OBJECTIVE To investigate the effects of baicalin （BC） on insulin resistance in rats with gestational diabetes mellitus （GDM） and its underlying mechanism based on the adenosine monophosphate-activated protein kinase （AMPK）/suppressor of variegation 3-9 homolog 1 （SUV39H1）/histone H3 lysine 9 trimethylation （H3K9me3） axis. METHODS A GDM rat model was established by a combination of a high-fat diet and streptozotocin injection. The successfully modeled rats were divided into the GDM group， BC low-dose group， BC high-dose group， and high-dose of BC+AMPK inhibitor （Compound C） group， with 10 rats in each group. Another 10 pregnant rats fed a normal diet served as the control group. Rats in each group were given corresponding drugs/normal saline intragastrically and/or intraperitoneally， once daily for 2 consecutive weeks. After the last administration， the levels of fasting blood glucose （FBG）， pancreatic function indexes [fasting insulin （FINS）， homeostasis model assessment of insulin resistance （HOMA-IR）， insulin sensitivity index （ISI）]， blood lipid indexes （total cholesterol， triglyceride， low-density lipoprotein cholesterol）， liver function indexes （alanine transferase， aspartate transferase， alkaline phosphatase）， inflammatory indicators （C-reactive protein， interleukin-1β， interleukin-6）， metabolic regulatory protein [complement-C1q/tumor necrosis factor-related protein 3 （CTRP3）]， insulin sensitivity related factors [glucose transporter 4 （GLUT4）， adiponectin]， and oxidative stress indicators [superoxide dismutase （SOD）， catalase （CAT）， malondialdehyde （MDA）] were measured. Pathological changes in liver tissue were observed， and the expressions of proteins related to the AMPK/SUV39H1/H3K9me3 axis in liver tissue were detected. RESULTS Compared with the GDM group， rats in the BC low- and high-dose groups showed varying degrees of improvement in pathological changes such as disordered cell arrangement， vacuolar degeneration， lipid deposition， and inflammatory cell infiltration in liver tissue. Their FBG and FINS levels， HOMA-IR， the levels of blood lipid indexes， liver function indexes， inflammatory indicators and MDA， and the expressions of SUV39H1 and H3K9me3 were significantly decreased or down-regulated， while metabolic regulatory protein， insulin sensitivity-related factors and AMPK protein phosphorylation levels were significantly increased （ P ＜0.05）. The improvement was more significant in the BC high-dose group （ P ＜0.05）. Compound C could significantly reverse the ameliorative effects of high-dose BC on the above quantitative indicators （ P ＜0.05）. CONCLUSIONS BC can significantly reduce oxidative stress and inflammatory responses， increase serum levels of CTRP3， GLUT4 and adiponectin， thereby improving insulin resistance in GDM rats. These effects may be related to the activation of AMPK and inhibition of SUV39H1-mediated H3K9me3 modification.

Objective: To analyze the association between insufficient sleep and score of depressive symptoms among junior and senior high school students, so as to provide a scientific reference for targeted early intervention measures of adolescents depressive symptoms. Methods: From September to November 2023, a stratified cluster random sampling method was used to select 96 080 junior and senior high school students from 409 schools in 113 districts and counties in Shaanxi Province. A questionnaire survey was conducted using the 2023 Shaanxi Provincial Common Student Diseases and Health Influencing Factors Survey Form, and their height and weight were measured. Propensity score (PS) matched (1∶1) analysis was used to match participants with insufficient sleep to those sufficient sleep students. Through the gradual correction of the confounders, three multilevel linear models were established to analyze the association between insufficient sleep and depressive symptoms score, and subgroup analysis was conducted afterward. Results: A total of 70 135 (73.00%) students had insufficient sleep. After PS matching, 25 894 pairs were matched. Before PS matching, after adjusting for gender, educational stage, region, adolescent characteristics, boarding status, smoking, alcohol consumption, outdoor activities and body mass index grouping, linear regression analysis results showed that compared with students who got adequate sleep, students who lacked sleep had an increase of 1.39 scores ( B=1.39, 95%CI =1.28-1.51) in depressive symptoms; after PS matching, students with insufficient sleep got an increase of 1.32 scores ( B=1.32, 95%CI =1.17- 1.45 ) in depressive symptoms score compared with those who had adequate sleep (both P <0.05). Conclusions The insufficient sleep is associated with the increase of the depressive symptoms score of junior and senior high school students. It is recommended that junior and senior high school students should keep a good sleeping habit, so as to reduce the prevalence of depressive symptoms.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

ObjectiveTo study on the different therapeutic effects and potential mechanisms of Rhei Radix et Rhizoma（RH） before and after steaming with wine on constipation model mice. MethodsFifty-four male ICR mice were randomly divided into control group， model group， lactulose group（1.5 mg·kg^-1）， high， medium and low dose groups of RH and RH steaming with wine（PRH）（8， 4， 1 g·kg^-1）. Except for the control group， the constipation model was replicated by gavage of loperamide hydrochloride（6 mg·kg^-1） in the other groups. After 2 weeks of modeling， each administration group was gavaged with the corresponding dose of drug solution， and the control and model groups were given an equal volume of normal saline， 1 time/d for 2 consecutive weeks. After administration， the feces were collected for 16S rRNA sequencing， the levels of gastrin（GAS）， motilin（MTL）， interleukin-6（IL-6）， γ-interferon（IFN-γ） in the colonic tissue were detected by enzyme-linked immunosorbent assay（ELISA）， the histopathological changes of colon were observed by hematoxylin-eosin（HE） staining， flow cytometry was used to detect the proportion changes of CD4⁺， CD8⁺ and regulatory T cell（Treg） in peripheral blood. ResultsCompared with the control group， the model group showed significantly decrease in fecal number in 24 h， fecal quality and fecal water rate（P<0.01）， the colon was seen to have necrotic shedding of mucosal epithelium， localized intestinal glands in the lamina propria were degenerated， necrotic and atrophied， a few lymphocytes were seen to infiltrate in the necrotic area in a scattered manner， the contents of GAS and MTL， the proportions of CD4⁺， CD8⁺ and Treg were significantly reduced（P<0.01）， the contents of IL-6 and IFN-γ were significantly elevated（P<0.05， P<0.01）. Compared with the model group， the fecal number in 24 h， fecal quality and fecal water rate of high-dose groups of RH and PRH were significantly increased（P<0.05， P<0.01）， the pathological damage of the colon was alleviated to varying degrees， the contents of GAS， MTL， IL-6 and IFN-γ were significantly regressed（P<0.05， P<0.01）， and the proportions of CD4⁺ and CD8⁺ were significantly increased（P<0.01）， although the proportion of Treg showed an upward trend， there was no significant difference. In addition， the results of intestinal flora showed that the number of amplicon sequence variant（ASV） and Alpha diversity were decreased in the model group compared with the control group， and there was a significant difference in Beta diversity， with a decrease in the relative abundance of Lactobacillus and an increase in the relative abundances of Bacillus and Helicobacter. Compared with the model group， the ASV number and Alpha diversity were increased in the high-dose groups of RH and PRH， and there was a trend of regression of Beta diversity to the control group， the relative abundance of Lactobacillus increased， and the relative abundances of Bacillus and Helicobacter decreased. ConclusionRH and PRH can improve dysbacteriosis， promote immune system activation， inhibit the release of inflammatory factors for enhancing the gastrointestinal function， which may be one of the potential mechanisms of their therapeutic effect on constipation.

Congenital heart disease (CHD) is a congenital malformation resulting from abnormal embryonic development of the heart and great vessels, accounting for approximately 25% of all congenital malformations. Children with CHD are often complicated by short stature. Although surgical treatment can improve their growth and development to a certain extent, some children still experience growth retardation after surgery. Recombinant human growth hormone (rhGH) is the main drug for treating short stature, but its efficacy and safety in the treatment of patients with concomitant CHD warrant further investigation. This article reports six cases of children with CHD and short stature who were treated with rhGH. Through a literature review, we summarize and discuss the therapeutic efficacy, follow-up experiences, and adverse reactions of rhGH treatment, aiming to provide references for clinicians in applying rhGH to treat patients with CHD and short stature.

Objective To analyze the differences in distribution of traditional Chinese medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without, and to explore the potential correlation between the distribution of TCM syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of TCM syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between TCM syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary TCM syndrome elements related to disease location were the lung and liver, and the primary TCM syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary TCM syndrome elements related to disease location were the lung and spleen, and the primary TCM syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of TCM syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there was significant difference in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, the results showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of TCM syndrome elements and the species abundance and composition of salivary microbiota between the patients with pulmonary nodules and the healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

ObjectiveTo assess the level of health literacy and its influencing factors among middle school students aged 12‒18 years in Jing’an District, Shanghai, so as to provide a solid scientific foundation for further developing more targeted intervention measures. MethodsA stratified cluster random sampling method was used to randomly select 4 middle schools in Jing’an District, Shanghai from November to December 2023, and conducted a health literacy questionnaire survey on non-graduating middle and high school students, respectively. The2023 Survey on the Status of Health Literacy among Middle School Students in Jing’an District, Shanghai was adopted, which consisted of two parts: health literacy and basic information. Health literacy was divided into three dimensions: health knowledge and concept literacy, healthy lifestyle and behavior literacy, and health skill literacy. Three dimensions could be categorized into six types of health literacy issue: scientific health literacy, infectious disease prevention and control literacy, chronic disease prevention and control literacy, safety and first aid literacy, basic health literacy, and health information literacy. ResultsA total of 1 161 middle school students were enrolled into this study, including 571 males and 570 females. The overall health literacy level of middle school students was 33.51%, with 34.81% among middle school students and 31.69% among high school students, respectively. Results of logistic regression analysis showed that health knowledge acquisition and awareness, as well as application frequency of health knowledge, were the influencing factors for the overall health literacy level among middle school students (P<0.05). The degree of family attention to health maintenance, health knowledge acquisition and awareness, and application frequency of health knowledge were the main influencing factors for the three dimensions and literacy of six types of health issues among middle school students (P<0.05). ConclusionThe levels of different types of health literacy among middle school students in Jing’an District are uneven, with the highest being safety and first aid literacy and the lowest being basic health literacy. It is recommended to take targeted measures to comprehensively improve the health literacy level of middle school students.

Abelmoschi Corolla, the dried corolla of Abelmoschus manihot, has anti-inflammatory, antioxidant, and anti-fibrosis activities. Its chemical constituents mainly include flavonoids, organic acids, steroids, and polysaccharides. This study reviewed the research progress in the chemical constituents and pharmacological activities of Abelmoschi Corolla in recent 20 years. According to the concept of quality marker(Q-marker), the Q-markers of Abelmoschi Corolla were predicted from plant phylogeny, chemical constituent specificity, traditional efficacy, chemical constituent measurability, and absorbed constituents. The primary Q-markers for Abelmoschi Corolla were anticipated to include quercetin-3'-O-β-D-glucopyranoside, gossypetin-8-O-β-D-glucuronide, isoquercetin, myricetin,quercetin, and hyperoside, with the aim of providing reference data for improving the quality evaluation system of Abelmoschi Corolla.
Abelmoschus/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Flowers/chemistry* ; Humans ; Animals ; Quality Control ; Flavonoids/chemistry*

The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Molecular Structure ; Asteraceae/chemistry* ; Chromatography, High Pressure Liquid ; Magnetic Resonance Spectroscopy