Objective:To develop and evaluate a medical visual question answering (VQA) model for neonatal lung ultrasound (LUS) images to enhance intelligent auxiliary diagnosis of neonatal pulmonary diseases.Methods:Using data from neonates admitted to Beijing Obstetrics and Gynecology Hospital, Capital Medical University (January 2023 to December 2024), an image-question-answer dataset comprising 251 LUS images was constructed [43 pneumonia (17.1%), 42 neonatal respiratory distress syndrome (16.7%), 83 transient tachypnea (33.1%), and 83 normal (33.1%) images] with a four-tier medical question-answer framework. Building upon the Qwen2.5-VL-7B base model and integrating LoRA fine-tuning with chain-of-thought prompting, we developed the NLUS-VQA model to enhance visual-language semantic alignment and enable stepwise clinical reasoning, achieving efficient small-sample adaptation. Model performance was comprehensively assessed through natural language generation metrics (BLEU-4, ROUGE-1/2/L), qualitative evaluation of characteristic recognition, and clinical consistency analysis.Results:(1) Quantitative evaluation demonstrated that NLUS-VQA achieved scores of 22.38 (BLEU-4), 48.26 (ROUGE-1), 22.40 (ROUGE-2), and 37.20 (ROUGE-L), representing significant improvements over baseline models. (2) Qualitatively, the model exhibited strong performance in identifying lung consolidation, coalescent B-lines, and snowflake signs, with its chain-of-thought strategy enhancing clinical interpretability and answer accuracy. (3) Clinically, NLUS-VQA achieved a Cohen's Kappa coefficient of 0.78 and diagnostic accuracy of 80.8% (21/26), indicating substantial agreement with clinical experts.Conclusion:The NLUS-VQA model demonstrates robust interpretability in recognizing key sonographic patterns (e.g. lung consolidation, confluent B-lines, and snowflake signs), providing a scalable framework for small-sample medical image analysis, though diagnostic performance on complex conditions remains limited by dataset scale and minority class representation.

Objective:To develop and evaluate a medical visual question answering (VQA) model for neonatal lung ultrasound (LUS) images to enhance intelligent auxiliary diagnosis of neonatal pulmonary diseases.Methods:Using data from neonates admitted to Beijing Obstetrics and Gynecology Hospital, Capital Medical University (January 2023 to December 2024), an image-question-answer dataset comprising 251 LUS images was constructed [43 pneumonia (17.1%), 42 neonatal respiratory distress syndrome (16.7%), 83 transient tachypnea (33.1%), and 83 normal (33.1%) images] with a four-tier medical question-answer framework. Building upon the Qwen2.5-VL-7B base model and integrating LoRA fine-tuning with chain-of-thought prompting, we developed the NLUS-VQA model to enhance visual-language semantic alignment and enable stepwise clinical reasoning, achieving efficient small-sample adaptation. Model performance was comprehensively assessed through natural language generation metrics (BLEU-4, ROUGE-1/2/L), qualitative evaluation of characteristic recognition, and clinical consistency analysis.Results:(1) Quantitative evaluation demonstrated that NLUS-VQA achieved scores of 22.38 (BLEU-4), 48.26 (ROUGE-1), 22.40 (ROUGE-2), and 37.20 (ROUGE-L), representing significant improvements over baseline models. (2) Qualitatively, the model exhibited strong performance in identifying lung consolidation, coalescent B-lines, and snowflake signs, with its chain-of-thought strategy enhancing clinical interpretability and answer accuracy. (3) Clinically, NLUS-VQA achieved a Cohen's Kappa coefficient of 0.78 and diagnostic accuracy of 80.8% (21/26), indicating substantial agreement with clinical experts.Conclusion:The NLUS-VQA model demonstrates robust interpretability in recognizing key sonographic patterns (e.g. lung consolidation, confluent B-lines, and snowflake signs), providing a scalable framework for small-sample medical image analysis, though diagnostic performance on complex conditions remains limited by dataset scale and minority class representation.

Primary hypertrophic osteoarthropathy(PHO)is a rare disease also known as pachydermo-periostosis.We reported a painless case whose diagnosis was confirmed by genetic test.A 24-year-old male presented a series of symptoms that first began at 14.He suffered from progressive clubbed-fingers accompa-nied by swelling of the wrist and ankle joints.Facial skin concentric thickening and alar nose broadening ap-peared simultaneously and increased progressively.He was also prone to acne and hyperhidrosis.X-rays showed thickening of the metacarpal and phalangeal bones,as well as symmetrical periosteal ossification of both the tibia and fibula.Clinical diagnosis of PHO is difficult because of the variable features.With acromeg-aly excluded,the diagnosis was confirmed by a genetic test.Whole exome sequencing revealed a heterozygous SLCO2A1 c.611C＞T(p.Ser204Lue)and SLCO2A1 c.1602C＞A(p.Asn534Lys)mutation from each par-ent.It suggests that primary hypertrophic osteoarthropathy should be considered for young limb hypertrophic patients especially when periosteal thickening signs were showed in X-ray.A confirmatory diagnosis can be made through the genetic test.

Objective·To evaluate the relationship between body mass index(BMI)and chronic metabolic diseases.Methods·The elderly(≥60 years old)who were underwent physical examination in the Physical Examination Center of Renji Hospital,Shanghai Jiao Tong University School of Medicine from 2014 to 2021 were studied.Their results of biochemical indicators were collected.Their height,body weight,and blood pressure were measured by trained nurses.The history of chronic metabolic diseases was collected by self-reported questionnaire.Systolic blood pressure≥140 mmHg(1 mmHg=0.133 kPa),diastolic blood pressure≥90 mmHg,or self-reported hypertension history was defined as hypertension.Fasting blood glucose≥7.0 mmol/L or self-reported history of diabetes was defined as diabetes.Total cholesterol≥6.2 mmol/L,triglyceride≥2.3 mmol/L,or self-reported history of dyslipidemia was defined as dyslipidemia.The relationship between BMI and hypertension,diabetes,and dyslipidemia was evaluated by using receiver operator characteristic(ROC)curve analysis and binary logistic regression.Results·Data of 59 083 subjects were collected[30 807 men and 28 276 women,average age:(67.9±6.3)years old].The prevalence of hypertension,diabetes and dyslipidemia was 76.5%(45 219/59 083),24.1%(14 225/59 083)and 50.0%(29 544/59 083),respectively.Compared to the elderly people aged 60?74 years,those aged 75 years and above had a higher proportion of hypertension and diabetes,and a lower proportion of dyslipidemia and no metabolic abnormalities.With ROC analysis,the BMI cut-off values for hypertension,diabetes,and dyslipidemia were 24.3,23.9,and 23.9 kg/m2.The BMI cut-off values for hypertension and diabetes in elderly men were similar to those in elderly women(for hypertension:24.3 kg/m2 in elderly men vs 24.2 kg/m2 in elderly women;for diabetes:24.0 kg/m2 in elderly men vs 23.7 kg/m2 in elderly women);however,BMI cut-off value for dyslipidemia was obviously higher in elderly men than that in elderly women(24.0 kg/m2 in elderly men vs 22.5 kg/m2 in elderly women).The BMI cut-off value for chronic metabolic diseases was higher in the elderly people aged 60?74 years than that in the elderly people aged 75 years and above(24.2?24.7 kg/m2 vs 22.9?23.8 kg/m2).Conclusion·Elderly people aged 60?74 years should maintain the BMI below 24.0 kg/m2,while those aged 75 years and above should aim for the BMI below 23.0 kg/m2,so as to reduce the risk of chronic metabolic diseases.

ObjectiveBased on network pharmacology and molecular docking techniques， the mechanism of essential oil from Chimonanthus nitens leaves （CLO） in the treatment of acute lung injury （ALI） was predicted， and a rat model of ALI was established to verify the mechanism of CLO. MethodThe composition of CLO was determined by gas chromatography-mass spectrometry （GC-MS）. The component targets were obtained from PharmMapper and SwissTargetPrediction databases， ALI-related targets were obtained from GeneCards， Online Mendelian Inheritance in Man （OMIM） and DisGeNET， cross-over analysis with differential expressed genes （DEGs） of ALI obtained from Gene Expression Omnibus （GEO） on the Venny 2.1.0 platform yielded potential anti-ALI targets of CLO. Protein-protein interaction （PPI） analysis of potential targets was carried out by STRING 11.5. The tissue expression profiles of potential targets were obtained from the National Center for Biotechnology Information （NCBI） and the target tissue distribution maps were constructed. Potential targets were analyzed for Gene Ontology （GO） function and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment by RStudio 4.0.0 software. Composition-target-pathway network was constructed by Cytoscape 3.9.1 software， and key components and pathways were screened out and verified by molecular docking. ALI model was established by lipopolysaccharide （LPS） induction， levels of interleukin （IL）-6 and tumor necrosis factor （TNF）-α in serum of rats were measured， the expression levels of IL-17 protein in the lung tissue of ALI rats were analyzed by immunohistochemistry. ResultA total of 19 components of CLO were identified by GC-MS， and 18 potential targets were obtained by target screening. After PPI analysis， 15 target proteins with interaction relationship were obtained， further analysis showed that they were highly expressed in lung and thymus. The network diagram of component-target-pathway was analyzed to obtain the key components， including bornyl acetate， linalool， elemol， geranyl isobutyrate， and the core targets of matrix metalloproteinase 13 （MMP13）， S100 calcium binding protein A9 （S100A9）， spleen tyrosine kinase （SYK）， as well as the main signaling pathways， such as IL-17 and TNF. The results of molecular docking showed that the key components were stably bound to MMP13 and S100A9 of IL-17 signaling pathway. The results of pharmacological experiment confirmed that CLO could significantly inhibit the expression of IL-6 and TNF-α in serum of ALI rats， and decrease the expression of IL-17 protein in lung tissue of ALI rats. ConclusionCLO can achieve the therapeutic effect on ALI and protect lung tissue， the mechanism may be related to the decrease of the expression of IL-6 and TNF-α in serum and the inhibition of the activation of IL-17 signaling pathway in lung tissue of ALI rats.

This article reports a case of a 38-year-old female who developed drug hypersensitivity syndrome one month after receiving propylthiouracil. The patient showed improvement with adalimumab, corticosteroids, intravenous immunoglobulin, and plasma exchange. Propylthiouracil is a rare medication associated with drug hypersensitivity syndrome. Additionally, during the follow-up after discharge, rapid changes in thyroid autoantibodies and thyroid function were observed in this patient. By analyzing the progression of this case and reviewing literature, it aims to enhance clinical understanding and management.

Objective To predict the molecular mechanism of Dihuang (Rehmanniae Radix) in the treatment of diabetic nephropathy (DN) complicated with depression based on network pharmacology. Methods The components of Dihuang (Rehmanniae Radix) were identified from the Integrated Pharmacology-based Research Platform of Traditional Chinese Medicine (TCMIP), Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and relevant literature. The component targets were detected by combining the SwissTargetPrediction and PubChem databases. Disease targets were collected from the Therapeutic Target Database (TTD), DisGeNET, and Ensembl databases with “diabetic nephropathy” and “depression” as keywords. The disease-component targets were mapped using Venny 2.1.0 to obtain potential targets. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and Cytoscape 3.7.2. The co-expression genes of the key targets were collected based on the COXPRESdb 7.3. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for potential targets using R language. Target-component docking was verified and evaluated using Discovery Studio 4.5. Results According to the databases and literature reports, Dihuang (Rehmanniae Radix) contained 65 active components, and had 155 related targets for the treatment of DN complicated with depression. PPI screening showed that the key targets included serine/threonine protein kinase 1 (AKT1), signal transducer and activator transcription 3 (STAT3), interleukin 6 (IL-6), mitogen-activated protein kinase 1 (MAPK1), and vascular endothelial growth factor A (VEGFA), etc. GO enrichment analysis mainly involved biological processes, such as lipid metabolism, protein secretion regulation, cell homeostasis, and phosphatidylinositol 3 kinase activity. KEGG pathway enrichment analysis included the role of the AGE-RAGE signaling pathway in diabetic complements, insulin resistance (IR), neurotrophin signal path, Toll-like receptor signaling pathway, relaxin signaling pathway, epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), etc. Molecular docking showed that the target had high affinity for stachyose, manninotriose, verbascose, nigerose, etc. Conclusion Based on network parmacology, this study preliminarily predict the effects of Dihuang (Rehmanniae Radix) in treating DN complicated with depression by regulating inflammation, glucose metabolism, nution nerve, etc.

Objective:To investigate the value of serum miR-143 level combined with MRI in predicting the early response to concurrent chemoradiotherapy (CCRT) in cervical cancer.Methods:A total of 85 patients with pathologically confirmed cervical cancer underwent conventional MRI, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), and dynamic contrast-enhanced MRI (DCE-MRI) before CCRT. The biopsy tissues and serum samples were collected. The differential expression of miRNA in the biopsy tissues was determined by microarray chip. The expression level of miR-143 in the serum samples was analyzed by qRT-PCR. All patients were divided into the non-residual and residual tumor groups according to post-treatment MRI. Pre-treatment clinical factors, MRI parameters and miR-143 between two groups were statistically analyzed by the univariate and multivariate analyses. The optimal thresholds and predictive performance for post-treatment incidence of residual tumors were estimated by drawing the ROC curve.Results:At one month after CCRT, there were 52 patients in the non-residual tumor group and 33 patients in the residual tumor group. In the residual tumor group, pre-treatment FIGO staging, apparent diffusion coefficient (ADC), D and V e were significantly higher (all P<0.05), whereas K trans value was significantly lower ( P<0.001) when compared to those in the non-residual tumor group. The miRNA array analysis showed that there were 16 miRNAs with differential expression levels between two groups (all P<0.05). Among them, the increase of miR-143 was the most significant in the residual tumor group. Compared with the residual tumor group, the expression level of serum miR-143 was significantly down-regulated in the non-residual tumor group ( P=0.002). Compared with the SiHa cells, the expression level of miR-143 in the SiHa-R cells was significantly up-regulated ( P<0.05). Multivariate analysis showed that only miR-143, D, K trans and V e were the independent prognostic factors. The combination of multi-parametric MRI and miR-143 exhibited the highest predictive performance (AUC=0.975), with a sensitivity of 84.8% and a specificity of 96.2%. Conclusion:The combination of multi-parametric MRI with miR-143 further improves the predictive performance for residual tumors after CCRT, which contributes to the personalized treatment of cervical cancer.

Objective To study the clinical efficacy of Bushen Huoxue decoction in the treatment of varicocele infertility and its influence on epididymis function and sperm vitality. Methods A total of 98 patients with varicocele infertility who were treated in our hospital from August 2016 to July 2018 were selected. The patients were randomly divided into control group of 49 cases and study group of 49 cases. The patients in the control group were treated with Maizhiling plus Wuzi Yanzong pill; the patients in the study group were treated with Bushen Huoxue decoction. After 12 weeks of treatment, the clinical efficacy of the patients was evaluated. The semen quality (including semen volume, sperm density, sperm motility, forward-moving sperm), sex hormones, and seminal plasma neutral α-glucosidase in the two groups were compared before and after treatment. After the end of treatment, the patients were followed up for 3 months to observe the pregnancy of the patients' spouse. Results After treatment, the total effective rate of the study group was87.76％, and the total effective rate of the control group was 69.39％. The semen quality, sex hormone and neutral α-glucosidase levels in the study group were better than those in the control group (P<0.05). Conclusion Bushen Huoxue decoction has a significant clinical effect in treating varicocele infertility. It can improve the semen quality, improve testosterone level and seminal plasma neutral α-glucosidase level, and improve the fertility of patients with varicocele.It is worthy of clinical promotion.

Osteoporosis is a complex disease caused by genetic and environmental factors,which the genetic architecture is not completely understood.Genome-wide association study(GWAS)have reformed the identification of genetic determinants of complex diseases including osteoporosis.In the past decade, more than 30 GWASes which were related to bone mass density identified nearly 100 independent loci.The bivariate GWAS approach is an effective approach to detect pleiotropic genes for two osteoporosis traits. However, genetic analyses must be combined with functional studies to understand the underlying mechanisms.The insight of bone metabolism by GWAS is of huge potential for the identification of novel drug targets for osteoporosis.