefore, low NM scores could have a synergistic effect with high TME scores and combining the NM model with the TME model may be a feasible method.

Correlation between the NM scores and TME cells. (A) The correlation between NMRGs and TME cells. (B) t-SNE plot of 10 gastric cancer samples. (C,D) Distribution of NM scores in different cell types. (E,F) The inferred signalling networks between different cell clusters. The significantly related ligandreceptor interactions of (G) NMlowMonocytes and (H) NMlowEndothelial cells. NM nucleotide metabolism, TME tumour microenvironment, NMRGs nucleotide metabolism-related genes.

Next, we constructed the NM-TME classifier by combining the NM and TME scores. It divided patients with GC into four categories: NMhigh/TMEhigh, NMhigh/TMElow, NMlow/TMEhigh and NMlow/TMElow. Survival analysis revealed that the NMhigh/TMElow group had a poorer prognosis while the NMlow/TMEhigh group had a better prognosis among the groups (Fig.4A). Patients in the NMhigh/TME high and NMlow/TME low subgroups showed less divergent prognoses. As a result, we combined them to form a mixed subgroup (Fig.4B). Additionally, the area under the curve (AUC) values of the NM-TME classifier were 0.732, 0.708, 0.702 and 0.807 for 1, 3, 5 and 7years, respectively (Fig.4C), indicating that the NM-TME classifier plays a significant role in the survival prediction of patients with GC.

Construction of the NM-TME classifier and functional enrichment analysis. (A) Survival analysis of the four subgroups was obtained based on the NM-TME classifier. (B) Survival analysis after merging the NMlow/TMElow and NMhigh/TMEhigh subgroups. (C) Receiver operating characteristic (ROC) curve of the NM-TME classifier. (D) Functional enrichment analysis of the three subgroups was obtained based on the NM-TME classifier. NM nucleotide metabolism, TME tumour microenvironment.

Furthermore, we also verified the prognostic significance of the NM-TME classifier in the GEO cohort, which revealed significant prognostic differences between the groups (Supplementary Fig.4A). Moreover, the evaluation of the predictive performance of the classifier under different clinical features in the TCGA cohort revealed good predictive performance (Supplementary Fig.4B).

Functional enrichment of the three groups revealed that the NMhigh/TMElow group was mainly enriched in the regulation of the olefinic compound metabolic process, endothelial cell differentiation and stem cell proliferation, while the NMlow/TMEhigh was majorly positively associated with the positive regulation of T cell migration and negatively associated with the canonical Wnt signalling pathway (Fig.4D).

Furthermore, WGCNA identified four modules (Fig.5A,B). Among them, the turquoise module was most relevant and opposite to each other for the NMlow/TMEhigh and NMhigh/TMElow groups. Therefore, the turquoise module gene could be associated with significantly different prognoses between the NMlow/TMEhigh and NMhigh/TMElow groups. Using the Metascape database, enrichment analysis of these genes revealed that they were mainly enriched in vasculature development, NABA core matrisome and extracellular matrix organization (Fig.5C).

Exploring key module eigengenes associated with the NMlow/TMEhigh and NMlow/TMElow groups using weighted gene co-expression network analysis. (A) Evaluation of the scale-free fit index for differing soft-thresholding powers () and examination of the connectivity of various soft-thresholding powers. (B) A heatmap depicts the association between module eigengenes and various subgroups. (C) Functional enrichment analysis of key module eigengenes. NM nucleotide metabolism, TME tumour microenvironment.

First, we compared the abundance of immune cell infiltration between the different groups. The immune cell infiltration was more abundant in the NMlow/TMEhigh group, especially CD8 T cells, Th1 cells, NK cells, CD4 T cells and macrophages (Fig.6A). Notably, the better prognosis in the NMlow/TMEhigh group could be attributed to the abundant immune cell infiltration. Meanwhile, we also explored whether the expression of common ICGs differed between the groups. Most ICGs were differentially expressed between the groups, with high expression observed in the NMlow/TMEhigh group (Fig.6B). These differentially expressed ICGs could be potential therapeutic targets. Additionally, it also suggests that NMlow/TMEhigh patients may benefit more from immune checkpoint blockade (ICB) therapy. HLA is a polygenic and polymorphic complex involved in antigen presentation43. Figure6C shows that HLA-B, HLA-C, HLA-F and HLA-DOB were expressed the highest in the NMlow/TMEhigh group.

Immune status of different subgroups based on the NM-TME classifier. (A) Differences in immune cell infiltration. (B) Differences in ICGs. (C) Differences in antigen presentation-related genes in different subgroups. NM nucleotide metabolism, TME tumour microenvironment, ICG immune checkpoint gene.

Numerous studies have demonstrated the association between somatic mutations in tumour genomes and the response to immunotherapy44. We therefore examined the TMB distributions among the various groups based on the NM-TME classifier. The NMlow/TMEhigh group had a higher TMB, while the NMhigh/TMElow group had a lower TMB, indicating that the NMlow/TMEhigh group may benefit more from immunotherapy (Fig.7A). Additionally, the NMhigh/TMElow/TMBhigh group had a lower prognosis than patients in the other groups (Fig.7B). Figure7C,D display the top 20 genes with high mutation frequencies in the NMlow/TMEhigh and NMhigh/TMElow groups.

TMB analysis. (A) Comparison of TMB among the defined subgroups. (B) Survival analysis based on the NM-TME classifier and TMB. The top 20 mutation genes of the (C) NMhigh/TMElow and (D) NMlow/TMEhigh groups. NM nucleotide metabolism, TME tumour microenvironment, TMB tumour mutation burden.

Considering that drugs targeting PD-1 and CTLA-4 have recently received approval for the treatment of several cancers, we evaluated whether the NM-TME classifier could predict patients reactions to immunotherapy. The patients in the NMlow/TMEhigh group were observed to have a better response rate to immunotherapy than the other two groups (Fig.8A). Microsatellite instability-high (MSI-H) is a potential predictor of immunotherapy response targeting PD-1 or its ligand PD-L145. Accordingly, the proportion of MSI-H in the NMlow/TMEhigh group was higher than that in the other two groups (Fig.8B). Additionally, we investigated the relationship between the NM-TME classifier and IPS in patients with GC to predict the response to ICIs. Figure8CF presents the differences in the results of CTLA-4/PD-1 inhibitor treatment between the NMlow/TMEhigh and Nmhigh/TMElow groups. The NMlow/TMEhigh group has higher IPS scores, implying more immunogenicity in the NMlow/TMEhigh group. Furthermore, we performed a difference analysis between the immunotherapy-responsive and non-responsive groups and also the NMlow/TMEhigh and NMhigh/TMElow groups. DEGs were then analysed using the Proteomaps 2.0 database46. Notably, the pattern of proteomap in the NMlow/TMEhigh group and immunotherapy-responsive groups were similar (Fig.8G,H). These findings suggest that the NM-TME classifier can be used to predict patients responses to immunotherapy.

The role of NM-TME classifier in immunotherapy. (A) Proportion of response to immunotherapy in different groups. (B) Proportion of MSI in different groups. (CF) Comparison of the relative distribution of IPS across groups with high NM/low TME and low NM/high TME. Functional analysis in the NMlow/TMEhigh group (G) and responder of patients under immunotherapy (H) illustrated using Proteomaps. A little polygon represents a unique KEGG pathway. NM nucleotide metabolism, TME tumour microenvironment, MSI microsatellite instability, IPS immunophenoscore.

Given that targeted therapy is an effective approach in the treatment of GC, it has important clinical applications and prospects. We, therefore, investigated whether the NM-TME classifier could predict drug sensitivity in patients with GC. The NMhigh/TMElow group benefited more from Imatinib, Midostaurin and OSI-906 (Linsitinib), while those in the NMlow/TMEhigh group benefited more from Paclitaxel, Methotrexate and Camptothecin (Supplementary Fig.5AF).

Univariate and multivariate Cox regression analyses indicated that the NM-TME classifier was an independent predictor of prognosis with the highest hazard ratio (HR) (Fig.9A,B). Following this, the NM-TME classifier and clinical features were combined to construct a nomogram. To predict the survival of patients with GC over 1 to 5years, the values of each variable can be added to obtain the total score (Fig.9C). Moreover, the AUC values of the nomogram for 1-, 3- and 5-year OS were 0.826, 0.841 and 0.822, respectively (Fig.9D).

Construction of a nomogram. (A,B) Forest map of univariable and multivariable Cox regression in the test cohort. (C) Nomogram based on the NM-TME classifiers and clinical features. (D) Receiver operating characteristic (ROC) curves of the nomogram model in predicting the 15years survival rate. NM nucleotide metabolism, TME tumour microenvironment.

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Centers for Disease Control and Prevention. Past Seasons Vaccine Effectiveness Estimates, https://www.cdc.gov/flu/vaccines-work/past-seasons-estimates.html (2022). Accessed 10 March 2022.

Centers for Disease Control and Prevention. Pandemic influenzapast pandemics, https://www.cdc.gov/flu/pandemic-resources/basics/past-pandemics.html (2022). Accessed 10 March 2022.

Erbelding, E. J. et al. A universal influenza vaccine: the strategic plan for the National Institute of Allergy and Infectious Diseases. J. Infect. Dis. 218, 347354 (2018).

Article CAS PubMed PubMed Central Google Scholar

Giles, B. M. & Ross, T. M. A computationally optimized broadly reactive antigen (COBRA) based H5N1 VLP vaccine elicits broadly reactive antibodies in mice and ferrets. Vaccine 29, 30433054 (2011).

Article CAS PubMed PubMed Central Google Scholar

Giles, B. M., Bissel, S. J., Dealmeida, D. R., Wiley, C. A. & Ross, T. M. Antibody breadth and protective efficacy are increased by vaccination with computationally optimized hemagglutinin but not with polyvalent hemagglutinin-based H5N1 virus-like particle vaccines. Clin. Vaccin. Immunol. 19, 128139 (2012).

Article CAS Google Scholar

Giles, B. M. et al. A computationally optimized hemagglutinin virus-like particle vaccine elicits broadly reactive antibodies that protect nonhuman primates from H5N1 infection. J. Infect. Dis. 205, 15621570 (2012).

Article CAS PubMed PubMed Central Google Scholar

Sautto, G. A. et al. Elicitation of broadly protective antibodies following infection with influenza viruses expressing H1N1 computationally optimized broadly reactive hemagglutinin antigens. Immunohorizons 2, 226237 (2018).

Article CAS PubMed Google Scholar

Sautto, G. A., Ecker, J. W. & Ross, T. M. An H1N1 computationally optimized broadly reactive antigen elicits a neutralizing antibody response against an emerging human-infecting eurasian avian-like swine influenza virus. J. Virol. 95, e0242120 (2021).

Article PubMed Google Scholar

Ross, T. M. et al. A computationally designed H5 antigen shows immunological breadth of coverage and protects against drifting avian strains. Vaccine 37, 23692376 (2019).

Article CAS PubMed Google Scholar

Carter, D. M. et al. Design and characterization of a computationally optimized broadly reactive hemagglutinin vaccine for H1N1 influenza viruses. J. Virol. 90, 47204734 (2016).

Article CAS PubMed PubMed Central Google Scholar

Sautto, G. A. et al. A computationally optimized broadly reactive antigen subtype-specific influenza vaccine strategy elicits unique potent broadly neutralizing antibodies against hemagglutinin. J. Immunol. 204, 375385 (2020).

Article CAS PubMed Google Scholar

Skarlupka, A. L. et al. Computationally optimized broadly reactive vaccine based upon swine H1N1 influenza hemagglutinin sequences protects against both swine and human isolated viruses. Hum. Vaccin Immunother. 15, 20132029 (2019).

Article PubMed PubMed Central Google Scholar

Huang, Y., Owino, S. O., Crevar, C. J., Carter, D. M. & Ross, T. M. N-linked glycans and K147 residue on hemagglutinin synergize to elicit broadly reactive H1N1 influenza virus antibodies. J. Virol. 94, https://doi.org/10.1128/JVI.01432-19 (2020).

Brownlee, G. G. & Fodor, E. The predicted antigenicity of the haemagglutinin of the 1918 Spanish influenza pandemic suggests an avian origin. Philos. Trans. R. Soc. Lond. B Biol. Sci. 356, 18711876 (2001).

Article CAS PubMed PubMed Central Google Scholar

Caton, A. J., Brownlee, G. G., Yewdell, J. W. & Gerhard, W. The antigenic structure of the influenza virus A/PR/8/34 hemagglutinin (H1 subtype). Cell 31, 417427 (1982).

Ekiert, D. C. et al. Antibody recognition of a highly conserved influenza virus epitope. Science 324, 246251 (2009).

Article CAS PubMed PubMed Central Google Scholar

Guthmiller, J. J. et al. Broadly neutralizing antibodies target a haemagglutinin anchor epitope. Nature 602, 314320 (2022).

Article CAS PubMed Google Scholar

Sui, J. et al. Structural and functional bases for broad-spectrum neutralization of avian and human influenza A viruses. Nat. Struct. Mol. Biol. 16, 265273 (2009).

Article CAS PubMed PubMed Central Google Scholar

Nagashima, K. et al. The pre-existing human antibody repertoire to computationally optimized influenza H1 hemagglutinin vaccines. J. Immunol. 209, 515 (2022).

Article CAS PubMed Google Scholar

Bajic, G. & Harrison, S. C. Antibodies that engage the hemagglutinin receptor-binding site of influenza B viruses. ACS Infect. Dis. 7, 15 (2021).

Article CAS PubMed Google Scholar

Ekiert, D. C. et al. Cross-neutralization of influenza A viruses mediated by a single antibody loop. Nature 489, 526532 (2012).

Article CAS PubMed PubMed Central Google Scholar

Guthmiller, J. J. et al. First exposure to the pandemic H1N1 virus induced broadly neutralizing antibodies targeting hemagglutinin head epitopes. Sci. Transl. Med. 13, https://doi.org/10.1126/scitranslmed.abg4535 (2021).

Krause, J. C. et al. A broadly neutralizing human monoclonal antibody that recognizes a conserved, novel epitope on the globular head of the influenza H1N1 virus hemagglutinin. J. Virol. 85, 1090510908 (2011).

Article CAS PubMed PubMed Central Google Scholar

Lee, P. S. et al. Receptor mimicry by antibody F045-092 facilitates universal binding to the H3 subtype of influenza virus. Nat. Commun. 5, 3614 (2014).

Article PubMed Google Scholar

Lee, P. S. et al. Heterosubtypic antibody recognition of the influenza virus hemagglutinin receptor binding site enhanced by avidity. Proc. Natl Acad. Sci. USA 109, 1704017045 (2012).

Article CAS PubMed PubMed Central Google Scholar

McCarthy, K. R. et al. Memory B cells that cross-react with Group 1 and Group 2 Influenza A viruses are abundant in adult human repertoires. Immunity 48, 174184 e179 (2018).

Article CAS PubMed PubMed Central Google Scholar

Schmidt, A. G. et al. Viral receptor-binding site antibodies with diverse germline origins. Cell 161, 10261034 (2015).

Article CAS PubMed PubMed Central Google Scholar

Tsibane, T. et al. Influenza human monoclonal antibody 1F1 interacts with three major antigenic sites and residues mediating human receptor specificity in H1N1 viruses. PLoS Pathog. 8, e1003067 (2012).

Article CAS PubMed PubMed Central Google Scholar

Whittle, J. R. et al. Broadly neutralizing human antibody that recognizes the receptor-binding pocket of influenza virus hemagglutinin. Proc. Natl Acad. Sci. USA 108, 1421614221 (2011).

Article CAS PubMed PubMed Central Google Scholar

Winarski, K. L. et al. Vaccine-elicited antibody that neutralizes H5N1 influenza and variants binds the receptor site and polymorphic sites. Proc. Natl Acad. Sci. USA 112, 93469351 (2015).

Article CAS PubMed PubMed Central Google Scholar

Xu, R. et al. A recurring motif for antibody recognition of the receptor-binding site of influenza hemagglutinin. Nat. Struct. Mol. Biol. 20, 363370 (2013).

Article CAS PubMed PubMed Central Google Scholar

Bullard, B. L. & Weaver, E. A. Strategies targeting hemagglutinin as a universal influenza vaccine. Vaccines 9, https://doi.org/10.3390/vaccines9030257 (2021).

Gao, D. et al. Membrane-anchored stalk domain of influenza HA enhanced immune responses in mice. Micro. Pathog. 113, 421426 (2017).

Article CAS Google Scholar

Nachbagauer, R. et al. A chimeric hemagglutinin-based universal influenza virus vaccine approach induces broad and long-lasting immunity in a randomized, placebo-controlled phase I trial. Nat. Med. 27, 106114 (2021).

Article CAS PubMed Google Scholar

Nagashima, K. A. & Mousa, J. J. Next-generation influenza HA immunogens and adjuvants in pursuit of a broadly protective vaccine. Viruses 13, https://doi.org/10.3390/v13040546 (2021).

Wohlbold, T. J. et al. Vaccination with soluble headless hemagglutinin protects mice from challenge with divergent influenza viruses. Vaccine 33, 33143321 (2015).

Article CAS PubMed PubMed Central Google Scholar

Eggink, D., Goff, P. H. & Palese, P. Guiding the immune response against influenza virus hemagglutinin toward the conserved stalk domain by hyperglycosylation of the globular head domain. J. Virol. 88, 699704 (2014).

Article PubMed PubMed Central Google Scholar

Lin, S. C., Lin, Y. F., Chong, P. & Wu, S. C. Broader neutralizing antibodies against H5N1 viruses using prime-boost immunization of hyperglycosylated hemagglutinin DNA and virus-like particles. PLoS One 7, e39075 (2012).

Article CAS PubMed PubMed Central Google Scholar

Thornlow, D. N. et al. Altering the immunogenicity of hemagglutinin immunogens by hyperglycosylation and disulfide stabilization. Front Immunol. 12, 737973 (2021).

Article CAS PubMed PubMed Central Google Scholar

Medina, R. A. et al. Glycosylations in the globular head of the hemagglutinin protein modulate the virulence and antigenic properties of the H1N1 influenza viruses. Sci. Transl. Med. 5, 187ra170 (2013).

Article Google Scholar

Nunez, I. A. & Ross, T. M. Human COBRA 2 vaccine contains two major epitopes that are responsible for eliciting neutralizing antibody responses against heterologous clades of viruses. Vaccine 38, 830839 (2020).

Article CAS PubMed Google Scholar

Zhang, Y. et al. Influenza research database: an integrated bioinformatics resource for influenza virus research. Nucleic Acids Res. 45, D466D474 (2017).

Article CAS PubMed Google Scholar

Das, S. R. et al. Fitness costs limit influenza A virus hemagglutinin glycosylation as an immune evasion strategy. Proc. Natl Acad. Sci. USA 108, E1417E1422 (2011).

Article CAS PubMed PubMed Central Google Scholar

Wang, C. C. et al. Glycans on influenza hemagglutinin affect receptor binding and immune response. Proc. Natl Acad. Sci. USA 106, 1813718142 (2009).

Article CAS PubMed PubMed Central Google Scholar

Li, T. et al. Identification of a cross-neutralizing antibody that targets the receptor binding site of H1N1 and H5N1 influenza viruses. Nat. Commun. 13, 5182 (2022).

Article CAS PubMed PubMed Central Google Scholar

Ye, J., Ma, N., Madden, T. L. & Ostell, J. M. IgBLAST: an immunoglobulin variable domain sequence analysis tool. Nucleic Acids Res 41, W34W40 (2013).

Article PubMed PubMed Central Google Scholar

Carter, D. M. et al. Elicitation of protective antibodies against a broad panel of H1N1 viruses in ferrets preimmune to historical H1N1 influenza viruses. J. Virol. 91, https://doi.org/10.1128/JVI.01283-17 (2017).

Abbadi, N., Nagashima, K., Pena-Briseno, A., Ross, T. M. & Mousa, J. J. Differential recognition of computationally optimized H3 hemagglutinin influenza vaccine candidates by human antibodies. J. Virol. 96, e0089622 (2022).

Article PubMed Google Scholar

Evans, P. R. & Murshudov, G. N. How good are my data and what is the resolution? Acta Crystallogr. D. Biol. Crystallogr. 69, 12041214 (2013).

Article CAS PubMed PubMed Central Google Scholar

Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. D. Biol. Crystallogr. 67, 235242 (2011).

Article CAS PubMed PubMed Central Google Scholar

Winter, G. et al. DIALS: implementation and evaluation of a new integration package. Acta Crystallogr. D. Struct. Biol. 74, 8597 (2018).

Article CAS PubMed PubMed Central Google Scholar

McCoy, A. J. et al. Phaser crystallographic software. J. Appl Crystallogr. 40, 658674 (2007).

Article CAS PubMed PubMed Central Google Scholar

Afonine, P. V. et al. Towards automated crystallographic structure refinement with phenix.refine. Acta Crystallogr. D. Biol. Crystallogr. 68, 352367 (2012).

Article CAS PubMed PubMed Central Google Scholar

Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D. Biol. Crystallogr. 66, 486501 (2010).

Article CAS PubMed PubMed Central Google Scholar

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2023 Stem Cell Therapy Market Key Trends: Dynamics Shaping the … – Digital Journal

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Additionally, Stem Cell Therapy market (125 Pages) report is a valuable addition to any company's future strategies and path forward, as it offers a deep understanding of the industry revenue and competitive landscape. With its precise information and thoughtful analysis, the report provides businesses with the necessary tools to make informed decisions and stay ahead of the competition.

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The global Stem Cell Therapy market size was valued at USD 12932.56 million in 2022 and is expected to expand at a CAGR of 8.2% during the forecast period, reaching USD 20753.25 million by 2028.Stem-cell therapy is the use of stem cells to treat or prevent a disease or condition.Bone marrow transplant is the most widely used stem-cell therapy, but some therapies derived from umbilical cord blood are also in use. Research is underway to develop various sources for stem cells, and to apply stem-cell treatments for neurodegenerative diseases and conditions, diabetes, heart disease, and other conditions.With the ability of scientists to isolate and culture embryonic stem cells, and with scientists' growing ability to create stem cells using somatic cell nuclear transfer and techniques to create induced pluripotent stem cells, controversy has crept in, both related to abortion politics and to human cloning. Additionally, efforts to market treatments based on transplant of stored umbilical cord blood have been controversial.

Key Players covered in the global Stem Cell Therapy Market are:

The report focuses on the Stem Cell Therapy market size, segment size (mainly covering product type, application, and geography), competitor landscape, recent status, and development trends. Furthermore, the report provides detailed cost analysis, supply chain. Technological innovation and advancement will further optimize the performance of the product, making it more widely used in downstream applications. Moreover, Consumer behavior analysis and market dynamics (drivers, restraints, opportunities) provides crucial information for knowing the Stem Cell Therapy market.

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Most important types of Stem Cell Therapy products covered in this report are:

Most widely used downstream fields of Stem Cell Therapy market covered in this report are:

Key Takeaways from the Global Stem Cell Therapy Market Report:

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Following Chapter Covered in the Stem Cell Therapy Market Research:

Chapter 1 mainly defines the market scope and introduces the macro overview of the industry, with an executive summary of different market segments ((by type, application, region, etc.), including the definition, market size, and trend of each market segment.

Chapter 2 provides a qualitative analysis of the current status and future trends of the market. Industry Entry Barriers, market drivers, market challenges, emerging markets, consumer preference analysis, together with the impact of the COVID-19 outbreak will all be thoroughly explained.

Chapter 3 analyzes the current competitive situation of the market by providing data regarding the players, including their sales volume and revenue with corresponding market shares, price and gross margin. In addition, information about market concentration ratio, mergers, acquisitions, and expansion plans will also be covered.

Chapter 4 focuses on the regional market, presenting detailed data (i.e., sales volume, revenue, price, gross margin) of the most representative regions and countries in the world.

Chapter 5 provides the analysis of various market segments according to product types, covering sales volume, revenue along with market share and growth rate, plus the price analysis of each type.

Chapter 6 shows the breakdown data of different applications, including the consumption and revenue with market share and growth rate, with the aim of helping the readers to take a close-up look at the downstream market.Chapter 7 provides a combination of quantitative and qualitative analyses of the market size and development trends in the next five years. The forecast information of the whole, as well as the breakdown market, offers the readers a chance to look into the future of the industry.

Chapter 8 is the analysis of the whole market industrial chain, covering key raw materials suppliers and price analysis, manufacturing cost structure analysis, alternative product analysis, also providing information on major distributors, downstream buyers, and the impact of COVID-19 pandemic.

Chapter 9 shares a list of the key players in the market, together with their basic information, product profiles, market performance (i.e., sales volume, price, revenue, gross margin), recent development, SWOT analysis, etc.

Chapter 10 is the conclusion of the report which helps the readers to sum up the main findings and points.

Chapter 11 introduces the market research methods and data sources.

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The report delivers a comprehensive study of all the segments and shares information regarding the leading regions in the market. This report also states import/export consumption, supply and demand Figures, cost, industry share, policy, price, revenue, and gross margins.

Client Focus:

Yes. As the COVID-19 and the Russia-Ukraine war are profoundly affecting the global supply chain relationship and raw material price system, we have definitely taken them into consideration throughout the research

With the aim of clearly revealing the competitive situation of the industry, we concretely analyze not only the leading enterprises that have a voice on a global scale, but also the regional small and medium-sized companies that play key roles and have plenty of potential growth.

Both Primary and Secondary data sources are being used while compiling the report.

Primary sources include extensive interviews of key opinion leaders and industry experts (such as experienced front-line staff, directors, CEOs, and marketing executives), downstream distributors, as well as end-users.

Secondary sources include the research of the annual and financial reports of the top companies, public files, new journals, etc. We also cooperate with some third-party databases.

Yes. Customized requirements of multi-dimensional, deep-level and high-quality can help our customers precisely grasp market opportunities, effortlessly confront market challenges, properly formulate market strategies and act promptly, thus to win them sufficient time and space for market competition.

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Detailed TOC of Stem Cell Therapy Market Forecast Report 2023-2028:

1 Stem Cell Therapy Market Overview

1.1 Product Overview and Scope of Stem Cell Therapy Market

1.2 Stem Cell Therapy Market Segment by Type

1.2.1 Global Stem Cell Therapy Market Sales Volume and CAGR (%) Comparison by Type (2018-2028)

1.3 Global Stem Cell Therapy Market Segment by Application

1.3.1 Stem Cell Therapy Market Consumption (Sales Volume) Comparison by Application (2018-2028)

1.4 Global Stem Cell Therapy Market, Region Wise (2018-2028)

1.5 Global Market Size of Stem Cell Therapy (2018-2028)

1.5.1 Global Stem Cell Therapy Market Revenue Status and Outlook (2018-2028)

1.5.2 Global Stem Cell Therapy Market Sales Volume Status and Outlook (2018-2028)

1.6 Global Macroeconomic Analysis

1.7 The impact of the Russia-Ukraine war on the Stem Cell Therapy Market

2 Industry Outlook

2.1 Stem Cell Therapy Industry Technology Status and Trends

2.2 Industry Entry Barriers

2.2.1 Analysis of Financial Barriers

2.2.2 Analysis of Technical Barriers

2.2.3 Analysis of Talent Barriers

2.2.4 Analysis of Brand Barrier

2.3 Stem Cell Therapy Market Drivers Analysis

2.4 Stem Cell Therapy Market Challenges Analysis

2.5 Emerging Market Trends

2.6 Consumer Preference Analysis

2.7 Stem Cell Therapy Industry Development Trends under COVID-19 Outbreak

2.7.1 Global COVID-19 Status Overview

2.7.2 Influence of COVID-19 Outbreak on Stem Cell Therapy Industry Development

3 Global Stem Cell Therapy Market Landscape by Player

3.1 Global Stem Cell Therapy Sales Volume and Share by Player (2018-2023)

3.2 Global Stem Cell Therapy Revenue and Market Share by Player (2018-2023)

3.3 Global Stem Cell Therapy Average Price by Player (2018-2023)

3.4 Global Stem Cell Therapy Gross Margin by Player (2018-2023)

3.5 Stem Cell Therapy Market Competitive Situation and Trends

3.5.1 Stem Cell Therapy Market Concentration Rate

3.5.2 Stem Cell Therapy Market Share of Top 3 and Top 6 Players

3.5.3 Mergers and Acquisitions, Expansion

4 Global Stem Cell Therapy Sales Volume and Revenue Region Wise (2018-2023)

4.1 Global Stem Cell Therapy Sales Volume and Market Share, Region Wise (2018-2023)

4.2 Global Stem Cell Therapy Revenue and Market Share, Region Wise (2018-2023)

4.3 Global Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.4 United States Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.4.1 United States Stem Cell Therapy Market Under COVID-19

4.5 Europe Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.5.1 Europe Stem Cell Therapy Market Under COVID-19

4.6 China Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.6.1 China Stem Cell Therapy Market Under COVID-19

4.7 Japan Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.7.1 Japan Stem Cell Therapy Market Under COVID-19

4.8 India Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.8.1 India Stem Cell Therapy Market Under COVID-19

4.9 Southeast Asia Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.9.1 Southeast Asia Stem Cell Therapy Market Under COVID-19

4.10 Latin America Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.10.1 Latin America Stem Cell Therapy Market Under COVID-19

4.11 Middle East and Africa Stem Cell Therapy Sales Volume, Revenue, Price and Gross Margin (2018-2023)

4.11.1 Middle East and Africa Stem Cell Therapy Market Under COVID-19

5 Global Stem Cell Therapy Sales Volume, Revenue, Price Trend by Type

5.1 Global Stem Cell Therapy Sales Volume and Market Share by Type (2018-2023)

5.2 Global Stem Cell Therapy Revenue and Market Share by Type (2018-2023)

5.3 Global Stem Cell Therapy Price by Type (2018-2023)

5.4 Global Stem Cell Therapy Sales Volume, Revenue and Growth Rate by Type (2018-2023)

6 Global Stem Cell Therapy Market Analysis by Application

6.1 Global Stem Cell Therapy Consumption and Market Share by Application (2018-2023)

6.2 Global Stem Cell Therapy Consumption Revenue and Market Share by Application (2018-2023)

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2023 Stem Cell Therapy Market Key Trends: Dynamics Shaping the ... - Digital Journal

Research identifies new target that may prevent blood cancer – VUMC Reporter

Alexander Bick, MD, PhD

by Bill Snyder

An international coalition of biomedical researchers co-led by Alexander Bick, MD, PhD, at Vanderbilt University Medical Center has determined a new way to measure the growth rate of precancerous clones of blood stem cells that one day could help doctors lower their patients risk of blood cancer.

The technique, called PACER, led to the identification of a gene that, when activated, drives clonal expansion. The findings, published April 12 in the journal Nature, suggest that drugs targeting this gene, TCL1A, may be able to suppress clonal growth and associated cancers.

We think that TCL1A is a new important drug target for preventing blood cancer, said Bick, the studys co-corresponding author with Stanford Universitys Siddhartha Jaiswal, MD, PhD.

More than 10% of older adults develop somatic (non-inherited) mutations in blood stem cells that can trigger explosive, clonal expansions of abnormal cells, increasing the risk for blood cancer and cardiovascular disease.

Since arriving at VUMC in 2020, Bick, assistant professor of Medicine in the Division of Genetic Medicine and director of the Vanderbilt Genomics and Therapeutics Clinic, has contributed to more than 30 scientific papers that are revealing the mysteries of clonal growth (hematopoiesis).

With age, dividing cells in the body acquire mutations. Most of these mutations are innocuous passenger mutations. But sometimes, a mutation occurs that drives the development of a clone and ultimately causes cancer.

Prior to this study, scientists would measure clonal growth rate by comparing blood samples taken decades apart. Bick and his colleagues figured out a way to determine the growth rate from a single timepoint, by counting the number of passenger mutations.

You can think of passenger mutations like rings on a tree, Bick said. The more rings a tree has, the older it is. If we know how old the clone is (how long ago it was born) and how big it is (what percentage of blood it takes up), we can estimate the growth rate.

The PACER technique for determining the passenger-approximated clonal expansion rate was applied to more than 5,000 individuals who had acquired specific, cancer-associated driver mutations in their blood stem cells, called clonal hematopoiesis of indeterminate potential or CHIP, but who did not have blood cancer.

Using a genome-wide association study, the investigators then looked for genetic variations that were associated with different clonal growth rates. To their surprise, they discovered that TCL1A, a gene which had not previously been implicated in blood stem cell biology, was a major driver of clonal expansion when activated.

The researchers also found that a commonly inherited variant of the TCL1A promoter, the DNA region which normally initiates transcription (and thus activation) of the gene, was associated with a slower clonal expansion rate and a markedly reduced prevalence of several driver mutations in CHIP, the second step in the development of blood cancer.

Experimental studies demonstrated that the variant suppresses gene activation.

Some people have a mutation that prevents TCL1A from being turned on, which protects them from both faster clone growth and from blood cancer, Bick said. Thats what makes the gene so interesting as a potential drug target.

The research is continuing with the hope of identifying additional important pathways relevant to precancerous growth in other tissues as well as blood, he added.

Researchers from more than 50 institutions across the United States, as well as Germany, Sweden and the Netherlands participated in the study. Other VUMC co-authors were Taralyn Mack, Benjamin Shoemaker, MD, MSCI, and Dan Roden, MD.

The research at VUMC is supported by National Institutes of Health grant OD029586, a Burroughs Wellcome Fund Career Award for Medical Scientists, the E.P. Evans Foundation & RUNX1 Research Program, a Pew-Stewart Scholar for Cancer Research Award, the VUMC Brock Family Endowment, and a Young Ambassador Award from the Vanderbilt-Ingram Cancer Center.

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Research identifies new target that may prevent blood cancer - VUMC Reporter

Arthritis: The Latest on Joint Replacement, Repair, and New … – Healthline

For the millions of Americans who live with arthritis (inflammation of the joints that can affect one or multiple joints), the condition can significantly impact ones quality of life.

For those who have osteoarthritis, the degenerative disease is caused by the regular mechanical wear-and-tear on the joints over time. Those who have rheumatoid arthritis find the autoimmune disease causing pain and inflammation throughout their body, with their own immune systems attacking the tissue lining in their joints.

Arthritis can affect ones ability to get around easily, perform common everyday tasks, and simply live in comfort without inflammation and pain.

About 24% of all adults in the United States have arthritis, which is a leading cause of work disability, leading to a total annual cost of wages lost and escalating medical bills totaling $303.5 billion, according to the Centers for Disease Control and Prevention (CDC).

Many may have to turn to joint repair and replacement procedures as a way to treat their arthritis. Its so common that about 790,000 total knee replacements and 450,000 hip replacements are performed each year in the U.S., a number that will only keep growing as the nations population ages, reports the American College of Rheumatology.

To address this need, a range of technological innovations and advancements in treatment have emerged in recent years to create more long-lasting, effective treatments to repair joints affected by arthritis.

Healthline spoke with experts about the latest advancements from growing new cartilage cells to using injectables to spur more efficient healing in joint repair for arthritis, and whats next as we look to the future of the field.

When asked to assess the overall state of the field of joint repair and replacement, Dr. Susan Goodman, an attending rheumatologist at the Hospital for Special Surgery in New York, said she believes we are looking at a future with no need for joint replacements.

But to get to that point, she told Healthline that there are several significant hurdles ahead.

For a condition such as rheumatoid arthritis [RA], the problem of joint damage develops from the unchecked inflammation that erodes cartilage. For patients with RA, it is critical to control the inflammatory disease so that the new or engineered cartilage doesnt get damaged in the same way, Goodman said. For the time being, since artificial/engineered tissue has only been used in small areas of the damaged joint, it would not be a solution for patients with inflammatory arthritis who have abnormalities in their entire joint.

When it comes to joints like the knee, which are very susceptible to mechanical forces of weight and impact, a condition like obesity will also lead to damage in the engineered joint.

Dr. Kristofer Jones, a board-certified, fellowship-trained orthopedic surgeon who specializes in sports-related musculoskeletal injuries of the knee, shoulder, and elbow, told Healthline that we are ahead of where we were 10 to 15 years ago and a lot of new research has come out along with a lot of new products that look at alternative ways to resurface new cartilage, with either a patients own cells or using allograft tissue, or transplanted tissue between patients.

The research shows these new tissue types are certainly durable and provide patients with long-lasting pain relief, but the issue is the progression of joint degeneration in other areas of the knee, Jones added.

He said its not uncommon to have performed a cartilage transplant procedure to address one part of the knee and then two or three years later see the same patient experience degeneration in other areas, with new symptoms.

We are good right now at resurfacing small-to-medium size lesions with the durable tissue, but we havent quite figured out how to turn off the button that has started in some of these patients where you are looking at progressive joint degeneration in other areas, Jones explained.

From his perspective, Dr. Sid Padia, a specialist in vascular and interventional radiology at UCLA Medical Center, told Healthline that, in general, there really has been no significant impact or change in the standard of care for patients with joint disease.

Theres been no seismic shift reorienting how we view the treatment of people with joint disease, but there have been several promising and new therapies that have shown potential benefits in the treatment of various joint diseases. That being said, much of these potential new therapies currently being studied have not come to fruition with respect to long term clinical benefit, he said.

Many of the new minimally invasive therapies have shown in studies or have shown short term benefit and thats because these studies have not assessed long-term outcomes and have not compared it [the given procedure] to a control group, so its hard for the medical community to really accept these new treatment options, Padia added. So, I think there is a tremendous opportunity for a breakthrough treatment simply because in many of these patients, the treatment options are still quite limited.

Jones said one of the current advancements that stands out the most to him is the use of biologic injectables, or orthobiologics.

These are injectable substances used by orthopaedic surgeons to help your injuries heal more quickly. They can be used for tendons, ligaments, and broken bones, for example, and are derived from substances that naturally occur in your body, according to the American Academy of Orthopaedic Surgeons.

Jones cited injectable therapies like those using platelet-rich plasma (PRP), where the plasma is injected right into a tissue, and bone marrow aspirate concentrate, which uses bone marrow cells, as two examples.

PRP, bone marrow aspirate concentrate, amniotic suspension allograft injections these are all things that we are studying to determine how we can best utilize them to treat patients who have knee pain from arthritis, he said.

Jones explained that many of these injectable therapies that are being developed are to augment surgical procedures to move the healing process along and also better create more favorable cell homeostasis so further joint degeneration doesnt happen.

He said we can expect to see a lot more of these kinds of injections available in the coming years to treat symptomatic knee pain. Jones cited a Phase III trial for which he is the principal investigator at UCLA.

At UCLA we have this Phase III FDA trial that is looking at one of these products, the trial ended and we are currently crunching the numbers to look at the data to see if there are no adverse patient events, he said.

At UCLA, Padia has been working on an alternative to knee replacement that could offer pain relief to those individuals who might not be candidates for surgery.

You might not qualify for knee surgery due to a medical complication that puts you at high risk or if you are at advanced age, for instance. Younger people might also delay surgery due to the fact theyll ultimately need another knee replacement surgery or procedure within the next 20 years.

The procedure is called genicular artery embolization. Its a minimally invasive procedure during which particles that are smaller than grains of sand are injected by way of a small catheter into enlarged knee arteries. This only takes two hours to perform and you can head home the same day and return to regular physical activities later that day.

Weve published our results, done randomized trials that show genicular artery embolization in the knee can lead to reduction in pain and weve adapted this procedure for people with tennis elbow, which is something fairly common in people who play racket sports, Padia explained. Given the increase in the use of pickleball, we are starting to see a lot more people with tennis elbow.

He added that treating something like tennis elbow is fairly limited and surgical correction is rarely done. As a result, steroid injections are often the mainstay treatment for this condition, offering a short-term benefit.

People are often left with no other option than to quit their physical activity, so weve developed this procedure for tennis elbow and its had a very promising effect in people, he said.

A 2022 study in the journal Advanced Functional Materials highlights research out of Duke University that shed light on what was described as the first synthetic gel-based substitute for cartilage.

The researchers behind this gel say it can be pulled and pressed with more force and weight than naturally occurring cartilage. This substance is also three times more resistant to the regular wear and tear that often fuels osteoarthritis and joint pain.

A company called Sparta Biomedical is developing this hydrogel product and testing them on sheep, with human clinical trials expected to start this year, according to a press release.

To put in perspective how powerful this material is, natural cartilage can handle 5,800 to 8,500 pounds per inch of tugging and squishing before hitting its breaking point. The hydrogel is reportedly 26% stronger than natural cartilage in suspension and 66% stronger in compression, reads the release.

When asked what is exciting to him in the field outside of surgery right now, Jones pointed to synthetic forms of cartilage that are as durable if not more durable than the real thing.

We are a little further away from seeing that being used clinically, the issue is trying to figure out how to get those different synthetic tissue types to adhere to bone and be durable for the long term, Jones explained. That may be something that down the line is a possible alternative to traditional joint replacement. The whole point of all of this is to preserve your joint and the natural feel for it.

In late 2022, research from The Forsyth Institute was published in the journal Science Advances, pointing to a potential mechanism for generating new cartilage cells.

The goal of this study was to figure out how to regenerate cartilage. We wanted to determine how to control cell fate, to cause the somatic cell to become cartilage instead of bone, Dr. Takamitsu Maruyama of Forsyth said in a release.

The research contributes to a growing body of research that suggests future of joint repair to treat arthritis might be at the cellular level.

I think the greatest potential [for the future] are the use of stem cells, Padia said. The use of stem cells is, number one, a relatively straightforward minimally invasive procedure. It does have the potential to have significant impact on people with joint diseases. The key is there needs to be an appropriate and accurate way to select the ideal patients who benefit from a stem cell treatment, there needs to be comparative studies ideally with a placebo studies conducted with adequate amount of time for long-term results.

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Arthritis: The Latest on Joint Replacement, Repair, and New ... - Healthline

Association between birth by caesarian section and anxiety, self … – BMC Psychiatry

Stein DJ, Phillips KA, Bolton D, Fulford KWM, Sadler JZ, Kendler KS. What is a mental/psychiatric disorder? From DSM-IV to DSM-V. Psychol Med. 2010;40(11):175965.

Article CAS PubMed PubMed Central Google Scholar

Vigo D, Thornicroft G, Atun R. Estimating the true global burden of mental illness. The Lancet Psychiatry. 2016;3(2):1718.

Article PubMed Google Scholar

Baxter AJ, Scott KM, Vos T, Whiteford HA. Global prevalence of anxiety disorders: a systematic review and meta-regression. Psychol Med. 2013;43(5):897910.

Article CAS PubMed Google Scholar

Baxter AJ, Vos T, Scott KM, Ferrari AJ, Whiteford HA. The global burden of anxiety disorders in 2010. Psychol Med. 2014;44(11):236374.

Article CAS PubMed Google Scholar

Wang R, Yang R, Ran H, Xu X, Yang G, Wang T, et al. Mobile phone addiction and non-suicidal self-injury among adolescents in China. PeerJ. 2022;10:e14057.

Article PubMed PubMed Central Google Scholar

Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the global burden of Disease Study 2010. The Lancet. 2012;380(9859):2095128.

Article Google Scholar

Strawbridge RJ, Ward J, Ferguson A, Graham N, Shaw RJ, Cullen B, et al. Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide. EBioMedicine. 2019;41:51725.

Article PubMed PubMed Central Google Scholar

Maciejewski DF, Creemers HE, Lynskey MT, Madden PAF, Heath AC, Statham DJ, et al. Overlapping genetic and environmental influences on nonsuicidal self-injury and suicidal ideation: different outcomes, same etiology? JAMA Psychiatry. 2014;71(6):699705.

Article PubMed PubMed Central Google Scholar

Pedersen NL, Fiske A. Genetic influences on suicide and nonfatal suicidal behavior: twin study findings. Eur Psychiatry. 2010;25(5):2647.

Article CAS PubMed Google Scholar

Reynolds CA, Robert Plomin JC, DeFries VS, Knopik JM, Neiderhiser. Behavioral Genetics (6th Edition). Behavior Genetics. 2013; 43(4):360361.

Arango C, Diazcaneja CM, McGorry PD, Rapoport JL, Sommer IE, Vorstman J, et al. Preventive strategies for mental health. The Lancet Psychiatry. 2018;5(7):591604.

Article PubMed Google Scholar

Arnau-Soler A, Macdonald-Dunlop E, Adams MJ, Clarke T-K, MacIntyre DJ, Milburn K, et al. Genome-wide by environment interaction studies of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland. Transl Psychiatry. 2019;9(1):14.

Article PubMed PubMed Central Google Scholar

Boks MP, He Y, Schubart CD, Gastel Wv, Elkrief L, Huguet G, et al. Cannabinoids and psychotic symptoms: a potential role for a genetic variant in the P2X purinoceptor 7 (P2RX7) gene. Behavior, and Immunity: Brain; 2020.

Google Scholar

Sandall J, Tribe RM, Avery L, Mola G, Visser GHA, Homer CSE, et al. Short-term and long-term effects of caesarean section on the health of women and children. The Lancet. 2018;392(10155):134957.

Article Google Scholar

Curran EA, ONeill SM, Cryan JF, Kenny LC, Dinan TG, Khashan AS, et al. Research Review: birth by caesarean section and development of autism spectrum disorder and attention-deficit/hyperactivity disorder: a systematic review and meta-analysis. J Child Psychol Psychiatry. 2015;56(5):5008.

Article PubMed Google Scholar

Huang K, Yan S, Wu X, Zhu P, Tao F. Elective caesarean section on maternal request prior to 39 gestational weeks and childhood psychopathology: a birth cohort study in China. BMC Psychiatry. 2019;19(1):222.

Article PubMed PubMed Central Google Scholar

Xie J, Qin X, Shu L, Li P, Liu Z, Zhu P, et al. Caesarean section and offsprings emotional development: sex differences and the role of key neurotransmitters. Brain Res. 2021;1767:147562.

Article CAS PubMed Google Scholar

Dinan TG, Kennedy PJ, Morais LH, Murphy A, Long-Smith CM, Moloney GM, et al. Altered stress responses in adults born by caesarean section. Neurobiol Stress. 2022;16:100425.

Article PubMed Google Scholar

Moore B. Appropriate technology for birth. Lancet. 1985;326(8458):787.

Article Google Scholar

Betrn AP, Ye J, Moller A-B, Zhang J, Glmezoglu AM, Torloni MR. The increasing Trend in caesarean section rates: Global, Regional and National estimates: 19902014. PLoS ONE. 2016;11(2):e0148343.

Article PubMed PubMed Central Google Scholar

Sudlow C, Gallacher J, Allen NE, Beral V, Burton PR, Danesh J et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.PLOS Medicine. 2015; 12(3).

Bycroft C, Freeman C, Petkova D, Elliott LT, Sharp K, Motyer A, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):2039.

Article CAS PubMed PubMed Central Google Scholar

Canelaxandri O, Rawlik K, Tenesa A. An atlas of genetic associations in UK Biobank. Nat Genet. 2018;50(11):15939.

Article CAS PubMed Google Scholar

Davis KAS, Cullen B, Adams MJ, Brailean A, Breen G, Coleman JRI et al. Indicators of Mental Disorders in UK Biobank A comparison of approaches.International Journal of Methods in Psychiatric Research. 2019; 28(3).

Kroenke K, Spitzer RL, Williams JBW, Lowe B. The Patient Health Questionnaire somatic, anxiety, and depressive Symptom Scales: a systematic review. Gen Hosp Psychiatry. 2010;32(4):34559.

Article PubMed Google Scholar

Kessler RC, Andrews G, Mroczek D, Ustun B, Wittchen H-U. The World Health Organization Composite International Diagnostic interview short-form (CIDI-SF). Int J Methods Psychiatr Res. 1998;7(4):17185.

Article Google Scholar

Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.

Article PubMed PubMed Central Google Scholar

Clarke GM, Morris AP. A comparison of sample size and power in case-only association studies of gene-environment interaction. Am J Epidemiol. 2010;171(4):498505.

Article PubMed PubMed Central Google Scholar

Rivera NV, Patasova K, Kullberg S, Diaz-Gallo LM, Iseda T, Bengtsson C, et al. A Gene-Environment Interaction between Smoking and Gene polymorphisms provides a high risk of two subgroups of sarcoidosis. Sci Rep. 2019;9(1):18633.

Article CAS PubMed PubMed Central Google Scholar

Oscanoa J, Sivapalan L, Gadaleta E, Dayem Ullah AZ, Lemoine NR, Chelala C. SNPnexus: a web server for functional annotation of human genome sequence variation (2020 update). Nucleic Acids Res. 2020;48(W1):W18592.

Article CAS PubMed PubMed Central Google Scholar

Ueki M, Fujii M, Tamiya G. Quick assessment for systematic test statistic inflation/deflation due to null model misspecifications in genome-wide environment interaction studies. PLoS ONE. 2019;14(7):e0219825.

Article CAS PubMed PubMed Central Google Scholar

Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8(1):1826.

Article PubMed PubMed Central Google Scholar

Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010;26(18):23367.

Article CAS PubMed PubMed Central Google Scholar

ONeill SM, Curran EA, Dalman C, Kenny LC, Kearney PM, Clarke G, et al. Birth by caesarean section and the risk of adult psychosis: a Population-Based Cohort Study. Schizophr Bull. 2015;42(3):63341.

Article PubMed PubMed Central Google Scholar

Polidano C, Zhu A, Bornstein JC. The relation between cesarean birth and child cognitive development. Sci Rep. 2017;7(1):11483.

Article PubMed PubMed Central Google Scholar

Krupnik VE, Sharp JD, Jiang C, Robison KE, Chickering T, Amaravadi L, et al. Functional and structural diversity of the human dickkopf gene family. Gene. 1999;238(2):30113.

Article CAS PubMed Google Scholar

Ren C, Gu X, Li H, Lei S, Wang Z, Wang J, et al. The role of DKK1 in Alzheimers disease: a potential intervention point of brain damage prevention? Pharmacol Res. 2019;144:3315.

Article CAS PubMed Google Scholar

Devotta A, Hong CS, Saintjeannet J. Dkk2 promotes neural crest specification by activating Wnt/-catenin signaling in a GSK3 independent manner.eLife. 2018;7.

Zhao Y, Zhang L, Wang M, Yu J, Yang J, Liu A, et al. Anxiety specific response and contribution of active hippocampal neural stem cells to Chronic Pain through Wnt/-Catenin signaling in mice. Front Mol Neurosci. 2018;11:2966.

Article CAS PubMed PubMed Central Google Scholar

Lu H-C, Tan Q, Rousseaux MWC, Wang W, Kim J-Y, Richman R, et al. Disruption of the ATXN1CIC complex causes a spectrum of neurobehavioral phenotypes in mice and humans. Nat Genet. 2017;49(4):52736.

Article CAS PubMed PubMed Central Google Scholar

Sarro EC, Sullivan RM, Barr G. Unpredictable neonatal stress enhances adult anxiety and alters amygdala gene expression related to serotonin and GABA. Neuroscience. 2014;258:14761.

Article CAS PubMed Google Scholar

Olfson M, Wall MM, Wang S, Crystal S, Bridge JA, Liu S et al. Suicide After Deliberate Self-Harm in Adolescents and Young Adults.Pediatrics. 2018; 141(4).

Jakhar K, Beniwal RP, Bhatia T, Deshpande SN. Self-harm and suicide attempts in Schizophrenia. Asian J psychiatry. 2017;30:1026.

Article Google Scholar

Wan C, Shi Y, Zhao X, Tang W, Zhang M, Ji B, et al. Positive association between ALDH1A2 and schizophrenia in the chinese population. Prog Neuropsychopharmacol Biol Psychiatry. 2009;33(8):14915.

Article CAS PubMed Google Scholar

Chan RF, Shabalin AA, Montano C, Hannon E, Hultman CM, Fallin MD, et al. Independent methylome-wide Association Studies of Schizophrenia detect consistent casecontrol differences. Schizophr Bull. 2019;46(2):31927.

PubMed Central Google Scholar

Niu S, Renfro A, Quattrocchi CC, Sheldon M, DArcangelo G. Reelin promotes hippocampal Dendrite Development through the VLDLR/ApoER2-Dab1 pathway. Neuron. 2004;41(1):7184.

Article CAS PubMed Google Scholar

Imai H, Shoji H, Ogata M, Kagawa Y, Owada Y, Miyakawa T, et al. Dorsal Forebrain-Specific Deficiency of Reelin-Dab1 Signal causes behavioral abnormalities related to Psychiatric Disorders. Cereb Cortex. 2016;27(7):3485501.

Article Google Scholar

Teixeira CM, Masachs N, Muhaisen A, Bosch C, Prez-Martnez J, Howell B, et al. Transient downregulation of Dab1 protein levels during development leads to behavioral and structural deficits: relevance for Psychiatric Disorders. Neuropsychopharmacology. 2014;39(3):55668.

Article CAS PubMed Google Scholar

Fry A, Littlejohns TJ, Sudlow C, Doherty N, Adamska L, Sprosen T, et al. Comparison of Sociodemographic and Health-Related characteristics of UK Biobank participants with those of the General Population. Am J Epidemiol. 2017;186(9):102634.

Article PubMed PubMed Central Google Scholar

Chung RY-N, Chung GK-K, Gordon D, Wong SY-S, Chan D, Lau MK-W, et al. Deprivation is associated with worse physical and mental health beyond income poverty: a population-based household survey among chinese adults. Qual Life Res. 2018;27(8):212735.

Article PubMed Google Scholar

Lang IA, Llewellyn DJ, Hubbard RE, Langa KM, Melzer D. Income and the midlife peak in common mental disorder prevalence. Psychol Med. 2011;41(7):136572.

Article CAS PubMed Google Scholar

Ye J, Wen Y, Sun X, Chu X, Li P, Cheng B, et al. Socioeconomic deprivation index is Associated with Psychiatric Disorders: an observational and genome-wide gene-by-Environment Interaction Analysis in the UK Biobank Cohort. Biol Psychiatry. 2021;89(9):88895.

Article CAS PubMed Google Scholar

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Association between birth by caesarian section and anxiety, self ... - BMC Psychiatry

Global Cell And Gene Therapy Market Size To Grow At A CAGR Of 19.02% During The Forecast Period Of 2023-2031 – openPR

The 'Global Cell and Gene Therapy Market Size, Share, Trends, Growth, Analysis, Key Players, Report and Forecast 2023-2031' by Expert Market Research gives an extensive outlook of the global cell and gene therapy market, assessing the market on the basis of its segments like therapeutic class, type, product type, end-user, and major regions.

The key highlights of the report include:

Market Overview (2016-2031)

Forecast CAGR (2023-2031): 19.02%

The global cell and gene therapy market is expected to grow at a significant rate during the forecast period. The market growth is attributed to the increasing prevalence of chronic diseases such as cancer, genetic disorders, and others, rising investments in research and development, and increasing adoption of advanced technologies in healthcare.

Get a Free Sample Report with Table of Contents- https://www.expertmarketresearch.com/reports/cell-and-gene-therapy-cgt-market/requestsample

North America is expected to dominate the global cell and gene therapy market owing to the presence of a large number of key players in the region, advanced healthcare infrastructure, and increasing government funding for research and development. The Asia Pacific region is expected to grow at the highest rate during the forecast period due to the increasing adoption of advanced technologies in healthcare, rising healthcare expenditure, and the presence of a large patient population.

Europe is expected to hold a significant share of the global cell and gene therapy market due to the presence of a large number of key players in the region and increasing government funding for research and development.

Overall, the global cell and gene therapy market is expected to witness a significant growth rate during the forecast period due to the increasing prevalence of chronic diseases, rising investments in research and development, and increasing adoption of advanced technologies in healthcare.

Cell and Gene Therapy Industry Definition and Major Segments

Cell and gene therapy refers to the use of living cells and genetic material to treat or prevent diseases. This can include the use of stem cells to regenerate damaged tissue, the use of genetically modified cells to attack cancer cells, and the delivery of therapeutic genes to correct genetic disorders. Cell and gene therapy is a rapidly growing field of medicine that holds great promise for the treatment of a wide range of diseases.

Market Breakup by Therapeutic Class

Rare DiseasesOncologyHaematologyCardiologyOphthalmologyNeurologyOthers

Market Breakup by Type

Cell Therapy TypesAutologous Cell TherapyAutogenic Cell TherapyEx-vivo Cell TherapyIn-vivo Cell TherapyGene Therapy TypesSomatic Cell Gene TherapyGermline Gene TherapyEx-vivo Gene TherapyIn-vivo Gene Therapy

Market Breakup by Product Type

YescartaProvengeLuxturaKymriahImlygicGintuitMACILavivGendicineOncorineNeovasculgenStrimvelisInvossaZolgenesmaTecartusLisocelZyntelegoOthers

Market Breakup by End User

HospitalsAmbulatory Surgical CentresWound Care CentresCancer Care CentresOthers

Market Breakup by Region

North AmericaEuropeAsia PacificMiddle East and AfricaLatin America

Read Full Report with Table of Contents- https://www.expertmarketresearch.com/reports/cell-and-gene-therapy-cgt-market

Cell and Gene Therapy Market Trends

The growth of the cell and gene therapy market is driven by advances in technology and research, as well as increasing investment in the field. The increasing understanding of genetic disorders and the development of new genetic engineering techniques, such as CRISPR, have led to the development of more targeted and effective therapies.

The use of stem cells in regenerative medicine has the potential to revolutionize the treatment of a wide range of diseases. The growing prevalence of chronic diseases, such as cancer and genetic disorders, is also driving demand for cell and gene therapies. The increasing ageing population, coupled with the high costs of traditional therapies, is also expected to drive the market.

Furthermore, increasing government funding and collaborations between pharmaceutical companies and academic institutions are also driving the growth of the market. The increasing number of clinical trials and FDA approvals for cell and gene therapy products is also expected to drive market growth. However, the high cost of these therapies and the lack of reimbursement options may pose a challenge to market growth.

Key Market Players

The major players in the cell and gene therapy market report are:

Amgen, Inc.Bluebird Bio, Inc.Castle Creek Pharmaceutical HoldingsKite Pharma, Inc.Novartis AGOrchard Therapeutics plc.Pfizer, Inc.Spark Therapeutics, Inc.Vericel CorporationDendreon Pharmaceuticals LLC.Human Stem Cells InstituteDendreon Pharmaceuticals LLC.Kolon Tissuegene Inc.Organogenesis Holdings Inc.Renova Therapeutics.Others

The report studies the latest updates in the market, along with their impact across the market. It also analyses the market demand, together with its price and demand indicators. The report also tracks the market on the bases of SWOT and Porter's Five Forces Models.

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Global Cell And Gene Therapy Market Size To Grow At A CAGR Of 19.02% During The Forecast Period Of 2023-2031 - openPR

Structural basis of spike RBM-specific human antibodies … – Nature.com

Convalescent and uninfected human blood samples

Volunteers aged 23 to 93 with a history of convalescent COVID-19 were enrolled from April 2020 to January 2021. Blood samples were collected on the day or one day before discharging from the hospital after symptom resolution. Duration is the time between PCR positive and blood sample collection. All blood samples used in this study were collected before taking any SARS-CoV-2 vaccination. Uninfected healthy volunteers aged 36 to 62 who do not have severe immunological symptoms such as immunodeficiency, autoimmune, and allergic diseases were enrolled, and we confirmed uninfected/unvaccinated donors by their clinical history and ELISA titer. Detailed information on the cohort is in Supplementary Table1. PBMCs and plasma samples were isolated by density gradient centrifugation with Ficoll-Paque PLUS (GE Healthcare) and stored at 80C until use. The study was approved by the Ethical Committee for Epidemiology of Hiroshima University (E-2011) for studies involving humans. Informed consent was obtained from all subjects involved in the study.

For single-cell sorting, PBMCs were treated with FcX blocking antibodies (BioLegend, #4422302) to reduce non-specific labeling of the cells. PBMCs were stained with S-trimer-Strep-tag, CD19-APC-Cy7 (BioLegend, #302217), and IgD-FITC (BioLegend, #348206) for 20min on ice. After washing, cells were stained with Strep-Tactin XT-DY649 (IBA) for 20min on ice. The cells were resuspended in FACS buffer (PBS containing 1% FCS, 1mM EDTA, and 0.05% NaN3) supplemented with 0.2g/ml propidium iodide (PI) to exclude dead cells. Cell sorting was performed on Special Order System BD FACSAria II (BD Biosciences) to isolate S-trimer+ CD19+ IgD cells from the PI live cell gate. Cells were directly sorted into a 96-well PCR plate. Plates containing single-cells were stored at 80C until proceeding to RT-PCR. Flow cytometric data were acquired on BD LSRFortessa (BD Biosciences) or CytoFLEX S (Beckman Coulter). Flow cytometric data were analyzed using BD FACSDiva (v8.0.2, BD Biosciences), CytExpert software (v2.4, Beckman Coulter), or FlowJo software (v10.8.1, BD Biosciences).

Single-cell sorted PCR plates were added to each well by 2l of pre-RT-PCR mix containing the custom reverse primers. After heating at 65C for 5min, plates were immediately cooled on ice. 2l of the pre-RT-PCR2 (PrimeScript II Reverse Transcriptase, Takara Bio) mix was added to each well. For RT reaction, samples were incubated at 45C for 40min followed by heating at 72C for 15min, then cooled on ice. For PCR amplification of full-length immunoglobulin heavy and light chain genes, PrimeSTAR DNA polymerase (Takara Bio) and custom primers were used. For first PCR, the initial denaturation at 98C for 1min was followed by 25 cycles of sequential reaction of 98C for 10s, 55C for 5s, and 72C for 1.5min. For second PCR, the initial denaturation at 98C for 1min was followed by 35 cycles of sequential reaction of 98C for 10s, 58C for 5s, and 72C for 1.5min. PCR fragments were assembled into a linearized pcDNA vector using NEBuilder HiFi DNA Assembly Master Mix (New England Biolabs) according to the manufacturers instructions. The pcDNA3 (Invitrogen) vectors containing an Ig light chain gene and the pcDNA4 (Invitrogen) vectors containing an Ig heavy chain gene were simultaneously transfected into Expi293 cells using Expi293 Expression System Kit (Thermo Fisher Scientific). Four days after the transfection, the culture supernatants were collected and subjected to ELISA.

For the production of recombinant S-trimer, soluble S protein (amino acids 11213), including the T4 foldon trimerization domain, a histidine tag, and a strep-tag, was cloned into the mammalian expression vector. The protein sequence was modified to remove the polybasic cleavage site (RRAR to A), and two stabilizing mutations were also introduced (K986P and V987P; wild-type numbering)34,35. The human codon-optimized nucleotide sequence encoding for the S protein of SARS-CoV-2 (GenBank: MN994467) was synthesized commercially (Eurofins Genomics). A soluble version of the S protein (amino acids 11213), including the T4 foldon trimerization domain, a histidine tag, and a strep-tag, was cloned into the mammalian expression vector pCMV. The protein sequence was modified to remove the polybasic cleavage site (RRAR to A), and two stabilizing mutations were also introduced (K986P and V987P; wild-type numbering)35. The gene encoding RBD of SARS-CoV-2, Wuhan-Hu-1, was synthesized and cloned into vector pcDNA containing a human Ig leader sequence and C-terminal 6xHis tag. RBD mutants were generated by overlap PCR using primers containing mutations. The vector was transfected into Expi293 cells and incubated at 37C for 4 days. Supernatants were purified using Capturem His-Tagged Purification kit (Takara Bio), then dialyzed by PBS buffer overnight. Protein purity was confirmed by SDS-PAGE. Protein concentration was determined spectrophotometrically at 280nm.

MaxiSorp ELISA plates (Thermo Fisher Scientific) were coated with 2g/ml purified spike RBD or trimer in 1xBBS (140mM NaCl, 172mM H3BO3, 28mM NaOH) overnight at 4C, and then blocked with blocking buffer containing 1% BSA in PBS for 1h. Antibodies diluted in Reagent Diluent (0.1% BSA, 0.05% Tween in Tris-buffered Saline) were added and incubated for 2h. HRP-conjugated antibodies were added and incubated for 2h. Wells were reacted with the TMB substrate (KPL) and the reaction was stopped using 1M HCl. The absorbance at 450nm was measured on iMark Microplate Reader (Bio-Rad) and analyzed on MPM 6 software (Bio-Rad). Antigen-specific Ig titers were determined using serial serum dilution on antigen-coated wells next to Ig-capturing antibody standard wells on the same ELISA plate.

The binding affinity of obtained antibodies to RBD was examined by the BLItz system (Sartorius Japan) using protein A-coated biosensors. 10g/ml of antibody was captured by the biosensor and equilibrated, followed by sequential binding of each concentration of RBD. For dissociation, biosensors were dipped in PBST for 900sec. Results were analyzed on BLItz Pro (v1.3.1.3, Molecular Devices).

psPAX2 (Addgene, no.12260) was a gift from Didier Trono. pCDNA3.3_CoV2_B.1.1.7 (Addgene, no.170451) for Alpha-S and pcDNA3.3-SARS2-B.1.617.2 (Addgene, no.172320) for Delta-S proteins, were gifts from David Nemazee36. pTwist-SARS-CoV-2 18 B.1.351v1 (Addgene, no.169462) for Beta-S protein was a gift from Alejandro Balazs37. Lentiviral vector, pWPI-ffLuc-P2A-EGFP for luciferase reporter assay and pTRC2puro-ACE2-P2A-TMPRSS2 for the generation of 293T cell line susceptible to SARS-CoV-2 infection was created from pWPI-IRES-Puro-Ak-ACE2-TMPRSS2, a gift from Sonja Best (Addgene, no.154987) by In-Fusion technology (Takara Bio). pcDNA3.4 expression plasmids encoding SARS-CoV-2 S proteins with human codon optimization and 19 a.a deletion of C-terminus (C-del19) from Wuhan, D614G, and Omicron were generated by assembly of PCR products, annealed oligonucleotides, or artificial synthetic gene fragments (Integrated DNA Technologies, IDT) using In-Fusion technology. For Delta plus, Kappa and Lambda variants, S proteins with only RBD, D614, and P681 mutations were created from pcDNA3.4 encoding human codon-optimized Wuhan S protein (C-del19). LentiX-293T cells (Takara Bio) and 293T cells were maintained in culture with Dulbeccos Modified Eagles Medium (DMEM) containing 10% fetal bovine serum (FBS), penicillin-streptomycin (Nacalai tesque), and 25mM HEPES (Nacalai tesque).

To generate stable 293T-ACE2.TMPRSS2 cells (293T/TRCAT), lentiviral vector VSV-G-pseudotyped lentivirus carrying ACE2 and TMPRSS2 genes were produced in LentiX-293T cells (Clontech) by transfecting with pTRC2puro-ACE2-P2A-TMPRSS2, psPAX2 (gag-pol), and pMD2G-VSV-G (envelope) using PEI-MAX (Polysciences). Packaged lentivirus was used to transduce 293T cells (Applied Biological Materials) in the presence of 5g/mL polybrene. At 72h post-infection, the resulting bulk transduced population positive for Human ACE2 expression stained by FITC-anti-ACE2 Antibody (Sinobiological) was sorted by Special Order System BD FACSAria II (BD Biosciences) and maintained in the culture medium in the presence of 2g/ml of puromycin.

Pseudoviruses bearing SARS-Cov2 S-glycoprotein and carrying a firefly luciferase (ffLuc) reporter gene were produced in LentiX-293T cells by transfecting with pWPI-ffLuc-P2A-EGFP, psPAX2, and either of S variant from Wuhan, D614G, Alpha, Beta, Delta, Delta plus, Kappa, Lambda, or Omicron using PEI-MAX (Polyscience). Pseudovirus supernatants were collected approximately 72h post-transfection and used immediately or stored at 80C. Pseudovirus titers were measured by infecting 293T/TRCAT cells for 72h before measuring luciferase activity (ONE-Glo Luciferase Assay System, Promega, Madison, WI). Pseudovirus titers were expressed as relative luminescence units per milliliter of pseudovirus supernatants (RLU/ml). For neutralization assay, pseudoviruses with titers of 14106RLU/ml were incubated with antibodies or sera for 0.5h at 37C. Pseudovirus and antibody mixtures (50l) were then inoculated with 5g/ml of polybrene onto 96-well plates that were seeded with 50l of 1104 293T/TRCAT cells/well one day before infection. Pseudovirus infectivity was scored 72h later for luciferase activity measured on ARVO X13 and 2030 Workstation (Perkin Elmer). The serum dilution or antibody concentration causing a 50% reduction of RLU compared to control (ED50 or IC50, respectively) were reported as the neutralizing antibody titers. ED50 or IC50 were calculated using a nonlinear regression curve fit on Prism (v9.0, GraphPad).

VeroE6/TMPRSS2 cells (African green monkey kidney-derived cells expressing human TMPRSS2, purchased from the Japanese Collection of Research Bioresources (JCRB) Cell Bank, JCRB1819, were maintained in DMEM containing 10% FBS and 1mg/ml G418 at 37C in 5% CO2. The virus was propagated in VeroE6/TMPRSS2 cells and the virus titer was determined by the 50% tissue culture infectious dose (TCID50) method and expressed as TCID50/ml38. The viral strains used are SARS-CoV-2/JP/Hiroshima-46059T/2020 (B.1.1, D614G, EPI_ISL_628993239), SARS-CoV-2/JP/HiroC77/2021, (AY.29, Delta, EPI_ISL_6316561), and SARS-CoV-2/JP/FH-229/2021 (BA.1.1, Omicron, EPI_ISL_11505197).

The serially diluted antibody (50l) was mixed with 100 TCID50/50l of the virus and reacted at 37C for 1h, then inoculated into VeroE6/TMPRSS2 cells to determine the minimum inhibitory concentration (MIC). Alternatively, the infectivity of the reacted antibody-virus mixture was measured by inoculating to 8 wells of a 96-well plate and observing cytopathic effects (CPE) or by the plaque assay using 10% methylcellulose to determine 50% effective dose (ED50) of the antibody. SARS-CoV-2 infection was performed in the BSL3 facility of Hiroshima University.

SARS-CoV-2 was incubated with mAb at twice the concentration of the EC50 corresponding to that viral load at 37C for 60min. After the incubation, 100l of the mixture was added to one well of a 24-well plate with confluent VeroE6/TMPRSS2 cells and incubated for 72h at 37C with 5% CO2. The supernatants were collected as an escape-mutant virus when CPE was manifested. A no-antibody-control was included to confirm the amount of test virus required.

Viral RNA was extracted from virus-infected culture medium by using Maxwell RSC Instrument (Promega, AS4500). cDNA preparation and amplification were done in accordance with protocols published by the ARTIC network (https://artic.network/ncov-2019) using V4 version of the ARTIC primer set from Integrated DNA Technologies to create tiled amplicons across the virus genome. The sequencing library was prepared using the NEB Next Ultra II DNA Library Prep Kit for Illumina (New England Biolabs, E7645). Paired-end, 300bp sequencing was performed using MiSeq (Illumina) with the MiSeq reagent kit v3 (Illumina, MS-102-3003). Consensus sequences were obtained by using the DRAGEN COVID lineage software (Illumina, ver. 3.5.6). Variant calling and annotation were performed using the Nextclade website (https://clades.nextstrain.org).

RBD from Wuhan-Hu-1, Delta, and Omicron variant and Fab fragment from NCV2SG48 with 6xHis-tag expressed in Expi293F cells (Thermo Fisher Scientific) were purified using Ni-NTA Agarose resin (QIAGEN). Fab fragment of NCV2SG53 was isolated from papain digests of the monoclonal antibody expressed in Expi293F cells using HP Protein G column (Cytiva). Purified each Fab fragments and RBD were mixed in the molar ration of 1:1.2 and incubated on ice for 1h. The mixture was loaded onto a Superdex 200 increase 10/300 GL column (Cytiva) equilibrated in 20mM Tris-HCl pH7.5, 150mM NaCl for removing the excess RBD. Fractions containing RBD and each Fab were collected and concentrated for crystallization. Chromatography was performed using NGC Chromatography Systems (BIO-RAD) and ChromLab v6 (BIO-RAD).

Crystallization was carried out by the sitting-drop vapor diffusion method at 20C. Crystals of RBD (Wuhan-Hu-1)-Fab (NCV2SG48) were grown in 2l drops containing a 1:1 (v/v) mixture of 7.5mg/ml RBD solution and 0.1M Bis-Tris pH5.5, 0.5M ammonium sulfate and 19% PEG3350. Crystals of RBD (Delta)-Fab (NCV2SG48) were grown in 2l drops containing a 1:1 (v/v) mixture of 7.5mg/ml RBD solution and 0.1M Bis-Tris pH6.5, 17.5% PEG10000, 100mM Ammonium acetate and 5% Glycerol. Crystals of RBD (Omicron BA.1)-Fab (NCV2SG48) were grown in 2l drops containing a 1:1 (v/v) mixture of 7.5mg/ml RBD solution and 0.1M Bis-Tris pH 5.5, 0.5M ammonium sulfate, 19.5% PEG 3350, 1mM EDTA and 10% glycerol. Crystals of RBD (Wuhan-Hu-1)-Fab (NCV2SG53) were grown in 2l drops containing a 1:1 (v/v) mixture of 7.5mg/ml RBD solution and 0.1M MES pH 6.0, 0.25M ammonium sulfate and 22.5% PEG3350. Crystals of RBD (Delta)-Fab (NCV2SG53) were grown in 0.6l drops containing a 1:1 (v/v) mixture of 7.5mg/ml RBD solution and 25% PEG1500. The single crystals suitable for X-ray experiments were obtained in a few weeks. X-ray diffraction data collections were performed using synchrotron radiation at SPring-8 beamline BL44XU40 in a nitrogen vapor stream at 100K. The data sets were indexed and integrated using the XDS package41, scaled, and merged using the program Aimless42 in the CCP4 program package43. The scaling statistics were shown in Table1.

Phase determinations were carried out by the molecular replacement method using the program Phaser44 in the PHENIX package45 and the program Molrep46 in the CCP4 program package with the combination of RBD structure (PDB ID:7EAM) and Fab structures (PDB ID:7CHB and 7CHP) as search models. The structure refinement was performed using the program phenix.refine47 in the PHENIX package and the program coot48 in the CCP4 program package. The final refinement statistics were shown in Table1. Interactions between RBD and Fabs were analyzed using the program PISA49 in the CCP4 program package. All figures of structures were generated by the program pymol (The PyMOL Molecular Graphics System, Version 2.4.0., Schrdinger, LLC.). Class 2a/AZD8895 (PDB ID:7L7D), Class 3a/REGN10987 (PDB ID:6XDG), Class 3b/S309 (PDB ID:7JX3), Class 4a/CR3022 (PDB ID:6ZLR), Class 4b/S2X259 (PDB ID:7M7W), and Class 5/S2H97 (PDB ID:7M7W) open data were used in Fig.3a.

The statistical analysis was performed using Prism 9.0 (GraphPad, La Jolla, CA, USA). Ordinary One-way ANOVA, Two-way ANOVA, Kruskal-Wallis test, Wilcoxon rank test, and Friedman test were used to compare data. P-value 0.05 was considered statistically significant. Statistical tests are reported in figure legends and significance is reported at p0.05. To verify reproducibility, we repeated experiments more than two times as indicated in Figure legends. Detailed information on the sample is provided in Supplementary Tables.

Further information on research design is available in theNature Portfolio Reporting Summary linked to this article.

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Structural basis of spike RBM-specific human antibodies ... - Nature.com

An Introduction to Transfection, Transfection Protocol and Applications – Technology Networks

The ability to alter the genetic composition of living cells has revolutionized biology. Scientific advances, from treating genetic disorders through gene therapy to reprograming skin cells into neurons, have been made possible by the increasing proficiency in introducing foreign nucleic acids (DNA and RNA) into cells using a technique known as transfection.

In 1928, Griffith proposed the transforming principle having observed that bacterial cells could take up foreign hereditary genetic material.1 This led to the discovery of DNA as that genetic material,2 a discovery that enabled great strides in science. In the 1960s, viruses were employed to transfer genetic material into animal cells in a controlled manner and it was shown that foreign genetic material could be expressed in animal cells; this opened up the possibility of gene therapy.3 The simultaneous advances in the field of recombinant technology the discovery of plasmids4 followed by an increased application of plasmids in the 1970s and the discovery of restriction enzymes5,6 facilitated the manipulation of genes. Around the same time, chemical and physical methods of introducing the genetic material into cells, such as electroporation,7 calcium phosphate transfection8 and liposomal9 transfection were also developed, thus providing a plethora of methods to deliver the modified genes into cells of interest.

With the development of transfection methods, many discoveries in basic and translational sciences have been possible and the technique has a plethora of applications in biology. This includes understanding the role of target genes in healthy and diseased cells, unraveling molecular pathways, designing gene therapeutic approaches, cellular reprograming and many more. Thus, transfection is now an indispensable molecular and cell biology laboratory technique. In this article, we discuss the fundamentals of transfection and provide an overview of some of the commonly employed methods. A sample protocol that can be used as a starting point is included and finally, we consider some of the key applications of transfection.

Transfection is a commonly used technique employed to transfer foreign nucleic acids into eukaryotic cells.10 The purpose of transfection is to alter the genetic content of the host cells, thus changing the expression of desired genes in these cells.

It is important here to distinguish between the terms transfection and transformation. While the term transfection is used when the host cells are eukaryotic, the term transformation is used to denote the transfer of nucleic acids to bacterial cells. This distinction is vital because in higher eukaryotic cells, transformation refers to the process by which the cells become malignant.11

The primary objective of a transfection technique is to ensure that the desired foreign nucleic acid can cross the cell membrane and that a substantial amount of that nucleic acid is protected from degradation to allow its expression within the cell. The transfer of nucleic acids into host cells can be achieved through various physical, chemical and biological methods. In most of these cases, the cellular uptake of the nucleic acids is mediated through endocytosis12 of the nucleic acid along with a carrier (Figure 1). A portion of these nucleic acids can avoid lysosomal degradation through what is known as endosomal escape and make their way to the nucleus where they can be transcribed to affect gene expression. While this is not an exhaustive list of the methodologies employed to achieve transfection, we summarize here some of the most commonly used transfection methods.

Figure 1:Diagrammatic representation of the generalized mechanism of transfection.

Physical methods of transfection apply electrical, mechanical or thermal forces13 to facilitate nucleic acid entry into host cells. Some examples include microinjection, electroporation, biolistic transfection (gene gun), sonoporation, magnetofection and laser optoporation. While the microinjection method employs a special needle to inject the nucleic acids directly into the cells, the other physical methods involve inducing transient and reversible permeabilization of the cell membrane while simultaneously placing the nucleic acids in the vicinity of the permeabilized membrane.14 In electroporation, short and intense electrical pulses are applied to achieve transient permeabilization of the cell membrane. Similarly, ultrasound waves achieve transient cell membrane permeabilization in the case of sonoporation; and the same effect is achieved using controlled exposure to a laser beam in the case of laser optoporation. Biolistic approaches propel naked DNA coated with heavy metal particles into the cell using gas discharge. Magnetofection utilizes magnetic nanoparticles to guide the nucleic acids to the cell membrane where they can be taken up by the process of endocytosis. Physical methods of transfection have the advantage that they do not pose an immunogenic risk like viral methods and are not restricted in the length of the nucleic acid sequences that can be used like viral and some chemical methods. However, these methods require dedicated and expensive equipment and reagents, and they often offer low transfection efficiencies with high cellular mortality.

A number of chemical reagents have been developed to assist DNA/RNA to cross the cell membrane.15 These include cationic lipids, calcium phosphate, cationic polymers and nanoparticles. Transfection using cationic liposomal lipids is termed as lipofection and involves the formation of positively charged lipid aggregates surrounding the negatively charged nucleic acid molecules that can easily merge with the bilipid cell membrane and enter the host cell. Positively charged calcium phosphate molecules form a complex with the negatively charged nucleic acid molecules and generate a precipitate that enters the host cells through endocytosis. The calcium phosphate method of transfection does not require special reagents and is inexpensive. However, this method has limited reproducibility with low transfection efficiency that depends on the cell type. Cationic polymers, such as dendrimers, linear or branched poly (ethylene imine) (PEI), poly (L-lysine) and others are examples of cationic polymers. Several polymeric nanoparticles, solid lipid nanoparticles (SLNP) and inorganic nanoparticles have been used for chemical transfection.12

Viral vectors of transfection offer the highest efficiency and can transfect a large variety of cell types. Virus-mediated biological transfection is termed transduction. Although the term transfection is sometimes used when nucleic acid delivery into host cells is achieved using viral particles, transduction is the correct term that should be used to refer to this process of viral-mediated delivery. Adenoviruses, adeno-associated viruses and retroviruses have been developed for transduction.16 Adenoviruses are double-stranded DNA viruses that can be used to transduce both dividing and non-dividing cells for a short duration. They can elicit strong host immune responses and the experiments with adenoviruses need to be performed in biosafety level 2 laboratories. Adeno-associated viruses (AAV) are single-stranded DNA viruses with an inability to replicate. They induce a weaker immune response in host cells. Retroviruses are RNA viruses that are characterized by the integration of their RNA into the host genome after reverse transcription. This leads to prolonged expression of the gene of interest. Lentiviruses, gammaretroviruses, spumaviruses and alphateroviruses are examples of retroviruses that have been used for biological transfection.12

Whats the difference between stable transfection and transient transfection?

Transfection can be classified as stable or transient (Figure 2) depending on the duration of retention of the genetic material in the host cells.17 If the transfected nucleic acids are incorporated into the host DNA or are retained in the host nucleus as an extrachromosomal element, leading to a permanent change in the expression of the desired gene, the process is termed stable transfection. Stable transfection facilitates constitutive expression of genetic material in cell lines and is useful for the generation of clonal cell lines, large-scale protein production applications and also for stable expression during gene therapy.

Transient transfection, on the other hand, does not involve the incorporation of the foreign nucleic acid into the host cell genome, resulting in short-term expression of the target genetic material. The nucleic acids are often removed from the cell as a result of environmental perturbation or cell division. Transient transfection is often used to understand the temporary effect of the change in expression on the desired cellular processes.

Here, we describe a generalized lipofection protocol18 for adherent secondary cell lines and primary cell cultures with plasmid DNA (Figure 3). The quantities of the plasmid DNA and reagents used are applicable for a single well of a 6-well plate and will have to be scaled depending on the size of the culture dish. Lipofection is a relatively low cost, safe, easy and quick method of transfecting cells. While this protocol can be a good starting point, the parameters will have to be standardized and optimized based on the properties of the DNA/RNA as well the host cell type. All procedures are performed under sterile conditions.

A) Before transfection:

Plasmid DNA: The quality of plasmid DNA is very important for efficient transfection. The gene of interest is usually cloned into an appropriate plasmid DNA backbone downstream from a suitable promoter. A pure and concentrated plasmid DNA preparation is required for transfection.

Plating of cells: The host cells are trypsinized, counted and plated onto an appropriate culture dish in complete culture media 1824 h before transfection. The cell numbers need to be adjusted so that they reach a confluency of 5075% at the time of transfection. Care must be taken to avoid contamination and maintain optimal cell health.

B) Transfection:

C) Post-transfection:

The transfection mix is replaced with 3 mL of complete culture media in each well. The cells are incubated for at least 48 h at 37 in the 5% CO2 incubator. The health of the cells should be monitored regularly.

We have previously described the biological methods of transfection that employ viruses for the delivery of nucleic acids. The term transduction is often used to describe virus-mediated delivery of nucleic acids into host cells. Bacteriophages were first shown to transduce bacterial cells in 1952.19 Since then, viral vectors have been developed to deliver genetic material into host cells by exploiting the natural propensity of certain viruses to transduce cells. Table 1 summarizes the differences between non-viral transfection and transduction.

Table 1: Comparison of transfection and transduction.

Transfection

Transduction

Delivery of foreign nucleic acids using non-viral methods

Delivery of foreign nucleic acids using viral vectors

Gene-transfer efficiency depends on the type of cells, media conditions etc. and is relatively low

Greater gene transfer efficiency

Serum in the media interferes with cellular uptake of nucleic acids

Transduction can be performed in the presence of serum

These methods are relatively harmless to the lab personnel

Viral contamination needs to be carefully handled. Appropriate biosafety measures should be practiced

Often requires specialized equipment and/or special reagents

Relatively easy to perform

Some methods and reagents can be cytotoxic

Viral infection of cells may induce cytopathic effects, such as insertional mutagenesis and immunogenicity

Physical methods, such as electroporation, gene gun and microinjection, and chemical methods, such as lipofection and calcium phosphate transfection, are examples of transfection

Viral transduction is mediated by DNA viruses, such as adenovirus and adeno-associated virus and RNA viruses, such as lentiviruses

Transfection methods have a wide range of applications. Here, a few of them have been briefly described.

Gene therapy: Gene therapy refers to treating genetic diseases by either silencing a defective gene, replacing a defective gene with the corrected version or amplifying the expression of a gene. Over the years, gene therapy has been used to treat diseases such as sickle cell anemia, beta thalassemia, Duchennes muscular dystrophy and hemophilia.20

DNA vaccines: DNA vaccines are vaccines that transfect host cells with engineered DNA plasmids to facilitate the expression of recombinant antigens in vivo.21 These antigens are recognized by the hosts body and stimulate the generation of adaptive immunity. The entry of DNA plasmids into host cells is achieved through in vivo electroporation.

Gene silencing: Transfection of cells with RNA interference (RNAi) molecules such as small interfering RNA (siRNA), which disintegrate the mRNA, or micro-RNA (miRNA), which suppress the translation of the gene of interest, leads to gene knockdown. Gene silencing can also be achieved using the CRISPR/Cas9 system.

Stable cell line generation: Stable transfection is used to generate stable cell lines that express a recombinant protein constitutively. These stable cell lines are extremely useful for large scale production of recombinant proteins. Stable cell lines that express recombinant proteins or have gene knock in/down are often used to study cellular processes and understand the structures of proteins22 in laboratories.

Virus production: Viral vectors for applications such as gene therapy involve the insertion of the desired gene into the viral plasmid backbone. The plasmids encoding the different components of the viral vector are transfected into a secondary cell line for assembly and large-scale production of the viruses. Moreover, viral production is employed for the generation of recombinant viruses such as, the influenza A virus, to study the effects of novel mutations and viral strains on the ability of the virus to infect and the efficiency of vaccines.23

Large-scale protein production: Recombinant proteins have many applications in therapeutics and several monoclonal antibodies, hormones, enzymes and clotting factors are produced as recombinant proteins on an industrial scale.24 Further, the rapidly progressing field of precision cellular agriculture, which is a sustainable alternative to traditional agriculture, employs transfection as an important step to enable lab-based production of future foods such as, milk, eggs and plant hemoglobin.25 Large-scale production of recombinant proteins has been achieved through transfection of recombinant DNA into mammalian cells, bacteria, yeast, plant and insect cells.

Stem cell reprograming and differentiation: Somatic cells can be reprogramed into induced pluripotent stem cells (iPSCs), which can be differentiated into specific cell types by inducing the expression of certain transcription factors. The development of iPSC technology has been possible thanks to the ability to transfect the genes required for reprograming and differentiation of the stem cells. This technology has led to the development of cellular models of human diseases and has immense therapeutic potential.26,27

References:

1. Griffith F. The significance of pneumococcal types. J Hyg (Lond). 1928;27(2):113-159. doi:10.1017/s0022172400031879

2. Avery OT, Macleod CM, McCarty M. Studies on the chemical nature of the substance inducing transformation of pneumococcal types: induction of transformation by a deoxyribonucleic acid fraction isolated from pneumococcus type III. J Exp Med. 1944;79(2):137-158. doi:10.1084/jem.79.2.137

3. Rogers S, Pfuderer P. Use of viruses as carriers of added genetic information. Nature. 1968;219(5155):749-751. doi:10.1038/219749a0

4. Lederberg J. Cell genetics and hereditary symbiosis. Physiol Rev. 1952;32(4):403-430. doi:10.1152/physrev.1952.32.4.403

5. Danna K, Nathans D. Specific cleavage of simian virus 40 DNA by restriction endonuclease of Hemophilus influenzae. Proc Natl Acad Sci U S A. 1971;68(12):2913-2917. doi:10.1073/pnas.68.12.2913

6. Smith HO, Wilcox KW. A restriction enzyme from Hemophilus influenzae. I. Purification and general properties. J Mol Biol. 1970;51(2):379-391. doi:10.1016/0022-2836(70)90149-x

7. Neumann E, Schaefer-Ridder M, Wang Y, Hofschneider PH. Gene transfer into mouse lyoma cells by electroporation in high electric fields. EMBO J. 1982;1(7):841-845. doi:10.1002/j.1460-2075.1982.tb01257.x

8. Graham FL, van der Eb AJ. A new technique for the assay of infectivity of human adenovirus 5 DNA. Virology. 1973;52(2):456-467. doi:10.1016/0042-6822(73)90341-3

9. Felgner PL, Gadek TR, Holm M, et al. Lipofection: a highly efficient, lipid-mediated DNA-transfection procedure. Proc Natl Acad Sci U S A. 1987;84(21):7413-7417. doi:10.1073/pnas.84.21.7413

10. Chong ZX, Yeap SK, Ho WY. Transfection types, methods and strategies: A technical review. PeerJ. 2021;9:e11165. doi:10.7717/peerj.11165

11. Seeber F. Transfection vs transformation: Defining terms. Parasitol Today. 2000;16(9):404. doi:10.1016/s0169-4758(00)01736-1

12. Fus-Kujawa A, Prus P, Bajdak-Rusinek K, et al. An overview of methods and tools for transfection of eukaryotic cells in vitro. Front Bioeng Biotechnol. 2021;9. doi:10.3389/fbioe.2021.701031

13. Fajrial AK, He QQ, Wirusanti NI, Slansky JE, Ding X. A review of emerging physical transfection methods for CRISPR/Cas9-mediated gene editing. Theranostics. 2020;10(12):5532-5549. doi:10.7150/thno.43465

14. Villemejane J, Mir LM. Physical methods of nucleic acid transfer: General concepts and applications. Br J Pharmacol. 2009;157(2):207-219. doi:10.1111/j.1476-5381.2009.00032.x

15. Midoux P, Pichon C, Yaouanc J-J, Jaffrs P-A. Chemical vectors for gene delivery: a current review on polymers, peptides and lipids containing histidine or imidazole as nucleic acids carriers. Br J Pharmacol. 2009;157(2):166-178. doi:10.1111/j.1476-5381.2009.00288.x

16. Bouard D, Alazard-Dany D, Cosset F-L. Viral vectors: From virology to transgene expression. Br J Pharmacol. 2009;157(2):153-165. doi:10.1038/bjp.2008.349

17. Kim TK, Eberwine JH. Mammalian cell transfection: The present and the future. Anal Bioanal Chem. 2010;397(8):3173-3178. doi:10.1007/s00216-010-3821-6

18. Hawley-Nelson P, Ciccarone V, Moore ML. Transfection of cultured eukaryotic cells using cationic lipid reagents. Curr Protoc Mol Biol. 2008;81(1):9.4.1-9.4.17. doi:10.1002/0471142727.mb0904s81

19. Zinder ND, lederberg J. Genetic exchange in Salmonella. J Bacteriol. 1952;64(5):679-699. doi:10.1128/jb.64.5.679-699.1952

20. Bulaklak K, Gersbach CA. The once and future gene therapy. Nat Commun. 2020;11(1):5820. doi:10.1038/s41467-020-19505-2

21. Flingai S, Czerwonko M, Goodman J, Kudchodkar S, Muthumani K, Weiner D. Synthetic DNA vaccines: improved vaccine potency by electroporation and co-delivered genetic adjuvants.Front Immunol. 2013;4:354. doi:10.3389/fimmu.2013.00354

22. Bssow K. Stable mammalian producer cell lines for structural biology. Curr Opin Struct Biol. 2015;32:81-90. doi:10.1016/j.sbi.2015.03.002

23. Hoffmann E, Neumann G, Kawaoka Y, Hobom G, Webster RG. A DNA transfection system for generation of influenza A virus from eight plasmids.Proc Natl Acad Sci U S A. 2000;97(11):6108-6113. doi:10.1073/pnas.100133697

24. Tripathi NK, Shrivastava A. Recent developments in bioprocessing of recombinant proteins: Expression hosts and process development. Front Bioeng Biotechnol. 2019;7:420. doi:10.3389/fbioe.2019.00420

25. Dupuis JH, Cheung LKY, Newman L, Dee DR, Yada RY. Precision cellular agriculture: The future role of recombinantly expressed protein as food. Compr Rev Food Sci Food Saf. 2023;22(2):882-912. doi:10.1111/1541-4337.13094

26. Mertens J, Marchetto MC, Bardy C, Gage FH. Evaluating cell reprogramming, differentiation and conversion technologies in neuroscience. Nat Rev Neurosci. 2016;17(7):424-437. doi:10.1038/nrn.2016.46

27. Madrid M, Sumen C, Aivio S, Saklayen N. Autologous induced pluripotent stem cell-based cell therapies: Promise, progress, and challenges. Curr Protoc. 2021;1(3):e88. doi:10.1002/cpz1.88

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An Introduction to Transfection, Transfection Protocol and Applications - Technology Networks