ObjectiveTo investigate the disruptive effects of perinatal exposure to the environmental endocrine disruptor bisphenol AF (BPAF) on hepatic lipid metabolism in prepubertal (postnatal day 21, PND21) male offspring rats, and to provide scientific evidence for assessing the obesogenic effect of BPAF. MethodsSprague-Dawley (SD) rats aged 8 weeks were used in this study. Pregnant rats were divided into BPAF dose groups (2, 10, 50 mg·kg⁻¹) and a vehicle control group (corn oil), with 6 confirmed pregnant females per group. Gavage administration started from gestational day 0 and continued until the end of lactation. At PND21, one male offspring per litter was randomly selected. Serum concentrations of glucose (GLU), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), leptin (LEP), free fatty acid (FFA), as well as oxidative stress markers superoxide dismutase (SOD) and malondialdehyde (MDA), were measured. Pathological changes in liver and adipose tissues were evaluated, and the expression levels of genes related to hepatic lipid metabolism were measured. ResultsCompared to the vehicle control group, the 50 mg·kg⁻¹ group showed significantly increased serum LEP and MDA levels in male offspring (P<0.05), and significant upregulation of hepatic lipoprotein lipase (Lpl), fatty acid synthetase (Fas), and peroxisome proliferator-activated receptor γ (Pparg) gene expression (P<0.05). The 2 mg·kg⁻¹ group exhibited a significant increase in adipocyte length (P<0.05), while the 50 mg·kg⁻¹ group showed significant increases in both adipocyte area and length (P<0.05). No significant abnormalities were observed in liver histopathological examination. ConclusionPerinatal exposure to 50 mg·kg⁻¹ BPAF induced adipocyte hypertrophy, elevated leptin levels, upregulation of lipid synthesis gene expression, and enhanced oxidative stress in prepubertal male offspring, suggesting that BPAF may exert environmental obesogenic effects by disrupting lipid metabolism pathways.

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Uveal melanoma(UM)is the most common primary intraocular malignancy in adults, characterized by high invasiveness and unique metastatic biological features. Although local treatments(such as proton beam therapy and brachytherapy)can effectively control the primary lesion, approximately 50% of patients eventually develop distant metastasis, with the liver being the primary target organ(occurring in 90% of cases). This highlights a paradigm shift in treatment focus from mere local control to systemic prevention and management. For metastatic UM(mUM), current treatment strategies encompass biomarker-guided molecular targeted therapy, immunotherapy(including Tebentafusp, vaccines, and oncolytic virus therapy), and liver-directed therapy. Focusing on the synergy between local and systemic prevention and control, this article systematically elaborates on the precision local treatment for primary UM, the decision-making pathway for systemic treatment of metastatic UM based on molecular subtyping, the integration of local and systemic therapies for liver metastases, and the translational value of nanomedicine in addressing therapeutic bottlenecks. It provides insights for optimizing clinical management of mUM and developing novel therapeutic strategies.

ObjectiveTo investigate the protective effect of α-ketoglutarate （α-KG） on hepatic lipid deposition in offspring caused by arsenic exposure during pregnancy. Methods8-week-old institute of cancer research （ICR） mice were mated in a ratio of 2∶1 between females and males， and the detection of vaginal plugs confirmed pregnant. A total of 32 pregnant mice were randomly divided into four groups： control group， arsenic group， α-KG group， arsenic+α-KG group. On gestational day 0-16 （GD0-GD16）， the arsenic and arsenic+α-KG groups were exposed to sodium arsenite （NaAsO₂ ，15 mg/L） in drinking water everyday， and the α-KG and arsenic+α-KG groups were gavaged with α-KG （2 g/kg） everyday. On GD16， pregnant mice were euthanized to collect fetal liver， and fetal body weight and crown-rump length were measured. Gene expression differences between the control group and the arsenic group were analyzed by transcriptome. The total triglycerides （TGs） and subtypes in fetal liver were detected by liquid chromatography tandem mass spectrometry （LC-MS/MS）. Oil red O staining was used to observe the histopathological changes in the liver. Quantitative polymerase chain reaction （qPCR） was used to detect the expression level of genes related to lipid synthesis， transport， and degradation， and phosphatidylinositol 3' -kinase/ protein kinase B （PI3K/AKT） in the liver of fetus. ResultsTranscriptomics analysis showed that 2 144 genes were downregulated and 1 675 genes were upregulated in the arsenic exposed fetal liver； body weight and crown-rump length were reduced （P_TuKey<0.05）； the level of hepatic TGs was elevated in arsenic group （P_TuKey<0.05）； oil-red O staining showed a significant increase in lipid droplets in arsenic group （P_TuKey<0.01）； the expression of lipid synthesis-related genes were significantly upregulated （P_TuKey<0.05）； the expression of β-oxidation-related genes and lipid degradation-related genes were downregulated （P_TuKey<0.05）； the expression of PI3K， AKT decreased（P_TuKey<0.05）. Compared with the arsenic group， the body weight and crown-rump length of fetus increased in the arsenic+α-KG group （P_TuKey<0.05）； the level of hepatic TGs decreased in the arsenic+α-KG group （P_TuKey<0.05）； oil red O staining showed lipid droplets significantly decreased （P_TuKey<0.01）； the expression of lipid synthesis-related genes were downregulated （P_TuKey<0.05）， the expression of β-oxidation-related genes and lipid degradation-related genes were upregulated （P_TuKey<0.05）； the expression levels of PI3K and AKT increased （P_TuKey<0.05）. Conclusionα-KG alleviated hepatic lipid deposition in offspring exposed to arsenic during pregnancy through activating PI3K/AKT signaling pathway.

Medical parasitology, as a course bridging basic medical sciences and clinical medicine, has an important disciplinary value in the medical education system. This study investigated the composition of parasitology teachers from multiple medical colleges and universities across China. The results showed that there was a significant difference in the proportion of teachers with clinical medicine background knowledge, and there was common dilemma that there were insufficient clinical medicine knowledge reserves among teachers in some medical colleges and universities, who encountered severe teaching challenges. Based on this issue, this study constructed a basic-clinical medicine collaborative problem-based learning (PBL) teaching model. This model integrated theoretical teaching, case analyses, and experimental operations, and combined transdisciplinary team building and multidimensional teacher training, which significantly improved the clinical teaching capability among parasitology teachers, and effectively compensated the impact of insufficient clinical medicine knowledge reserves on teaching. Following teaching reform, students' scores significantly improved, and their case analysis capability enhanced. This study provides a practical path to address the shortage of clinical medicine background knowledge among parasitology teachers, which facilitates the progress of educational reform of medical parasitology and improvement of teaching quality.

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveZheng’s San Qi San (ZSQS) power, a classic traditional Chinese medicine (TCM) formula, is used for treating soft tissue injuries involving muscles, tendons, and ligaments. However, its underlying therapeutic mechanisms remain unclear. This study aimed to screen and identify pharmaceutically active ingredients and their candidate biomolecule targets, and further elucidate the molecular mechanism of ZSQS in the treatment of skeletal muscle injury. MethodsNetwork pharmacology was employed to construct “ZSQS-component-target”, “protein-protein interaction (PPI)” and “active ingredient-core protein-pathway” networks to predict the key active ingredients and potential core targets of ZSQS for skeletal muscle injury. The predicted results were then validated via microarray data from the GEO database. Molecular docking was then performed to assess the binding ability between the screened active ingredients of ZSQS and the candidate core targets. Moreover, liquid chromatography-mass spectrometry (LC-MS) was used for qualitative and quantitative analysis to verify the active components of the drug and ZSQS serum. Finally, an animal model of eccentric exercise-induced skeletal muscle injury and a myotube cell model of oxidative stress-induced injury were established to validate the effects of ZSQS and its interventional effects on the biological functions of critical targets, thereby demonstrating the potential therapeutic mechanism of ZSQS. ResultsAmong the 111 active components identified in ZSQS and their corresponding 204 targets related to the skeletal muscle injury repair process, 14 core targets (including AKT1) and 4 core active components (quercetin, luteolin, kaempferol, and β‑sitosterol) were screened out, while the corresponding metabolites of quercetin, luteolin and kaempferol were detected in the ZSQS serum. Among these targets, 5 candidate genes (IL-6, CASP3, HIF1A, STAT3, and JUN) overlapped with the differential expression screening results with GEO data, and IL-6 was confirmed to be enriched in the PI3K/AKT pathway. Combined with the prediction results of the AKT expression levels, these findings suggest that the phosphorylation level of AKT1 plays a core role in the therapeutic mechanism of ZSQS. Molecular docking analysis further revealed that the PH domain of AKT1 had high binding energy with all 4 core active components, as verified by LC-MS. Finally, animal model studies have shown the promoting effect of ZSQS administration on skeletal muscle injury repair and its possible antioxidant damage mechanism. Cell model studies further demonstrated that ZSQS-containing serum, core active ingredient combination therapy, and quercetin monomer could increase the phosphorylation level of AKT, promote the nuclear translocation of Nrf2, upregulate the expression of downstream antioxidant enzymes (SOD, GPx, and GR), and inhibit the expression of inflammatory factors (IL-6 and TNF-α), thereby alleviating oxidative stress and the inflammatory response. ConclusionZSQS alleviates skeletal muscle injury mainly by activating the AKT/Nrf2 signaling pathway, enhancing cellular antioxidant and anti-inflammatory capabilities. The results of this study provide a scientific basis for the clinical application and modernized development of ZSQS.

Wilson disease （WD） is an autosomal recessive disorder of copper metabolism， and decoppering therapy and symptomatic treatment are the main Western medicine therapies for WD. This article systematically reviews the understanding of the etiology and pathogenesis of WD in traditional Chinese medicine （TCM） and points out that abnormal natural endowment is the core etiology and pathogenesis of WD， with internal accumulation of copper toxicity as the manifestation， liver/spleen/kidney dysfunction as the root cause， and intermingled “toxin， stasis， phlegm， and deficiency” as the key pathogenesis. Literature research and clinical observation are conducted to summarize the common TCM syndromes of WD， including stagnation of liver Qi， internal retention of damp-heat， phlegm-stasis-heat accumulation syndrome， liver-kidney Yin deficiency syndrome， spleen-kidney Yang deficiency， and syndrome of deficiency damage and phlegm stasis. This article proposes the corresponding therapies and representative prescriptions for each syndrome and discusses the advantages of treatment by stage and integrated traditional Chinese and Western medicine therapy. This article aims to provide a systematic reference for the syndrome differentiation-based treatment of WD in clinical practice of TCM， thereby giving full play to the advantages of TCM in the treatment of this disease.