ObjectiveTo investigate the differences in pregnancy outcomes between dichorionic diamniotic （DCDA） twin pregnancies conceived via assisted reproductive technology （ART） and those from spontaneous conception， in order to provide evidence for the perinatal management of ART-conceived DCDA twins. MethodsA retrospective analysis was conducted on the clinical data of 549 DCDA twin parturients. Based on the mode of conception， they were divided into ART group （423 cases） and spontaneous conception group （126 cases）. The baseline characteristics， pregnancy complications and neonatal outcomes were compared between the two groups. ResultsRegarding baseline characteristics， the ART group had higher maternal age， number of previous abortions， proportions of primiparas， proportions of advanced maternal age and greater 24-hour postpartum blood loss， but lower parity and proportion of scarred uterus compared to the spontaneous conception group （P<0.05）. For pregnancy complications， the ART group exhibited higher incidences of hypertensive disorders of pregnancy， placental adhesion， postpartum hemorrhage and a higher application rate of uterine artery ascending branch ligation （P<0.05）. There were no statistically significant differences in neonatal-related indicators between the two groups. After adjusting for confounding factors such as age， number of abortions and parities， ART remained an independent risk factor for hypertensive disorders of pregnancy， placental adhesion and postpartum hemorrhage （P<0.05）， while it did not increase the risk of adverse neonatal outcomes. Further subgroup analysis by gestational age showed that in the late preterm subgroup， the risk of ART-related pregnancy complications remained elevated （P<0.05）. Additionally， neonatal outcomes showed no significant difference between the two groups in both the late preterm and term subgroups. ConclusionART increases the risk of hypertensive disorders of pregnancy， placental adhesion and postpartum hemorrhage in DCDA twin parturients. Clinically， enhanced monitoring of blood pressure during pregnancy and blood loss during delivery and postpartum， along with targeted prevention and management of these complications， are crucial for improving pregnancy outcomes.

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: To explore the correlation between parent-child separation experience and non suicidal self injury (NSSI) behavior among junior and senior high school students, so as to provide a reference for the prevention and improvement of NSSI behavior among junior and senior high school students. Methods: Using a stratified cluster random sampling method, 3 114 junior and senior high school students aged 11-19 years were recruited from Chenzhou and Jishou cities in Hunan Province between November 2024 and September 2025. A self designed questionnaire and the Functional Self injury Behavior Assessment Scale were used to collect information on parental labor migration and adolescents NSSI behavior status. Binary Logistic regression model was used to analyse the association between parent-child separation experiences and NSSI behavior among junior and senior high school students, with further stratified analysis by gender. Results: The prevalence rate of NSSI behavior among junior and senior high school students was 9.9%, and the overall incidence of parent-child separation was 48.9%, comprising 17.1% separated from their father only, 5.5% separated from their mother only, and 26.3% separated from both parents. After adjusting for variables such as age, gender, and ethnicity, the results of binary Logistic regression analyses indicated that adolescents with parent-child separation experiences had a higher risk of NSSI behavior ( OR =1.31, 95% CI =1.01-1.69, P <0.05). Compared with those without parent-child separation experiences, adolescents who were separated from their mother only ( OR =1.68, 95% CI =1.03-2.74) or from both parents ( OR =1.41, 95% CI =1.04-1.92) showed significantly increased risks of NSSI behavior (both P <0.05). Conclusions Parent-child separation experiences are associated with an increased risk of NSSI behavior among junior and senior high school students. Strengthened attention should be paid to left behind senior high school students to reduce the occurrence of NSSI in adolescents.

Renal cell carcinoma is one of the most common malignant tumors of the urinary system.Its pronounced heterogeneity plays a crucial role in disease progression, treatment responses, and clinical outcomes.This review focuses on the heterogeneity of the tumor microenvironment in renal cell carcinoma, summarizing the key cellular interactions, the evolution of immunosuppressive states, and the reciprocal regulation between tumor and stromal components.The paper further discusses the clinical impacts of heterogeneity on immuno-targeted combination therapy, along with the application of emerging technologies, such as single-cell sequencing and spatial transcriptomics, so as to provide theoretical insights and practical guidance for the precision therapy for renal cell carcinoma.

Purpose: Postmicturition dribbling (PMD) is a common but underrecognized lower urinary tract symptom (LUTS). This study evaluated the clinical and urodynamic characteristics of PMD in men with medication-refractory LUTS. Methods: From 2008 to 2010, 150 male patients underwent questionnaire assessment, urodynamic study (UDS), and transrectal ultrasound of the prostate (TRUSP). PMD was defined as a Likert score ≥3. Results: PMD was reported by 47% of patients and was significantly associated with higher International Prostate Symptom Score (IPSS) scores, particularly LUTS such as urgency, incomplete emptying, and weak stream. PMD also adversely affected quality of life, especially motivation, sexual function, and psychological well-being. Among the UDS and TRUSP parameters, only poor bladder compliance was significantly associated with PMD (4% vs. 17%, P=0.016), corresponding to a 4-fold higher risk. Conclusions PMD was prevalent and clinically meaningful in men with LUTS and was strongly associated with core LUTS and reduced bladder compliance. Because PMD is not included in the IPSS, it may be underrecognized in routine clinical evaluation, underscoring the need for broader symptom assessment.

Laboratory animal science is an emerging interdisciplinary field supporting life science and medical research, and a key component of talent cultivation and technological innovation in medical colleges. Currently, this field faces challenges such as a significant imbalance between talent supply and demand and a weak systematic training system. To respond to national strategies and societal needs, Shandong First Medical University established the School of Laboratory Animal through industry-education integration during the 14th Five-Year Plan period. The school is based on The Medical Laboratory Technology major, cultivates application-oriented, interdisciplinary professionals in laboratory animal science, and has constructed a three-in-one training system integrating "course learning–scientific research–industry practice". Specific measures for talent cultivation include: optimizing the general education, professional courses, and intensive practical modules in the talent training program, and establishing the "Yellow River Class" integrating industry and education; implementing an undergraduate mentor system, and conducting scientific research training based on The Model Animal Research and Development Engineering Laboratory; collaborating with bases across the entire industrial chain of laboratory animal production, research, application, and quality control, appointing industry mentors, and strengthening practical teaching. Practice has shown that this system has been remarkably effective: a total of 320 undergraduate students have been enrolled since 2020; the employment rate of undergraduate graduates for two consecutive cohorts has reached 100%, and the postgraduate enrollment rate has exceeded 50%; undergraduate students have won numerous national and provincial awards in academic competitions, and have obtained multiple patents and published papers. In the future, the school will further integrate the advantages of medicine, agriculture, and science, optimize the depth and breadth of courses, strengthen the construction of faculty and teaching materials, and improve the undergraduate-master's integrated training mechanism. This article can provide a reference for the training of professionals in laboratory animal science and related biomedical fields in medical colleges.

Objective To explore the molecular mechanism of Jianfu mixture in the treatment of erectile dysfunction （ED） by network pharmacology and molecular docking techniques, and validate its core targets and mechanisms through in vitro experiments. Methods The active components and corresponding molecular targets of Jianfu mixture were searched by searching TCMSP and Batman-TCM databases, and the disease targets of ED were searched by using GeneCards database. Find the intersection of drug ingredient target and disease target. The interaction between intersected targets was described and analyzed by String database, and the analysis results were visualized by Cytoscape software to determine the core target and the corresponding active components. GO functional enrichment analysis and KEGG pathway enrichment analysis were performed for intersection targets; the core target within the intersection were found through MCODE plug-in on Cytoscape software and molecular docking was performed with the corresponding active ingredients. An endothelial dysfunction model was established by transfecting HUVECs with si-eNOS. Intervene with different concentrations of the Jianfu mixture for the model cells for 24 h. QPCR was used to detect mRNA expression of core targets （MAPK1, MAPK3, JUN, ESR1, MAPK8）; Western blot was used to analyze protein expression （eNOS, JUN, p-JUN, MAPK, p-MAPK） and phosphorylation levels. Results 144 effective active components and 168 active components target-disease targe intersection of Jianfu mixture were obtained. GO analysis revealed 200 5 biological processes, 151 molecular functions, and 63 cellular components. KEGG analysis yielded 181 pathways. 5 core targets including MAPK1, MAPK3, JUN, ESR1 and MAPK8 were screened out. The active components such as β-sitosterol, kaempferol, astapterocarpan had good binding affinity with the core target. In vitro experiments confirmed successful construction of the endothelial dysfunction model （eNOS expression significantly decreased after si-eNOS transfection）. Jianfu mixture dose-dependently inhibited mRNA expression of MAPK1, MAPK3, JUN, ESR1, and MAPK8. Additionally, it reduced phosphorylation levels of JUN and MAPK, indicating inhibition of the JNK/c-Jun and ERK/MAPK signaling pathways to improve endothelial function. Conclusion Jianfu mixture treats ED by suppressing abnormal activation of multi-target signaling pathways （MAPK/JUN/ESR1）, reducing endothelial apoptosis, and promoting NO synthesis. This mechanism aligns with the traditional Chinese medicine principle of “activating blood circulation, resolving stasis, tonifying Qi, and strengthening cardiovascular function.” The study provided molecular-level evidence for the therapeutic efficacy of Jianfu mixture in ED management.

Objective To explore the molecular mechanism of Jianfu mixture in the treatment of erectile dysfunction （ED） by network pharmacology and molecular docking techniques, and validate its core targets and mechanisms through in vitro experiments. Methods The active components and corresponding molecular targets of Jianfu mixture were searched by searching TCMSP and Batman-TCM databases, and the disease targets of ED were searched by using GeneCards database. Find the intersection of drug ingredient target and disease target. The interaction between intersected targets was described and analyzed by String database, and the analysis results were visualized by Cytoscape software to determine the core target and the corresponding active components. GO functional enrichment analysis and KEGG pathway enrichment analysis were performed for intersection targets; the core target within the intersection were found through MCODE plug-in on Cytoscape software and molecular docking was performed with the corresponding active ingredients. An endothelial dysfunction model was established by transfecting HUVECs with si-eNOS. Intervene with different concentrations of the Jianfu mixture for the model cells for 24 h. QPCR was used to detect mRNA expression of core targets （MAPK1, MAPK3, JUN, ESR1, MAPK8）; Western blot was used to analyze protein expression （eNOS, JUN, p-JUN, MAPK, p-MAPK） and phosphorylation levels. Results 144 effective active components and 168 active components target-disease targe intersection of Jianfu mixture were obtained. GO analysis revealed 200 5 biological processes, 151 molecular functions, and 63 cellular components. KEGG analysis yielded 181 pathways. 5 core targets including MAPK1, MAPK3, JUN, ESR1 and MAPK8 were screened out. The active components such as β-sitosterol, kaempferol, astapterocarpan had good binding affinity with the core target. In vitro experiments confirmed successful construction of the endothelial dysfunction model （eNOS expression significantly decreased after si-eNOS transfection）. Jianfu mixture dose-dependently inhibited mRNA expression of MAPK1, MAPK3, JUN, ESR1, and MAPK8. Additionally, it reduced phosphorylation levels of JUN and MAPK, indicating inhibition of the JNK/c-Jun and ERK/MAPK signaling pathways to improve endothelial function. Conclusion Jianfu mixture treats ED by suppressing abnormal activation of multi-target signaling pathways （MAPK/JUN/ESR1）, reducing endothelial apoptosis, and promoting NO synthesis. This mechanism aligns with the traditional Chinese medicine principle of “activating blood circulation, resolving stasis, tonifying Qi, and strengthening cardiovascular function.” The study provided molecular-level evidence for the therapeutic efficacy of Jianfu mixture in ED management.

ObjectiveTo construct a prediction model for high responsiveness to short-term aerobic training in patients with Parkinson's disease (PD) based on dual-task gait assessment, and to provide evidence for identifying individuals who are most likely to benefit from such interventions. MethodsA total of 42 patients with PD who visited the outpatient clinic of Tianjin Huanhu Hospital between August 29, 2023 and December 19, 2024 were enrolled. All participants completed a 4-week home-based aerobic cycling training program and underwent dual-task gait assessments pre- and post-training. Patients were classified into high-response group (n = 12) and low-response group (n = 30) according to whether the improvement in gait speed reached the minimal clinically important difference of 0.1 m/s. The clinical validity of this grouping was verified by comparing differences in cardiopulmonary exercise testing parameters and dual-task gait indicators between the two groups pre- and post-training. Based on baseline characteristics, Firth's penalized maximum likelihood logistic regression was applied to construct a predictive model for high responsiveness, and the discriminative performance of the model was assessed preliminarily. ResultsThe high-response group showed significantly greater improvement in gait speed, step length, cadence and the anaerobic threshold to maximal oxygen uptake ratio after training compared with the low-response group (P < 0.05), confirming the clinical validity of the grouping. The baseline anaerobic threshold to maximal oxygen uptake ratio (OR = 3.348), body mass index (OR = 2.229) and age (OR = 0.428) demonstrated certain discriminative ability in the present sample. The area under the receiver operating characteristic curve was 0.831, with an overall prediction accuracy of 81.0%, specificity of 83.3% and sensitivity of 75.0%. Robustness of the model was confirmed via internal validation using the Bootstrap method, which suggested that the results were informative, but further validation was still required. ConclusionThe anaerobic threshold/maximal oxygen uptake ratio, body mass index and age may predict the response to short-term aerobic training in patients with PD.

ObjectiveTo address the shortage of high-caliber multidisciplinary professionals in China's rehabilitation engineering field and the prominent issue of "separation between medicine and engineering" in existing curricula, this study introduces the World Health Organization rehabilitation competency framework (RCF) to construct a systematic curriculum system for rehabilitation engineering. MethodsGuided by the four core competency domains of RCF (practice, professionalism, learning and development, management and leadership) and their associated supporting knowledge, the rehabilitation engineering curriculum was restructured into a modular framework, piloted and validated within the Biomedical Engineering (Intelligent Robotics) program at University of Health and Rehabilitation Sciences. ResultsA four-tiered curriculum system comprising General Education-Disciplinary Platform-Professional Core-Diverse Electives with a total of 160 credits was established, achieving precise mapping between competency objectives and course content. The students in the pilot cohort demonstrated outstanding academic performance (50% ranked in the top ten of their major), they also gained a deeper understanding and mastery of interdisciplinary knowledge integrating medicine and engineering. ConclusionThe RCF-based curriculum system effectively promotes the organic integration of medical and engineering knowledge, providing an internationally aligned competency-oriented paradigm for rehabilitation engineering talent cultivation, which holds significant value for broader application.