The effects of oral vitamin D supplements on vaginal health in postmenopausal women with vulvovaginal atrophy (VVA) was evaluated. A double-blinded, randomized placebo-controlled trial was conducted for 12 weeks to investigate changes on vaginal maturation index (VMI), vaginal pH, and the visual analog scale (VAS) of VVA symptoms. The vitamin D group received oral ergocalciferol, at 40,000 IU per week, while the placebo group received an identical placebo capsule. Eighty postmenopausal women were enrolled. There were no significant differences in baseline characteristics between both groups. In an intention-to-treat analysis, VMI, vaginal pH, and VAS of VVA symptoms showed no significant differences between both groups at the six and 12 weeks. However, the mean difference of VMI in the vitamin D group between baseline and at six weeks showed significant improvement (5.5 + 16.27, p less then 0.05). Moreover, the mean vaginal pH and VAS of VVA patients in the vitamin D group were significantly improved at both six and 12 weeks compared to baseline. The oral vitamin D supplementation for 12 weeks potentially improves vaginal health outcomes in postmenopausal women with VVA symptoms, demonstrated by the improved mean VMI, vaginal pH, and VAS at six and 12 weeks between baseline, however, no significant differences were observed from the placebo treatment.A now substantial body of science implicates a dynamic interplay between genetic and environmental variation in the development of individual differences in behavior and health. Such outcomes are affected by molecular, often epigenetic, processes involving gene-environment (G-E) interplay that can influence gene expression. Early environments with exposures to poverty, chronic adversities, and acutely stressful events have been linked to maladaptive development and compromised health and behavior. Genetic differences can impart either enhanced or blunted susceptibility to the effects of such pathogenic environments. However, largely missing from present discourse regarding G-E interplay is the role of time, a "third factor" guiding the emergence of complex developmental endpoints across different scales of time. Trajectories of development increasingly appear best accounted for by a complex, dynamic interchange among the highly linked elements of genes, contexts, and time at multiple scales, including neurobiological (minutes to milliseconds), genomic (hours to minutes), developmental (years and months), and evolutionary (centuries and millennia) time. This special issue of PNAS thus explores time and timing among G-E transactions The importance of timing and timescales in plasticity and critical periods of brain development; epigenetics and the molecular underpinnings of biologically embedded experience; the encoding of experience across time and biological levels of organization; and gene-regulatory networks in behavior and development and their linkages to neuronal networks. Taken together, the collection of papers offers perspectives on how G-E interplay operates contingently within and against a backdrop of time and timescales.Background WHO's 2015 End TB Strategy advocates social and economic (socioeconomic) support for TB-affected households to improve TB control. However, evidence concerning socioeconomic support for TB-affected households remains limited, especially in low-income countries. Protocol This mixed-methods study in Nepal will evaluate the socioeconomic impact of accessing TB diagnosis and care (Project 1); and create a shortlist of feasible, locally-appropriate interventions to mitigate this impact (Project 2). The study will be conducted in the Chitwan, Mahottari, Makawanpur, and Dhanusha districts of Nepal, which have frequent TB and poverty. The study population will include approximately 200 people with TB (Cases) starting TB treatment with Nepal's National TB Program and 100 randomly-selected people without TB (Controls) in the same sites (Project 1); and approximately 40 key in-country stakeholders from Nepal including people with TB, community leaders, and TB healthcare professionals (Project 2). During Projenomic interventions for TB-affected households for trial evaluation.Obesity and overweight are associated with the burden of chronic diseases. The aim of the present meta-analysis is to determine the efficacy of spirulina in reducing of obesity indices. PubMed, Web of Science, Scopus, EMBASE and Cochrane library databases were searched up to November 2019. Randomized controlled trials comparing spirulina supplementation with a placebo or no treatment for anthropometric indices were included. Meta-analysis was performed using random-effects model. Subgroup analysis and meta-regression were carried out. Publication bias was evaluated using standard methods. Spirulina had ameliorative effects on weight (WMD = -1.85 Kg; 95% CI -2.44, -1.26; p  less then  .001; I2 = 82.4%, p  less then  .001), and waist circumference (WMD = -1.09 cm; 95% CI -2.16, -0.01; p = .046; I2 = 0.0%, p = .757) while no significant effect was shown on body mass index, even after sensitivity analysis (SMD = -0.53 Kg/m2 ; 95% CI -1.25, 0.19; p = .149; I2 = 92.9%, p  less then  .001); however, spirulina was effective in studies lasted for at least 12 weeks (SMD = -1.25 Kg/m2 ; 95% CI -2.21, -0.28; p = .011; I2 = 90.8%, p  less then  .001). Spirulina supplementation exerts beneficial effects on weight and waist circumference. The ameliorative effect of spirulina on body mass index was revealed in longer duration of supplementation.Current studies have shown that long non-coding RNAs (lncRNAs) may serve as prognostic biomarkers in multiple cancers. Therefore, we postulated that expression patterns of multiple lncRNAs combined into a single signature could improve clinicopathological risk stratification and prediction of overall survival rate for breast cancer patients. Two algorithms, Least Absolute Shrinkage and Selector Operation (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE), were used to select candidate lncRNAs. Univariate and multivariate Cox regression analyses were employed to construct a seven-lncRNA signature for breast cancer. selleck kinase inhibitor Stratified analysis revealed that the signature was significantly associated with multiple clinicopathological risk factors. For clinical use, we developed a nomogram model to predict overall survival and odds of death for breast cancer patients. Single-sample gene set enrichment analysis (ssGSEA), CIBERSORT algorithm and ESTIMATE method were employed to assess the relative immune cell infiltrations of each sample.