Stem Cell Clinic

Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with … – Nature.com

Genetic algorithm

We used the GA to optimize the conductance of each current so that the AP model reproduced the experimental values in previous studies24,29. We executed the GA optimization using a program implemented in C# with reference to the method of Bot et al.55, and its type was a real-coded GA. We evaluated the degree of adaptation of each model in the population using the score calculated using Eq.(1). We calculated the AP for each model 60s after the initial state. We performed numerical integration to compute APs using the forward Euler method with a time step of 0.01ms. The initial values of ion concentration inside and outside the cell, and temperature were equivalent to the conditions of the experiments. We fixed the intracellular potassium and sarcoplasmic reticulum calcium concentrations to accelerate convergence. We estimated the cell volume from the cell surface area data24,56. We used the same value as that in the Paci model for the ratio of the sarcoplasmic reticulum volume to the cytoplasmic volume23. We used a model population with random values assigned to each conductance as the starting generation. The upper and lower scaling limits were 0.010.0 for GNa, GCaL, and Gf in the ventricular-type model and 0.05.0 for all others. We describe the details of the GA optimization of AP models in the Supplementary Methods.

To estimate magnetic signals from iPS-CMs, we simulated the 2D electrical activity of the cell population. We set the intracellular ion concentrations using adult mouse cardiac AP model values57. We determined the extracellular ion concentrations from the composition of the culture medium and set the temperature to room temperature (RT: 24C). The temperature coefficients (Q10) used in the AP models referred to values from the published literature58. We computed the solution to the partial differential Eq.(2) using the CrankNicolson method, with the spatial step set to x=y=60m and the time step set to t=0.01ms. We determined the averaged cellular resistivity to reproduce the conduction velocity measured in neonatal rat cardiac cell sheets40 (Supplementary Methods and Supplementary Fig. S7). The list of parameters used in the simulation is summarized in Supplementary Table S3. We calculated the magnetic field using BiotSavart's law from the currents flowing in the cells at each time point. We estimated the observed waveforms using integration in the area of each pickup coil. We assumed that the cancellation component of the magnetic field caused by the extracellular return current was negligibly small because the volume of the medium was sufficiently large relative to the spreading of cultured cells. We also checked how much the observed waveforms were affected when the cell position was shifted from directly under the sensor. As a result, we confirmed that a displacement of2mm in the x-axis or y-axis directions had almost no effect on the measurements (Supplementary Fig. S8).

The procedure for dataset preparation is as follows: A peak region (250ms) was cut from the magnetic signals estimated using simulation and subjected to random stretching and scaling. Non-peak regions between peak regions were linearly interpolated to make data of 120s each. For the background noise, four data of the x component of the magnetic field with no current applied (for artificial signal experiments) or eight data of the y component with no cell sample placed (for cell experiments) were used in equal proportions within each dataset. Random time shifts were performed in the superposition of these magnetic signals and noise data. Even when the cycle length and amplitude were fixed, this shift brought diversity to the dataset. Finally, datasets (n=160 for artificial signal experiments or 640 for cell experiments) were generated, including three data types in a 1:1:2 ratio: positive peak direction, negative peak direction, and background noise only. Representative waveforms are shown in Supplementary Fig. S9.

The window used in the spectral calculation with the FSST33 was the Kaiser window, with a size of 512 points. The sidelobe attenuation was 13.6dB. The real and imaginary parts of the spectral were input as separate features. The input values were pre-standardized by subtracting the mean and dividing by the standard deviation. Training was iterated for up to 60 epochs (one epoch means one round of data). The network was validated using the validation data for each epoch. If the validation loss exceeded the previous minimum value more than ten times, it was decided that there was no further improvement and training was stopped. The initial learning rate was set to 0.001 and the learning rate was dropped by a factor of 0.1 every 20 epochs. The training data were divided into segments of 10s lengths and the mini-batch size (a subset of the training data used in one step to evaluate the gradient of the loss function and update the weights) was set to 16.

We calculated the AUROC36 to evaluate network classification performance. The AUROC is the area under the curve plotted with the false positive rate on the horizontal axis and the true positive rate on the vertical axis. The AUROC is 1.0 when separation performance is best and 0.5 when classification is performed randomly. In this study, we defined each data point as positive if it was peak (P) or negative if it was non-peak (N).

From the output label data, we plotted a histogram of the lengths of segments labeled as class P (Fig.4f). Using this histogram as a reference, we estimated the appropriate distribution of peak region lengths, set a lower limit, and identified segments longer than this threshold as peak regions (Fig.1c). We used the average count number for the analysis of samples measured multiple times. We obtained the average waveform by superimposing magnetic signals of 175ms before and after the center position of each peak region and averaging their amplitudes. Then, we repeated the adaptive correlation filter59 ten times to correct for positional fluctuations.

A vector-type SQUID magnetometer12,15 was applied to measure magnetic fields. The vector-type SQUID magnetometer had an axial-type first-order gradiometric pickup coil with a diameter of 15.5mm and two planar-type first-order gradiometric squared pickup coils of 915.5 mm2 and 1115.5 mm2. The baseline length of each gradiometric pickup coil was 50mm. The three gradiometric pickup coils were oriented perpendicular to each other and assembled on a cylindrical bobbin. Three Ketchen-type low-temperature SQUIDs were individually coupled to each pickup coil and simultaneously detected the three independent components of the magnetic field: Bx, By, and Bz. The SQUID readouts were connected to double-integrator type flux-locked loop (FLL) circuits for output linearization and dynamic range improvement. The total noise level, including environmental noise, was 1020 fT/Hz at 10Hz. The SQUID magnetometer was installed in a glass-fiber reinforced plastic (GFRP) cryostat with an MSB. The MSB comprised two 1mm thick mu-metal layers with double front doors. The shielding factor of the MSB was more than 40dB at 10Hz. The GFRP cryostat consisted of a cylindrical main body that stored 6-L liquid helium and a narrow GFRP tube that dropped from the bottom of the main body. The main body was installed in the ceiling of the MSB and only the GFRP tube penetrated the MSB through a hole in its top. The SQUID magnetometer was installed at the bottom end of the GFRP tube and placed at the center of the MSB.

The cell sample was placed on a height-adjustable stage made of non-magnetic materials and adjusted to 3mm from the bottom edge of the pickup coil. Measurements were taken at room temperature, and the FLL readout signals were digitally recorded at the sampling rate of 1kHz with HPF at 3Hz, LPF at 100Hz, and notch filters at 60Hz.

We kept the resistance fixed and varied the output voltage of the function generator to adjust the current that generated magnetic signals. With no filtering, we increased the voltage until the peak of the magnetic signal could be identified by visual inspection and recorded the peak amplitude at that point. Based on that value, we adjusted the voltage to generate the desired magnetic signals. We enhanced the artificial signal (2.74) so that the signal-to-noise ratio was equivalent to that in the cell sample experiment. To confirm the validity of this procedure, we compared the amplitude spectrum densities of the background noise between the artificial signal experiment and the cell sample experiment (Supplementary Fig. S4). Although differences in amplitude existed, the spectral distribution had the same trend within the range of 3.540Hz used to train the LSTM networks.

We implemented the scaled template technique following previous research22. We slid the template (the event waveform of interest to detect) along the time series data and scaled it to fit the data at each position. Then, we divided the template scaling factor by the standard error of the time series data, which was the detection criterion, and we considered the event waveform of interest to be detected when this criterion exceeded a threshold value. The template was a peak waveform of 250ms in length cut from the magnetic signal estimated using numerical simulation, which we also used as the training data in deep learning. To compare the two methods without bias, we set the threshold so that the number of detected peaks from background noise was equal to that of deep learning.

The mouse iPS cell line iPS-MEF-Ng-20D-17 (Expressing GFP by Nanog promoter)44, established by the Center for iPS Cell Research and Application, Kyoto University, was provided by the RIKEN BRC through the National BioResource Project of the Ministry of Education, Culture, Sports, Science, and Technology, Japan. For the culture method, we referred to previous studies44,60,61. To maintain the undifferentiated state of iPS cells, MEFs (EmbryoMax Primary Mouse Embryonic Fibroblasts, PMEF-NL, Neo Resistant, Strain FVB; purchased from Sigma-Aldrich, St Louis, MO, USA), in which cell proliferation was arrested by mitomycin C (Nacalai Tesque, Kyoto, Japan) treatment, were cocultured as feeder cells. The maintenance medium was composed of Dulbecco's modified Eagle's medium (Sigma-Aldrich) with 15% fetal bovine serum (Equitech-Bio Inc., Kerrville, TX, USA), 50 U/ml penicillin, 50g/ml streptomycin (Sigma-Aldrich), 2mM L-glutamine (Sigma-Aldrich), nonessential amino acids (100) (Sigma-Aldrich), 0.1mM 2-mercaptoethanol (FUJIFILM Wako Chemicals, Osaka, Japan), and 0.1% human leukemia inhibitory factor (FUJIFILM Wako Chemicals). The medium was refreshed daily and iPS cells were passaged every two days. Colonies were detached with 0.25% trypsin/1mM EDTA (FUJIFILM Wako Chemicals), dispersed in cell suspension, counted, and 1.0106 cells were seeded into MEFs on 60mm plates.

Based on previous studies37,62, cardiomyocyte differentiation was induced by forming EB. The differentiation medium was Iscove's modified Dulbecco's medium (Sigma-Aldrich) containing 20% fetal bovine serum, 50 U/ml penicillin, 50g/ml streptomycin, 2mM L-glutamine, nonessential amino acids (100), and 0.1mM 2-mercaptoethanol. Mouse iPS cells were suspended at 1.5104 cells/ml in the differentiation medium and seeded 0.2ml into each well of a 96-well U-shaped-bottom microplate (Nunclon Sphera; Thermo Fisher Scientific, Waltham, MA, USA). The plates had a cell-nonadherent surface treatment, which allowed uniform and stable EBs to form. For further differentiation, the culture was switched from floating to adherent on day 5. Plastic dishes of 100mm diameter and MEA (Alpha MED Scientific, Osaka, Japan) were used for magnetic measurement, and glass bottom dishes (AGC Techno Glass, Shizuoka, Japan) were used for fluorescence microscopy. These dishes were coated with 0.1 w/v% gelatin solution (FUJIFILM Wako Chemicals) and one EB was transplanted at the center of each dish. Beating areas began to appear on day 7. Magnetic measurement was performed during days 1921 when the area of differentiated cells was extensive and synchronized beating was observed. Fluorescence microscopy was also performed at this time. To ensure that one peak corresponded to the electrical activity of the entire cell population, samples with a single beating area larger than 3mm square were selected for measurement. To bring the cells closer to the sensor, the cylinder of the MEA was excised to a height of 1mm. For comparison with iPS-CMs, MEFs were also cultured in cloning rings with an inner diameter of 5mm. In the experiment to detect the drug's chronotropic effects from magnetic signals, the medium was replaced with a medium supplemented with isoproterenol at a final concentration of 10M, and magnetic signals were measured from iPS-CMs after incubation for 30min.

Cardiomyocytes were immunostained on day 19 of differentiation, and the expression of cardiomyocyte marker cardiac troponin T and connexin 43 that forms gap junctions was confirmed. iPS-CMs were fixed in 4% paraformaldehyde for 20min at 4C, followed by blocking with 5% goat serum (Nichirei, Tokyo, Japan) and 0.1% Triton-X diluted in Dulbecco's phosphate buffered saline (DPBS) for 20min at RT. The cells were washed three times for 5min with DPBS and incubated with a primary antibody diluted in DPBS containing 1% goat serum for 1h at RT and then overnight at 4C. The primary antibodies were rabbit polyclonal IgG anti cardiac troponin T antibody (1.4g/mL; Proteintech, Rosemont, IL, USA) and rabbit polyclonal IgG anti connexin 43 antibody (10g/mL; Thermo Fisher Scientific). The cells were washed three times for 5min with DPBS with shaking and further incubated with the secondary antibody Alexa fluor 546 goat anti rabbit IgG (Invitrogen, Carlsbad, CA, USA; 1:1000 dilution in DPBS/0.05% Triton X-100) for 30min at RT. The cells incubated with connexin 43 antibody were also treated with Alexa fluor 488 Phalloidin (Thermo Fisher Scientific; 1:50 dilution in DPBS/0.05% Triton X-100) and stained for actin filaments. The cells were washed three times with tris buffered saline for 5min and once with DPBS for 5min, and immersed in 4',6-diamidino-2-phenylindole (DAPI)-added anti-fading agent (Nacalai Tesque). Observation and imaging were performed with an IX71 fluorescence microscope (Olympus, Tokyo, Japan).

We measured FPs using MEA38. We selected the electrode near the center of the beating area and recorded the potential difference between it and a reference electrode not in contact with the cells. To avoid noise when measuring simultaneously with magnetic signals, we output the electrical signals from the probe externally through an IC clip and did not use the attached connector. When measuring FP only, we used it. We performed the measurement at room temperature and recorded data at the sampling rate of 1kHz with HPF at 0.16Hz, LPF at 160Hz, and notch filters at 60Hz.

Deep learning network training and data classification were performed in MATLAB (Mathworks Inc., Natick, MA, USA). The GA for parameter optimization of the AP model and the numerical simulation of the electrical activity of cardiomyocytes were performed using our programs implemented in C#.

Data are presented as meanstandard error of the mean (SEM). Comparisons between two groups were analyzed using the unpaired t-test unless otherwise indicated. For comparisons of three or more groups, when equal variances could be assumed, one-way ANOVA was used, followed by Tukey's test as a post hoc test. When equal variances could not be accepted, the BrownForsythe correction was performed, followed by the GamesHowell test as a post hoc test. Differences between data were considered statistically significant at p<0.05.

See the rest here:
Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with ... - Nature.com

Orthogonal analysis of mitochondrial function in Parkinson’s disease patients | Cell Death & Disease – Nature.com

Human subjects

PD patients were recruited from the outpatient clinic for Movement Disorders of the Department of Neurology of the Leiden University Medical Center (Leiden, the Netherlands) and nearby university and regional hospitals. All participants fulfilled the U.K. Parkinsons Disease Society Brain Bank criteria for idiopathic PD. The study was approved by the medical ethics committee of the Leiden University Medical Center (P12.194/NV/ib), and written informed consent was obtained from all PD patients.

Fibroblasts were isolated at Leiden University Medical Center from skin biopsies derived from the ventral side of the upper leg and cultured under highly standardized conditions as previously described in [14]. Peripheral whole blood was collected from PD patients at Leiden University Medical Center and PBMCs were isolated at the Department of Molecular Genetics at the Erasmus Medical Center in Rotterdam. Control iPSC were obtained from the Eramsus MC iPS Core facility.

Peripheral whole blood from 24 age-matched healthy controls (age >55 years) was obtained from Sanquin Rotterdam (NVT0585.00 Mantel, NVT0585.01 Annex).

Bioinformatic analysis was performed using the Parkinsons Progression Markers Initiative (PPMI) database.

To generate erythroblasts, PD patients peripheral blood mononuclear cells (PBMC) were extracted from 10ml of freshly extracted blood with the use of Lympholyte-H (Cedarline) and Leucosep polypropylene tubes (227290, Greiner) according to manufacturers indications. Briefly, blood was diluted in PBS at a 1:2 ratio and loaded on a 15mL Lympholyte Leucosep tube. Blood was centrifuged at 800g for 25min with no brakes at 4C. Upon removal of the plasma, the PBMC enriched cell fraction was collected, washed several times with sterile PBS and upon PBMCs were cultured in StemSpan SFEM medium (Stemcell Technologies) containing 2mM Ultraglutamine (Lonza), 1% Nonessential aminoacids (NEAA), 1% penicillin/streptomycin, 50ng/ml Stem Cell Factor, 2U/ml Erythropoietin, 1uM Dexamethasone (Sigma), 10ng/ml Interleukin-3 (R&D Systems), 10ng/ml Interleukin-6 (R&D Systems), 40ng/ml IGF-1 (R&D Systems) and 50ug/ml Ascorbic Acid (Merck) for 69 days refreshing half of the medium every other day starting from day 2. Erythroblasts were isolated when reaching 6070% of the total cell population by gradient centrifugation at 1000g for 20minutes at room temperature over Percoll (GE Healthcare). Isolated erythroblasts were frozen in FBS containing 10% DMSO at 80C. Metabolic analysis was performed within 2 days after thawing.

PD patients fibroblasts used in this study were prepared and isolated at Leiden University Medical Center from skin biopsies derived from the ventral side of the upper leg and cultured under highly standardized conditions as previously described in [14]. The study was approved by the medical ethics committee of the Leiden University Medical Center, and written informed consent was obtained from all PD patients.

Fibroblasts were reprogrammed to pluripotent stem cells using the CytoTune-iPS 2.0 Sendai Reprogramming Kit (A16517, Thermo Fisher) according to the manufacturers protocol.

Human iPSC lines were generated as previously described [18]. Briefly, to generate embryoid bodies with neuroepithelial outgrowths (EBs), iPSC colonies were dissociated with 2mg/mL collagenase IV and transferred to non-adherent plates in hESC medium.

(Dulbeccos modified Eagles medium (DMEM)/F12 (Thermo Fisher Scientific), 20% knockout serum (Thermo Fisher Scientific), 1% minimum essential medium/non-essential amino acid (NEAA, Sigma-Aldrich, St Louis, MO, USA), 7nlml1 -mercaptoethanol (Sigma-Aldrich), 1% L-glutamine (Thermo Fisher Scientific) and 1% penicillin/streptomycin (P/S, Thermo Fisher Scientific) supplemented with 10M SB-431542 (Ascent Scientific), 1M dorsomorphin (Tocris), 3M CHIR 99021 (Axon Medchem) and 0.5M Purmorphamine (Alexis) on a shaker in an incubator at 37C/5% CO2. On the second day, medium was replaced with N2B27 medium [DMEM-F12/neurobasal 50:50 (Thermo Fisher Scientific), 1% P/S, 1:100 B27 supplement lacking vitamin A (Thermo Fisher Scientific) and 1:200 N2 supplement (Thermo Fisher Scientific)] containing 10M SB-431542, 1M dorsomorphin, 3M CHIR99021 and 0,5M Purmorphamine. On day 4, N2B27 medium was replaced and supplemented with 3M CHIR99021, 0.5M Purmorphamine, and 150M Ascorbic Acid (Sigma).

On day 6, EBs were slightly triturated and plated on Matrigel-coated (Matrigel - 354277, Corning) plates at a density 1015 EB per well containing smNPC expansion medium (N2B27 medium containing 3M CHIR 99021, 200M Ascorbic Acid, 0.5M Purmorphamine) and expanded for 5 passages before final differentiation. The medium was refreshed every other day.

smNPC were dissociated with Accutase at RT, diluted, and seeded on Poly-D-lysine Matrigel-coated cover glasses in a 12-well plate at the concentration of 5104 cells per well in the Patterning medium [N2B27 medium containing 1ng/mL GDNF (Peprotech), 2ng/ml BDNF (Pepotech), 200M Ascorbic Acid and 0.5M Smoothened Agonist (SAG Pepotech)]. The medium was refreshed every 2 days.

At day 8, the medium wash switched to the Maturation medium containing N2B27 medium, 2ng/ml GDNF, 2ng/ml BDNF, 1ng/mL TGF-b3 (Peprotech), 200M ascorbic Acid and 5ng/ml of ActivinA for the first feeding and 2ng/ml ActivinA for the following feedings. Medium change occurred every third day.

Erythroblasts and iPSCs were washed and resuspended in FC buffer (HBSS w/o calcium and magnesium + 0.5% BSA) and incubated with PE Mouse Anti-Human CD44 antibody (1:25, BD, 550989), FITC Mouse Anti-Human CD71 antibody (1:50, BD, 555536), or 7-AAD (Thermo Fisher, A1310) for 30min at 4C. Mitochondria were stained with Mitotracker Green FM (100nm, Cell Signaling, 9074) and active mitochondria with TMRM (100nm, Thermo Fisher, T668) for 30min at 37C. Cells were detected by flow cytometry using a LSRFortessa Cell Analyzer (BD, USA). Flowjo software (BD, USA) was used for data analysis.

Oxygen consumption rates (OCR) and extracellular acidification rate (ECAR) were measured using a XF-24 Extracellular Flux Analyzer (Agilent Technologies), as previously described [14]. Erythroblasts were seeded at a density of 2105 cells/well on Cell-Tak (Corning, 354240) coated Seahorse plates in unbuffered XF DMEM medium (Agilent Technologies) supplemented with 1mM sodium pyruvate, 2mM glutamine and 10mM glucose or galactose. Immediately after seeding, cells were centrifuged at 200g for 1minute to attach evenly to the bottom of the well and the plate was equilibrated for 30minutes at 37C in the absence of CO2. iPSCs derived from fibroblasts of PD patients and healthy controls were seeded at a density of 8103 cells/well on Seahorse plates and differentiated to dopaminergic neurons over a period of 3 weeks according to the described methodology. On an experimental day, the medium was changed to an unbuffered XF DMEM medium supplemented with 1mM sodium pyruvate, 2mM glutamine and 10mM glucose or galactose. Cells were incubated for 1h at 37C in the absence of CO2, before the Seahorse assay. For each assay, medium and reagent acidity were adjusted to pH 7.4 on the day of the assay, according to the manufacturers procedure. Optimal cell densities were determined experimentally to ensure a proportional response to FCCP (oxidative phosphorylation uncoupler).

After 3 measurements to detect the oxygen consumption ratio baseline, cells were then challenged with sequential injections of mitochondrial toxins: 1M oligomycin (Adenosine triphosphate ATP - synthase inhibitor), 1M FCCP, and 1M antimycin (complex III inhibitor). A minimum number of 5 replicates were performed for each cell line; data represent the mean of the different replicates. Basal respiration (measured as the average OCR rates at the baseline), maximal mitochondrial respiration (maximal respiration), reserve capacity (difference between maximal respiration and basal respiration), and respiration dedicated to ATP production (difference between basal respiration and oligomycin-dependent respiration) were used to investigate mitochondrial bioenergetics. Basal glycolysis, measured as extracellular acidification rate (ECAR) maximal glycolysis and reserve glycolytic capacity (difference between maximal glycolysis and basal glycolysis) were taken into account to investigate glycolytic properties.

Reprogrammed iPSCs cells cultured in an 8-chamber slide were fixed with 4% PFA for 15min at room temperature. After incubation in ice-cold methanol for 10min cells were permeabilized in 0.1% Triton in PBS for 10min and blocked using 1% BSA in PBS/0.05% Tween-20 for 30min. Next, cells were incubated with primary antibodies diluted in blocking buffer overnight at 4C - Mouse Anti-Human TRA1-81 (1:75, Abcam, AB16289#20), Rabbit Anti-Human OCT4 (1:250, Abcam, AB19857#8), Goat Anti-Human NCAM (1:100, R&D, AF2408), Goat-Anti Human SOX17 (1:100, R&D, AF1924) or Mouse Anti-Human Beta-Tubulin (1:1000, Merck, T8660) primary Chicken Anti-Human MAP2 (1:2000, Abcam, AB5392), Mouse Anti-Human TH (1:200, Millipore, MAB318). After washing with PBS cells were incubated with respective secondary Goat Anti-Mouse Alexa Fluor 546 (1:500, Invitrogen, A21045), Goat Anti-Rabbit Alexa Fluor 488 (1:500, Invitrogen, A11008#8a), Donkey Anti-Goat Alexa Fluor 488 (1:500, Invitrogen, A11055) or Goat Anti-Mouse Dylight 594 (1:500, Jackson, 115-515-166#7) antibodies diluted in blocking buffer for 1h at room temperature. Nuclei were stained with Hoechst 33342 (1:1000 in PBS, Thermo Fisher) for 10min. Cells were next washed with PBS, mounted with ProLong Diamond Antifade Mountant (P36965, Thermo Fisher), and imaged using a Leica Stellaris5 confocal microscope.

Blood transcriptome data from the Parkinson Progressive Markers Initiative (PPMI) cohort (PPMI website: https://ida.loni.usc.edu/pages/access/geneticData.jsp#441) were obtained. The libraries were prepared using the NEB/Kapa (NEBKAP) based library prep, with second-strand synthesis. RNA sequencing was performed at Hudson Alphas Genomic Services Lab on an Illumina NovaSeq6000, generating 100 million 125bp paired reads per sample. The Salmon files were imported into R using Tximport. To identify differentially expressed genes between PD groups and controls, the DESeq2 package was used. Normalized counts were subjected to Rlog transformation to improve distances/clustering for the principal component analysis (PCA). The cohort of subjects was divided into subgroups based on the delta-UPDRS-III (MDS-Unified Parkinsons Disease Rating Scale, UPDRS-III at last visit - UPDRS-III at first visit) of PD subjects: those with a delta-UPDRS-III less than 0 (defined as mild) and those with a delta-UPDRS-III greater than 0 (defined as severe), as well as controls (CTRL). A threshold of significance at FDR<0.05 was applied.

Gene Set Enrichment Analysis (GSEA) was conducted on an unfiltered, ranked list of genes. The analysis involved various terms from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome Pathway Databases, Hallmark Gene Set Collection, and WikiPathways (GSEA website: http://www.gsea-msigdb.org/gsea/msigdb/collections.jsp). Pathway information was obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) available at the Molecular Signatures Database (http://www.broadinstitute.org/gsea/msigdb/index.jsp) or from the Hallmark Gene Set Collection (http://www.gsea-msigdb.org/gsea/msigdb/collections.jsp). Gene set enrichment with FDR<0.1 was considered significant. Genes in each PD group were ranked based on the level of differential expression using a signal-to-noise metric and a weighted enrichment statistic.

Transcriptomic analysis was performed using R Studio version 4.2.3. The experiments were conducted with a minimum of three independent biological replicates. GraphPad Prism version 9 (GraphPad Software, La Jolla California USA) was used for all statistical analyses and graphical representations. P values were denoted as *P<0.05, **P<0.01, ***P<0.001, and were considered significant. In the absence of indications, comparisons should be considered non-significant. Comparisons between two groups were analyzed using unpaired two-tailed Students t-tests, and comparisons between more than two groups were analyzed using either one-way ANOVA followed by Dunnetts (comparison of PD means vs. healthy subjects) or Tukeys (comparison of all the means) posthoc test for multiple comparisons.

Go here to see the original:
Orthogonal analysis of mitochondrial function in Parkinson's disease patients | Cell Death & Disease - Nature.com

Targeting Age-Related Macular Degeneration With Stem Cell Therapy – BioProcess Online

Age-related macular degeneration (AMD), a common eye disorder leading to permanent loss of central vision, is the leading cause of blindness in developed countries. Current treatments for AMD are often ineffective, particularly for dry AMD, the most common form of the disorder. Cell therapy technologies offer potential new treatments for AMD, however, the efficacy of such treatments depends on the ability to deliver therapeutic cells to the target region and to produce enough RPE cells. On the back of the success of Induced pluripotent stem cell (iPSC) technology, a novel stem-cell therapy based upon iPSC-derived RPE cell transplantation was conceptualized as a promising new treatment for AMD and other retinal diseases. Bio-Techne aims to offer a range of animal-free cell culture products and GMP proteins for clinical manufacturing, which may boost the success of cell therapies. iPSC-based cell therapy is seen as a promising solution for AMD patients unresponsive to traditional treatments.

Read the original post:
Targeting Age-Related Macular Degeneration With Stem Cell Therapy - BioProcess Online