Including cell content predictions in the analysis of microarray data improves model fit and enhances the detection of previously-identified diagnosis-related genes in some dataset... by Megan Hastings Hagenauer (5523191)

“…M5, M3 vs. M5). Bottom graphs: In some datasets we see an enrichment of psychiatric effects (*p<0.05) in previously-identified psychiatric gene sets only after controlling for cell type (Barnes: M3, M4, Pritzker: M5, M3). …”

Relationship between endometrial inflammation and PRRSV RNA concentration (log₁₀/gram) in fetal thymus. by Predrag Novakovic (2559787)

DHA induces weak cell cycle arrest at G1/S and G2/M. by Arlet Hernandez (12289155)

IHC comparison of selected proteins in WT and <i>SPARC -/-</i> mice in the JCT. by Ling Yu (330944)

SP-D and rhSP-D interfere with binding of gp120 to CD4. by Hrishikesh Pandit (504240)

“…Each data point represents the mean ± S.D. (n = 3). Presence of SP-D and rhSP-D significantly decreased gp120 and CD4 binding and further β-gal positive TZM-bl cells.…”

Image_3_Non-parametric Heat Map Representation of Flow Cytometry Data: Identifying Cellular Changes Associated With Genetic Immunodeficiency Disorders.TIF by Julia I. Ellyard (7369643)

“…We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished CTLA4 haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with CARD11 gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). …”

Data_Sheet_1_Non-parametric Heat Map Representation of Flow Cytometry Data: Identifying Cellular Changes Associated With Genetic Immunodeficiency Disorders.PDF by Julia I. Ellyard (7369643)

“…We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished CTLA4 haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with CARD11 gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). …”

Image_1_Non-parametric Heat Map Representation of Flow Cytometry Data: Identifying Cellular Changes Associated With Genetic Immunodeficiency Disorders.TIF by Julia I. Ellyard (7369643)

“…We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished CTLA4 haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with CARD11 gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). …”

Image_4_Non-parametric Heat Map Representation of Flow Cytometry Data: Identifying Cellular Changes Associated With Genetic Immunodeficiency Disorders.TIFF by Julia I. Ellyard (7369643)

“…We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished CTLA4 haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with CARD11 gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). …”

Image_2_Non-parametric Heat Map Representation of Flow Cytometry Data: Identifying Cellular Changes Associated With Genetic Immunodeficiency Disorders.TIF by Julia I. Ellyard (7369643)

“…We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished CTLA4 haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with CARD11 gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). …”

Data_Sheet_2_Non-parametric Heat Map Representation of Flow Cytometry Data: Identifying Cellular Changes Associated With Genetic Immunodeficiency Disorders.PDF by Julia I. Ellyard (7369643)

“…We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished CTLA4 haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with CARD11 gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). …”

Data_Sheet_3_Non-parametric Heat Map Representation of Flow Cytometry Data: Identifying Cellular Changes Associated With Genetic Immunodeficiency Disorders.PDF by Julia I. Ellyard (7369643)

“…We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished CTLA4 haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with CARD11 gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). …”

Substance P inhibits K⁺ background conductance. by Carolina Thörn Pérez (773130)

“…Current traces from hyperpolarizing voltage steps (-60 to -130 mV) applied in control conditions. …”

Data_Sheet_1_Estimating COVID-19 cases in Puerto Rico using an automated surveillance system.DOCX by Marijulie Martinez-Lozano (13197423)

“…Test positivity decreased from 13.2% in November to 6.4% in March, increased in April (11.1%), and decreased in June (1.5%). …”

HDAC6 Regulates Mitochondrial Transport in Hippocampal Neurons by Sigeng Chen (248428)

“…Concordantly, the administration of 5-HT, 8-OH-DPAT (a specific 5-HT1A receptor agonist), or fluoxetine (a 5-HT reuptake inhibitor) increased tubulin acetylation. …”

Image_4_A Comprehensive Analysis of the Association Between SNCA Polymorphisms and the Risk of Parkinson's Disease.PDF by Yuan Zhang (41832)

“…To find the most relevant SNCA SNPs, we used a cutoff point of p < 1 × 10⁻⁵ in an analysis based on the allele model. …”

Image_3_A Comprehensive Analysis of the Association Between SNCA Polymorphisms and the Risk of Parkinson's Disease.PDF by Yuan Zhang (41832)

“…To find the most relevant SNCA SNPs, we used a cutoff point of p < 1 × 10⁻⁵ in an analysis based on the allele model. …”

Image_1_A Comprehensive Analysis of the Association Between SNCA Polymorphisms and the Risk of Parkinson's Disease.PDF by Yuan Zhang (41832)

“…To find the most relevant SNCA SNPs, we used a cutoff point of p < 1 × 10⁻⁵ in an analysis based on the allele model. …”

Image_6_A Comprehensive Analysis of the Association Between SNCA Polymorphisms and the Risk of Parkinson's Disease.PDF by Yuan Zhang (41832)

“…To find the most relevant SNCA SNPs, we used a cutoff point of p < 1 × 10⁻⁵ in an analysis based on the allele model. …”

Table_2_A Comprehensive Analysis of the Association Between SNCA Polymorphisms and the Risk of Parkinson's Disease.DOCX by Yuan Zhang (41832)

“…To find the most relevant SNCA SNPs, we used a cutoff point of p < 1 × 10⁻⁵ in an analysis based on the allele model. …”