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To accurately phenocopy human biology in vitro, researchers have been reducing their dependence on standard, static two-dimensional (2D) cultures and instead are moving towards three-dimensional (3D) and/or multicellular culture techniques. While these culture innovations are becoming more commonplace, there is a growing body of research that illustrates the benefits and even necessity of recapitulating the dynamic flow of nutrients, gas, waste exchange and tissue interactions that occur in vivo. However, cost and engineering complexity are two main factors that hinder the adoption of these technologies and incorporation into standard laboratory workflows. We developed LATTICE, a plug-and-play microfluidic platform able to house up to eight large tissue or organ models that can be cultured individually or in an interconnected fashion. The functionality of the platform to model both healthy and diseased tissue states was demonstrated using 3D cultures of reproductive tissues including murine ovarian tissues and human fallopian tube explants (hFTE). When exogenously exposed to pathological doses of gonadotropins and androgens to mimic the endocrinology of polycystic ovarian syndrome (PCOS), subsequent ovarian follicle development, hormone production and ovulation copied key features of this endocrinopathy. Further, hFTE cilia beating decreased significantly only when experiencing continuous media exchanges. We were then able to endogenously recreate this phenotype on the platform by dynamically co-culturing the PCOS ovary and hFTE. LATTICE was designed to be customizable with flexibility in 3D culture formats and can serve as a powerful automated tool to enable the study of tissue and cellular dynamics in health and disease in all fields of research. [ABSTRACT FROM AUTHOR]

Mating structure can have important effects on population genetic phenomena, including inbreeding and genetic drift. However, data necessary to test predictions based on mathematical models or identify sensitivity to simplifying assumptions are difficult to collect. We used two sources of such data, pedigrees and genotypes, collected in a human-population isolate. The population studied was Native American and located in New Mexico. It was founded in the mid-19th century by ca. 30 individuals, primarily of Navajo origin, and its size increased steadily thereafter. A complete tribal pedigree spanning ca. 100 years (up to 1948) was collected by anthropologists starting in the 1920s. Probabilities of allelic identity by descent (IBD) within and among individuals were calculated for all generations directly from the pedigree. Wright's F-statistics were calculated from the IBD probabilities, and [N.sub.e] was obtained from the statistic [F.sub.ST]. Genetic typings were performed on blood samples collected from the population between 1991-1993. A second set of F-statistics were calculated from genetic typings. Genetic kinship between individuals ([F.sub.ST]) and average inbreeding within individuals ([F.sub.IT]) stabilized after the first two generations. However, [F.sub.ST] was always greater than [F.sub.IT] of the next generation, suggesting that the net effect of social practices was inbreeding avoidance. In contrast to general expectations for growing populations, [N.sub.e] increased over generations due to immigration. F-statistics estimated from the genetic typings were remarkably close to pedigree estimates, suggesting a drift-migration steady state. Key words: human-population isolate, F-statistics, pedigrees, marker typings

Objective: Women with metabolic syndrome (MetS) have higher endogenous testosterone (T) levels than unaffected women. This study investigated whether hyperandrogenemia (HA) was a marker for increased cardiometabolic risk in reproductively normal premenopausal women.Methods: Reproductive hormones and metabolic parameters were assessed in 198 women with regular menses and no clinical hyperandrogenism (eumenorrheic [EM]). Hyperandrogenic EM women were compared with 110 women with NIH criteria polycystic ovary syndrome.Results: Twenty-two percent of EM women had HA. Levels of non-sex hormone-binding globulin (SHBG)-bound T were elevated in 68% of women, total T levels were elevated in 43% of women, and dehydroepiandrosterone sulfate levels were elevated in 30% of women. The prevalence of HA increased with BMI category (P = 0.01): 12% for BMI < 25 kg/m2 , 22% for BMI of 25 to 30 kg/m2 , and 31% for BMI ≥ 30 kg/m2 . MetS (adjusted odds ratio 2.9; 95% CI: 1.2-6.9) and dysglycemia risks (adjusted odds ratio 2.7; 95% CI: 1.2-5.8) were increased in hyperandrogenic EM women compared with normoandrogenic EM women, with adjustment for BMI. SHBG levels were independently associated with these metabolic end points (P < 0.001), whereas androgen levels were not. A cluster analysis confirmed that there was a discrete subset of EM women with HA and metabolic abnormalities.Conclusions: HA is common in EM women and is associated with increased risks for MetS and dysglycemia. However, low SHBG levels rather than elevated androgen levels may be the primary predictor of this relationship with metabolic dysfunction. [ABSTRACT FROM AUTHOR]

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health. [ABSTRACT FROM AUTHOR]