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Stem cell technology developed at UWMadison leads to new understanding of Autism risks – University of Wisconsin-Madison

RosetteArrays, developed at UWMadison, grow fields of neural rosettes embroynic versions of down-scaled, simplified brain structures from stem cells, giving scientists the opportunity to study the development of disorders like autism, spina bifida and epilepsy. Image courtesy of Neurosetta

Technology developed at the University of WisconsinMadison to grow rosettes of brain and spinal tissue gives scientists new ways to study the growing human brain, including a recent study of how genetic mutations linked to autism affect early stages of human brain development.

Its the latest discovery using RosetteArray technology, a screening tool that uses stem cells to generate embryonic forebrain or spinal cord tissue structures called neural rosettes. Neural rosettes are the starting material for generating human stem cell-derived neural organoids clusters of cells that resemble larger, more complex organs and can be used to assess whether different genetic makeups or exposure to chemicals increase the risk of neurodevelopmental disruptions.

Randolph Ashton

This technology gives us access to an embryonic model of human central nervous system development that we would otherwise not have access to, says Randolph Ashton, a UWMadison professor of biomedical engineering and associate director of the Stem Cell and Regenerative Medicine Center. This is useful, because not only can we now understand more about human development, but we can get an understanding of when it goes wrong.

Ashton and Gavin Knight, a scientist at the Wisconsin Institute for Discovery who earned his doctorate in Asthons lab, developed the technology behind RosetteArrays, which are marketed by Neurosetta, a company they co-founded with support from UWMadison Discovery to Product and the Wisconsin Alumni Research Foundations (WARF) Accelerator Program.

RosetteArray technology played an important role in a study published recently in Nature Neuroscience. The study, led by University of Southern California stem cell biologist Giorgia Quadrato, with Ashton and Knight as co-authors, investigated mutations of a gene called SYNGAP1.

SYNGAP1 mutations have long been associated with risk factors for autism spectrum disorder, epilepsy, neurodevelopmental disability and more, but until now the gene has mainly been studied in animal models and focued on the impact of SYNGAP1 on synapses, the structure at the tips of long brain cells called neurons that allow them to pass signals to neighboring cells.

In their new SYNGAP1 autism study, Quadrato and her lab used RosetteArray technology to grow neural rosettes from healthy human cells as well as from the cells of a patient with a disease-causing variant in SYNGAP1. By analyzing these young, developing neural organoids, Quadrato determined that human radial glia cells the cells responsible for producing all the neurons in the outer layer of the brain called the cerebral cortex can express SYNGAP1. When SYNGAP1 is mutated, it leads to disrupted organization of the cortical plate, an early brain structure that gives rise to the cerebral cortex. This shows that SYNGAP1-related brain disorders can arise through non-synaptic mechanisms.

Quadrato Lab and Neurosetta plan to partner on further studies to explore the extent of autism spectrum disorder genetic backgrounds that can be modeled using RosetteArray technology, which Ashton hopes will eventually lead to new precision medicine approaches.

Simply being able to model early human development, in this case brain and spinal cord formation, gives you a very powerful platform to try to improve human health, says Ashton. Weve been surprised to see the effects of neurological disease-causing mutations in the earliest stages of these tissues formation. RosetteArrays model approximately four to six weeks post conception, and were learning that you can start to see markers for autism then, which is a disease that people typically arent diagnosed with until post 2 years of age. So, the fact that we can see this very early in our model of human development is amazing.

Ashton says researchers using technologies like the RosetteArray are finding that the risk factors for autism spectrum disorder are boiling down to a couple of core pathways, that seem to have roles very early in human brain development, which is helpful information as researchers work on treatments.

While this paper focused on studying brain tissue, Ashton has used the RosetteArray platform in his own lab to study defects in neural tube formation.

(The neural tube) is a structure that goes from the head of the embryo all the way down through the back of the spinal cord. All brain, spinal cord and eye tissue comes from this neural tube, says Ashton. It so happens that a lot of things can disrupt that process, and if that formation is disrupted early enough, then it causes lots of issues. It can cause congenital birth defects known as neural tube defects, for example spinal bifida, which is when the lower spine doesnt fully close. Or, if you have a failure of closure higher in the neural tube that leads to a failed pregnancy, so understanding this process is crucial.

Ashton and his lab members have been using RosetteArrays to investigate what may be causing spina bifida defects and how they can be mitigated.

There are examples of known chemicals we use in our food supply, pesticides, and anti-cancer drugs that have historically been correlated with causing neural tube defects. So, its important that we have a way to test new chemistries and chemical processes to make sure they dont have these effects on human development, says Ashton. Weve used rodent models but theres a difference between animals and humans. The RosetteArray provides a way to test these chemicals on early human brain and spinal cord development.

The RosetteArray platform may also be used for individualized medicine, as it can be used to screen individual patients cell lines to better understand how mutations in a persons genomic background can lead to a disorder as well as how the interaction between a persons genomic background and the chemicals that theyre exposed to may lead to a health risk.

We think this platform will be highly useful for both commercial applications for screening for chemicals that can cause neurodevelopmental risk, as well as for clinical application, Ashton says. And I think the real power of the tool is for precision medicine and drug discovery.

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Stem cell technology developed at UWMadison leads to new understanding of Autism risks - University of Wisconsin-Madison

Casgevy and Lyfgenia: Two Gene Therapies Approved for Sickle Cell Disease – Yale Medicine

Until recently, the only possible cure for sickle cell disease, an inherited genetic blood disorder most common in people with African ancestry, was a bone marrow transplant, which has its own set of challenges.

Now, people with sickle cell disease (SCD)which affects an estimated 100,000 Americans and can cause chronic pain, organ damage, strokes, and shortened life expectancyhave additional, potentially curative options. In early December, the Food and Drug Administration (FDA) approved two gene therapies for SCD, one of which is the first approved medication that uses the gene-editing tool CRISPR.

Both treatmentsCasgevy, which is made by Vertex Pharmaceuticals and CRISPR Therapeutics, and Lyfgenia, by Bluebird Bioare for people 12 and older. Sickle cell disease is a red blood cell disorder that affects hemoglobin, the protein that carries oxygen throughout the body. These two therapies work in different ways, but both are intended to be a one-time fix, although that will require years of follow-up to know for sure.

With Casgevy, an edit (or cut) is made in a particular gene to reactivate the production of fetal hemoglobin, which dilutes the faulty red blood cells caused by sickle cell disease (more on that below). Lyfgenia, on the other hand, uses a viral envelope to deliver a healthy hemoglobin-producing gene.

The therapies are hailed as groundbreaking as they represent the first-ever gene therapies to potentially cure a hereditary condition.

For many years, we only had one treatment for sickle cell disease, and then medicine advanced to the point where we could offer bone marrow transplant, the first potential cure for sickle cell disease, says Cece Calhoun, MD, MBA, a Yale Medicine hematologist-oncologist. But trying to find a good match for a transplant is a big barrier. This new technology uses gene therapy to allow patients to be their own match.

This is significant, she notes, because a sickle cell crisisthe pain the disease causesis unpredictable and intense, akin to how it feels to have a long bone fracture.

But, says Dr. Calhoun, the pain sickle cell disease causes is not the only problem faced by people with the condition.

Sickle cell disease impacts every organ. Children are having strokes, and young adultspeople in their 30sare experiencing kidney failureall because of sickle cell disease. If we can intervene and prevent these complications and let these patients live full lives, that is huge, Dr. Calhoun says.

Lakshmanan Krishnamurti, MD, chief of Yale Medicine Pediatric Hematology & Oncology, agrees.

Many cant have bone marrow transplantation because only about 15% of patients have a matched sibling, and we can find an unrelated donor for only another 10% to 12%. That means we are only helping 25% of patients, says Dr. Krishnamurti, who was an author on the Lyfgenia study published in The New England Journal of Medicine. This is a big step forward.

However, the gene therapies are time-intensivetaking about a year to complete the processand grueling. As with bone marrow transplants, they require high-dose chemotherapy to kill the faulty stem cells before they are replaced with modified stem cells.

The gene therapies will be available only at large, authorized medical centers because they require advanced care. They are also expensive (estimates put it at $2 to $3 million per patient), and its yet to be determined if or how insurance companies, including Medicaid, will cover the treatment.

Dr. Krishnamurti says both treatments will be available at Yale and that anyone interested in learning more should speak to their physician.

Below, Drs. Calhoun and Krishnamurti answer common questions about sickle cell disease and these new gene therapies.

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Casgevy and Lyfgenia: Two Gene Therapies Approved for Sickle Cell Disease - Yale Medicine

Paralyzed B.C. man has hopes in stem cell treatment for recovery journey – Global News

A paralyzed B.C. man has hopes that stem cell treatment will help him regain sensation and movement in his body.

On July 21, 2021, Cameron Thompson, 25, was swimming at Puntledge River in Courtenay, B.C., on Vancouver Island. He dove into the water head first and ended up severing his spinal cord.

That day when I dove into the water, I knew instantly that I had become paralyzed, he told Global News.

I just thought, I dont want to choke on water so I just held my breath thinking I would hold it until I passed out.

Thompsons friends then were able to pull him out of the water and called 911.

I remember everything until I got into the ambulance, he said. And then I woke up the next day in Vancouver.

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Thompson had lost the majority of the functions of his body, except partial movement to his shoulders and arms.

Super thankful for my friends without them I would have floated down the river, Thompson said.

The Thompson family has created an online fundraiser, hoping to raise $50,000 for stem cell treatment at BioXcellerator.

According to BioXcellerator, the company is recognized as a global leader in treating a wide range of conditions based on 25 years of clinically-based research with stem cell therapy.

2:00 B.C. communities rank high on list of Canadas most generous cities

With the stem cell treatment, Thompson hopes to reduce his nerve pain which will boost his immune system and could help him regain sensation and movement in his body.

Thomson said his recovery journey so far has been a tough road to travel but he has not let the injury affect his mindset and outlook on life.

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I have the same outlook on life I have hard days thinking about what life could have been. But, day by day, things get easier. I understand there will always be struggles with life. Other people have it worse so you just deal with what you got, he said.

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In terms of a possible future career, Thompson said he is focusing on investments and the stock markets.

I want other people that have spinal injuries to know there are things that can help them and there are people that understand what they are going through, Thompson said.

Reaching out and talking can make a really big difference.

Global News spoke with Camerons mother who said the road has been tough, but she is very hopeful for the stem cell treatment.

Even if it partly works, it will be amazing, said Christina Thompson

Its a blessing. The fundraiser is just for the treatment. If we could raise the money it would be a godsend.

She said none of the costs would be covered by the government.

1:42 Friends and family set up fundraiser for Pitt Meadows boy killed in crash

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Paralyzed B.C. man has hopes in stem cell treatment for recovery journey - Global News

Embryonic-stem-cell-derived mesenchymal stem cells relieve experimental contact urticaria by regulating the functions … – Nature.com

Animals

All animal experimental procedures were approved by the Dong-A University Medical School Institutional Animal Care and Use Committee (Approval No. DIACUC-21-11) at 22.03.2021. Female BALB/c mice that were 78weeks old were purchased from Orient Bio Inc. (Gyeonggi-do, korea). The classification of experimental groups involves the random assignment of mice of the same age and within a 1g difference in body weight after the acclimatization process. The mice are then housed in a pathogen-free facility at Dong-A University (Busan, Korea). Mice were maintained at Dong-A University facility at 22C1C room temperature, 4060% humidity, on a 12h lightdark cycle (7a.m. to 7p.m.), and given food and water freely, according to institutional guidelines. All experiments were performed under inhalation anesthesia with isoflurane, and mice were euthanized by CO2 inhalation at the end of the experiment. This study adhered to the guidelines set forth by the laboratory animal ethics committee of Dong-A University and the ARRIVE guidelines. To ensure statistical significance, 5 or more mice per group were used, and all experimental protocols were approved by the Institutional Animal Care and Use Committee (IACUC) of Dong-A University. Inhalational anesthesia using isoflurane was used to induce anesthesia when sacrificing all experimental animals.

Contact urticaria mouse model was induced according to a previously reported method31,32. Mice were initially sensitized by applying 100l of a TMA (trimellitic anhydride; 500mg/ml, Alfa Aesar, Ward Hill, MA, USA) in acetone/olive oil (4:1, v/v) on the shaved hind flank. This sensitization process is essential for inducing an immune response to TMA. Secondary sensitizations were performed on the hind flank to reinforce the immune response. On the 7th and 10th days after the first sensitization, mice sensitized 50l of a TMA solution (250mg/ml) in acetone/olive oil (4:1, v/v). On day 13 after the initial sensitization, contact urticaria (CU) was induced by challenging the ears with 25l of a TMA solution (100mg/ml) dissolved in acetone/olive oil (4:1, v/v). The disease symptoms were assessed by measuring ear thickness, itching, and lesions on the skin. Particularly, skin lesions were evaluated by determining the ratio of the affected area, indicating erythema and edema on a 3 cm2 area of the dorsal skin. The symptom evaluation of experimental animals was evaluated based on all animals without exclusion criteria. For histological analysis, H&E and mast cell staining were conducted. Cellular and molecular analysis involved the use of flow cytometry to assess immune cell activity in mouse lymphoid organs, along with genetic analysis of the lesions. Experimental animals of 10 mice per group were performed by blindly selecting 56 mice for efficient handling of animal-derived flow cytometric and genetic analysis. The corresponding author and one of the first authors (S.Y. Hyun) were aware of the group assignment, and the symptoms, flow cytometry, and other molecular analysis results were evaluated together by multiple blinded co-authors.

For the purposes of in vitro experiments, we used the nave CD3+ T cell isolation Kit (Miltenyi Biotec, Bergisch-Gladbach, Germany) to enrich nave CD3+ cells from the spleens of BALB/c mice (6weeks old). All steps were conducted strictly following the manufacturers protocol.

M-MSCs used in this study was provided Mirae Cell Bio (Seoul, Korea). M-MSCs differentiated from H9 hESCs30 were maintained in EGM2-MV medium (Lonza, San Diego, CA, USA) containing supplement Mix (promocell, Heidelberg, Germany) and 50 ug/ml Gentamicin (Gibco, NewYork, USA) in a humidified atmosphere containing 5% CO2 at 37, as previously described33. M-MSCs at less than ten passages were used for in vitro cell culture and in vivo animal experiments. Bone marrow-derived MSCs (BM-MSCs) were maintained in MSCBM medium (Lonza, Basel, Switzerland) containing supplement kit (Lonza) in a humidified incubator at 5% CO2 at 37. Bone marrow-derived mast cells (BMMCs) derived from BALB/c mice were cultured in RPMI 1640 medium containing 2mM L-glutamine, 0.1mM nonessential amino acids, antibiotics, 10% fetal bovine serum (FBS), and IL-3 (10ng/ml; PeproTech Inc., Rocky hill, NJ, USA). After 4weeks,>98% of the cells were verified as BMMCs, as previously described34. Mouse splenic T cells were presorted by CD3 mAb-microbeads (Miltenyi Biotec, Bergisch Gladbach, Germany) followed by the manufacturer's method. For T cell polarization, splenic nave CD3+ T cells were cultured onto a 24-well plate coated with 1g/ml of anti-CD3 (eBioscience, San Diego, CA, USA) in complete RPMI 1640 medium and supplemented with TH1 reagents [IL-2 (20ng/ml, PeproTech Inc.), IL-12 (20ng/ml, PeproTech Inc.), and anti-IL-4 (10g/ml, Bio X cell, West Lebanon, NH, USA)] or TH2 reagents [IL-2 (20ng/ml, PeproTech Inc.), IL-4 (100ng/ml, PeproTech Inc.), and anti-IFN- (10g/ml, Bio X cell)]. After 48h, the cells were co-cultured with M-MSCs for 24h under polarized conditions. To confirm the regulation of immune cells by M-MSCs in vitro, BMMCs (5.0105 cells/well), splenic T cells (5.0105 cells/well), or polarizing splenic T cells (5.0105 cells/well) were co-cultured with the indicated ratio of M-MSCs for 24h. Co-cultured splenic T cells were identified by flow cytometry analysis. The analysis of polarized T cells was assessed by distinguishing them using the gating strategy as depicted in Supplementary Fig.S1. The ratio of degranulation of BMMCs was analyzed by -hexosaminidase secretion.

After the primary sensitization of the contact urticaria model, M-MSCs were injected subcutaneously into the ear as a single administration on the 10th days or twice on the 10th and 12th days. A primary disease improvement evaluation was performed through single administration or two administrations, and an appropriate cell administration group for disease efficacy was selected. The administration of an equal amount of BM-MSCs and oral administration of cetirizine (50mg/kg) (Sigma-Aldrich, St. Louis, MO, USA) were used as positive controls. To deplete TGF-, BALB/c mice were intraperitoneally injected with 300g of anti-TGF- mAb (1D11.16.8, Bio X cell) or an isotype-matched control mAb (Bio X cell) twice on days 0 and 3 of M-MSCs administration.

Single-cell suspensions were isolated from the spleen, cervical lymph node (cLN), and ear. Ear tissues were isolated into single cells using the gentleMACS dissociator (Miltenyi Biotec) followed by the manufacturers method. For the detection of intracellular cytokines, the isolated cells were stimulated with PMA (50ng/ml; Sigma-Aldrich), ionomycin (500ng/ml; Sigma-Aldrich), and brefeldin A (3g/ml; eBioscience) for 4h before analysis and a fixation/permeabilization kit were from eBioscience. Before cell surface markers were stained, Fc receptors were blocked with anti-CD16 and anti-CD32 mAbs (2.4G2, BD Biosciences), and conjugated and dead cells were excluded by analysis on the basis of forward and side light scatter parameters and staining with a Zombie NIR Fixable Viability Kit (Biolegend, San Diego, CA, USA). The antibodies against proteins were as follows: Antibodies against CD3 (17A2) and CD8a (53-6.7) were obtained from BioLegend. Antibodies for CD4 (RM4-5), IFN- ((XMG1.2), IL-4 (11B11) were obtained from eBioscience. Antibodies for CD3 (17A2), CD45 (30-F11), and CD127 (A7R34) were obtained from BioLegend. The cells were then analyzed with a NovoCyte flow cytometer (Agilent) and FlowJo version 10 software (Tree Star, Ashland, OR, USA).

BMMCs (5.0105 cells/well) co-cultured with M-MSCs (0.5 to 2106 cells/well) for 24h were sensitized for 4h with Monoclonal dinitrophenol (DNP)-specific IgE (100ng/ml; Sigma). The IgE-primed BMMCs were then stimulated with 50ng/ml of DNP-human serum albumin (DNP-HSA, Sigma-Aldrich) in Tyrode-BSA buffer (20mM Hepes (pH 7.4), 135mM NaCl, 5mM KCl, 1.8mM CaCl2, 1mM MgCl2, 5.6mM glucose, and 0.1% BSA) for 15min in the presence or absence of the M-MSCs.

Degranulation was determined by measuring the release of the granule marker -hexosaminidase as previously described35. The degree of degranulation of BMMCs was expressed as the % of the activity of -hexosaminidase secreted out of the cells compared to the total activity of -hexosaminidase.

M-MSCs were co-cultured with splenic T cells or BMMCs for 24h and then effector cells were removed. M-MSCs were rinsed with PBS and left on ice for 5min to stop the reaction. Total RNA was extracted using AccuPrep Universal RNA Extraction Kit (Bioneer, Daejeon, Korea), and cDNA was synthesized using AccuPower CycleScript RT PreMix (Bioneer) according to the manufacturers instructions. The PCR reaction was amplified using AccuPower PCR PreMix (Bioneer) and PCR was performed at 95 for 2min, 95 for 20s, 58 for 40s, 72 for 30s, 72 for 5min for 30 cycles. Primers used as follow: human Hgf (forward 5-TCCATGATACCACACGAACACAGC-3, reverse 5-TGCACAGTACTCCCAGCGGGTGTG-3); human Ido1 (forward 5-TTTGCTAAAGGCGCTGTTGG-3, reverse 5-CCTTCATACACCAGACCGTCTGA-3); human Pdl1 (forward 5-TATGGTGGTGCCGACTACAA-3, reverse 5-TGCTTGTCCAGATGACTTCG-3); human Il10 (forward 5-AGACATCAGGGTGGCGACTCTAT-3, reverse 5-GGCTCCCTGGTTTCTCTTCCTAAG-3); human Pge2 (forward 5-ACCATCTACCCCTTCCTTT-3, reverse 5-CCGCTTCCCAGAGGATCT-3); human Tgfb (forward 5-GGGACTATCCACCTGCAAGA -3, reverse 5-CCTCTTGGCGTAGTAGTCG-3); human Gapdh (forward 5-ACCACAGTCCATGCCATCAC-3, reverse 5-TCCACCACCCTGTTGCTGTA-3). Snap-frozen disease-inducing mouse ear tissues were ground to powder. Total RNA isolation and PCR reaction were performed in the same manner as above. Real-time PCR was performed Thermal Cycler Dice Real Time System III TP950 (Takara, Shiga-ken, Japan). Primers used as follow: mouse Il4 (forward 5-ACAGGAGAAGGGACGCCAT-3, reverse 5-GAAGCCCTACAGACGAGCTCA-3); mouse Il6 (forward 5-GAGGATACCACTCCCAACAGACC-3, reverse 5-AAGTGCATCATCGTTGTTCATACA-3); mouse Ifng (forward 5-CAGCAACAGCAAGGCGAAAAAGG-3, reverse 5-TTTCCGCTTCCTGAGGCTGGAT-3); mouse Tnfa (forward 5-AGTGACAAGCCTGTAGCCCACGT -3, reverse 5-CCATCGGCTGGCACCACTAGTT-3); mouse Gapdh (forward 5-CATCACTGCCACCCAGAAGACTG-3, reverse 5-ATGCCAGTGAGCTTCCCGTTCAG-3);

After the induction of contact urticaria in mice, their ear tissues were fixed in 4% paraformaldehyde in phosphate-buffered saline for 24h and then embedded in paraffin. The tissues were dehydrated in a graded ethanol series (70 to 100%), rinsed three times with xylene for 3min each, and then embedded in paraffin. Sections of paraffin-embedded tissues, with a thickness of 6m, were prepared and stained with hematoxylin (Sigma-Aldrich) and eosin (Sigma-Aldrich) to compare and analyze the degree of cell invasion and epidermal thickness in the tissue. Additionally, sections of tissues with a thickness of 6m were stained with a 1% toluidine blue (Sigma-Aldrich) solution to assess the number of infiltrating mast cells and the degree of degranulation.

The in vitro experiment was repeated three independent times, and the animal experiment was based on five or more animals per group, and if the results of the first experiment were insufficient, the significance was evaluated within a total of 10 animals in the group. The data are presented as the meanstandard error (SEM) from three or more independent experiments for in vitro experiments. Statistical analysis was done by unpaired Student's t-test. One-way analysis of variance (ANOVA) with Tukey's post hoc test was performed for multiple comparisons. Statistical significance (*P<0.05 and **P<0.01) was determined with Prism version 7.0 (GraphPad, San Diego, CA).

This study was approved by the Institutional Animal Care and Use Committee (IACUC) of Dong-A University(DIACUC-21-11). All animal experiments were performed in accordance with the guidelines and regulationsof the institutional guidelines.

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Embryonic-stem-cell-derived mesenchymal stem cells relieve experimental contact urticaria by regulating the functions ... - Nature.com

Machine learning-based estimation of spatial gene expression pattern during ESC-derived retinal organoid … – Nature.com

CNN architecture and dataset for estimating spatial gene expression patterns

Our model utilizes a CNN that takes a phase-contrast image as input and estimates a fluorescent image as output (Fig.1A). The typical input to a CNN is a two-dimensional (2D) image. This 2D image is passed through several convolution layers, each followed by a nonlinear activation function. The training parameters correspond to the weights of these convolution kernels and the biases. Our network has a U-Net-like architecture27, which is an encoder-decoder structure with skip connections. The embedded features from the encoder are passed through the decoder, which consists of upsampling and convolution layers to increase the resolution of the intermediate feature maps to obtain a fluorescent image as output.

In our model, the ResNet5028 was used as the backbone of the encoder. The size of the input image for the ResNet50 is (3times Htimes W). To use the pre-trained model of the ResNet50, gray-scale phase-contrast images were replicated in the axis of the channel to create three-channel images. At the first layer, a convolution with stride 2 is applied to the input image to generate features of size (64times frac{H}{2}times frac{W}{2}). The ResNet50 has 4 residual blocks and the size of the output features of these blocks are (256times frac{H}{4}times frac{W}{4}), (512times frac{H}{8}times frac{W}{8}), (1024times frac{H}{16}times frac{W}{16}), and (2048times frac{H}{32}times frac{W}{32}), respectively. These features are then concatenated to the decoder to exploit multi-scale information. The output of the decoder is a fluorescent image of size (1times frac{H}{2}times frac{W}{2}). Note that each convolution layer has a batch normalization (BN) layer and a rectified linear unit (ReLU) activation function, except for the final convolution layer, which has a sigmoid activation function to constrain the range of the output values between 0 and 1.

The network was optimized by minimizing the training loss computed on the output and corresponding ground-truth fluorescent images. The combination of mean squared error (MSE) and cosine similarity, which captures structural patterns from the entire image, was used as the training loss.

To train, validate, and test our model, we cultured retinal organoids derived from mouse ESCs using the SFEBq method10. In this culture, a GFP gene was knocked-in under the promoter of a master gene of retinal differentiation, Rax. Using this method, we obtained a dataset of a pair of phase-contrast image and fluorescent image of Rax during retinal differentiation (Fig.1B). Images were captured for 96 organoids at 4.5, 5, 6, 7, and 8days after the start of SFEBq, where each sample was captured as 14 Z-stack images. This resulted in a total of (96times 5times 14=6720) image pairs were obtained. These image pairs were divided into 5880, 420, and 420 samples for training, validation, and test, respectively. 84, 6, and 6 organoids were used for training, validation, and test, respectively; thus, each organoid does not appear in the different datasets. For data augmentation, we randomly flipped the input images vertically and horizontally during training. While the image resolution of both phase-contrast and fluorescent images is (960times 720), the (512times 512) regions where organoids appear were extracted.

To demonstrate our model, we applied it to 420 samples of the test data. As a result, the proposed model successfully estimated the spatial expression patterns of Rax from phase-contrast images during retinal organoid development (Fig.2). During development, multiple optic vesicles are formed through large and complicated deformations (Fig.2A). This process begins with a spherical embryonic body, with some portions of the tissue surface evaginating outward to form hemispherical vesicles, i.e., optic vesicles. Importantly, the resulting morphology of retinal organoids, especially optic vesicles, varies widely29. This process is known to be governed by the expression of the Rax gene (Fig.2B). That is, the Rax gene is gradually expressed in several parts of the tissue surface, so-called eye field, where cells differentiate from neuroepithelium into several types of retinal cells.

Estimated spatial Rax expression patterns during retinal organoid development. (A) Phase-contrast images from day 4.5 to day 8. (B) Captured fluorescent images of Rax as ground-truths. (C) Estimated fluorescent images with our model. (D) Error maps between captured and estimated images. The error metric was a squared error. The organoids in (AD) are identical. Scale bars indicate 200m.

Our model successfully recapitulated the above features of Rax expression (Fig.2C), i.e., the Rax intensity was relatively low and homogenous at days 4.5, 5, 6, and gradually increased around the evaginated tissue regions at days 7 and 8. Remarkably, the regions of high Rax expression were accurately estimated even in organoids with various morphologies. On the other hand, as the Rax intensity increases, especially around the evaginated tissue regions, the error of the estimated image from the ground-truth image increases with time (Fig.2D).

To quantitatively evaluate the accuracy of the estimation, we statistically analyzed the estimation results at each stage. To clarify whether the model can estimate Rax intensity in both samples with high and low Rax expression, each of the ground-truth and estimated fluorescence images was divided into two categories by the coefficient of variation of the foreground pixels in a fluorescent image at day 8 (Fig.3A). The samples in each group were labeled as positive and negative, respectively. For each of these categories, the mean and coefficient of variation of the pixel values were calculated (Fig.3BE). In calculating these values, the phase-contrast images were binarized to obtain foreground and background masks, and then computed using only the foreground pixels and normalized to those of the background pixels.

Statistical analysis of fluorescence at each developmental stage for positive and negative samples. (A) Histogram of coefficient of variation for foreground pixel values of fluorescent images at day 8. (B, C) Means of pixel values in positive and negative samples at each stage for ground-truth (green bars) and estimated fluorescent images (blue bars), respectively. (D, E) Coefficients of variation in positive samples at each stage for both ground-truth (green bars) and estimated fluorescent images (red bars), respectively. (F, G) Plots of ground-truth and estimated pixel values in positive and negative samples at each stage, respectively. Errors are 0% and 25% on the solid and dotted black lines, respectively. Error bars in (BE) indicate standard deviations.

Positive samples showed a gradual increase in mean and intensity over the days passed (Fig.3B). The negative sample, on the other hand, showed relatively low values from the beginning and did not change significantly over the days (Fig.3C). Similarly, the coefficients of variation increased in the positive samples but not in the negative samples (Fig.3D,E). These results indicate that the model successfully estimates the feature of the spatial Rax expression patterns during retinal organoid development, i.e., positive samples gradually increase Rax expressions and their heterogeneity, but negative samples do not. The intensity of the estimated images is relatively lower than the intensity of the ground-truth images in the positive samples and vice versa in the negative samples.

To clarify whether the model is capable to estimate intermediate values of the Rax expression, we analyzed the correlations between ground-truth and estimated values on foreground pixels at each stage, respectively (Fig.3F,G). The results show that in the positive sample (Fig.3F), the distribution of intensities is initially concentrated at low intensities and gradually expands to high intensities as the day progresses, with a wide distribution from low to high intensities. Similarly, in the negative sample, the luminance distribution is initially concentrated at low intensities, but does not expand as much as in the positive sample (Fig.3G). These results indicate that the model successfully estimated the plausible values across all pixel intensities, demonstrating the capability of our method to infer intermediate levels of gene expression. Notably, predicting Rax expression in the organoids at later stages, such as day 8 in our experiments, becomes more feasible for the model due to their characteristic morphologies. These distinct morphologies provide features that can be efficiently extracted by the convolution operators of the model.

To determine whether the estimated Rax expression patterns correspond to tissue morphologies, we quantified the spatial distribution of Rax intensity and the mean curvature along the tissue contour around each optic vesicle (Fig.4). For this analysis, four typical optic vesicles were selected from the positive samples and their curvature and Rax distribution were quantified. In this analysis, tissue contours were extracted and the radius of a circle passing through three points on the tissue contour was calculated as the inverse of the curvature. Moreover, the Rax intensity was measured as the average value along the depth direction from the tissue contour.

Correlation analysis of spatial Rax expression patterns and optic-vesicle morphologies. (A) Phase-contrast images. (B) Captured fluorescent images of Rax as ground-truths. (C) Estimated fluorescent images with our model. (D) Mean curvatures as a function of the distance along the organoid contour. (E) Captured and estimated fluorescent intensities of Rax along the organoid contour. The organoids in (AC) are identical and captured on day 8. The mean curvatures and fluorescence in (D, E) are for the regions indicated by the red line starting from the red dot in (A). Scale bars indicate 200m.

Optic vesicles are hemispherical, with positive curvature at the distal portion and negative curvature at the root (Fig.4A,D). The Rax intensity is continuously distributed around each vesicle, being highest at the distal part and gradually decreasing toward the root (Fig.4B,E). Furthermore, because the test images were taken with a conventional fluorescence microscope, structures above and below the focal plane are included in each image. Therefore, although some images have multiple overlapping vesicles (e.g., samples iii and iv), the model successfully estimated the Rax intensity of the overlapping regions as well.

MSE is commonly used as the training loss for training regression models. In addition to MSE, this model also uses cosine similarity, which can capture structural patterns from the entire image. To analyze the effect of cosine similarity on the estimation accuracy, we tested the model with different weights for both error metrics (Fig.5). The trained models were evaluated with MSE for each test dataset on different days (Fig.5A). The results demonstrated that cosine similarity improved the estimation accuracy at the early and intermediate stages, such as from day 4.5 to day 6. At these stages, the intensity in the differentiated region is weak, making it difficult for the network to capture structural patterns using MSE alone. Cosine similarity, on the other hand, enabled the network to learn the patterns from the weak intensity by calculating the correlation between the normalized ground-truth and the estimated images (Fig.5B). Therefore, our model has the capability to achieve the best estimate at different stages with appropriate weight balancing.

Effects of the balance of training loss on estimation accuracy. (A) Mean squared error at each stage with different hyperparameters, where bold and underlined numbers stand for the best and second best results on each day, respectively. (B) Examples of estimated fluorescent images at days 6 and 8 with different hyperparameters. The MSE of each estimated image is described in the upper left. The results with the lowest MSEs are surrounded by the red boxes. Scale bars indicate 200m.

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Crucial blood stem cell creation step found by ISU researchers – Tech Explorist

A microbial sensor, Nod1, identifies bacterial infections and aids in developing blood stem cells, offering valuable insights. Raquel Espin Palazons team at Iowa State University discovered this, potentially eliminating the need for bone marrow transplants.

Published in Nature Communications, the finding builds on Espin Palazons earlier work, revealing the role of inflammatory signals in the embryos early stages and activating Nod1 in embryos forces vascular cells to become blood stem cells. This knowledge could pave the way for creating patient-specific blood stem cells derived from their own blood in the lab.

Espin Palazon said, This would eliminate the challenging task of finding compatible bone marrow transplant donors and the complications that occur after a transplant, improving the lives of many leukemia, lymphoma, and anemia patients.

Stem cells act as both the builders and raw materials in our bodies, constantly dividing to renew and create cells for different tissues. Embryonic pluripotent stem cells can become any cell type, while adult stem cells are limited.

Blood stem cells, or hematopoietic stem cells, produce all blood components and are formed before birth in embryos. Raquel Espin Palazons team discovered an immune receptor that activates in embryos, preparing endothelial cells to become stem cells. This finding holds the potential for understanding and manipulating the creation of blood stem cells.

Raquel Espin Palazon said, We know blood stem cells form from endothelial cells, but the factors that set up the cell to switch identity were enigmatic. We didnt know that this receptor was needed or that it was needed this early before blood stem cells even form.

Researchers identified Nod1s role in blood stem cell creation by studying human embryos and using zebrafish. Nod1 levels are closely correlated with blood stem cell development. They collaborated with the Childrens Hospital of Philadelphia to validate this in humans, using induced pluripotent stem cells. Removing Nod1 hindered blood production, confirming its crucial role, similar to its impact on zebrafish blood stem cells.

Researchers, led by Raquel Espin Palazon, found that Nod1 is crucial for blood stem cell development. This discovery opens possibilities for creating blood stem cells from patients samples, a potential game-changer for treating blood disorders without needing bone marrow transplants.

The self-derived stem cells could mitigate risks like graft-versus-host disease. The ongoing research aims to understand the intricate timeline of blood stem cell formation, focusing on developing precise methods. Collaborating with the Childrens Hospital of Philadelphia enhances this effort.

The ultimate goal is therapeutic-grade blood stem cells for curing blood disorder patients. The study involves various Iowa State researchers and collaborators from the University of Edinburgh and Childrens Hospital of Philadelphia.

ISU researchers found a vital step in making blood stem cells. This discovery could create therapeutic-grade stem cells for treating blood disorders, offering a potential breakthrough in regenerative medicine.

The ongoing study focuses on refining methods and understanding the precise timeline of blood stem cell formation. Collaboration with the Childrens Hospital of Philadelphia enhances their efforts. The goal is to provide patients with a revolutionary option, using stem cells derived from their bodies, reducing risks associated with traditional treatments.

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Crucial blood stem cell creation step found by ISU researchers - Tech Explorist

The first multi-chamber heart organoids developed – Drug Target Review

The first multi-chamber cardioids derived from hiPSCs have enabled scientists to investigate heart development and defects.

Researchers, led by Dr Sasha Mendjan at the Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, have developed the first multi-chamber heart organoids that reflect the organs intricate structures. This promises advanced screening platforms for understanding heart development, drug development and toxicology studies.

The leading cause of death worldwide is cardiovascular disease, yet there are limited therapies for it. Similarly, one in 50 babies born suffer from a congenital heart defect but scientists have little understanding of why these occur. However, the team at IMBA have produced a new physiological organoid model that comprises the major regions of the human heart, enabling scientists to study cardiac disease and development.

In 2021, the Mendjan lab developed the first chamber-like heart organoid formed from human induced pluripotent stem cells (hiPSCs). hiPSCs have many benefits, such as overcoming the ethical and immune-compatibility issues faced due to the use of human embryonic stem cells (hESCs). hiPSCs can be derived from patient-specific somatic cells (eg, skin fibroblasts and hematopoietic cells) and be directly reprogrammed by defined factors to induce pluripotency. These hiPSCs displayed similarities in morphology, proliferation, feeder dependence, surface markers, gene expression, promoter activities, in vitro differentiation potential, and teratoma formation characteristics to hESCs.1

These heart organoids, named cardioids, were self-organising and mimicked the development of the hearts left ventricular chamber in the very early days of embryogenesis. Dr Mendjan said: These cardioids were a proof-of-principle and an important step forwardWhile most adult diseases affect the left ventricle, which pumps oxygenated blood through the body, congenital defects affect mostly other heart regions essential to establish and maintain circulation.

For the new study, the IMBA scientists furthered this work and derived organoid model of each developing heart structure individually. Dr Mendjan explained: Then we asked: If we let all these organoids co-develop together, do we get a heart model that co-ordinately beats like the early human heart?

The researchers grew the left and right ventricular and the atrial organoids together. Dr Mendjan remarked: Indeed, an electrical signal spread from the atrium to the left and then the right ventricular chambers just like in early foetal heart development in animalsWe now observed this fundamental process in a human heart model for the first time, with all its chambers.

We now observed this fundamental process in a human heart model for the first time, with all its chambers.

This model allowed the team to investigate how regional gene expression differences led to specific chamber contraction patterns and the intricate communication between them.

Also, insight was gained into early heart development, especially how the human heart starts beating, which was previously unknown. One of the studys first authors Alison Deyett, a PhD student in the Mendjan group detailed: At first, the left ventricular chamber leads the budding right ventricular and atrium chambers at its rhythm. Then, as the atrium develops two days later the ventricles follow the atrial lead. This mirrors what is seen in animals before the final leaders, the pacemakers, control the heart rhythm.

Multi-chamber cardioids also allowed the scientists to study chamber-specific defects. The team established a screening platform for defects for a proof-of-principle experiment, in which they investigated how teratogens and mutations affect hundreds of heart organoids simultaneously.

Thalidomide, a well-known teratogen in humans, as well as retinoid derivatives, that are used in treatments against leukaemia, psoriasis, and acne, are known to cause severe heart defects in the foetus. Both teratogens induced similar, serious compartment-specific defects in the heart organoids. Similarly, mutations in three cardiac transcription factor genes resulted in chamber-specific defects observed in human development. Dr Mendjan summarised: Our tests show that multi-chamber cardioids recapitulate embryonic heart development and can uncover disruptive effects on the whole heart with high specificity. We do this using a holistic approach, looking at multiple readouts simultaneously.

Someday, multi-chamber heart organoids could be used for toxicology studies and to develop novel drugs with heart chamber-specific effects. Drug-induced cardiotoxicity is the leading cause of drug attrition during the development process,2 so these organoids are promising for the future.

Dr Mendjan said: For example, atrial arrhythmias are widespread, but we currently dont have good drugs to treat it. One reason is that no models existed comprising all regions of the developing heart working in a coordinated manner so far.

Developing heart organoids from patient-derived stem cells may provide insight into developmental defects and its potential treatment and prevention, which the Mendjan lab hope to understand further.

This study was published in Cell.

1 Ho Beatrice Xuan, Pek Nicole Min Qian, Soh Boon-Seng. Disease Modeling Using 3D Organoids Derived from Human Induced Pluripotent Stem Cells. International Journal of Molecular Sciences (IJMS) [Internet]. 2018 March 21 [2023 December 7];19(4)936. Available from: https://doi.org/10.3390/ijms19040936

2 Cook D, Brown D, Alexander R, March R, Morgan P, Satterthwaite G, et al. Lessons Learned from the Fate of AstraZenecas Drug Pipeline: a Five-Dimensional Framework. Nature Review Drug Discovery. 2014 May 16 [2023 December 7];13(6)419-431. Available from: https://www.nature.com/articles/nrd4309

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The first multi-chamber heart organoids developed - Drug Target Review

Adult stem cell activity in naked mole rats for long-term tissue maintenance – Nature.com

Ethics

This study involved undertaking animal procedures in four different countries: U.K, USA, Austria, and the Republic of South Africa. Animal procedures were carried out in accordance with Home Office, UK regulations and the Animals (Scientific Procedures) Act, 1986 of UK, the Institutional Animal Care and Use Committee (IACUC) of USA, Act 7, 1991 of South Africa, and the Directive 2010/63/EU of the European Parliament.

Normal human colonoscopy samples were collected under the research tissue bank ethics 16/YH/0247 supported by NIHR Biomedical Research Centre, Oxford, U.K. and under the London Dulwich Research Ethics Committee (reference number 15/LO/1998). Written informed consent was obtained from all participants undergoing routine bowel cancer or IBD screening. All samples were anonymized.

Wild-caught mice (F1) were acquired from a founder population trapped in lower Austria and Vienna (2016) and housed at the Konrad Lorenz Institute of Ethology, University of Vienna, Austria. All C57BL/6J mice used in this study were purchased from Charles River (Kent, UK) or the Jackson Laboratory (USA) and housed at Biomedical Services Unit in John Radcliffe Hospital, Oxford, UK or at Rutgers University Animal Facility in Newark, New Jersey, USA. Mice were housed in individually ventilated cages under specific pathogen-free conditions and maintained at 1923C temperature with 45-65% relative humidity, in an alternating 12-h light/12-h dark cycles and fed with food and water ad libitum.

Naked mole rats (NMRs) were housed at the Animal Facility of the Department of Zoology and Entomology, University of Pretoria. The NMRs were kept in tunnel systems consisting of several Perspex chambers containing wood shavings as nestling material. The NMR room was maintained at temperatures ranging between 2932C, with relative humidity around 40-60%. NMRs were fed chopped fresh fruits and vegetables (apple, sweet potato, cucumber, and capsicum) daily ad libitum along with weekly supplement of ProNutro (Bokomo). Since NMRs obtain all their necessary water from food sources, no drinking water was provided to the animals. All scientific procedures on NMRs were conducted under ethics approval (NAS046-19 and NAS289-2020) by the Animal Ethics Committee, University of Pretoria. In addition, DAFF section 20 approval was granted (SDAH-Epi-20111909592).

For all analyses, both male and female mice, NMRs, and humans were included in the study.

15mg/mL solution of BrdU (5-bromo-2-deoxyuridine, Abcam, ab142567) and 12.3mg/mL solution of EdU (5-ethynyl-2-deoxyuridine, Merck, 900584) were prepared in sterile 1 PBS (Gibco, 10010023) and filtered through a 0.2m strainer. Using a 27-gauge needle and 1mL syringe, 100mg per kg bodyweight BrdU and 82.14mg per kg bodyweight EdU were administered intraperitoneally. Animals were checked regularly for signs of discomfort (hunched back, shivering, low mobility) after the injection.

For cumulative labelling protocol using BrdU, the first injection in naked mole rats was administered between 14:00 to 15:00. Subsequent BrdU injections were given every 8h for a duration of 5 days and intestinal tissues were collected every 8h after the first injection. In C57BL/6J mice, the first BrdU injection was also given between 14:00 to 15:00, with further injections given every 6h for a total of 2.25 days. Mouse intestinal tissues were collected 1h after each injection. The rationale for the frequency and total number of injections in the two species is discussed in Supplementary Note1.

Dextran sulphate sodium (DSS) salt (Merck, 42867) was dissolved in sterile ddH2O to prepare 0 to 8.75% (w/V) solution. Using a 2mL syringe fitted with a plastic feeding tube (Prime Bioscience, FTP-20-38), 50mL per kg bodyweight of DSS solution in NMRs or 12mL per kg bodyweight in mice was administered orally at specific intervals for 3 days. Body mass was monitored daily and stool samples collected while animals were also checked for signs of discomfort (e.g. hunched back, shivering, low mobility) every 3h.

After sacrificing the animals by approved procedures, the intestine was immediately isolated from the abdominal cavity and fatty tissue was removed. The small intestine was then divided into three equal sections: SB1 (duodenum), SB2 (jejunum) and SB3 (ileum). All three parts of the small intestine and colon were then flushed with 1 PBS (Phosphate Buffered Saline) solution using a P1000 pipette to clean all the faecal material. Each tissue section was then cut open longitudinally using a gut cutting device86 and the edges pinned down onto a 3MM filter paper such that the luminal side was facing upward. The tissue was then fixed in 10% neutral buffered formalin overnight at room temperature. The following day fixed intestinal tissues were rolled using the Swiss-rolling technique87 and stored in 70% ethanol at 4C. Next, formalin-fixed Swiss-rolls were dehydrated through increasing concentrations of ethanol, cleared through xylene, and embedded in paraffin. The paraffin blocks were sectioned at 4m thickness using a microtome (Anglia Scientific).

Tissue sections on SuperFrost Plus slides (VWR, 6310108) were deparaffinized by submerging slides in xylene (2 times, 10min each) and rehydrated in 100% ethanol (2 times, 5min each), 95% ethanol (2min), 70% ethanol (2min), 50% ethanol (2min), and distilled water (5min). Sections were then stained with Harris Haematoxylin (Merck, HHS32) for 2min 45s followed by washing in running tap water for 5min. Next, slides were dipped in 95% ethanol ten times before sections were counter-stained with Eosin solution (Merck, 117081) for 3min. This was followed by tissue sections being dehydrated in 95% ethanol (15s) and 100% ethanol (2 times, 15s each), dipped in xylene (2 times, 5min each), and finally coverslipped using DPX Mountant (Merck, 06522).

Tissue sections on SuperFrost Plus slides (VWR, 6310108) were first deparaffinized with xylene (2 times, 5min each). They were rehydrated in 100%, 90%, 70% ethanol (5min each) and tap water (2min), dipped in 3% acetic acid solution (3min) before staining with Alcian blue 8GX (Merck, A5268) solution (pH 2.5) for 30min. Tissue sections were then washed (5min) in running tap water and counterstained (5min) with Nuclear Fast Red (Merck, N3020). After 1min wash in running tap water again, tissue sections were dehydrated in ethanol, dipped in xylene and finally coverslipped using DPX Mountant (Merck, 06522).

To preserve the mucus layer of the colonic epithelium, contact with any aqueous solution was avoided after the excision of the intestinal tissue. Without removing the faecal matter, several segments of the colon were cut using a scalpel and fixed overnight at room temperature in methacran/Carnoys solution which was composed of 60% methanol, 30% chloroform, and 10% glacial acetic acid. On the second day, fixed tissues were processed in 100% methanol (2 times, 30min each), 100% ethanol (3 times, 60min each) and xylene (2 times, 60min each). Processed tissues were embedded in paraffin and 4m thick sections cut and stained with Alcian blue as described above. Stained tissues were photomicrographed at 60 magnification on an Olympus BX51 brightfield microscope. For both NMRs and mice, 30 independent measurements of the mucus layer were taken from 3 animals using the measure tool in Fiji package88.

Tissue sections on SuperFrost Plus slides (VWR, 6310108) were deparaffinized in xylene (2 times, 5min each) and rehydrated in 100%, 90%, 70% ethanol (5min each) and distilled water (5min). A hydrophobic barrier was drawn around the tissue sections using a PAP pen (Vector Lab, H-4000) before incubating in the AB solution (AP Staining kit, SystemBio, AP100B-1) for 20min at room temperature in the dark. All sections were then washed in 1 PBS (5min, on a shaker), counterstained with Nuclear Fast Red (5min), washed in running tap water (1min), dehydrated in ethanol, dipped in xylene and finally coverslipped with DPX Mountant (Merck, 06522).

4m thick formalin-fixed paraffin-embedded (FFPE) sections were cut using a microtome and dried overnight on SuperFrost Plus slides (VWR, 6310108). Tissue sections were baked at 60C for 1h the next day, deparaffinized in 3 rounds of xylene (5min each) and rehydrated in 100%, 90%, 70% ethanol and distilled H2O (5min each). Endogenous peroxidase activity was quenched by incubating sections in 3% H2O2 (Merck, 8222871000) for 20min. A heat mediated antigen retrieval was performed by boiling sections in 10mM sodium citrate buffer (pH 6.0) for 10min which was followed by 20min of cooling down in the same solution. This was followed by incubating the tissue sections in 1 PBSTX (0.1% Triton X) for 10min. All sections were then blocked for 1h at room temperature using 5% serum which matched the species of the secondary antibody. Next, primary antibodies were diluted in antibody diluent (1% BSA dissolved in 1 PBS) which was applied to the tissue sections and incubated overnight at 4C. The primary antibodies used in this study were Chromogranin A (Abcam, ab15160) at 1:2000 and BrdU (Abcam, ab6326) at 1:500. It is noteworthy that in our BrdU staining, we did not use HCl-mediated DNA denaturation and only performed heat-mediated antigen retrieval (98-100C) which has been shown to produce a brighter signal than acid hydrolysis89. After 3 rounds of washes (5min each) with 1 PBST (0.1% Tween20 in 1 PBS), tissue sections were then incubated for 1h at room temperature with biotinylated secondary antibodies diluted at 1:300. For our study specifically, we used goat anti-rabbit IgG (Vector Laboratories, BA-1000) and goat anti-rat IgG (Abcam, ab207997). To detect the biotinylated target, we used the Avidin/Biotinylated enzyme Complex (ABC) kit (Vector Laboratories, PK-6101) and developed the signal using the DAB (3,3-diaminobenzidine) solution (R&D systems, 4800-30-07). The tissue sections were then counterstained with Harris Haematoxylin (Merck, HHS32) for 5s, dehydrated in 70%, 90% and 100% ethanol for 15s each, dipped in xylene and coverslipped using DPX Mountant (Merck, 06522).

Species-specific RNAscope probes from ACD Bio-techne were used to detect Lgr5 mRNA expression in NMR (584631), mouse (312171) and human (311021) intestinal tissues. We used the RNAscope Multiplex Fluorescent Detection Kit v2 (ACD Bio-techne, 323110) and followed the instructions of the manufacturer (document number 323100-USM, ACD Bio-techne) to detect Lgr5 mRNA targets at a single cell level in FFPE tissue sections mounted on SuperFrost Plus slides (VWR, 6310108).

To enable multiplexing of mRNA and proteins, we adapted the manufacturers instructions (document number 323100-USM, ACD Bio-techne) for RNAscope Multiplex Fluorescent Detection Kit v2 (ACD Bio-techne, 323110) to exclude the step involving protease treatment. Once the mRNA signal was developed, we proceeded to detect proteins by first washing tissue sections (2 times, 2min each) in 1 TBST (0.1% Tween20 in 1 Tris-buffered saline). This was followed by blocking for 1h at room temperature with 10% serum which matched the species of the secondary antibodies. Multiple primary antibodies (diluted in 1% BSA in 1 TBS) were then applied to the tissue sections and incubated overnight at 4C. The dilutions of various primary antibodies used in our study were 1:500 for EpCAM (Abcam, ab71916), 1:500 for Ki67 (Cell Signaling, 12202), 1:200 for p27Kip1 (Cell Signaling, 3686 and 2552), 1:500 for BrdU (Abcam, ab6326) and 1:2000 for PHH3-S28 (Abcam, ab32388). Following primary antibody incubation, the next day we washed the sections thrice in 1 TBST (5min each) before incubating them with fluorophore-linked secondary antibodies (at 1:500 dilution) for 1h at room temperature. Fluorescent secondary antibodies used in our study included goat anti-rabbit Alexa 488 (Invitrogen, A11008), goat anti-rat Alexa 488 (Invitrogen, A11006), goat anti-rabbit Alexa 555 (Invitrogen, A21428) and goat anti-rabbit Alexa 633 (Invitrogen, A21070). Following the secondary antibody incubation, tissue sections were washed three times in 1 TBST (5min each) and counterstained with DAPI (Invitrogen, D1306) for 15min at room temperature before mounting with coverslips (VWR, 631-0138) using Diamond Antifade Mountant (Invitrogen, P36961).

Click-iT Plus TUNEL Assay Kit (Invitrogen, C10617) was used following the manufacturers instructions to detect apoptotic cells FFPE tissue sections.

EdU-Click 488 kit (Base Click, BCK-EdU488-1) was used according to the instructions provided by the manufacturer to detect EdU-positive cells in FFPE tissue sections.

Plasma BrdU concentration was determined following the protocol described by Barker et al.90. In brief, 100L naked mole rat blood was collected by a tail vein puncture after 8hand 16h of BrdU injection. The blood was mixed with heparin to stop clotting and centrifuged at 13,000g for 15min to separate all blood cells. Plasma was collected from the top layer and stored at 80C.

HEK293T cells (ATCC, CRL-3216) were cultured in high-glucose DMEM (Merck, D6546) containing 10% FBS (Gibco, 10270), 1 Penicillin-Streptomycin (Merck, P4333-100ML), and 2mM l-glutamine (Gibco, 25030-024) at 37C with 5% CO2. Cells were plated on a 13mm sterile glass coverslip precoated with poly l-lysine (VWR, 631-0149) in a 24-well plate (Starlab, CC7682-7524) and cultured overnight. The media was replaced with 500L fresh culture media containing 10L plasma or standard BrdU solution (3, 10, 20, 30, 40, 50g/ml) and incubated at 37C for 4h. Cells were then washed with 1 PBS and fixed in 4% paraformaldehyde for 20min at room temperature. Fixed cells were kept in 1 PBS at 4C before proceeding to immunocytochemical detection of BrdU.

Fixed cells on coverslips in 24 well plates were incubated with 3% H2O2 for 10min at room temperature. After washing with 1 PBS, cells were incubated in 2N HCl for 1h at room temperature to denature DNA strands. Fixed cells were then incubated in 0.1M Borate buffer (pH 8.5) for 30min at room temperature and in 1 PBSTX (0.1% Triton X) for 10min. Cells were blocked with 5% goat serum for 1h at room temperature and incubated with rat anti-BrdU primary antibody (Abcam, ab6326, 1:2000) overnight at 4C. The next day, cells were washed three times in 1 PBST and incubated with goat anti-rat-biotin-linked secondary antibody (Abcam, ab207997, 1:400) for 1h at room temperature. The biotinylated signal was developed using the ABC Kit (Vectastain, PK-6101) following the manufacturers instructions and detected with DAB solution (R&D systems, 4800-30-07). Gills No. 3 Haematoxylin (Merck, GHS316-500ML) was used for counterstaining and cells on the coverslips were mounted on glass slides using Aquatex mounting agent (Merck, 108562).

Intestinal tissue was washed with PBS, cut open longitudinally and laid flat on a glass slide with the luminal side facing upward. The small intestinal villi were scrapped off the flat tissue by a glass slide and collected in cold 1 PBS. The remaining tissue containing crypts was chopped into <2mm pieces using a scalpel, washed three times with ice-cold 1 PBS and incubated in chelation medium (2mM EDTA in 1 PBS without Ca2+ and Mg2+, Gibco 10010023) for 40min with agitation at 4C. The digested tissue was shaken vigorously for 30s in 1 PBS to release crypts and villi. To separate out crypts and villi of the small intestine, the solution was passed through a 100m cell strainer. The isolated crypts in the flow through were pelleted and transferred to RLT Buffer (Qiagen, 79216). RNeasy microkit (Qiagen, 74004) was used for RNA extraction. Extracted RNAs were incubated with DNase1 (ThermoFisher, EN0521) at 37C for 30min, followed by a 10min incubation with EDTA at 65C. High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, 4368814) was used to generate complementary DNA from total RNA. Quantitative real-time-PCR (qRT-PCR) was performed on LightCycler96 (Roche) with mouse and naked mole rat Gapdh used as an endogenous control. The IDs of Taqman Gene expression assays (Applied Biosystems) used in this study are Gapdh (Mm99999915_g1, Hg05064520_gH), Muc2 (Mm01276681_m1, Hg05250665_g1), Synaptophysin (Mm00436850_m1, Hg05249763_m1), and Aldolase B (Mm00523293_m1, Hg05103981_m1). The 2-Ct method was used to calculate the relative gene expression levels.

Brightfield images of tissue sections were captured using an Olympus BX51 microscope coupled with an Olympus DP70 camera system using DP controller software. Villi were imaged using 10 objective while crypts were imaged with 20 (for colon) or 60 (for small intestine) objective lens. Histopathological scoring in this study was performed based on the digital images obtained on Hamamatsu (Nanozoomer HT) scanner at 40 magnification.

To quantify cell numbers in crypt-villous structures from brightfield images, cell counter plugin of Fiji software was used. The dimensions of crypt-villous structure were calculated using the measure tool in Fiji.

Fluorescent images of intestinal crypts were acquired from 4m thick tissue sections with a Plan Apochromat 63 or 100 1.4 oil objective on a Zeiss LSM 780 upright or inverted confocal microscope. Images were acquired in Zen SP7 FP3 (black) software using 405nm, 488nm, 561nm, and 633nm laser lines in sequential tracks. Z-stacks of 6-12 optical sections with 50% overlap between subsequent planes were captured within the span of a single cell at 0.3m z-distance, 0.087m pixel dimension, and 12-bit depth.

For generating the RGB images used in the figures (Figs.1a, b, 2ad, 3d, 4d, 7a, d, Supplementary Figs.14, 5d, e, 11b), the original.czi raw files were imported into Fiji software package and a maximum intensity z-projection was created from the stacks. Using the split channel option of Fiji, the multicolour fluorescent images were separated into individual channels (DAPI, Alexa 488, Cy3, Alexa 633). The maximum and minimum displayed pixel values of individual channels were adjusted across the entire image set including in negative controls (i.e. linear adjustment) to correct for autofluorescence that had been introduced in the image stacks during acquisition. Then, using merge channel option in Fiji, two/more channels were combined to create a composite image (Lgr5/Ki67 or LGR5/KI67, Lgr5/EpCAM or LGR5/EPCAM, Lgr5/p27 or LGR5/P27, Lgr5/BrdU, Lgr5/pHH3 or LGR5/PHH3) while keeping the individual channels intact. Finally, all the individual and composite images were converted into RGB color type and saved in TIFF format. These images (TIFF) were compiled in Adobe Illustrator 2020 software to produce the panels presented in the figures.

Z-stack images were processed in batch mode of Fiji package. Firstly, a maximum intensity projection was created to generate a 2D image from the stacks. Next, each channel of the image was separated, and maximum and minimum displayed pixel values were adjusted across the entire image set including negative controls. To quantify the number of rodent Lgr5 or human LGR5 mRNA expressed in a single cell, all the ISH dots were manually counted within the cell periphery demarcated by EpCAM staining. As the Lgr5 or LGR5 signal was captured using confocal microscopy at a resolution of 237nm, overlapping/merged Lgr5 or LGR5 mRNA signal dots were rarely observed. To calculate the distribution of Lgr5+ or LGR5+ cells relative to other cells along the crypt axis, the cell present at the crypt apex was assigned position 0 and we counted cells on each side of this cell to acquire datapoints in our quantifications. Any cell containing more than three Lgr5 or LGR5 mRNA puncta was considered positive for Lgr5 or LGR5 expression (Lgr5+ or LGR5+).

We observed significant variation in autofluorescence levels between mouse, human and NMR intestinal tissues, with mouse tissue emitting the most and naked mole rats the least. This variation necessitated adjusting the laser powers of the confocal microscope during image acquisition so that maximal image contrast was achieved while also reducing the autofluorescence signals. The maximum and minimum displayed pixel values of individual channels were adjusted across the entire image set (i.e. linear adjustment), including in negative controls, to correct for autofluorescence. These adjustments resulted in varying intensities for specific signals in the three species and, therefore, we took a binary approach for the quantification of the antibody-based signals. The presence of any specific signal in the target compartment inside a cell was considered positive regardless of the staining intensity.

We determined the length of the cell cycle (TT) and S-phase (TS) in CBC cells (Lgr5+CBC) of naked mole rats by counting the fraction of BrdU-labelled Lgr5+CBC cells after successive pulsing over 5 days in NMRs and 2.25 days in mice. As the CBC cells (Lgr5+CBC) cells are on average asynchronously and asymmetrically dividing45, the labelling index (LI) which provides the ratio of labelled cells to the total population (LI=Lgr5+CBCBrdU+/Lgr5+CBC) at any given time (t) can be modelled by Eq.1 below where TT is the total cell division time33.

$${{{{{rm{LI}}}}}}= (1/{{{{{rm{T}}}}}}_{{{{{rm{T}}}}}}){{{{{rm{X}}}}}}t+({{{{{rm{T}}}}}}_{{{{{rm{S}}}}}}/{{{{{rm{T}}}}}}_{{{{{rm{T}}}}}}),{{{{{rm{for}}}}}},{t}{{{{{rm{le }}}}}}{{{{{{rm{T}}}}}}}_{{{{{{rm{T}}}}}}}-{{{{{{rm{T}}}}}}}_{{{{{{rm{S}}}}}}}\ {{{{{rm{LI}}}}}}= 1,{{{{{rm{for}}}}}},t > {{{{{{rm{T}}}}}}}_{{{{{{rm{T}}}}}}}-{{{{{{rm{T}}}}}}}_{{{{{{rm{S}}}}}}}$$

(1)

Equation1 assumes that there are no or only very few stem cells (based on p27 negativity in NMR and mouse Lgr5+CBC cells) that remain quiescent for the duration of the BrdU experiment. The lfit tool in STATA was used to calculate the least square fit of the data by considering the time points before LI reached saturation. We derived TT from the slope of the regression (TT=1/slope). When t=0, LI0=TS/TT which is the y-intercept of the graph. Thus, the duration of S-phase (TS) was estimated from the y-intercept of the regression line.

For human LGR5+CBC cells, we assumed KI67 is undetectable at G1/S transition and detected in the S to M phases of the cell cycle46. We determined the fraction of LGR5+CBC cells that expressed KI67 and calculated the length of S, G2 and M-phase (T(S, G2, M)) using Eq.2:

$${{{{{{rm{T}}}}}}_{{({{{{{rm{S}}}}}},{{{{{rm{G}}}}}}2,{{{{{rm{M}}}}}})}}}{{{{{rm{KI}}}}}}67^{+}={{{{{{{rm{T}}}}}}}_{{{{{rm{T}}}}}}^{({{{{{{rm{Ref}}}}}}},31)}}{{{{{rm{X}}}}}},{{{{{{rm{LGR}}}}}}5}^{+{{{{{rm{CBC}}}}}}}{{{{{rm{KI}}}}}}67^{+}/{{LGR}5}^{+{{{{{rm{CBC}}}}}}}$$

(2)

The time in mitosis (TM) was calculated after quantifying the fraction of rodent (mouse or NMR) Lgr5+CBC or human LGR5+CBC cells positive for phospho-histone H3 using Eq.3:

$${{{{{{rm{T}}}}}}{{{{{rm{M}}}}}}}^{{{{{{rm{Ki}}}}}}67+}={{{{{{{rm{T}}}}}}}_{{{{{{rm{T}}}}}}}}^{({{{{{rm{linear}}}}}},{{{{{rm{regression}}}}}})}{{{{{rm{X}}}}}},{{Lgr}5}^{+{{{{{rm{CBC}}}}}}}{{{{{rm{pHH}}}}}}3+({{{{{rm{Ser}}}}}}28)/{{Lgr}5}^{+{{{{{rm{CBC}}}}}}}$$

(3)

or

$${{{{{{{rm{T}}}}}}}_{{{{{{rm{M}}}}}}}}^{{{{{{rm{KI}}}}}}67+}={{{{{{{rm{T}}}}}}}_{{{{{{rm{T}}}}}}}}{({{{{{rm{ref}}}}}}31)}{{{{{rm{X}}}}}},{{LGR}5}^{+{{{{{rm{CBC}}}}}}}{{{{{{rm{PHH}}}}}}3}^{+}({{{{{rm{Ser}}}}}}28)/{{LGR}5}^{+{{{{{rm{CBC}}}}}}}$$

Using TS estimated by Ishikawa et al.31 previously, the length of G2-phase (TG2) was calculated using Eq.4:

$${{{{{{{rm{T}}}}}}}_{{{{{{rm{G}}}}}}2}}^{{{{{{rm{KI}}}}}}67+}={{{{{{rm{T}}}}}}}_{({{{{{rm{S}}}}}},{{{{{rm{G}}}}}}2,{{{{{rm{M}}}}}})}{{{{{{rm{KI}}}}}}67}^{+}-left({{{{{{{rm{T}}}}}}}_{{{{{{rm{S}}}}}}}}^{{{{{{rm{KI}}}}}}67+}+{{{{{{{rm{T}}}}}}}_{{{{{{rm{M}}}}}}}}^{{{{{{rm{KI}}}}}}67+}right)$$

(4)

After quantifying the fraction of LGR5+CBC cells expressing P27, we calculated the time spent in G0 and G1 (T(G1, G0)P27+) using Eq.5:

$${{{{{{{rm{T}}}}}}}_{({{{{{rm{G}}}}}}1,{{{{{rm{G}}}}}}0)}}^{{{{{{rm{P}}}}}}27+}={{{{{{{rm{T}}}}}}}_{{{{{{rm{T}}}}}}}}{({{{{{rm{ref}}}}}}31)}{{{{{rm{X}}}}}},{{LGR}5}^{+{{{{{rm{CBC}}}}}}}{{{{{rm{P}}}}}}27+/{{LGR}5}^{+{{{{{rm{CBC}}}}}}}$$

(5)

We took the fraction of LGR5+P27+ cells in G0 phase (QF) from Ishikawa et al. 31 to calculate the length of G0 in human LGR5+CBC cells using Eq.6:

$${{{{{{{rm{T}}}}}}}_{{{{{{rm{G}}}}}}0}}^{{{{{{rm{P}}}}}}27+}={{{{{{rm{QF}}}}}}}{({{{{{rm{ref}}}}}}31)}{{{{{rm{X}}}}}},{{{{{{{rm{T}}}}}}}_{(G1,G0)}}^{{{{{{rm{P}}}}}}27+}$$

(6)

Finally, using Eq.7, we quantified the time human colonic LGR5+CBC cells spend in G1 (TG1):

$${{{{{{rm{T}}}}}}}_{{{{{{rm{T}}}}}}}={{{{{{{rm{T}}}}}}}_{{{{{{rm{G}}}}}}0}}^{{{{{{rm{P}}}}}}27+}+{{{{{{{rm{T}}}}}}}_{{{{{{rm{G}}}}}}1}}^{{{{{{rm{P}}}}}}27+}+{{{{{{{rm{T}}}}}}}_{{{{{{rm{S}}}}}}}}^{{{{{{rm{KI}}}}}}67+}+{{{{{{{rm{T}}}}}}}_{{{{{{rm{G}}}}}}2}}^{{{{{{rm{KI}}}}}}67+}+{{{{{{{rm{T}}}}}}}_{{{{{{rm{M}}}}}}}}^{{{{{{rm{KI}}}}}}67+}$$

(7)

In NMR and mouse, Lgr5+CBC cells are negative for p27 such that TG0=0. For these species, we derived the combined length of time spent in G1 and G2 (TG1+TG2) from Eq.7.

Using the length of TS from cumulative BrdU labelling in Lgr5+CBC cells and assuming no change in TS in Lgr5+ cells located at different positions within the crypt31, we measured the total cell division time (TT) of Lgr5+above crypt base cells using Eq.1 by measuring the labelling index (LI) at a single time point (t) after pulsing animals with BrdU in vivo. More specifically, in C57BL/6 mice (n=3 animals, 4 months old), we administered BrdU once and analysed intestinal tissue at t=0.5h. In NMRs (n=3 animals, 6-24 months-old), we pulsed the animals with BrdU every 8h and analysed the intestine after t=1 day.

We used Microsoft Excel (v16.77.1) for inputting raw data after collection. All statistical tests and graphs displayed in this paper were generated using StataMP 14.1. Details of statistical tests performed are described in figure legends. P-values are generated by conducting two-tailed t-tests, F-test and Wilcoxon rank sum test as indicated in each figure legend. No blinding and randomization were performed during the analysis.

All the figures presented in this manuscript were prepared using Adobe Illustrator 2020 (version 24.1). Vector line arts shown in Figs.1c, d, 3a, h, 4a, h, 6a, Supplementary Figs.5d, e, and 9a, b were created using the curvature tool of Adobe Illustrator.

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

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Adult stem cell activity in naked mole rats for long-term tissue maintenance - Nature.com

Platelet-Rich Plasma Injections | What It’s Like Getting PRP Injections Into The Knee as a Skier – SnowBrains

In November 2021, I hiked up and skied Little Chute at Alta, UT.

When skiing down my knee swelled up and I could only bend it 90.

After arriving home the swelling went down.

This happened on a daily repeat cycle until February 2022 when the pain upon skiing became so intense I had to stop skiing altogether.

I talked to my surgeon.

He quickly diagnosed me with osteoarthritis caused by my knee surgery in 2015 to replace my ACL.

I had also vaporized my meniscus and ripped off a square centimeter of cartilage on the end of my femur resulting in a microfracture surgery (performed at the same time as my ACL replacement).

The first course of action was a Non-Steroidal Anti-Inflammatory Drug (NSAID) regimen (ibuprofen, etc).

That didnt work.

In February 2022, I had my first Platelet-Rich Plasma (PRP) injection.

I coupled the injection with 4 weeks off from skiing and physical therapy.

I returned to skiing in March 2022 and had a decent March, April, and May 2022.

I surfed great waves with no issues in the Maldives all of June and July (surfing is not hard on knees).

I returned to snow in August 2022 in Patagonia and on day #1 my knee swelled up and was painful again.

I was only able to ski 22 out of 60 days that summer

I went back in for another PRP injection in October.

This time it worked.

I had a strong 2022/23 ski season with record snowfall across the west and I skied 305 out of 365 days that year without issue, swelling, nor pain.

Since then, Ive officially drunk the Kool-Aid.

I found a doctor who will do PRP injections for $450 a pop and Im doing them every 3 months.

This week, I got my 5th PRP injection in the lateral compartment of my left knee (where there is no meniscus and no cartilage).

I plan on continuing with these PRP injections indefinitely.

In general, its advised to take it easy for a day or two after the injection.

I sometimes experience swelling for 24 hours after the PRP injection.

I believe that these injections are working for me and hopefully, theyll help me put off getting a knee replacement until Im at least 55.

Fingers crossed.

Im 45 years old, 61, 165lbs and Ive been skiing full time since I was 22 and Ive skied year round the last 13 years.

PRP treatment is not yet fully proven by science and therefore, health insurance generally wont cover it.

I also do a lot of physical therapy (building up the muscles in my legs) and I have a custom-made DonJoy knee brace that I wear anytime I ski that is called an unloader knee brace because it bends my knee bowlegged taking pressure off the lateral compartment of my left knee where I lack cartilage.

Unloader knee braces are also not well-proven in science.

You may have to get an MRI before you can get into a doctor to get PRP injections and the doctor you see (orthopedic surgeon) will also most likely take an x-ray of your knees.

All info below from Johns Hopkins University

Platelet-rich plasma consists of two elements: plasma, or the liquid portion of blood, and platelets, a type of blood cell that plays an important role in healing throughout the body. Platelets are well-known for their clotting abilities, but they also contain growth factors that can trigger cell reproduction and stimulate tissue regeneration or healing in the treated area. Platelet-rich plasma is simply blood that contains more platelets than normal.

To create platelet-rich plasma, clinicians take a blood sample from the patient and place it into a device called a centrifuge that rapidly spins the sample, separating out the other components of the blood from the platelets and concentrating them within the plasma.

After creating platelet-rich plasma from a patients blood sample, that solution is injected into the target area, such as an injured knee or a tendon. In some cases, the clinician may use ultrasound to guide the injection. The idea is to increase the concentration of specific bioproteins or hormones, called growth factors, in a specific area to accelerate the healing process.

The mechanism behind PRP injections is not completely understood. Studies show that the increased concentration of growth factors in platelet-rich plasma may stimulate or speed up the healing process, shortening healing time for injuries, decreasing pain, and even encouraging hair growth.

PRP injections are used for a range of conditions,* from musculoskeletal pain and injuries to cosmetic procedures.

Tendon, Ligament, Muscle and Joint Injuries

PRP injections may be able to treat a range of musculoskeletal injuries and conditions. For example, chronic tendon injuries such as tennis elbow or jumpers knee can often take a long time to heal, so adding PRP shots to a treatment regimen can help to stimulate the healing process, decrease pain, and enable a return to activities sooner.

Post-surgical Healing

Clinicians first used PRP to accelerate healing after jaw or plastic surgeries. Now, post-surgical PRP injections have expanded to help heal muscles, tendons, and ligaments, as procedures on these tissues have notoriously long recovery times.

Osteoarthritis

Early studies indicate that PRP injections may help treat osteoarthritis pain and stiffness by modulating the joint environment and reducing inflammation, but research is growing.

Hair Loss

PRP injections can be effective in treating male pattern baldness, both in preventing hair loss and promoting new hair growth. PRP can also aid in the stimulation of hair growth after hair transplants.

Skin Rejuvenation

PRP injections are sometimes used as an anti-aging treatment, but there is little evidence to show that PRP reduces wrinkles and other signs of aging.

PRP Therapy Risks and Side Effects

A PRP injection is a low-risk procedure and does not usually cause major side effects. The procedure involves a blood draw, so you should make sure you are hydrated and have eaten beforehand to prevent feeling lightheaded. After the procedure, you may experience some soreness and bruising at the injection site.

Because PRP injections are made up of your own cells and plasma, the risk of an allergic reaction is much lower than with other injectable medications like corticosteroids. Less common risks of PRP injections include:

If you are considering PRP injections, be sure to talk with your healthcare provider about all the benefits and risks.

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Platelet-Rich Plasma Injections | What It's Like Getting PRP Injections Into The Knee as a Skier - SnowBrains

Half of pediatric patients with aHUS benefit from Soliris after… – AHUS News

Treatment withSoliris (eculizumab) helped about half of the children diagnosed with atypical hemolytic uremic syndrome (aHUS) after they received a stem cell transplant, according to a small study.

Among 13 patients who started taking Soliris, seven survived and saw their disease-associated biomarkers normalize. Six died due to complications related to the stem cell transplant.

The study, Eculizumab treatment in paediatric patients diagnosed with aHUS after haematopoietic stem cell transplantation: a HSCT-TMA case series from Japanese aHUS post-marketing surveillance, was published in Bone Marrow Transplantation. The analysis was sponsored by Alexion, now a part of AstraZeneca Rare Disease, which developed Soliris.

aHUS is a type of thrombotic microangiopathy (TMA), a group of diseases wherein blood clots form in small blood vessels. In aHUS, this is caused by abnormal activity of the immune systems complement cascade. While there are often genetic factors, another trigger is typically needed for symptoms to manifest.

One such trigger can be a hematopoietic stem cell transplant (HSCT), which is used to treat a range of blood and autoimmune disorders. It involves transplanting blood cell precursors into a patient to help repopulate their body with healthy blood cells.

Certain immune complications can occur that drive TMA symptoms, however, especially in people with underlying genetic risk factors. TMA is associated with high mortality rates after a stem cell transplant and the appropriate treatment strategy remains to be established. Soliris is approved for aHUS and other complement-mediated diseases, and inhibits the C5 protein to prevent the complement cascades activation, potentially making it an appropriate treatment for managing HSCT-TMA.

Here, scientists retrospectively analyzed clinical data from 13 pediatric patients in Japan who received Soliris after being diagnosed with aHUS following an HSCT procedure, whichwas intended to treat various forms of cancer or immune system diseases. TMA symptoms emerged about a month later, on average.

Three children had existing risk factors for aHUS, including a history or family history of TMA. Eleven patients had complications from the procedure that could have caused the complement cascade to overact, according to the scientists.

All the children were treated with other therapies before starting Soliris, which was initiated a median of 16 days after the onset of TMA. Soliris was infused into the vein, or intravenously, in a similar regimen as that approved for aHUS, with patients receiving a median of three doses.

Over a median observation period of nearly six months, seven patients survived, leading to a predicted survival of 53.8% six months after the onset of HSCT-TMA.

Among the survivors, Soliris decreased levels of lactate dehydrogenase, a marker of organ damage, after 22 days. It also increased the count of platelets, blood clotting cells that are lost as a cardinal aHUS symptom, after a median of 280 days (about nine months).

Median blood levels of creatinine, a marker of kidney damage, didnt change, but four of the seven survivors did see improvements. Three children who previously required dialysis, a blood cleaning procedure for when the kidneys are failing, discontinued it by the last follow-up visit.

None of the survivors had a TMA recurrence over a median of 111.5 days (around 3.6 months) after stopping Soliris.

Three patients died due to ongoing side effects that started before Soliris was initiated and two died due to infection-related side effects that arose after immunosuppressive therapy to treat an HSCT-associated immune complication. One patient didnt respond well to Soliris and died due to TMA.

The survival rates in those treated with Soliris after HSCT-TMA were lower than in a previous report. That could be because in that study, Soliris was started early as a first-line treatment and at individualized dosing regimens.

Early treatment with complement inhibitor and early evaluation of treatment response can be a preferential treatment strategy once complement dysfunction is suspected in HSCT-TMA, the researchers wrote.

No significant prognostic risk factors were identified by comparing survivors with non-survivors, which could be attributed in part to the small nature of the study.

Further research into the risk stratification of HSCT-TMA and the use of C5 inhibitors are needed to confirm appropriate use in HSCT-TMA and to identify factors that might predict patients responses to therapy, the researchers said.

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Half of pediatric patients with aHUS benefit from Soliris after... - AHUS News