A 44-year-old male presented with a 19-year history of urinary calculi and a 1-year history of polydipsia and weight loss. Laboratory tests revealed hyperparathyroidism and evidence of glucagonoma-associated diabetes. Imaging studies identified masses in the pancreatic head and body/tail, suggestive of glucagonoma and a parathyroid adenoma. Furthermore, the patient exhibited hypercalcitoninemia and elevated cortisol and adrenocorticotropic hormone levels. Genetic testing revealed a heterozygous MEN1 mutation [c.65T>G (p.Leu22Arg)], confirming the diagnosis of multiple endocrine neoplasia type 1 (MEN-1). The patient subsequently underwent near-total parathyroidectomy and total pancreatectomy. Postoperative immunohistochemical staining of the pancreatic tail tumor was positive for glucagon and calcitonin. The patient′s postoperative hormone levels (calcitonin, glucagon, adrenocorticotropic hormone, cortisol) normalized, suggesting a rare pancreatic neuroendocrine tumor (pNET) that was co-secreting multiple hormones. Postoperative management included pancreatic enzyme supplementation, calcium supplementation, vitamin D supplementation, and insulin for glycemic control. Follow-up evaluations at 10 months demonstrated a stable clinical condition, well-controlled blood glucose and biochemical parameters, and an acceptable quality of life. This case study highlights that the presence of pNETs should be considered in patients with MEN-1 and multiple abnormal hormone levels. Timely surgical management of the involved glands and postoperative complications can effectively improve prognosis.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Objective:To construct an esophageal language rehabilitation program for patients after total laryngectomy (TL) based on the behavioral change wheel theory and exploring its application effects.Methods:The multidisciplinary team constructed the first draft of the esophageal language rehabilitation program for patients after TL based on the behavioral change wheel theory, combined with a literature review, and used an expert meeting to revise the rehabilitation program to form the final draft of the program. Adopting experimental research, 35 patients after TL who attended the nursing outpatient clinic of Beijing Tongren Hospital, Capital Medical University from February 2023 to May 2023 were selected as the control group by convenience sampling method, and 35 patients after TL who attended the nursing outpatient clinic from June 2023 to September 2023 were selected as the experimental group. The experimental group applied the TL postoperative patients′ esophageal language rehabilitation program based on the behavioral change wheel theory on the basis of conventional nursing measures, and the control group received conventional nursing care. The status of language rehabilitation training, quality of life, social behavioral status, and anxiety and depression status before intervention, 1, 3, 6 months after intervention were compared between the two groups.Results:Both groups of patients completed the study. There were 29 males and 6 females in the control group, with an age of (54.63 ± 10.44) years old. There were 34 males and 1 female in the experimental group, with an age of (55.17 ± 10.67) years old. There was no statistically significant difference in the language rehabilitation training status, quality of life, social behavior status, and anxiety and depression status between the two groups before intervention (all P>0.05). The total scores of speech rehabilitation training in the experimental group at 1, 3, and 6 months after intervention were (32.80 ± 2.49), (39.80 ± 2.75), (51.91 ± 4.20) points, respectively, which were higher than those in the control group (23.40 ± 3.42), (24.40 ± 3.42), (25.80 ± 3.42) points, and the differences were statistically significant ( t=14.53, 23.44, 32.70, all P<0.05). The total scores of quality of life in the experimental group at 1, 3, and 6 months after intervention were (98.91 ± 8.49), (134.66 ± 11.31), (157.97 ± 13.97) points, respectively, which were higher than those in the control group (67.06 ± 7.64), (72.16 ± 7.64), (99.46 ± 8.09) points, and the differences were statistically significant ( t=17.53, 30.16, 21.45, all P<0.05). The scores for social occasion diet and language comprehension in the experimental group at 1, 3, and 6 months after intervention were (40.41 ± 13.94), (40.43 ± 24.08), (40.60 ± 18.56), and (43.71 ± 12.26), (47.40 ± 17.09), (52.50 ± 13.82), respectively, which were higher than those in the control group (30.59 ± 15.98), (30.57 ± 18.28), (27.21 ± 15.27), and (27.29 ± 15.13), (23.60 ± 14.78), (19.50 ± 12.78), and the differences were statistically significant ( t values were -6.88-2.16, all P<0.05). The total scores of anxiety and depression in the experimental group at 1, 3, and 6 months after intervention were (23.74 ± 2.73), (14.89 ± 3.89), (12.11 ± 3.14) points, respectively, which were lower than those in the control group (32.63 ± 1.85), (30.63 ± 1.85), (24.80 ± 2.75) points, and the differences were statistically significant (t=-19.55, -27.10, -17.97, all P<0.05). Conclusions:The esophageal language rehabilitation program for patients after TL based on the behavioral change wheel theory in this study is scientific, feasible, and can improve the patients′ esophageal language expression, quality of life, anxiety and depression, and social behavioral status, which can provide a reference for clinical care.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Objective To develop a virtual reality rehabilitation support system and evaluate its effects on improving discharge readiness in caregivers of laryngectomy patients.Methods The system is equipped with a virtual reality-based home nursing skills guidance module for post-laryngectomy patients and an evidence-based artificial intelligence Q&A module.A convenience sampling method was adopted to select 64 caregivers of patients who underwent laryngectomy for the first time in the otorhinolaryngology head and neck surgery department of a tertiary A hospital in Beijing from July 2024 to January 2025 for a systematic study on application effects.To avoid cross-contamination between an experimental group and a control group,ward-based grouping was applied.A coin toss was used to assign Ward 1 to an experimental group and Ward 2 to a control group,with 32 cases in each group.The experimental group received discharge guidance based on the virtual reality technology,while the control group was provided with conventional verbal and written discharge instructions.The readiness for hospital discharge and the quality of discharge teaching scores of caregivers were compared between the 2 groups after the intervention.Results No sample detachment.After the intervention,the patient caregivers in the experimental group scored significantly higher than those in the control group in terms of discharge readiness and quality of discharge guidance,with a statistically significant difference(P＜0.001).Conclusion This study developed the virtual reality rehabilitation system for laryngeal cancer patients demonstrated good feasibility and effectiveness.The application of this system for discharge education significantly improved discharge readiness of caregivers and quality of discharge guidance for post-laryngectomy patients.It also helped with the optimization of health education models,enhancement of nursing resource utilization efficiency,and improvement of transitional care.

Objective:To analyze the effect of different doses of estrogen on endometrial blood flow after tran-scervical resection of adhesion(TCRA)surgery in patients with intrauterine adhesion(IUA).Methods:A total of 70 moderate and severe IUA patients who underwent TCRA in the General Hospital of Ningxia Medical University from 2021 to 2023 were divided into group A(4 mg/day)and group B(6 mg/day)according to the dosage of es-trogen after operation.Reexamination of hysteroscopy was performed 2 months later,menstrual volume was fol-lowed up,uterine parameters in secretory phase were detected by B-ultrasound,and factors related to prolifera-tion,fibrosis and blood flow were detected by immunofluorescence after 3 months.Results:① In the severe IUA group,there was no difference in the rate of intrauterine re adhesion between group A2 and group B2.The satis-faction rate of endometrial epithelialization and endometrial glandular duct density in group B2 was higher than that in group A2,and the difference was statistically significant(P＜0.05).There was no significant difference in the three indicators within the moderate IUA group(P＞0.05).②Three months after operation,in the severe IUA group,there were statistically significant differences(P＜0.05)in menstrual flow,endometrial thickness ET,endo-metrial volume EV,endometrial blood flow values(VI,FI,VFI),and uterine artery blood flow values(PI,RI)be-tween the two groups;The above indicators showed no statistically significant differences within the moderate IUA group(P＞0.05).③Detection of endometrial markers:the expression of proliferation marker(Ki-67)and angio-genesis marker(CD31,CD34,CD146,b-FGF,VEGF)in group B2 was higher than that in group A2,while the ex-pression of fibrosis marker(α-SMA,TGF-β1)was lower,with statistical significance(P＜0.05).There was no sig-nificant difference in the expression of above indexes between group A,and group B,in moderate IUA group(P＞0.05).Conclusions:Short-term application of relatively high dose estrogen(6 mg/day)after TCRA can pro-mote better endometrial repair by improving endometrial blood flow in patients with severe IUA,while in patients with moderate IUA there is no significant difference in the effect on endometrial repair.

Objective:To explore the feasibility of high-level deep learning image reconstruction (DLIR-H) algorithm in dynamic myocardial perfusion (CTP) and coronary CT angiography (CCTA) extraction.Methods:From October 2021 to October 2022, 41 patients with confirmed or suspected coronary heart disease who underwent traditional CCTA and dynamic CTP examinations on GE Apex CT were prospectively collected. Traditional CCTA used 100 kVp tube voltage scan and DLIR-H to reconstruct the original image, while dynamic CTP used 80 kVp tube voltage scan to reconstruct the original image with ASiR-V 100% and DLIR-H, respectively. Comparing subjective and objective scores and myocardial blood flow (MBF) values?of rest and stress CTP between ASiR-V100% and DLIR-H. Subjective and objective scores, as well as stenosis degree and coronary CT blood flow reserve fraction (CT-FFR) value were analyzed on a vessel basis, and the image quality and diagnostic performance of traditional CCTA and single-phase CCTA (SP-CCTA) extracted under DLIR-H CTP were compared. Statistical analysis were performed using paired t test, Wilcoxon signed-rank test and χ2 test. Results:In the subjective image quality analysis of resting and stress CTP, DLIR-H was improved compared with ASiR-V100%, and the difference was statistically significant (all P<0.05). There was no significant difference in MBF values obtained by the two reconstruction methods in the assessment of quantitative myocardial perfusion ( P>0.05). Compared with traditional CCTA, the vascular CT value of SP-CCTA increased by 15.12%, the noise value increased by 32.27%, and the subjective score was also slightly lower (4.23±0.05). However, there were no statistically significant differences in total plaque volume, maximum stenosis degree, and number of CT-FFR positive vessels between SP-CCTA and traditional CCTA (all P>0.05). Conclusion:The deep learning reconstruction algorithm can not only improve the quality of the original image to a certain extent on dynamic CTP, but also extract high-quality single-phase CCTA to meet clinical diagnosis and realize a “one-stop” dynamic myocardial perfusion examination, which will help simplify the examination process, reduce contrast agent and radiation doses in the future.

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.