Effects of functional defects in the NMD pathway on rice phenotype and transcriptome.

Nonsense-mediated mRNA decay (NMD) is an important RNA quality control pathway. It aids in degrading harmful erroneous mRNA, thereby preserving a stable and healthy internal environment. In this study, we employed CRISPR/Cas9 and amiRNA technology to generate knock out or knock down mutants of realted genes in the rice NMD pathway. Through transcriptome sequencing and observing phenotype changes, the study explored the impact of NMD pathway defects on rice gene expression and alternative splicing. The results suggest that even partial defects will induce phenotypic changes such as plant height and pollen vitality to different degrees, showing necessity of NMD factors. Gene expression analysis reveals that most differentially expressed genes are upregulated in the mutants, with ko-upf1-like and kd-upf1 defects having a more significant impact than kd-upf2 and kd-upf3. Specifically, NMD pathway defects result in increased expression levels of rice defense response-related genes and decreased expression levels of secondary metabolism-related genes, with a wider range of affected genes observed in 60-day-old senescence mutants. Transcript analysis indicates that different NMD related genes defects alter hundreds of alternative splicing events, mostly enriched in genes involving alternative splicing regulatory pathways. Approximately half of these events are shared among different mutants, and a substantial number of affected transcripts show NMD target features. NMD could affect both the transcript abundance and their splicing subtypes to regulate the defense response and early-senescence associated pathways, which plays a vital role in rice growth and reproduction.

Prediction of positive pulmonary nodules based on machine learning algorithm combined with central carbon metabolism data.

BACKGROUND: Lung cancer causes a huge disease burden, and early detection of positive pulmonary nodules (PPNs) as an early sign of lung cancer is extremely important for effective intervention. It is necessary to develop PPNs risk recognizer based on machine learning algorithm combined with central carbon metabolomics. METHODS: The study included 2248 participants at high risk for lung cancer from the Ma'anshan Community Lung Cancer Screening cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to screen 18 central carbon-related metabolites in plasma, recursive feature elimination (RFE) was used to select all 42 features, followed by five machine learning algorithms for model development. The performance of the model was evaluated using area under the receiver operator characteristic curve (AUC), accuracy, precision, recall, and F1 scores. In addition, SHapley Additive exPlanations (SHAP) was performed to assess the interpretability of the final selected model and to gain insight into the impact of features on the predicted results. RESULTS: Finally, the two prediction models based on the random forest (RF) algorithm performed best, with AUC values of 0.87 and 0.83, respectively, better than other models. We found that homogentisic acid, fumaric acid, maleic acid, hippuric acid, gluconic acid, and succinic acid played a significant role in both PPNs prediction model and NPNs vs PPNs model, while 2-oxadipic acid only played a role in the former model and phosphopyruvate only played a role in the NPNs vs PPNs model. This model demonstrates the potential of central carbon metabolism for PPNs risk prediction and identification. CONCLUSION: We developed a series of predictive models for PPNs, which can help in the early detection of PPNs and thus reduce the risk of lung cancer.

Effect of exposures to multiple metals on blood pressure and hypertension in the elderly: a community-based study.

A chronic disease, hypertension (HTN) is prevalent among the elderly. Exploring the factors that influence HTN and blood pressure (BP) changes is of great public health significance. However, mixed exposure to multiple serum metals has had less research on the effects on BP and HTN for the elderly. From April to August 2019, 2372 people participated in the community physical examination program for the elderly in Tongling City, Anhui Province. We measured BP and serum levels of 10 metals and collected basic demographic information. We analyzed the relationship between metal levels and changes in BP and HTN by the least absolute shrinkage and selection operator regression, Bayesian kernel machine regression model, and generalized linear model. In multiple models, lead (Pb) and cadmium (Cd) were still significantly associated with HTN occurrence after adjusting for potential confounders (Pb: ORquartile 4 VS quartile 1 = 1.20, 95% CI 1.01-1.43; Cd: ORquartile 4 VS quartile 1 = 1.37, 95% CI 1.16-1.62). In the male subgroup, results were similar to those of the general population. In the female group, Cd was positively correlated with HTN and systolic blood pressure, while Pb was not. According to this study, Pb and Cd were correlated with BP and HTN positively, and there was a certain joint effect. To some extent, our findings provide clues for the prevention of hypertension in the elderly.

Targeted metabolomics reveals the association between central carbon metabolism and pulmonary nodules.

With the widespread application of low-dose computed tomography (LDCT) technology, pulmonary nodules have aroused more attention. Significant alteration in plasma metabolite levels, mainly amino acid and lipid, have been observed in patients of PNs. However, evidence on the association between central carbon metabolism and PNs are largely unknown. The aim of this study was to investigate the underlying association of PNs and plasma central carbon metabolites. We measured the levels of 16 plasma central carbon metabolites in 1954 participants who gained LDCT screening in MALSC cohort. The inverse probability weighting (IPW) technique was used to control for bias due to self-selection for LDCT in the assessed high-risk population. The least absolute shrinkage and selection operator (LASSO) penalized regression was used to deal with the problem of multicollinearity among metabolites and the combined association of central carbon metabolites with PNs was estimated by using quantile g-computation (QgC) models. A quartile increase in 3-hydroxybutyric acid, gluconic acid, succinic acid and hippuric acid was positively associated with the PNs risk, whereas a quartile increase in 2-oxadipic acid and fumaric acid was negatively associated with the risk of PNs in multiple-metabolite models. A positive but insignificant joint associations of the mixture of 16 metabolites with PNs was observed by using QgC models analyses. Further studies are warranted to clarify the association between circulating metabolites and PNs and the biological mechanisms.

[Concurrent Collection of Ammonia Gas and Aerosol Ammonium in Urban Beijing During National Celebration Days Utilizing an Acid-Coated Honeycomb Denuder in Combination with a Filter System].

Since 2013, the Chinese government implemented the Air Pollution Prevention and Control Action Plan. As a result, the atmospheric concentrations of sulfate reduced significantly, whereas the nitrate concentrations remain relatively high due to the excess of ammonia (NH3). To date, there is no official observation network monitoring NH3 concentrations in China. Previous studies have focused on NH3 or ammonium (NH4+) separately. These limitations hinder a complete understanding of their dynamic changes due to the rapid gas-to-particle conversion. In this study, the concentrations of NH3 and NH4+ were measured concurrently in urban Beijing during autumn 2019 utilizing an acid-coated denuder-filter combination with a time resolution from 2 h (PM2.5>35 µg·m-3) to 5 h (PM2.5<35 µg·m-3). The mean concentrations of NH3 and NH4+ during the study were (4.1±2.9)µg·m-3 and (1.7±1.4) µg·m-3, respectively. The temporal patterns of NH3 or NH4+ coincided with that of PM2.5, CO, and NO2 throughout the sampling period. The diurnal distributions of NH3 were bimodal, both on polluted (PM2.5>75 µg·m-3) and non-polluted (PM2.5<75 µg·m-3) days, peaking at 21:30-05:30 and 05:30-08:30, respectively. The NH3 concentrations on polluted days were relatively lower during 17:30-21:30, which may be related to higher wind speeds. In contrast to NH3, NH4+ had an obvious peak during 17:30-21:30 due to the formation of ammonium nitrate. The meteorological conditions favor the gas-to-particle conversion on polluted days, resulting in a lower NH3/NH4+ ratio of 0.8. However, this value may reach 2.8 on non-polluted days. The concentrations of NH3, CO, NO2, SO2, and PM2.5 in the emission control period showed a significant increase greater than or comparable to those in the non-control period by 54.2%, 40.4%, 33.3%, 0%, and 49.4%, respectively. This result shows that the stagnant conditions offset the benefit of emission control actions implemented during and before the National Celebration Day.

Research progress on analytical method and preparation technology of salvianolic acids / 药物评价研究

Salvianolic acid is the water soluble extract of Salvia miltiorrhiza,and it can improve the blood circulation of the brain and improve the cognitive disorder of depression,anti-inflammation,anti-tumor and so on.At present,the research on its technology is relatively less.This particle will mainly review the research progress of analytical methods,extraction and purification technology of salvianolic acids.The main analysis methods used for salvianolic acids include UV spectrophotometry,near-infrared spectroscopy,quantitative analysis of multi-components by single marker (QAMS),colorimetry and so on.The extraction process is mainly heating reflux extraction and warm soaking method,percolation method,enzymatic extraction,etc.The purification process is macroporous resin purification,ZnCl2 precipitation method,ultrafiltration and so on.

Research progress on analytical method and preparation technology of salvianolic acids / 药物评价研究

Salvianolic acid is the water soluble extract of Salvia miltiorrhiza,and it can improve the blood circulation of the brain and improve the cognitive disorder of depression,anti-inflammation,anti-tumor and so on.At present,the research on its technology is relatively less.This particle will mainly review the research progress of analytical methods,extraction and purification technology of salvianolic acids.The main analysis methods used for salvianolic acids include UV spectrophotometry,near-infrared spectroscopy,quantitative analysis of multi-components by single marker (QAMS),colorimetry and so on.The extraction process is mainly heating reflux extraction and warm soaking method,percolation method,enzymatic extraction,etc.The purification process is macroporous resin purification,ZnCl2 precipitation method,ultrafiltration and so on.