Targeting ARNT attenuates chemoresistance through destabilizing p38α-MAPK signaling in glioblastoma.

Glioblastoma (GBM) is the most aggressive and lethal brain tumor in adults. This study aimed to investigate the functional significance of aryl hydrocarbon receptor nuclear translocator (ARNT) in the pathogenesis of GBM. Analysis of public datasets revealed ARNT is upregulated in GBM tissues compared to lower grade gliomas or normal brain tissues. Higher ARNT expression correlated with the mesenchymal subtype and poorer survival in GBM patients. Silencing ARNT using lentiviral shRNAs attenuated the proliferative, invasive, and stem-like capabilities of GBM cell lines, while ARNT overexpression enhanced these malignant phenotypes. Single-cell RNA sequencing uncovered that ARNT is highly expressed in a stem-like subpopulation and is involved in regulating glycolysis, hypoxia response, and stress pathways. Mechanistic studies found ARNT activates p38 mitogen-activated protein kinase (MAPK) signaling to promote chemoresistance in GBM cells. Disrupting the ARNT/p38α protein interaction via the ARNT PAS-A domain restored temozolomide sensitivity. Overall, this study demonstrates ARNT functions as an oncogenic driver in GBM pathogenesis and represents a promising therapeutic target.

Revisiting the Immigrant Health Advantage: Self-Reported Health and Smoking Among Sexual Minority Immigrants.

This study aims to examine how the immigrant health advantage (IHA) may differ by sexual orientation. Using data from the 2015-2019 National Health Interview Survey, we examined general health status (n = 131,635) and smoking behavior (n = 131, 658) for US-born and foreign-born heterosexual and sexual minority adults, as well as how the duration of stay in the U.S. may influence sexual minority immigrants' health. Logistic regression models were adopted to examine the health outcomes of immigration in different immigrant groups divided by sexual orientation. Findings show a weaker immigrant health advantage among sexual minorities than heterosexual persons, which disappears or turns into a disadvantage for several subpopulations (i.e., foreign-born homosexual individuals who stayed for 10-15 or 15 + years in the U.S.). Foreign-born homosexual individuals having stayed in the U.S. for a decade or more have substantially higher odds of reporting poor/fair health and smoking currently than their US-born counterparts. Although immigrants' health advantage overall attenuates over time, sexual minority immigrants' health erodes more with time spent in the U.S. The disparities in immigrants' health advantages suggest a segmented health acculturation (or even marginalization) process and entail higher sexual orientation-based health disparities among immigrants than among US-born individuals, likely reinforcing the preexisting health disparities in the country. The findings call for policies to address the multifaceted barriers to health equity at the intersection of social disadvantages.

Social Drivers of Mental Health: A U.S. Study Using Machine Learning.

INTRODUCTION: Social drivers of mental health can be compared on an aggregated level. This study employed a machine learning approach to identify and rank social drivers of mental health across census tracts in the U.S. METHODS: Data for 38,379 census tracts in the U.S. were collected from multiple sources in 2021. Two measures of mental health problems-self-reported depression and self-assessed poor mental health-among adults and three domains of social drivers (behavioral, environmental, and social) were analyzed on the basis of the unit of census tracts using the Extreme Gradient Boosting machine learning approach in 2022. The leading social drivers were found in each domain in the main sample and in the subsamples divided on the basis of poverty and racial segregation. RESULTS: The three domains combined explained more than 90% of the variance of both mental illness indicators. Self-reported depression and self-assessed poor mental health differed in major social drivers. The two outcome indicators had one overlapping correlate from the behavioral domain: smoking. Other than smoking, climate zone and racial composition were the leading correlates from the environmental and social domains, respectively. Census tract characteristics moderated the impacts of social drivers on mental health problems; the major social drivers differed by census tract poverty and racial segregation. CONCLUSIONS: Population mental health is highly contextualized. Better interventions can be developed on the basis of census tract-level analyses of social drivers that characterize the upstream causes of mental health problems.

Social Determinants, Cardiovascular Disease, and Health Care Cost: A Nationwide Study in the United States Using Machine Learning.

Background Existing studies on cardiovascular diseases (CVDs) often focus on individual-level behavioral risk factors, but research examining social determinants is limited. This study applies a novel machine learning approach to identify the key predictors of county-level care costs and prevalence of CVDs (including atrial fibrillation, acute myocardial infarction, congestive heart failure, and ischemic heart disease). Methods and Results We applied the extreme gradient boosting machine learning approach to a total of 3137 counties. Data are from the Interactive Atlas of Heart Disease and Stroke and a variety of national data sets. We found that although demographic composition (eg, percentages of Black people and older adults) and risk factors (eg, smoking and physical inactivity) are among the most important predictors for inpatient care costs and CVD prevalence, contextual factors such as social vulnerability and racial and ethnic segregation are particularly important for the total and outpatient care costs. Poverty and income inequality are the major contributors to the total care costs for counties that are in nonmetro areas or have high segregation or social vulnerability levels. Racial and ethnic segregation is particularly important in shaping the total care costs for counties with low poverty rates or social vulnerability level. Demographic composition, education, and social vulnerability are consistently important across different scenarios. Conclusions The findings highlight the differences in predictors for different types of CVD cost outcomes and the importance of social determinants. Interventions directed toward areas that have been economically and socially marginalized may aid in reducing the impact of CVDs.

Determination and Correlation of Solubility of Metformin Hydrochloride in Aqueous Binary Solvents from 283.15 to 323.15 K.

Metformin hydrochloride (MET·HCl) is one of the most widely used oral hypoglycemic drugs in the world. In addition to hypoglycemic effects, MET·HCl also has anti-inflammatory, anti-tumor, anti-aging, and other effects, showing good efficacy and safety of single and combined treatment. The solubility of MET·HCl in water, water + N,N-dimethylformamide, water + acetonitrile, and water + n-propanol was measured by the gravimetric method under atmospheric pressure at temperatures ranging from 283.15 to 323.15 K. The solubility of MET·HCl has a positive correlation with temperature and water content. The experimental solubility data in binary solvents was correlated by the modified Apelblat model, CNIBS/R-K model, Apelblat-Jouyban-Acree model, and λh model. By comparing the average ARD % values of the four models, it is found that the modified Apelblat model (ARD % = 1.26) provides better correlation. Hansen solubility parameters and apparent thermodynamic parameters were calculated to analyze the solubility behavior, indicating that the dissolution process is endothermic and entropically favorable.

Subcritical Water Extraction of Natural Products.

Subcritical water refers to high-temperature and high-pressure water. A unique and useful characteristic of subcritical water is that its polarity can be dramatically decreased with increasing temperature. Therefore, subcritical water can behave similar to methanol or ethanol. This makes subcritical water a green extraction fluid used for a variety of organic species. This review focuses on the subcritical water extraction (SBWE) of natural products. The extracted materials include medicinal and seasoning herbs, vegetables, fruits, food by-products, algae, shrubs, tea leaves, grains, and seeds. A wide range of natural products such as alkaloids, carbohydrates, essential oil, flavonoids, glycosides, lignans, organic acids, polyphenolics, quinones, steroids, and terpenes have been extracted using subcritical water. Various SBWE systems and their advantages and drawbacks have also been discussed in this review. In addition, we have reviewed co-solvents including ethanol, methanol, salts, and ionic liquids used to assist SBWE. Other extraction techniques such as microwave and sonication combined with SBWE are also covered in this review. It is very clear that temperature has the most significant effect on SBWE efficiency, and thus, it can be optimized. The optimal temperature ranges from 130 to 240 °C for extracting the natural products mentioned above. This review can help readers learn more about the SBWE technology, especially for readers with an interest in the field of green extraction of natural products. The major advantage of SBWE of natural products is that water is nontoxic, and therefore, it is more suitable for the extraction of herbs, vegetables, and fruits. Another advantage is that no liquid waste disposal is required after SBWE. Compared with organic solvents, subcritical water not only has advantages in ecology, economy, and safety, but also its density, ion product, and dielectric constant can be adjusted by temperature. These tunable properties allow subcritical water to carry out class selective extractions such as extracting polar compounds at lower temperatures and less polar ingredients at higher temperatures. SBWE can mimic the traditional herbal decoction for preparing herbal medication and with higher extraction efficiency. Since SBWE employs high-temperature and high-pressure, great caution is needed for safe operation. Another challenge for application of SBWE is potential organic degradation under high temperature conditions. We highly recommend conducting analyte stability checks when carrying out SBWE. For analytes with poor SBWE efficiency, a small number of organic modifiers such as ethanol, surfactants, or ionic liquids may be added.

Electrochemiluminescence ultrasensitive immunoassay for carbohydrate antigen 125 based on AgInS2/ZnS nanocrystals.

We developed a near-infrared (NIR) electrochemiluminescence (ECL) immunosensor for sensitively and selectively determining carbohydrate antigen 125 (CA125) with toxic-element-free and environmental-friendly AgInS2/ZnS nanocrystals (NCs) as tags. The core/shell-structured AgInS2/ZnS NCs not only can be conveniently prepared via an aqueous synthetic procedure, but also has high photoluminescence quantum yield (PLQY) of up to 61.7%, highly monodispersed, water-soluble, and desired biological compatibility. As AgInS2/ZnS NCs can be oxidized via electrochemically injecting holes into their valence band at + 0.84 V, both the monodispersed AgInS2/ZnS NCs in solution and the surface-confined AgInS2/ZnS NCs immobilized in sandwich-typed immuno-complexes with CA125 as analyte can exhibit efficient oxidative-reduction ECL around 695 nm under physiological conditions with the presence of tri-n-propylamine (TPrA). The ECL intensity from the AgInS2/ZnS NCs immobilized in sandwich-typed immuno-complexes increases linearly and selectively with an increased concentration of CA125 from 5 × 10-6 to 5 × 10-3 U/mL, and limit of detection (LOD) was 1 × 10-6 U/mL (S/N = 3). This reliable platform can provide an effective detection method in the early diagnosis and treatment of ovarian cancer.

Tunable doping of N and S in carbon nanotubes by retarding pyrolysis-gas diffusion to promote electrocatalytic hydrogen evolution.

The doping amount of heteroatoms in N, S co-doped carbon nanotubes (CNT-NS) was accurately and extensively regulated by retarding pyrolysis-gas diffusion. The effect of the content of N and S on the hydrogen evolution activity of CNT-NS was revealed for the first time both experimentally and theoretically.