Objective To understand the status of body image disturbance and its influencing factors in patients with ankylosing spondylitis (AS), so as to provide a scientific basis for the clinical management of AS. Methods A total of 353 AS patients admitted from January 2022 to December 2024 were selected as research subjects. Chinese version of Body Image Disturbance Questionnaire (BIDQ) was used to investigate the body image disturbance in AS patients. Single factor analysis was performed by t test and analysis of variance, and multiple factors were analyzed by multivariate linear regression. Results The total score of BIDQ in 342 AS patients was (25.01±4.22). Multivariate linear regression analysis results showed that self-paid medical expense, nighttime VAS score and negative emotion PANAS score could positively predict body image disturbance in AS patients (standardized regression coefficient=0.413, 0.413, 0.460, P<0.05), and PSSS score, positive emotion PANAS score and exercise management CDSSM score could negatively predict body image disturbance (standardized regression coefficient=-0.245, -0.134, -0.247, P<0.05). Conclusion The body image disturbance in AS patients is worthy of clinical attention. Nighttime pain, negative emotion and self-paid medical treatment can increase the risk of body image disturbance. Positive emotion, social support and high self-management level of exercise behavior can reduce the formation of body image disturbance, which can provide new ideas for clinical management of AS patients.

Background Per- and poly-fluoroalkyl substances (PFAS) can influence gestational diabetes mellitus (GDM); however, current studies on their association are limited and have yielded inconsistent findings. Objective To investigate the association between maternal exposure to PFAS, as measured by urinary concentrations in early pregnancy, and the risk of developing GDM. Methods Based on the Wuhu Birth Cohort in Anhui Province conducted between 2020 and 2023, this study included 1910 pregnant women. Urine samples were collected during the first trimester, and a 75 g oral glucose tolerance test (OGTT) was completed at 24–28 gestational weeks. The concentrations of six PFAS in urine were measured using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Participants were categorized into low, medium, and high exposure groups according to tertiles of individual PFAS concentrations. Logistic regression analysis was employed to assess the potential impact of early-pregnancy PFAS exposure levels on the risk of GDM, with stratified analyses by maternal age and fetal sex. A generalized weighted quantile sum regression (gWQS) model was applied to evaluate the relative weight distribution of the six PFAS in their mixture effect. Results The logistic regression results revealed that both medium exposure to perfluorohexane sulfonate (PFHxS) (OR=1.475, 95%CI: 1.040, 2.093) and high exposure to perfluorononanoic acid (PFNA) (OR=1.430, 95%CI: 1.013, 2.018) were positively associated with diagnosed GDM. This association was more pronounced among women older than 28 years. Among pregnant women carrying male fetuses, high-level exposures to per fluorohexanoic acid (PFHxA) (OR=1.708, 95%CI: 1.006, 2.899) and PFHxS (OR=2.116, 95%CI: 1.247, 3.584) showed positive associations with diagnosed GDM. In contrast, among those carrying female fetuses, moderate perfluorooctanesulfonic acid (PFOS) exposure was associated with a lower risk of GDM (OR=0.542, 95%CI: 0.311, 0.946). The gWQS results demonstrated that PFOS (0.48) and perfluorobutane sulfonate (PFBS) (0.34) contributed the most to the mixture effect. Conclusion Early-pregnancy exposure to PFAS (particularly PFHxS and PFNA) may be an etiological factor for GDM, with maternal age and fetal sex potentially acting as effect modifiers in this association.

Objective: The cross sectional study aimed to identify predominant co-occurrence patterns among six common mental health issues in college students, so as to provide empirical basis for designing targeted interventions. Methods: From October 2024, a total of 9 837 students from 4 universities in Xiangtan City, Hunan Province, participated in the current study by multistage random cluster sampling method. Participants completed self report measures, including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7 item Scale (GAD-7), Young s Internet Addiction Diagnostic Questionnaire, the Adolescent Insomnia Symptom Self rating Scale, the Ottawa Self injury Inventory, and the Brief Community Assessment of Psychic Experiences Questionnaire. Demographic and co-occurrence characteristics were first compared using Chi square or trend Chi-square tests, followed by application of the Apriori algorithm to mine association rules for primary co-occurrence patterns. Results: The detection rate of co-occuring the common mental health issues was 46.44%. The detection rate was significantly higher in female than in male students (50.42%, 43.61%; χ 2=44.46) and in students from rural versus urban areas (47.22%, 44.60%; χ 2=5.67) (both P <0.05). Significant differences were observed among freshmen, sophomores, juniors, and seniors (46.63%, 48.35%, 45.05% , 43.66%, respectively; χ 2=9.22, P <0.05), although no statistically significant trend was detected ( χ 2 trend =3.75, P = 0.05 ). Association rule mining identified “anxiety + depression” “anxiety + psychotic experiences + depression” and “anxiety + sleep disorder + depression” as the combinations with the highest support. In addition, “anxiety+depression+Internet addiction+psychotic experiences =>sleep disorder (>= refered to the occurrence of the latter item under the condition that the former item occurs)” and “anxiety + depression+Internet addiction=>sleep disorder” were combinations with relatively high confidence. Conclusions Co-occurrence of these mental health issues among college students is high and exhibits diverse patterns. Strategies to address this burden should prioritize integrated interventions that target these specific combinations of factors.

Hyperthyroidism （HT） is frequently complicated by atrial fibrillation （AF） in clinical practice. Based on traditional Chinese medicine （TCM） zang-xiang （藏象） theory and clinical experience， both HT and AF are closely associated with dysfunction of the liver. The pathogenesis is initiated by the liver failing to govern the free flow of qi， and liver constraint and qi stagnation， with the key turning points being liver constraint transforming into fire and the internal stirring of liver wind， ultimately leading to liver blood depletion and insufficient nourishment of the heart spirit. Thus， it is proposed to treat the disease from the liver， with stage-specific therapeutic approaches according to the evolution of the disease. In the early stage， the treatment should focus on soothing the liver and relieving constraint to reduce goiter and calm the heart， while in the progressive stage， the method of clearing liver and draining fire is suggested to subdue yang and stabilize palpitations. In the acute stage， the strategy is calming the liver and nourishing yin to subdue yang and extinguish wind. In the later stage， it is suggested to soften the liver and benefit qi， so as to nourish yin and restore pulse. These methods are sequentially applied to synergistically reduce goiter and stabilize palpitations， providing a therapeutic approach for HT complicated by AF.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

Major depressive disorder (MDD) is a prevalent psychiatric condition characterized by high rates of prevalence and recurrence. Repetitive transcranial magnetic stimulation (rTMS) has been widely utilized in the acute phase treatment of MDD and has shown potential in maintenance therapy. However, the factors influencing the efficacy of rTMS during the acute phase and the sustainability of its long-term therapeutic effects remain incompletely understood. Additionally, a consensus on the optimal maintenance treatment protocol has yet to be established. This article reviews recent evidence on the application of rTMS in both acute and maintenance treatment of MDD, aiming to summarize current research progress and provide insights for the further promotion and application of rTMS in clinical practice.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective To explore the role of neogambogic acid in the characteristics of colorectal cancer stem cells (CRC-CSCs) through the Wnt/β-catenin signaling pathway. Methods The colorectal cells SW480 and HCT166 were divided into control group and neogambogic acid groups (1.5, 3, 6, and 12 μmol/L). The viability of CRC-CSCs was determined by MTT method, and spheroid and clone formation assays were used to assess the capacity of spheroid formation and self-renewal ability of the cells. The effects of neogambogic acid on the apoptosis and cell cycle of CRC-CSCs were evaluated by flow cytometry assays. Real-time quantitative PCR was used to detect the mRNA expression levels of relative markers (CD133, CD44, ALDH1, Oct4, and Nanog) of CRC-CSCs, and the protein expression levels of the self-renewal marker (PCNA), apoptosis markers (cleaved caspase-3 and cleaved caspase-9), and Wnt/β-catenin signaling pathway markers (p-GSK3β, GSK3β, β-catenin, and Wnt) were analyzed using Western blot. Results Compared with the control group, after neogambogic acid treatment, the viability of SW480 and HCT116 cells decreased (P<0.05), the spheroid forming ability and the clone numbers of CRC-CSCs decreased (P<0.001, P<0.01) but the cell apoptosis rate increased (P<0.01), and cell cycle was arrested in G₀/G₁ phase. Moreover, neogambogic acid downregulated the mRNA and protein expression of relative markers of CRC-CSCs (CD133, CD44, ALDH1, Oct4, and Nanog), PCNA, p-GSK3β, β-catenin, and Wnt (P<0.05) and upregulated the expression of cleaved caspase-3, cleaved caspase-9, and GSK3β (P<0.01). Conclusion Neogambogic can inhibit the stem cell properties of colorectal cells via inhibition of Wnt/β-catenin signaling pathway. As a result, neogambogic acid may be an attractive agent against colorectal cancer.