Control human putamen and Substantia Nigra
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ABSTRACT:
PROVIDER: EGAS00001003065 | EGA |
REPOSITORIES: EGA
Similar Datasets
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2022-08-12 | PXD033144 | Pride
Project description:Simple Markov model.
There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal.
The yearly transition probabilities are:
Healthy to Dead: 0.01; Healthy to Sick: 0.2 for Male and 0.1 for Female; Sick to Healthy: 0.1; Sick to Dead: 0.3.
The transition probability now depends on the cohort (Male or Female) and can be expressed as a function of a Boolean covariate Male.
Initial conditions: Healthy = (50 Male, 50 Female), Sick = (0,0) and Dead = (0,0).
Output: Number of men and women in each disease state for years 1-10.
2019-01-30 | MODEL1803120004 | BioModels
Project description:Males are 50% more likely to develop end stage kidney failure compared to women. In this study we wanted to find out the molecular mechanism responsible for this increased risk. We collected kidney samples from patients with and without kidney disease and performed a comprehensive gene expression analysis in healthy and diseased male and female kidneys. Interestingly, the set of gender biased genes in healthy kidneys were different from those in diseased kidneys indicating not only baseline gene expression differences but also that the male and female kidney respond differently to disease condition. Our studies indicate that men and women with kidney problems might need to be treated differently. Keywords: Gender difference
2010-04-13 | GSE12682 | GEO
Project description:Model with functions depending on Age, Male, BP (Blood Pressure).
There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal. The yearly transition probabilities are: Healthy to Dead: Age/1000; Healthy to Sick: According to function F1 depending on Age and Male and BP; Sick to Healthy: 0.1; Sick to Dead: according to function F2 depending on Age and Male.
Pre-Transition Rules: Age increased by 1 and BP by Age/10 each simulation cycle. Post-Transition Rules: Treatment = BP>140 , becomes 1 when BP crosses 140 threshold; BP =BP-Treatment*10 , meaning a drop of 10 once treatment is applied; CostThisYear = Age + \Treatment*10 , cost depends on age and if treatment was taken; Cost= Cost + CostThisYear , it accumulates cost over time.
Initial conditions: Healthy = (50 Male, 50 Female with Age =1,2,...,50 for each individual), BP =120, Sick = (0,0) and Dead = (0,0).
Output: Number of men and women in each disease state for years 1-10 and their ages and costs in each state. A stratified report by male and female and young – up to age 30 and old above age 30 is produced.
2019-01-30 | MODEL1803120006 | BioModels
Project description:Previous studies suggest that there may be age and gender related differences in salivary gland function. However, the limited and often conflicting information available from healthy populations makes it difficult to confirm these differences. The purpose of the present study was to evaluate and compare changes in gene expression associated with age and gender in the human parotid gland. Differential expression, defined as statistically significant differences with at least 1.5 fold changes, was detected using the Affymetrix® GeneChip® HGU133plus2.0 microarray in 787 gene probe sets; 320 showed higher expression in males, while 467 showed higher expression in females. Several genes associated with saliva secretion were differentially expressed in male and female parotid gland including vesicle-associated membrane protein 3 VAMP3, synaptosomal-associated protein SNAP23, RAS oncogene family member RAB1A, syntaxin binding protein STXBP1. When the gene expression results from the youngest (19-38 years old) and the oldest (65-69 years old) female subjects were further evaluated, it was found that the expression of 228 genes were altered during aging; 155 genes were down-regulated, whereas 73 genes were up-regulated in the female parotid gland. Of the genes that were altered during aging, 24 of the 28 genes (86%) classified as being associated with immune responses were down-regulated in the aged parotid gland. A panel of differentially expressed, age- and gender-related genes was selected for further study by quantitative, real-time RT-PCR. Comparable differences in gene expression were detected by both Affymetrix array and quantitative, real-time RT-PCR methods. Taken together, our data suggest that salivary gland function may be adversely affected in the aged population due, at least in part, to the down regulation of several categories of genes. Moreover, the gender specific gene expressions identified in the present study correlates with the previously observed sexual dimorphism in salivary gland function. Experiment Overall Design: Human parotid glands were obtained from healthy male and female subjects (19-85 years of age). 3 young female parotid glands were compared with 3 older female parotid gland. 8 Female samples were compared with 5 male samples
2009-01-13 | E-GEOD-8764 | biostudies-arrayexpress
Project description:Model dependent on changing parameters.
There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal.
The yearly transition probabilities are:
Healthy to Dead: Age/1000; Healthy to Sick: according to function F1 depending on Age and Male parameters; Sick to Healthy: 0.1; Sick to Dead: according to function F2 depending on Age and Male parameters. Pre-Transition Rules: Age increased by 1 each cycle.
Initial conditions: Healthy = (50 Male, 50 Female with Age =1,2,…,50 for each individual), Sick = (0,0) and Dead = (0,0).
Output: Number of men and women in each disease state for years 1-10 and their ages in each state.
2019-01-30 | MODEL1803120005 | BioModels
Project description:Males are 50% more likely to develop end stage kidney failure compared to women. As a model of the human condition we analyzed gene expression changes in healthy and diseased mouse kidneys. Interestingly, the set of gender biased genes in healthy kidneys were different from those in diseased kidneys indicating not only baseline gene expression differences but also that the male and female kidney respond differently to disease condition. Keywords: Gender difference
2009-12-01 | GSE12683 | GEO
Project description:Males are 50% more likely to develop end stage kidney failure compared to women. In this study we wanted to find out the molecular mechanism responsible for this increased risk. We collected kidney samples from patients with and without kidney disease and performed a comprehensive gene expression analysis in healthy and diseased male and female kidneys. Interestingly, the set of gender biased genes in healthy kidneys were different from those in diseased kidneys indicating not only baseline gene expression differences but also that the male and female kidney respond differently to disease condition. Our studies indicate that men and women with kidney problems might need to be treated differently. Keywords: Gender difference We collected 42 kidney samples from healthy living transplant donors, nephrectomies and from diagnostic kidney biopsies. Preliminary studies did not show significant gene expression differences in control kidneys based on the collection method (i.e. living kidney biopsy vs. unaffected portion of tumor nephrectomy). We grouped the tissue samples based on the histological readings of the kidney biopsies. Samples with evidence of glomerular and tubulointerstitial fibrosis were assigned into the diseased group. Characteristics of the research participants indicate diverse ethnic and disease groups and mild (StageIII) CKD. The tissue was microdissected into glomerular and tubulointerstitial fractions and expression arrays were performed separately.
2010-04-13 | E-GEOD-12682 | biostudies-arrayexpress
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2020-02-17 | PXD015610 | Pride
Project description:We examined the genetic profile of postmortem brain (hippocampal) samples; 15 brains from patients diagnosed with MDD were matched to brains from healthy subjects based on gender, race and age. Gene expression profiles in the dentate gyrus and CA1 subregions of the hippocampus were assessed by cDNA hybridization to 48K human HEEBO whole genome microarrays (Microarray, Inc). Two-group comparison: MDD (13 male, 8 female) vs. Control (11 male, 7 female). Dentate Gyrus (DG): 15 pairs of samples (1 array per pair); CA1: 15 pairs of samples (1 array per pair). Biological replicates. We can not provide a list of normalized values for each individual hybridization (per chip), but rather have a list of average expression values for all hybridizations used in the experiment (n=15). See supplementary files below. CODES: AAm, African American; C, Caucasian; CO, carbon monoxide; CVD, cardiovascular disease; ETOH, ethanol; F, female; Hx, history of alcohol abuse but not currently active; M, male; MDD, Major Depressive disorder, ND, no psychotropic medication detected; NOS, not otherwise specified, OD, drug overdose; PE, prior episode of major depression with psychotic features; PMI, postmortem interval (hours); SIGSW, self-inflicted gunshot wound; [1], Psychotrophic prescriptions within last month; [2], MDD in remission; [3], prescriptions for six days prior to death; *, samples present only in array sets for the dentate gyrus; **, samples present only in array sets for CA1.
2010-10-17 | E-GEOD-24095 | biostudies-arrayexpress