Objective To analyze the clinical manifestations of patients over 60 years old with acute respiratory infection in Pudong New Area of Shanghai and the risk factors of positive detection of novel coronavirus, and to provide reference for improving prevention and control strategies and measures. Methods General conditions, clinical features, basic complications and respiratory samples of inpatients over 60 years old with acute respiratory infection from eight hospitals in Pudong New Area of Shanghai from January to October 2023 were collected, and SARS-CoV-2 detection was carried out. Chi-square test and binary logistics regression were used for data analysis. Results A total of 604 patients over 60 years old were collected, including 356 (58.945) males with a median age of 77 (IQR:70-85) years. Of the 604 cases, 264 were detected positive for SARS-CoV-2, with a positive detection rate of 43.71%. The results of univariate analysis showed that there were significant differences in the detection rates of SARS-CoV-2 among different age groups (χ²=10.60, P=0.01) and different months (χ²=87.15, P=0.00), and among those with cough (χ²=5.28, P=0.02), sputum (χ²=4.19, P=0.04), sore throat (χ²=3.93, P=0.04), and hypertension (χ²=7.63, P=0.01). In the binary logistics regression analysis, month (P=0.00, OR=2.93, 95% CI=1.49-5.78) and age (P=0.00, OR=2.60, 95% CI=1.55-4.37) were independent risk factors for positive detection of SARS-CoV-2. Conclusion The majority of hospitalized cases of acute respiratory infection over 60 years old are male, and the risk factors for positive detection of novel coronavirus are age 80~89 years old and time between May and June.

Transdermal drug delivery offers advantages such as safety, convenience, and high patient compliance. However, the complex structure of the skin and significant individual variability, particularly the barrier function of the stratum corneum, result in generally low bioavailability for topical formulations. The formulation of topical drug products is complex, with numerous factors influencing quality, which requires strict control of product quality. Raman spectroscopy, as a non-destructive vibrational technique, combined with chemometric methods, imaging technology, and other spectroscopic techniques, can be applied to study the key quality attributes of topical drug formulations. The applications of Raman spectroscopy in studies of the crystal form, particle size distribution, excipient research, and in vitro transdermal experiments of topical drug formulations were summarized. In particular, it focused on the use of Raman spectroscopy in the selection of skin samples for in vitro permeation tests, the study of drug spatial distribution in the skin, and the interactions between drugs and the skin.

Objective To explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). Methods The Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. Gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients’ 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. Results Differentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. Conclusion The prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.

Objective: To explore the early effects of birth weight at different gestational ages on blood pressure trajectory among primary school students, so as to provide evidence for incorporating gestational age birth weight into individualized early warning and intervention strategies for childhood hypertension. Methods: From May to November 2023, a purposeful sampling method was used to recruit 1 676 students in grade 1-3 from three primary schools in a certain urban district of Chongqing. Follow up assessments were conducted in May 2024(T1), November 2024(T2), and May 2025(T3). General demographic and birth related information were collected via self administered questionnaires, while height, weight and blood pressure were obtained through physical examinations. Linear mixed effects model was used to analyze the associations between birth weight at different gestational ages and blood pressure trajectories. Results: During the T1-T3 period, the systolic blood pressure of boys were 98.5 (93.0, 104.5 ),98.5 (93.5, 105.0), and 97.5 (92.5, 103.5)mmHg, respectively, while the diastolic blood pressure were 60.5 (56.5, 65.0), 61.5 ( 57.0 , 65.5), and 60.0 (56.0, 64.0)mmHg, respectively. For girls, the systolic blood pressure were 95.5 (90.0, 102.0),95.5 (90.5, 101.5), and 96.0 (90.5, 101.5)mmHg, respectively, and the diastolic blood pressure were 60.5 (56.0, 64.5 ),61.5 (57.5, 65.5), and 59.5 (56.0, 63.0)mmHg, respectively. Through Friedman test within both boys and girls, diostolic blood pressure were statistically significant across three measurements( χ 2=48.85，81.54，both P <0.01). The proportion of normal blood pressure increased , and the proportion of prehypertension and hypertension decreased with time( χ 2=39.72，25.62，both P < 0.01 ). Linear mixed effects model analysis revealed that after adjusting for age, sex, household income monthly, parental education, family history of hypertension and maternal pregnancy complications, large for gestational age had significantly higher trajectories of systolic ( β = 1.50) and diastolic( β =0.94) blood pressure compared to appropriate for gestational age(both P <0.01). Conclusion Large for gestational age is associated with elevated blood pressure trajectories during school age, and it may be considered as an early indicator for individualized screening and intervention for childhood hypertension.

ObjectiveTo investigate the effect of different exercise interventions on metabolism and liver parameters in patients with metabolic dysfunction-associated fatty liver disease （MAFLD）， and to provide evidence-based recommendations for clinical exercise rehabilitation. MethodsThis study was conducted according to the PRISMA guidelines， and the protocol was registered on the PROSPERO platform， with a registration number of CRD42025641717. PubMed， Web of Science， Scopus， Wiley Online Library， CNKI， Wanfang Data， and VIP were searched for related articles published up to September 2024. The Cochrane tool for assessing risk of bias was used to assess the quality of articles， and Stata MP 17.0 was used to perform the network meta-analysis. ResultsA total of 57 articles were included， involving 2 648 patients. The results showed that aerobic exercise combined with resistance exercise had the best effect in improving body mass index （mean difference ［WMD］=-0.97， 95% confidence interval ［CI］： -1.66 to -0.28］， P<0.05， surface under the cumulative ranking curve ［SUCRA］=85.4） and triglycerides （WMD=-29.6， 95%CI： -46.66 to 12.54， P<0.05， SUCRA=87.3）； resistance exercise was the optimal intervention method for improving total cholesterol （WMD=-15.99， 95%CI： -24.19 to -7.79， P<0.05， SUCRA=79.9） and glutamine transaminase （WMD=-8.08， 95%CI： -12.13 to -4.02， P<0.05， SUCRA=87.3）； low-intensity aerobic exercise had the best effect in improving aspartate aminotransferase （WMD=-4.3， 95%CI： -8.45 to -0.15， P<0.05， SUCRA=73.5）， gamma-glutamyl transpeptidase （GGT） （WMD=-3.26， 95%CI： -7.79 to 1.27， P>0.05， SUCRA=82.3）， and glycated hemoglobin （HbA1c） （WMD=-0.6， 95%CI： -2.02 to 0.82， P>0.05， SUCRA=78.8）； moderate-intensity aerobic exercise was the optimal intervention modality to improve Homeostasis Model Assessment of Insulin Resistance （WMD=-0.92， 95%CI： -1.51 to -0.33， P<0.05， SUCRA=69.4）. It should be noted that there were no significant differences in HbA1c and GGT across different exercise interventions （all P>0.05）， suggesting that there was currently no sufficient statistical evidence to support that exercise could improve these two indicators. ConclusionBased on the comprehensive league table and cumulative probability ranking， aerobic exercise combined with resistance exercise， resistance exercise， and low- and moderate-intensity aerobic exercise may be the best exercise modality for improving key indicators in MAFLD patients， and targeted exercise modalities should be selected for intervention against different indicators； however， due to limitations of the original studies， further studies are needed for validation and exploration.

Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

Objective: To investigate the impact of disposable plastic food container usage on the executive function among primary school students, so as to provide the evidence for the formulation of relevant health policies. Methods: From November 2023 to May 2024, a convenience sampling method was employed to select 1 118 grade 1-3 students from three primary schools in a central district of Chongqing. A self developed questionnaire was used to collect demographic characteristics and data on disposable plastic food container usage. Executive function of primary school students was assessed using the Childhood Executive Functioning Inventory (CHEXI). Multivariate linear regression analysis was conducted to explore the associations between disposable plastic food container usage and heating with executive function among primary school students. Results: Median scores for working memory, inhibition and total executive function among primary school students were 32 (26, 39), 33 (28, 38), and 66 (54, 75), respectively. Multivariate linear regression analysis showed that among girls, higher frequencies of eating meals from plastic lunchboxes were associated with higher CHEXI working memory scores ( β =1.29), inhibition scores ( β =1.57), and total executive function scores ( β =2.85) ( P <0.05). Compared to girls who did not use plastic cups or drank bottled water, those who used plastic cups for drinking or drank bottled water had higher scores in working memory ( β =2.63), inhibition ( β =2.10), and total executive function ( β =4.73); compared to girls who did not eat canned food from metal cans, those who ate such food had higher scores in working memory ( β =3.62), inhibition ( β =1.89), and total executive function ( β =5.50) ( P <0.05).Among boys, higher frequencies of eating meals from plastic lunchboxes were associated with higher inhibition scores ( β =1.13) ( P <0.05). Compared to girls who ate with a plastic lunch box and did not heat it when they ate,girls who more frequent heating plastic lunchboxes with food inside had higher working memory scores ( β = 5.39), inhibition scores ( β =4.29), and total executive function scores ( β = 9.68) ( P <0.05). Conclusions The use of disposable plastic food containers may adversely affect executive function of primary school students, with a more pronounced effect observed in girls. Strengthened regulation of disposable plastic products and health education are urgently needed.

Salvia miltiorrhiza is a perennial herb of the genus Salvia(Lamiaceae). As one of the earliest medicinal plants to undergo molecular biology research, it has gradually become a model plant for molecular biology of medicinal plants. With the gradual analysis of the genome of S. miltiorrhiza and the biosynthetic pathways of its main active components tanshinone and salvianolic acids, the transcriptional regulation mediated by transcription factors and related regulatory proteins has gradually become a new research focus. Due to the lack of scientific and unified naming of transcription factors and different research indexes in different literature, this paper systematically sorted out the transcription factors in different literature with the genomes of DSS3 from selfing for three generations and bh2-7 from selfing for six generations as reference. In total, 73 transcription factors and related regulatory proteins belonging to 13 gene families were identified. The effects of overexpression or gene silencing experiments on tanshinone and salvianolic acids were also analyzed. This study unified the identified transcription factors, which laid a foundation for further constructing the regulatory networks of secondary metabolites and insect or stress resistance and improving the quality of medicinal materials by using global transcriptional regulation engineering.
Salvia miltiorrhiza/chemistry* ; Plant Proteins/metabolism* ; Gene Expression Regulation, Plant ; Transcription Factors/metabolism* ; Abietanes/metabolism*

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness