Project description:Background: pregnancy is associated with reduced activity of multiple sclerosis (MS). However, the biological mechanisms underlying this pregnancy-related decrease in disease activity are poorly understood. This data series contains the subset of data used to generate a MS signature comparing female healthy specimens with respect to MS patients
Project description:Background: pregnancy is associated with reduced activity of multiple sclerosis (MS). However, the biological mechanisms underlying this pregnancy-related decrease in disease activity are poorly understood. This data series contains the subset of data used to generate a MS signature comparing female MS specimens before pregnancy with respect to female MS specimens at ninth month pregnancy.
Project description:Background: pregnancy is associated with reduced activity of multiple sclerosis (MS). However, the biological mechanisms underlying this pregnancy-related decrease in disease activity are poorly understood. This data series contains the subset of data used to generate a MS signature comparing female healthy specimens with respect to MS patients Subjects were followed in the outpatients clinic and blood was collected before pregnancy and at the following time points during pregnancy: first trimester (gestational age at sampling 12 weeks), second trimester (24 weeks), and third trimester (36 weeks). Before-pregnancy samples were obtained in a treatment-free period and after anticonceptional drug withdrawal. Peripheral blood mononuclear cells (PBMCs) obtained from 15 women (8 MS patients and 7 healthy controls) were analyzed by oligonucleotide microarray technology.
Project description:Background: pregnancy is associated with reduced activity of multiple sclerosis (MS). However, the biological mechanisms underlying this pregnancy-related decrease in disease activity are poorly understood. This data series contains the subset of data used to generate a MS signature comparing female MS specimens before pregnancy with respect to female MS specimens at ninth month pregnancy. Subjects were followed in the outpatients clinic and blood was collected before pregnancy and at the following time points during pregnancy: first trimester (gestational age at sampling 12 weeks), second trimester (24 weeks), and third trimester (36 weeks). Before-pregnancy samples were obtained in a treatment-free period and after anticonceptional drug withdrawal. Peripheral blood mononuclear cells (PBMCs) obtained from 17 women (8 MS patients before pregnancy and 9 MS patients at 9th month pregnancy) were analyzed by oligonucleotide microarray technology.
Project description:We isolated QC cells and obtained their cell-type specific transcriptional profiles in a WT and in a pan mutant background by sorting GFP+ cells marked with pWOX5::GFP.
Project description:We isolated QC and CEI cells and obtained their cell-type specific transcriptional profiles in a WT and in a wox5 mutant background by sorting GFP+ cells marked with pWOX5::GFP and pCYCD6::GFP.
Project description:These files represent single cell RNA-Seq data generated on a 10x Chromium genomics platform from three biological replicates from the embryonic day (E)18.5 developing mouse kidney and three biological replicates of iPSC-derived human kidney organoids differentiated according to our published protocol (Takasato et al., Nature Protocols 2016). When aggregated, the mouse data represents >6000 cells that passed our QC, containing most major cell types known to exist in the developing mouse kidney. The aggregated human organoid data contains of >7000 cells that passed our QC and contains populations representing endothelial cells, podocytes, stroma, nephron, and off-target populations with similarity to neurons.
Project description:Background: pregnancy is associated with reduced activity of multiple sclerosis (MS). However, the biological mechanisms underlying this pregnancy-related decrease in disease activity are poorly understood. This data series contains the subset of data used to generate a healthy donors signature comparing female healthy specimens before pregnancy with respect to female healthy specimens at ninth month pregnancy.
Project description:Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collected 2638 files acquired by data independent acquisition (DIA) and paired DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data showed that DIA-based LC-MS/MS related consensus QC metric is more sensitive than DDA-based QC in detecting MS status changes. We then optimized 15 DIA-QC metrics, and invited to manually assess the quality of 2638 DIA files generated by 21 mass spectrometers based on each metric. Based on the annotation results, we developed an AI model for DIA-based QC in the training set of 2059 DIA files, and predicted the liquid chromatography (LC) performance with an AUC of 0.91 and the MS performance with an AUC of 0.97 in an independent validation dataset (n = 523). Finally, we developed an offline software called iDIA-QC for convenient adoption of this methodology for LC-MS QC