Study on transepithelial movement of 3H-androgen in the rat seminiferous and epididymal tubules

微小穿刺法と微小灌流法を用いた。精細管の管内アンドロゲン濃度は間質液中のその濃度が10-2, 000nMに増大するに従い直線的に増大したが, 精巣上体頭部における管内アンドロゲン濃度は間質液中の濃度が増大するに従い双曲線的に増大し, 精細管におけるそれよりもはるかに高い値を示した。灌流液中に0.1nMのジニトロフェノール, 0.1mMのKCN, 100μg/mlのサイクロヘキサミドを加えたとき, 管内アンドロゲンの移行は組織ATP濃度とともに有意に減少した。アンドロゲン結合蛋白を含まない人工的精上体頭部の管内液で管内を灌流したとき濃度勾配に抗したアンドロゲン移行は完全に抑制されたThe mechanisms involved in the maintenance of the endocrinological microenvironment of the seminiferous and epididymal tubules were examined in a series of experiments utilizing in vivo microperifusion, microperfusion, and micropuncture technique. The intraluminal 3H-androgen concentration in the seminiferous tubules increased linearly as the interstitial 3H-androgen concentrations increased from 10 nM to 2, 000 nM, but in the caput epididymidal tubules, the intraluminal 3H-androgen concentration increased hyperbolically across the same range of peritubular 3H-androgen concentration. Intraluminal 3H-androgen concentrations in the caput epididymidis did not rise above approximately 340 nM even when the peritubular 3H-androgen concentration exceeded 2, 000 nM. Perifusion of caput tubules with 0.1 mM dinitrophenol or potassium cyanide or 100 micrograms/ml cyclohexamide significantly reduced the proluminal 3H-androgen movement, but tubules perifused with control medium did not support antigrade 3H-androgen movement in the absence of native lumen fluids which contain androgen-binding protein. Energy-requiring protein synthesis is necessary for antigrade 3H-androgen movement in the caput epididymidis, but the mechanism for the interaction of intracellular protein(s) and 3H-androgen movement remains undetermined

Mbechsteinii_Epigenetics

R script used for the data analysis (linear regression, multiple linear regression, LOOCV)

Additional file 1: of Genome-wide methylomic analysis in individuals with HNF1B intragenic mutation and 17q12 microdeletion

Table S1. SLC1A3 bisulfite pyrosequencing assay conditions. (XLSX 11 kb

Additional file 5: of Genome-wide methylomic analysis in individuals with HNF1B intragenic mutation and 17q12 microdeletion

Figure S2. This Figure shows four significant differentially methylated regions (DMRs) identified between controls and 17q12 deletion carriers. A) SYNRG (corrected P = 1.32E-17), B) AATF (corrected P = 1.64E-11). C) LHX1 (corrected P = 3.37E-18), D) SMIM24 (corrected P = 1.01E-07). (PDF 223 kb

Additional file 2: of Genome-wide methylomic analysis in individuals with HNF1B intragenic mutation and 17q12 microdeletion

Figure S1. This figure illustrates the extent of the 17q12 deletion in each patient as estimated by the CNV calling algorithm within the CHAMP package. (PDF 15 kb

Additional file 1: Figure S1. of Methylomic markers of persistent childhood asthma: a longitudinal study of asthma-discordant monozygotic twins

Flow chart describing the methodological approach used in this study. Our analyses focused on identifying differentially methylated positions (DMPs) associated with asthma in (A) all asthma-discordant MZ twins at age 10 and (B) a sub-group with persistent asthma who were discordant for asthma at age 10 and also at age 18. Using DNA previously collected at age 5, we (C) subsequently assessed longitudinal changes in DNA methylation (between ages 5 and 10) in persistent-asthma-discordant MZ twins. Finally, we (D) examined epigenetic variation at top-ranked persistent-asthma-associated DMPs in an asthma-remission group, comprising of MZ twin pairs discordant for asthma at age 10 but concordant for no asthma phenotype at 18 and concordant unaffected MZ twin pairs where neither twin had asthma at both ages 10 and 18

Additional file 2: Tables S1–S7. of Methylomic markers of persistent childhood asthma: a longitudinal study of asthma-discordant monozygotic twins

Table S1. The top-ranked DMPs (P < 0.001) in discordant MZ twin pairs at age 10. Table S2. Gene ontology enrichment analysis for age-10 asthma-associated DMPs. Table S3. The top-ranked DMPs at age 10 in persistent-asthma-discordant MZ twins (between 10 and 18 years). Table S4. Gene ontology enrichment analysis for persistent-asthma age-10 DMPs. Table S5. The top-ranked CpG sites which show changes in DNA methylation levels between 5 and 10 years of age in the asthma-discordant MZ twins. Table S6. Gene ontology enrichment analysis of longitudinal DMPs between 5 and 10 years of age. Table S7. Monozygotic twin group details

The contribution of genetic and environmental influences on DNA methylation at autosomal sites differs as a function of average DNA methylation level at that location.

<p>Shown are estimates of additive genetic effects (A), shared environmental effects (C) and non-shared (or unique) environmental effects (E) against mean DNA methylation level. The most heritable sites are characterized by intermediate levels of DNA methylation.</p

The contribution of additive genetic and environmental factors to levels of DNA methylation.

<p>Shown are the results from structural equation models to estimate the mean proportion of variance in DNA methylation explained by additive genetic effects (A), shared environmental effects (C) and unshared (or unique) environmental effects (E) across Illumina 450K probes. Results are presented separately for DNA methylation sites located on the autosomes and X-chromosome, and stratified by whether they have intermediate levels of DNAm and/or are “variable”.</p

DNA methylation at sites associated with tobacco smoking is strongly influenced by additive genetic factors.

<p>Shown is a series of density plots for estimates of (<b>a</b>) additive genetic effects (A), (<b>b</b>) shared environmental effects (C) and (<b>c</b>) non-shared environmental effects (E) at 97 differentially methylated positions (DMPs) associated with smoking (green). Also shown are density plots for A, C and E at ‘background’ sites not associated with smoking (red). Shown below is a series of scatterplots showing the correlation in DNA methylation between MZ twins (x-axis) against DZ twins (y-axis) for sites associated with smoking in (<b>d</b>) all twins, (<b>e</b>) concordant non-smokers (n = 503 twin-pairs), (<b>f</b>) twins discordant for smoking status (n = 123 twin-pairs) and (<b>g</b>) concordant smokers (n = 106 twin-pairs). The shaded area on each plot indicates the heritability estimate (using Falconer’s formula) for each site.</p