Molar-incisor hypomineralization (MIH) is a developmental defect of enamel that is characterized primarily by abnormal enamel mineralization affecting the first permanent molars and permanent incisors. Due to insufficient mineralization, teeth affected by MIH are prone to post-eruptive breakdown and caries, potentially leading to sequelae such as tooth sensitivity and occlusal problems. The diagnosis of MIH is primarily based on relevant perinatal and infantile medical history, the characteristic distribution of affected teeth, and the morphological features of the enamel defects. Based on the extent and severity of the enamel defect, MIH is classified as mild or severe. Diagnosis and treatment strategies emphasize early screening, diagnosis, and intervention, prioritizing prevention, providing symptomatic care, and implementing regular recall assessments. Mild MIH predominantly manifests as demineralized enamel opacities or discoloration, typically without significant enamel breakdown. Treatment focuses on caries prevention and aesthetic restoration, employing techniques such as remineralization, micro-abrasion, resin infiltration, bleaching, fluoride application, and fissure sealants. Severe MIH typically presents with extensive enamel opacities accompanied by substantial enamel breakdown and may be complicated by caries and tooth sensitivity. Management primarily involves restoring the structural defects or, for teeth that cannot be preserved, extraction followed by orthodontic treatment. Comprehensive management often requires a multimodal approach integrating various therapeutic modalities to restore both the function and aesthetics of the affected teeth and overall dentition. This article provides a review of advancements in diagnosis and the treatment strategies for MIH, offering a reference for clinical practice.

Background Health literacy is closely related to mental health, and improving health literacy has been shown to promote mental well-being. However, whether occupational stress among workers in mining and manufacturing is associated with their occupational health literacy remains inconclusive. Objective To study the levels of occupational health literacy and occupational stress among workers in three industrial sectors (metal ores mining, metal smelting, and manufacture of non-metallic mineral products) in Gansu Province, and to analyze the correlation between them. Methods Between May and December 2024, a stratified cluster random sampling method was employed to survey workers from 73 large, medium, and small and micro sized enterprises across the aforementioned industries in Gansu Province. Participants’ occupational health literacy and occupational stress levels were assessed. The LASSO regression model was applied to identifykey factors influencing occupational stress, and subsequently a multilevel random intercept mixed-effects logistic model was used to study factors influencing occupational stress and to explore the relationship between occupational health literacy and occupational stress. Results A total of 3611 workers across the three industries were surveyed, among whom 1031 (28.55%) experienced occupational stress. Workers with adequate occupational health literacy—whether assessed in terms of overall literacy or specific dimensions—demonstrated a significantly lower prevalence of occupational stress compared to those without adequate literacy (P<0.05). Through the LASSO regression analysis, it was found that the factors closely related to occupational stress were dimension one (occupational health legal knowledge), dimension two (basic knowledge of occupational health protection), and dimension four (healthy working methods and behaviors) of occupational health literacy, gender, average monthly income, and night shifts. The results from the three-level random intercept mixed-effects logistic regression model indicated that dimensions one (OR=0.69, 95%CI: 0.58, 0.82), two (OR=0.71, 95%CI: 0.58, 0.87), and four (OR=0.81, 95%CI: 0.67, 0.98) of occupational health literacy were negatively correlated with the risk of occupational stress. Workers with an average monthly income of 3001–≤5000, 5001–≤7000, and ≥7001 yuan reported occupational stress risks that were 61% (OR=0.61, 95%CI: 0.45, 0.81), 56% (OR=0.56, 95%CI: 0.41, 0.78), and 36% (OR=0.36, 95%CI: 0.24, 0.53) of those with an average monthly income ≤3000 yuan, respectively. Male workers (OR=1.66, 95%CI: 1.32, 2.10) and those on night shifts (OR=2.29, 95%CI: 1.90, 2.76) had a higher risk of occupational stress. The random effects variance showed that the intraclass correlation coefficient was 0.12. Conclusion There is a negative correlation between occupational stress and occupational health literacy among workers in mining and manufacturing. Being male, having a low income, and working night shifts are risk factors affecting workers' occupational stress. It is recommended to focus on these groups of workers and incorporate occupational health literacy into workplace mental health promotion.

Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

BackgroundAnxiety disorder is a common mental disorder， with its prevalence showing a continuous upward trend， significantly affecting the quality of life and social function of patients. Due to the lack of objective and reliable biomarkers in clinical practice， the early identification and treatment of anxiety disorder have been somewhat limited. Plasma proteins have the potential to serve as biomarkers for mental diseases， however， the causal relationship between them and anxiety disorder remains unclear. ObjectiveTo identify the plasma proteins that have a causal relationship with anxiety disorders， and to elucidate the associated biological pathways， in order to provide references for the search for biomarkers of anxiety disorders and the exploration of potential therapeutic targets. MethodsBased on the protein quantitative trait locus （pQTL） data of 4 907 plasma proteins covering 35 559 Icelandic individuals from the deCODE database， and the genome-wide association studies （GWAS） data of 50 486 patients with anxiety disorders and 330 460 healthy controls， the inverse-variance weighted （IVW） method was used as the main analysis method， supplemented by MR-Egger method， weighted median method， simple model method， and weighted model method for bidirectional Mendelian randomization analysis. Enrichment analysis of gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathways was conducted for the related proteins. Sensitivity analysis was performed using Cochran's Q test， MR-Egger intercept test， MR-PRESSO test， and leave-one-out analysis to evaluate the robustness of the results. ResultsA total of 10 plasma proteins were identified as significantly associated with anxiety disorders. Among these， SPATA9 （OR=0.856， 95% CI： 0.784–0.934， P<0.01） and PDE5A （OR=0.911， 95% CI： 0.864–0.961， P<0.01） were identified as protective factors， while CRYGD （OR=1.209， 95% CI： 1.095–1.334， P<0.01）， BTN3A3 （OR=1.045， 95% CI： 1.018–1.073， P<0.01）， SERPINB13 （OR=1.102， 95% CI： 1.040–1.168， P<0.01）， ERBB4 （OR=1.283， 95% CI： 1.109–1.484， P<0.01）， LSAMP （OR=1.096， 95% CI： 1.037–1.158， P<0.01）， ICOSLG （OR=1.283， 95% CI： 1.104–1.490， P<0.01）， DNAJB11 （OR=1.172， 95% CI： 1.076–1.277， P<0.01）， and TREML1 （OR=1.115， 95% CI： 1.054–1.179， P<0.01） were identified as risk factors. The sensitivity analysis showed that the results were robust， with no heterogeneity （Cochran's Q test P>0.05） or pleiotropy （MR-Egger intercept test P>0.05）. Enrichment analysis indicated that these plasma proteins were enriched in biological processes such as T-cell signal transduction， lymphocyte proliferation， cell membrane structure and synaptic function， as well as the intestinal immune network that produces IgA and the ErbB signaling pathway. ConclusionThis study identified 10 plasma proteins associated with anxiety disorders. The functions of these plasma proteins involve multiple biological processes such as neural development and immune regulation.

BackgroundIndividuals with schizophrenia are prone to higher rates of hospital readmission， presenting significant clinical challenges and imposing considerable social burdens within the mental health domain. In recent years， various risk prediction models have been developed to forecast readmission in patients with schizophrenia and support clinical decision-making， but their predictive performance and clinical applicability require comprehensive evaluation. ObjectiveTo systematically evaluate the risk prediction models for readmission in patients with schizophrenia， so as to provide insights for the development of high-performance and highly applicable readmission risk prediction models for patients with schizophrenia. MethodsOn July 5， 2025， a systematic literature search was conducted across multiple electronic databases， including PubMed， Embase， Cochrane Library， Web of Science， CINAHL， CNKI， China Biomedical Literature Database， Wanfang Database， and VIP Database， to identify risk prediction models for readmission in patients with schizophrenia. The search period was from the establishment of the databases to July 1， 2025. Two researchers independently performed literature screening， data extraction， risk of bias assessment， and applicability assessment. ResultsA total of 9 studies were included in this review， encompassing 18 risk prediction models for readmission in patients with schizophrenia. Among them， 4 models reported the area under the receiver operating characteristic （ROC） curve （AUC）， ranging from 0.734 to 0.820， 16 models provided AUC values of 0.642–0.879 for internal validation， and 1 model demonstrated an AUC of 0.841 for external validation. Key predictors included disease duration and the concomitant therapy of antipsychotic medications. The risk of bias was assessed as "high" in all included studies. ConclusionThe development of risk prediction models for readmission in patients with schizophrenia remains in an exploratory stage. Although the model exhibits favorable predictive performance， it is associated with a high risk of bias and insufficient performance evaluation.

Objective To explore the adverse event signals of children using macrolide drugs （azithromycin, clarithromycin, and erythromycin）, and provide reference for rational medicine use in clinical practice. Methods Data from children under 12 years old were extracted from the US FAERS database spanning from the first quarter of 2004 to the second quarter of 2023. The adverse drug reaction （ADR） signal mining for three macrolide antibiotics was conducted using the Reporting Odds Ratio （ROR） and Bayesian Confidence Propagation Neural Network （BCPNN） methods. Special emphasis was placed on analyzing and contrasting the differences in adverse events among the three drugs. Results A total of 1 615 reports for children under 12 years old were retrieved from the FAERS database, including 1 024 reports of azithromycin, 460 reports of clarithromycin, and 131 reports of erythromycin. Among azithromycin and erythromycin, there were more reports from boys than girls, while for clarithromycin, there were more reports from girls than boys. Oral administration was the most common route of administration for all three drugs. Regarding the outcome of adverse events reported, azithromycin and clarithromycin were primarily associated with other serious adverse events, whereas erythromycin was mainly associated with hospitalization and other serious adverse events. The number of adverse events reported decreased with increasing age, with a higher number of reports in the 0-3 age group. Using the ROR and BCPNN methods for signal detection, 86 signals were identified for azithromycin, 91 for clarithromycin, and 34 for erythromycin. These signals involved 22 System Organ Classes （SOCs）, with azithromycin mainly concentrated in skin and subcutaneous tissue disorders （n=21）, clarithromycin in gastrointestinal disorders （n=15）, and erythromycin in gastrointestinal disorders （n=8）. Twenty-four signals of moderate to high risk were detected, with 13 for azithromycin, 9 for clarithromycin, and 2 for erythromycin. Conclusion The adverse events induced by the three drugs with different risks in different systems. When clinically treating Mycoplasma pneumoniae pneumonia in children, the risk profiles of drugs in different systems should be considered, and personalized dosing should be implemented.

Objective: To understand the epidemiological characteristics of a pertussis outbreak in Guangzhou, so as to provide references for outbreak response and prevention strategies. Methods: From April 5 to June 9, 2024, case screening was conducted among 246 preschool children, 35 staff members, and one full time school nurse in a kindergarten in Guangzhou based on case definition. Field epidemiological investigation methods were employed to collect relevant information, and screening samples were collected from individuals involved in the outbreak. The clinical manifestations, epidemiological characteristics, and risk factors for transmission of the outbreak were analyzed, with rate comparisons performed using the χ 2 test. Results: There were a total of 15 confirmed cases of pertussis in the kindergarten. The main clinical manifestations included intermittent cough in 14 cases ( 93.33 %), sputum production in 5 cases (33.33%), fever in 2 cases (13.33%), paroxysmal spasmodic cough in 1 case (6.67%), and vomiting in 1 case (6.67%). There was no statistically significant difference in the reporting rates of interrupted cough symptoms between pertussis cases (93.33%) and non pertussis cases (92.86%)( χ 2=3.74, P >0.05). The cases were aged 4-5 years, including 5 males and 10 females. The interval between symptom onset and diagnosis ranged from 2 to 25 days, with a median of 10 days. The outbreak involved two classes, with attack rates of 48.28% and 3.45%, respectively. Laboratory testing confirmed 14 close contacts positive for Bordetella pertussisnucleic acid. Among close contacts, only one received prophylactic medication as required. Conclusion The outbreak is a pertussis outbreak in a kindergarten caused by Bordetella pertussis infection, demonstrating distinct temporal and spatial clustering characteristics.

Objective To compare the clinical outcomes of subxiphoid robot-assisted thoracoscopic surgery (SRATS) and intercostal robot-assisted thoracoscopic surgery (IRATS) in the treatment of anterior mediastinal tumors. Methods A retrospective analysis was conducted on patients with anterior mediastinal tumors who underwent robot-assisted surgery in the Department of Thoracic Surgery, Gansu Provincial Hospital, from May 2020 to July 2022. According to the surgical approach, patients were divided into an SRATS group and an IRATS group. Perioperative data were compared between the two groups. Results A total of 87 patients were included. There were 41 patients in the SRATS group [23 males, 18 females; mean age, (44.51±11.28) years] and 46 patients in the IRATS group [21 males, 25 females; mean age, (46.67±8.76) years]. Compared with the IRATS group, the SRATS group had significantly less intraoperative blood loss [(24.41±6.67) mL vs. (37.93±9.23) mL, P<0.001], shorter postoperative drainage duration [(1.73±0.59) days vs. (2.54±0.50) days, P<0.001], lower postoperative drainage volume [(94.46±34.08) mLvs. (116.72±24.90) mL, P=0.001], lower visual analogue scale (VAS) pain scores on postoperative day 1 [(3.66±0.76) points vs. (4.15±0.84) points, P=0.005] and day 3 [(2.41±0.59) points vs. (2.89±0.82) points, P=0.003], shorter postoperative hospital stay [(4.12±0.81) days vs. (4.98±1.02) days, P<0.001], and lower hospitalization costs [(4.51±0.65) ten thousand yuan vs. (4.86±0.68) ten thousand yuan, P=0.020]. There were no statistical differences between the two groups in operative time or incidence of postoperative complications (P>0.05). Conclusion Both SRATS and IRATS are safe and effective for the treatment of anterior mediastinal tumors. However, SRATS is less invasive and more conducive to enhanced postoperative recovery.

ObjectiveThe biosynthesis of heterophyllin B （HB）， a cyclopeptide from Pseudostellaria heterophylla， is regulated by various abiotic stresses. Elucidating the transcriptional regulatory mechanism underlying HB biosynthesis is of great guiding significance for the directional improvement of P. heterophylla varieties and the enhancement of HB content. MethodsBased on transcriptome data from different tissues of P. heterophylla， transcription factors （TFs） specifically upregulated and highly expressed in the phloem of tuberous roots were screened through a combination of Mfuzz time-series clustering， transcription factor family prediction， and correlation analysis. Quantitative real-time polymerase chain reaction （Real-time PCR） was employed to analyze expression patterns of candidate TFs under abscisic acid （ABA） induction， and the dual-luciferase reporter assay was applied to verify their regulatory effects on HB precursor genes. ResultsContent determination showed that HB accumulated at the highest in the phloem of P. heterophylla tuberous roots （34 μg·g^-1 fresh weight）. Transcriptome analysis identified 15 868 up-regulated differentially expressed genes （DEGs）， among which 4 375 were specifically up-regulated in the phloem. From these， 25 TFs highly expressed in the phloem were screened. Correlation analysis revealed that the expression level of WRKY70 was significantly positively correlated with HB content， the expression of precursor genes prePhHB， and PhPOP1. Additionally， WRKY70 expression was significantly upregulated under ABA induction. Dual-luciferase reporter assay confirmed that WRKY70 specifically activated the transcriptional activity of the prePhHB promoter （Pro-prePhHB）. ConclusionHB is mainly accumulated in the phloem of P. heterophylla tuberous roots. WRKY70 positively regulates HB biosynthesis by directly activating the promoter activity of prePhHB. This study clarifies the key role of WRKY70 in the regulation of HB biosynthesis and provides an important theoretical basis for the in-depth analysis of the molecular regulatory mechanism underlying HB biosynthesis.