Gestational diabetes mellitus (GDM), characterized by a transitory form of diabetes induced by insulin resistance and pancreatic β-cell dysfunction during pregnancy, has been identified as one of the major obstacles in achieving improved maternal and child health. Approximately 9–25% of pregnancies worldwide are impacted by the acute, long-term, and transgenerational health complications of this disease. Here, we discuss how GDM affects longstanding maternal and neonatal outcomes, as well as health risks that likely persist into future generations. In addition to the current challenges in the management and diagnosis of and the complications associated with GDM, we discuss current preclinical models of GDM to better understand the underlying pathophysiology of the disease and the timely need to increase our scientific toolbox to identify strategies to prevent and treat GDM, thereby advancing clinical care.

Fetal growth restriction, or low birth weight, is a strong determinant for eventual obesity and type 2 diabetes. Clinical studies suggest placental mechanistic target of rapamycin (mTOR) signaling regulates fetal birth weight and the metabolic health trajectory of the offspring. In the current study, we used a genetic model with loss of placental mTOR function (mTOR-KO ^Placenta ) to test the direct role of mTOR signaling on birth weight and metabolic health in the adult offspring. mTOR-KO ^Placenta animals displayed reduced placental area and total weight, as well as fetal body weight at embryonic day (E) 17.5. Birth weight and serum insulin levels were reduced; however, β cell mass was normal in mTOR-KO ^Placenta newborns. Adult mTOR-KO ^Placenta offspring, under a metabolic high-fat challenge, displayed exacerbated obesity and metabolic dysfunction compared with littermate controls. Subsequently, we tested whether enhancing placental mTOR complex 1 (mTORC1) signaling, via genetic ablation of TSC2, in utero would improve glucose homeostasis in the offspring. Indeed, increased placental mTORC1 conferred protection from diet-induced obesity in the offspring. In conclusion, placental mTORC1 serves as a mechanistic link between placental function and programming of obesity and insulin resistance in the adult offspring.

Leptospirosis, a common zoonotic infection in developing countries, usually progresses to severe conditions and poor outcomes when not detected early. Microscopic agglutination test (MAT) and culture are available but are not accessible in all areas and are usually confined to specialized laboratories. There are several available immunochromatographic test kits (ICT) that offer ease of use, access, and affordability, but diagnostic accuracy is not yet well established. In this paper, we aim to review published literature on the use of ICTs for the detection of leptospirosis and evaluate their diagnostic efficiency. We systematically searched multiple databases (PubMed, Cochrane Library, and Google Scholar), including gray literature sources for published research articles as of April 13, 2022, on the diagnosis of acute leptospirosis using ICT. We assessed the methodological quality of each article using the revised QUADAS-2. From a total of 41 articles, 30 (73.2%) were identified as potentially relevant after reviewing the title and abstract and eliminating duplicate articles; then, 22 (53.7%) articles were included after scrutinizing and applying the inclusion/exclusion criteria to the full text. Almost all test kits detect IgM antibodies against the Leptospira species except for one which used IgG as a marker for diagnosis of acute leptospirosis. A wide range of sensitivity (15.8%–100.0%) and specificity (37.3%–100.0%) were recorded. Lipopolysaccharide (LPS)-specific Immunochromatographic Lateral Flow Assay presented the highest sensitivity (∼93–100%) and specificity (∼99.19–100%). Rapid diagnosis of acute leptospirosis is highly warranted; however, available test kits present a wide range of diagnostic accuracy. We found that LPS-specific ICT kit has the highest diagnostic efficiency; however, our analysis was limited by the included studies’ heterogeneity in design and reporting; thus, we recommend standardization in the conduct and reporting of diagnostic accuracy of test kits as it is vital to evaluate the reliability of the test kit.

Context: Dengue control may be done by targeting its vector. In this study, we used Artocarpus blancoi (Elm.) Merr. (Moraceae) leaves, an endemic hematophagous insect repellent as a larvicide and ovicide. Objective: We investigated the larvicidal and ovicidal activities of its soluble crude ethanol extract and the hexane, aqueous, and ethyl acetate fractions against Aedes aegypti. Materials and methods: Third to early fourth instar A. aegypti larvae were exposed to 200, 400, 600, 800 and 1000 ppm of crude ethanol; to 10, 20, 40, 60 and 80 ppm of ethyl acetate; and to 500, 750, 1000, 1250 and 1500 ppm of hexane fractions of A. blancoi; 48 h LC₅₀ and LC₉₀ values were determined. For the ovicidal assay, an average of 25 eggs/paper strip was used; inhibition of egg hatchability was counted 72 h after exposure. Fractions were screened qualitatively for phytochemicals. Results: Ethyl acetate soluble fraction gave the lowest LC₅₀ value (18.59 ppm) followed by the crude ethanol (411 ppm), hexane (685 ppm) and aqueous (20,158 ppm) fractions. Similarly, ethyl acetate soluble fraction appeared to be the most ovicidal (80 ppm). Larvicidal and ovicidal activities of the fractions were dose dependent. Qualitative phytochemical screening revealed moderate presence of glycosides and sterols and trace amounts of triterpenes, flavonoids, saponins and tannins. Discussion and conclusions: A. blancoi is a potential larvicide and ovicide against A. aegypti, and future studies isolating the specific components responsible for such actions would be significant.

Objective: To correlate climatic and environmental factors such as land surface temperature, rainfall, humidity and normalized difference vegetation index with the incidence of dengue to develop prediction models for the Philippines using remote-sensing data. Methods: Time-series analysis was performed using dengue cases in four regions of the Philippines and monthly climatic variables extracted from Global Satellite Mapping of Precipitation for rainfall, and MODIS for the land surface temperature and normalized difference vegetation index from 2008-2015. Consistent dataset during the period of study was utilized in Autoregressive Integrated Moving Average models to predict dengue incidence in the four regions being studied. Results: The best-fitting models were selected to characterize the relationship between dengue incidence and climate variables. The predicted cases of dengue for January to December 2015 period fitted well with the actual dengue cases of the same timeframe. It also showed significantly good linear regression with a square of correlation of 0.869 5 for the four regions combined. Conclusion: Climatic and environmental variables are positively associated with dengue incidence and suit best as predictor factors using Autoregressive Integrated Moving Average models. This finding could be a meaningful tool in developing an early warning model based on weather forecasts to deliver effective public health prevention and mitigation programs.