Stress response membrane protein OsSMP2 negatively regulates rice tolerance to drought.

In a gene chip analysis, rice (Oryza sativa) OsSMP2 gene expression was induced under various abiotic stresses, prompting an investigation into its role in drought resistance and abscisic acid signaling. Subsequent experiments, including qRT-PCR and ß-glucuronidase activity detection, affirmed the OsSMP2 gene's predominant induction by drought stress. Subcellular localization experiments indicated the OsSMP2 protein primarily localizes to the cell membrane system. Overexpressing OsSMP2 increased sensitivity to exogenous abscisic acid, reducing drought resistance and leading to reactive oxygen species accumulation under drought stress. Conversely, in simulated drought experiments, OsSMP2-silenced transgenic plants showed significantly longer roots compared with the wild-type Nipponbare. These results suggest that OsSMP2 overexpression negatively affects rice drought resistance, offering valuable insights into molecular mechanisms, and highlight OsSMP2 as a potential target for enhancing crop resilience to drought stress.

Association and mediation between educational attainment and respiratory diseases: a Mendelian randomization study.

BACKGROUND: Respiratory diseases are a major health burden, and educational inequalities may influence disease prevalence. We aim to evaluate the causal link between educational attainment and respiratory disease, and to determine the mediating influence of several known modifiable risk factors. METHODS: We conducted a two-step, two-sample Mendelian randomization (MR) analysis using summary statistics from genome-wide association studies (GWAS) and single nucleotide polymorphisms (SNPs) as instrumental variables for educational attainment and respiratory diseases. Additionally, we performed a multivariable MR analysis to estimate the direct causal effect of each exposure variable included in the analysis on the outcome, conditional on the other exposure variables included in the model. The mediating roles of body mass index (BMI), physical activity, and smoking were also assessed. FINDINGS: MR analyses provide evidence of genetically predicted educational attainment on the risk of FEV1 (ß = 0.10, 95% CI 0.06, 0.14), FVC (ß = 0.12, 95% CI 0.07, 0.16), FEV1/FVC (ß = - 0.005, 95% CI - 0.05, 0.04), lung cancer (OR = 0.54, 95% CI 0.45, 0.65) and asthma (OR = 0.86, 95% CI 0.78, 0.94). Multivariable MR dicated the effect of educational attainment on FEV1 (ß = 0.10, 95% CI 0.04, 0.16), FVC (ß = 0.07, 95% CI 0.01, 0.12), FEV1/FVC (ß = 0.07, 95% CI 0.01, 0.01), lung cancer (OR = 0.55, 95% CI 0.42, 0.71) and asthma (OR = 0.88, 95% CI 0.78, 0.99) persisted after adjusting BMI and cigarettes per day. Of the 23 potential risk factors, BMI, smoking may partially mediate the relationship between education and lung disease. CONCLUSION: High levels of educational attainment have a potential causal protective effect on respiratory diseases. Reducing smoking and adiposity may be a target for the prevention of respiratory diseases attributable to low educational attainment.

Association between plasma metal exposure and health span in very elderly adults: a prospective cohort study with mixture statistical approach.

BACKGROUND: Metals have been linked to a diverse spectrum of age-related diseases; however, the effects of metal exposure on health span remains largely unknown. This cohort study aims to determine the association between plasma metal and health span in elder adults aged ≥ 90 years. METHODS: The plasma concentrations of seven metals were measured at baseline in 300 elder adults. The end of the health span (EHS) was identified as the occurrence of one of eight major morbidities or mortality events. We used Cox regression to assess hazard ratios (HR). The combined effects of multiple metal mixtures were estimated using grouped-weighted quantile sum (GWQS), quantile g-computation (Q-gcomp), and Bayesian kernel machine regression (BKMR) methods. RESULTS: The estimated HR for EHS with an inter-quartile range (IQR) increment for selenium (Se) was 0.826 (95% confidence interval [CI]: 0.737-0.926); magnesium (Mg), 0.806 (95% CI: 0.691-0.941); iron (Fe), 0.756 (95% CI: 0.623-0.917), and copper (Cu), 0.856 (95% CI: 0.750-0.976). The P for trend of Se, Mg, and Fe were all < 0.05. In the mixture analyses, Q-gcomp showed a negative correlation with EHS (P = 0.904), with the sum of the negative coefficients being -0.211. CONCLUSION: Higher plasma Se, Mg, and Fe reduced the risk of premature end of health span, suggesting that essential metal elements played a role in health maintenance in elder adults.

Quantitative Membrane Proteomics for Discovery of Actionable Drug Targets at the Surface of RAS-Driven Human Cancer Cells.

With the advent of promising lung cancer immunotherapies targeting proteins at the cell surface of RAS-driven human cancers, the mass spectrometry (MS)-based surfaceomics remains a feasible strategy for therapeutic target discovery. This chapter describes a protocol for discovery of druggable protein targets at the surface of RAS-driven human cancer cells. This method relies on bottom-up MS-based quantitative surfaceomics that employs in parallel, targeted hydrazide-based cell-surface glycoproteomics and global shotgun membrane proteomics to enable unbiased quantitative profiling of thousands of cell surface membrane proteins. A large-scale molecular map of the KRASG12V surface was attained, resulting in confident detection and quantitation of more than 500 cell surface membrane proteins that were found to be unique or upregulated at the surface of cells harboring the KRASG12V mutant. A multistep bioinformatic progression revealed a subset of unique and/or significantly upregulated proteins as priority drug targets selected for orthogonal cross-validation using immunofluorescence, structured illumination microscopy, and western blotting. Among cross-validated targets, CUB domain containing protein 1 (CDCP1) and basigin (BSG-CD147) were selected as leading targets due to their involvement in cell adhesion and migration, consistent with the KRASG12V malignant phenotype as revealed by scanning electron microscopy and phenotypic cancer cell assays. Follow-up studies confirmed CDCP1 as an actionable therapeutic target, resulting in development of recombinant antibodies capable of killing KRAS-transformed cancer cells in preclinical setting. The present MS-based surfaceomics workflow represents a powerful drug target discovery platform that enables development of innovative immunotherapeutics (e.g., antibody drug conjugate against CDCP1) for attacking oncogenic RAS-driven cancers at the cell surface.

Selenium in rice: Impact on protein content and distribution for enhanced food and feed security in agroclimatic challenges.

Countries face exasperating and inclement climate worldwide. Food and feed security could be their paramount life objective. The study aimed to investigate the impact of selenium on the protein content and distribution in different parts of rice. For this purpose, advanced selenium biofortified breeding material developed after generations of breeding efforts was investigated at the field area, rice research institute, Chengdu, China during cropping season 2021-22. The accumulation and distribution of selenium and protein contents were observed in various fractions of selenium-enriched rice (Z3057B) and positive control (727). The correlation studies for selenium and protein quantification leads to the optimization of the breeding material and relevance in virtue. The rice fractions indicated rice embryo retains highest selenium contents, which gradually decreases in succession (other rice parts). The difference in protein content between the embryo and endosperm of Se-enriched rice is significant, while that between embryo and aleurone layer is not obvious. The selenium protein was found with molecular weight of 13.6-122.6 kDa. The protein of each molecular weight is found to bind with selenium, but the binding strength of selenium is negatively correlated with the molecular weight of protein. The 67.5% of the total selenium sticks with protein having molecular weight less than 38.8 kDa. In summary, protein with low molecular weight (13.4 kDa) binds maximum selenium and accounts for highest total protein content (40.76%).