Project description:Differences in female and male immunity may contribute to variations in response to infections and predisposition to autoimmunity. The characterization of the mechanisms that drive differential neutrophil phenotypes between genders has been investigated. This provides new insights that distinct sex difference in neutrophil biology related to responses to type I IFNs, immunometabolism and maturation status that may have prominent functional and pathogenic implications. The transcriptome of neutrophils from healthy adult males and females was characterized using bulk RNASeq. The transcriptome of whole blood leukocytes was elucidated using scRNASeq.
Project description:Differences in female and male immunity may contribute to variations in response to infections and predisposition to autoimmunity. The characterization of the mechanisms that drive differential neutrophil phenotypes between genders has been investigated. This provides new insights that distinct sex difference in neutrophil biology related to responses to type I IFNs, immunometabolism and maturation status that may have prominent functional and pathogenic implications. The transcriptome of neutrophils from healthy adult males and females was characterized using bulk RNASeq. The transcriptome of whole blood leukocytes was elucidated using scRNASeq.
Project description:Genome wide DNA methylation profiling of peripheral blood samples. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs. Samples included 63 of male samples,and 54 of female samples from peripheral leukocytes. All samples were healthy controls.
Project description:This project examined if sex differences in K48 polyubiquitination in the amygdala were developmentally regulated. This used basolateral amygdala (BLA) samples collected from 4 and 9 week old male and female Sprague-Dawley rats.
Project description:ACL tear rates in females is significantly higher compared to their male counterpart. We utilized 9 patient samples to explore the biological and transcriptomic differences that exist in male and female ACL.
Project description:Epienome-wide DNA methylation profiling of normal human kidney tissue samples. The Illumina HumanMethylation450K Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs in normal human kidney samples. Samples included 15 male and 16 female normal human kidney samples tissue.
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.
Project description:Bladder cancer (BC) is significantly more prevalent in men than in women, yet female patients often experience higher recurrence rates and poorer prognosis. Our study aimed to investigated sex-specific gene expression differences in early-stage BC using whole-transcriptome sequencing. A total of 51 patients diagnosed with low-grade Ta stage non-muscle-invasive bladder cancer were recruited. Paired tissue samples from tumor lesions and adjacent healthy bladder mucosa were analyzed to identify differentially expressed genes (DEGs). Among the top 100 most significant DEGs, overwhelmingly more upregulated were in male than female tissues (90% vs. 19%). The most significantly altered expression in female BC tissues included MT-ND6, ARL4C, ASGR1, MYBL1, and SCAMP5, whereas in males, ONECUT2, SPEG, CTSE, GJB2, and SYNM. Notably, 753 DEGs were unique to female patients, while 3989 were specific to males, with 1633 shared between both sexes. Functional annotation revealed that female-unique DEGs were significantly enriched in immune-related pathways, including regulation of leukocyte activation and cell-cell adhesion, and lymphocyte differentiation. Whereas male-unique DEGs were predominantly associated with pathways related to cell cycle regulation, mitochondrial function, and androgen receptor signaling. Immune-related gene expression indicated that female-specific DEGs were involved in leukocyte activation and antigen receptor signaling, whereas male-specific DEGs were linked to B-cell activation and neutrophil-mediated immune responses. A two-factor interaction model identified S100A14 as the only protein-coding gene whose expression exhibited a significant sex-dependent pattern, with four additional genes (GJB2, DSC2, TM4SF and ALOX15B) showing a probable interaction effect. These findings highlight the necessity for sex-specific therapeutic strategies in BC management.
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.