A Comparative Assessment of Non-Laboratory-Based versus Commonly Used Laboratory-Based Cardiovascular Disease Risk Scores in the NHANES III Population

National and international primary CVD risk screening guidelines focus on using total CVD risk scores. Recently, we developed a non-laboratory-based CVD risk score (inputs: age, sex, smoking, diabetes, systolic blood pressure, treatment of hypertension, body-mass index), which can assess risk faster and at lower costs compared to laboratory-based scores (inputs include cholesterol values). We aimed to assess the exchangeability of the non-laboratory-based risk score to four commonly used laboratory-based scores (Framingham CVD [2008, 1991 versions], and Systematic COronary Risk Evaluation [SCORE] for low and high risk settings) in an external validation population.Analyses were based on individual-level, score-specific rankings of risk for adults in the Third National Health and Nutrition Examination Survey (NHANES III) aged 25–74 years, without history of CVD or cancer (n = 5,999). Risk characterization agreement was based on overlap in dichotomous risk characterization (thresholds of 10-year risk >10–20%) and Spearman rank correlation. Risk discrimination was assessed using receiver operator characteristic curve analysis (10-year CVD death outcome). Risk characterization agreement ranged from 91.9–95.7% and 94.2–95.1% with Spearman correlation ranges of 0.957–0.980 and 0.946–0.970 for men and women, respectively. In men, c-statistics for the non-laboratory-based, Framingham (2008, 1991), and SCORE (high, low) functions were 0.782, 0.776, 0.781, 0.785, and 0.785, with p-values for differences relative to the non-laboratory-based score of 0.44, 0.89, 0.68 and 0.65, respectively. In women, the corresponding c-statistics were 0.809, 0.834, 0.821, 0.792, and 0.792, with corresponding p-values of 0.04, 0.34, 0.11 and 0.09, respectively.Every score discriminated risk of CVD death well, and there was high agreement in risk characterization between non-laboratory-based and laboratory-based risk scores, which suggests that the non-laboratory-based score can be a useful proxy for Framingham or SCORE functions in resource-limited settings. Future external validation studies can assess whether the sex-specific risk discrimination results hold in other populations

Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis

Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip) coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes) that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties

Transforming Growth Factor β Receptor Type 1 Is Essential for Female Reproductive Tract Integrity and Function

The transforming growth factor β (TGFβ) superfamily proteins are principle regulators of numerous biological functions. Although recent studies have gained tremendous insights into this growth factor family in female reproduction, the functions of the receptors in vivo remain poorly defined. TGFβ type 1 receptor (TGFBR1), also known as activin receptor-like kinase 5, is the major type 1 receptor for TGFβ ligands. Tgfbr1 null mice die embryonically, precluding functional characterization of TGFBR1 postnatally. To study TGFBR1–mediated signaling in female reproduction, we generated a mouse model with conditional knockout (cKO) of Tgfbr1 in the female reproductive tract using anti-Müllerian hormone receptor type 2 promoter-driven Cre recombinase. We found that Tgfbr1 cKO females are sterile. However, unlike its role in growth differentiation factor 9 (GDF9) signaling in vitro, TGFBR1 seems to be dispensable for GDF9 signaling in vivo. Strikingly, we discovered that the Tgfbr1 cKO females develop oviductal diverticula, which impair embryo development and transit of embryos to the uterus. Molecular analysis further demonstrated the dysregulation of several cell differentiation and migration genes (e.g., Krt12, Ace2, and MyoR) that are potentially associated with female reproductive tract development. Moreover, defective smooth muscle development was also revealed in the uteri of the Tgfbr1 cKO mice. Thus, TGFBR1 is required for female reproductive tract integrity and function, and disruption of TGFBR1–mediated signaling leads to catastrophic structural and functional consequences in the oviduct and uterus

Revolutionizing goat milk gels: A central composite design approach for synthesizing ascorbic acid-functionalized iron oxide nanoparticles decorated alginate-chitosan nanoparticles fortified smart gels

Goat milk gels (GMGs) are popular food due to their high water content, low-calorie density, appealing taste, texture enhancers, stability, and satiety-enhancing characteristics, making them ideal for achieving food security and zero hunger. The GMGs were optimized using the central composite design matrix of response surface methodology using goat milk powder (35–55 g), whole milk powder (10–25 g), and potato powder (10–15 g) as independent variables. In contrast, complex modulus, flow stress, and forward extrudability were chosen as dependent variables. The maximum value of complex modulus 33670.9 N, good flow stress 7863.6 N, and good extrudability 65.32 N was achieved under optimal conditions. The optimized goat milk gel was fortified with ascorbic acid-coated iron oxide nanoparticle (magnetic nature) decorated alginate-chitosan nanoparticles (AA-MNP@CANPs), making it nutritionally rich in an economically feasible way—the decorated AA-MNP@CANPs characterized for size, shape, crystallinity, surface charge, and optical characteristics. Finally, the optimized fortified smart GMGs were further characterized via Scanning electron microscopy, Rheology, Texture profile analysis, Fourier transforms infrared (FTIR), and X-Ray Diffraction (XRD). The fortified smart GMGs carry more nutritional diversity, targeted iron delivery, and the fundamental sustainability development goal of food security

Evaluation of a quality improvement intervention for obstetric and neonatal care in selected public health facilities across six states of India

Background While increase in the number of women delivering in health facilities has been rapid, the quality of obstetric and neonatal care continues to be poor in India, contributing to high maternal and neonatal mortality. Methods The USAID ASSIST Project supported health workers in 125 public health facilities (delivering approximately 180,000 babies per year) across six states to use quality improvement (QI) approaches to provide better care to women and babies before, during and immediately after delivery. As part of this intervention, each month, health workers recorded data related to nine elements of routine care alongside data on perinatal mortality. We aggregated facility level data and conducted segmented regression to analyse the effect of the intervention over time. Results Care improved to 90–99% significantly (p < 0.001) for eight of the nine process elements. A significant (p < 0.001) positive change of 30–70% points was observed during post intervention for all the indicators and 3–17% points month-to-month progress shown from the segmented results. Perinatal mortality declined from 26.7 to 22.9 deaths/1000 live births (p < 0.01) over time, however, it is not clear that the intervention had any significant effect on it. Conclusion These results demonstrate the effectiveness of QI approaches in improving provision of routine care, yet these approaches are underused in the Indian health system. We discuss the implications of this for policy makers.by Enisha Sarin, Subir K. Kole, Rachana Patel, Ankur Sooden, Sanchit Kharwal, Rashmi Singh, Mirwais Rahimzai and Nige Livesle