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.

Study on primary screening technique for children with autism spectrum disorder / 中华预防医学杂志

To explore screening tools for children with autism spectrum disorder (ASD), which are convenient for primary hospitals, it can provide basic data for formulating ASD prevention policies. This was a cross-sectional study by cluster sampling. Huyi District and Xincheng District were extracted for investigation in Xi'an City. From July 2021 to September 2022, all children aged from 3 months to 36 months who live in the two districts were subjected to primary screening. The child care physician used the routine screening tool "warning signs checklist for screening psychological, behavioral and developmental problems of children" and cartoon pictures of "early high-risk warning signs of autism", the children who were positive in the initial screening were referred to the district level maternal and child health hospital for re-screening, and those who were positive in the re-screening were referred to Xi 'an Children's Hospital for diagnosis. The results showed that a total of 17 905 children aged from 3 months to 36 months were initially screened in the two districts, including 10 588 children aged from 18 months to 36 months, 50 children who were positive in the initial screening and 50 children who were re-screened. 23 children (18 boys and 5 girls) were diagnosed with ASD. The prevalence rate of ASD in children was 2.17‰ (95% confidence interval:1.29‰-3.06‰). 42 children were positive for "warning signs checklist" at the preliminary screening, and 19 were confirmed as ASD. 27 children were positive for "cartoon pictures" in the preliminary screening, and 23 were confirmed with ASD. The "cartoon pictures" in the preliminary screening and diagnosis of consistent rate was higher than the "warning signs checklist", two kinds of screening methods comparison were statistically significant difference in the odds of consistent (χ2=11.01, P=0.001). In conclusion, relying on the three-level network of maternal and child health care, it is conducive to the whole process management of screening and diagnosis of children with ASD, and to guide the formulation of prevention policies. The cartoon pictures of "early high-risk warning signs of autism" can assist the identification of children with ASD based on the "warning signs checklist", which is simple, effective and suitable for promotion in the community health care.

Study on primary screening technique for children with autism spectrum disorder / 中华预防医学杂志

To explore screening tools for children with autism spectrum disorder (ASD), which are convenient for primary hospitals, it can provide basic data for formulating ASD prevention policies. This was a cross-sectional study by cluster sampling. Huyi District and Xincheng District were extracted for investigation in Xi'an City. From July 2021 to September 2022, all children aged from 3 months to 36 months who live in the two districts were subjected to primary screening. The child care physician used the routine screening tool "warning signs checklist for screening psychological, behavioral and developmental problems of children" and cartoon pictures of "early high-risk warning signs of autism", the children who were positive in the initial screening were referred to the district level maternal and child health hospital for re-screening, and those who were positive in the re-screening were referred to Xi 'an Children's Hospital for diagnosis. The results showed that a total of 17 905 children aged from 3 months to 36 months were initially screened in the two districts, including 10 588 children aged from 18 months to 36 months, 50 children who were positive in the initial screening and 50 children who were re-screened. 23 children (18 boys and 5 girls) were diagnosed with ASD. The prevalence rate of ASD in children was 2.17‰ (95% confidence interval:1.29‰-3.06‰). 42 children were positive for "warning signs checklist" at the preliminary screening, and 19 were confirmed as ASD. 27 children were positive for "cartoon pictures" in the preliminary screening, and 23 were confirmed with ASD. The "cartoon pictures" in the preliminary screening and diagnosis of consistent rate was higher than the "warning signs checklist", two kinds of screening methods comparison were statistically significant difference in the odds of consistent (χ2=11.01, P=0.001). In conclusion, relying on the three-level network of maternal and child health care, it is conducive to the whole process management of screening and diagnosis of children with ASD, and to guide the formulation of prevention policies. The cartoon pictures of "early high-risk warning signs of autism" can assist the identification of children with ASD based on the "warning signs checklist", which is simple, effective and suitable for promotion in the community health care.

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.