OBJECTIVE: To investigate the current status of clinical genetics specialization development and the diagnostic and therapeutic capabilities for hereditary diseases across medical institutions in Shanghai, and to assess the necessity and feasibility of establishing training bases for clinical genetics specialists. METHODS: By employing a cross-sectional survey design, the Clinical Genetics Committee of Shanghai Medical Association has conducted questionnaire surveys from March to April 2025 across 54 healthcare institutions in Shanghai (including 33 tertiary hospitals and 21 secondary hospitals). The survey involved administrative departments and medical personnel from 15 clinical specialties. The survey has covered current genetic disease diagnosis and treatment practices, relevant and specialised disease types, genetic department establishment, testing capabilities, personnel teams, and training requirements. RESULTS: The results revealed that 78.0% of clinical departments surveyed had treated patients with hereditary disorders. Shanghai possesses diagnostic and therapeutic expertise for over 95% of hereditary diseases listed in its rare disease catalogue, reflecting both the practical clinical demand for such conditions and the city's overall diagnostic and therapeutic strengths in this field. Nevertheless, significant disparities exist in the development of genetics departments across different tiers of healthcare institutions. Resources for genetic testing capabilities (including molecular, cellular, and biochemical testing) are also unevenly distributed across different tiers of hospitals. The survey further revealed that only 26.0% of departments believe that their current physician structure fully meets the diagnostic and treatment demands. Over 90% of departments consider standard training for clinical genetic specialists necessary, with 74.0% expressing willingness to participate in establishing training bases. Based on above findings and thorough deliberation, the Clinical Genetics Committee of the Shanghai Medical Association proposes advancing specialist training and discipline development through establishing a standard training system. The committee has drafted a three-year training protocol featuring a "joint training"-centered model, recommending a pilot-first, dynamically optimized strategy for steadily advancing training base development. CONCLUSION Shanghai faces substantial demand for genetic disease diagnosis and treatment, yet exhibits shortcomings in clinical genetics specialization development, resource allocation, and talent pipeline cultivation. To establish a standard training system holds significant practical importance and is underpinned by a broad demand.
Humans ; China ; Surveys and Questionnaires ; Genetic Diseases, Inborn/genetics* ; Cross-Sectional Studies ; Genetics, Medical/education* ; Genetic Testing

Objective To analyze the correlation between lesion volume,lesion mass,and maximum lesion diameter in the assessment of advanced hepatocarcinoma with lung metastasis,and to evaluate the application value of total volume response and total mass response of lung metastatic lesions in efficacy assessment.Methods A retrospective analysis was conducted on the CT imaging data of 20 patients clinically confirmed with hepatocarcinoma and lung metastases,followed by subsequent follow-up to monitor their survival outcomes.Volume measurement software was used to measure the volume of lesions before and after treatment.We recored lesion diameter,volume measurements and CT values,calculated the mass of the lesions.The correlation between lesion volume,mass and diameter was analyzed,as well as the correlation between the change rates of volume,mass and lesion diameter.Additionally,the total volume and total mass of all lesions were calculated.The correlation between the change rates of total volume/total mass and the change rate of pulmonary lesion diameter under the RECIST 1.1 criteria,as well as the correlation with changes in patients'tumor markers,were analyzed.Furthermore,the overall volume response and overall mass response of lesions were evaluated based on changes in total volume and total mass,and their consistencies with the RECIST 1.1 criteria for efficacy evaluation were analyzed.Finally,univariate Cox regression analysis was performed to explore the association between these variables and patient survival outcomes.Results There was strong correlation between lesion volume,mass and tumor diameter(r=0.771,0.775),between the rate of change in mass and the rate of change in lesion diameter(r=0.846),and between the rates of change in total volume/total mass and the rate of change in pulmonary lesion diameter under the RECIST 1.1 criteria(r=0.800,0.896).The correlation between the rates of change in total volume/total mass and patients'tumor markers was not statistically significant.There was moderate correlation between the rate of change in volume and the rate of change in lesion diameter(r=0.692).The evaluation results of total volume response and total mass response for pulmonary lesions in advanced hepatocarcinoma with lung metastasis were generally consistent with the RECIST 1.1 criteria(Kappa=0.486,0.426).Univariate Cox regression analysis revealed that total lesion volume(P=0.047)and total lesion mass(P=0.049)were independent prognostic factors for survival outcomes.Conclusion Lesion volume,mass,and diameter,as well as their respective change rates,were found to be interrelated.Furthermore,total lesion volume and total lesion mass were identified as independent prognostic factors for survival outcomes.The total volume response and total mass response are promising evaluation methods in evaluating the efficacy of lung metastasis of hepatocarcinoma,which are different from the RECIST 1.1 evaluation criteria.

Objective To design a combat rescue specialized physical training simulator to solve the problems of the existing combat rescue physical traing in multifunctionality and simulation vividness.Methods The simulator was divided into three types for stretcher handling,land combat rescue and marine rescue based on the application scenerio and functional positioning,and into three grades of basic level,intensive level and ultra intensive level based on the loaded mass and additional weight object.The main components of the simulator included a manikin,a bionic joint and addtional weight objects.The manikin was made up of outer skin,inner liner and skeleton;the bionic joint was made of stainless steel with surface electrophoresis treatment,and was composed of high-strength medal bearing shafts with multiple disc springs and damping mechanisms;the additional weight objects involued in high-intensity cast iron or lead blocks,which were pre-embedded,mounted or srtapped into the simulator.The simulator was verified with body shape and mass detection,drop test,waterproof test and drag test.Results It's proved the simulator gained advantages in vividness for body shape and mass,bionic joint structure and adaptability to training environments and could be used for graded physical training in typical combat rescue scenerios.Conclusion The simulator developed solves the problems of the combat rescue specialized physical training equipment,and facilitates the enhancement of physical training of combat rescue personnel.[Chinese Medical Equipment Journal,2025,46(1):33-37]

Objective:This prospective study is conducted to explored the influence of Shumian Capsules combine with quetiapine on negative symptoms,sleep quality and neurotransmitters in patients with schizophrenia.Methods:50 patients with schizophrenia admitted to Fuzhou Gulou District Hospital of Fujian Province from April 2022 to May 2024 were retrospectively selected as the study group.According to the principle of 1∶1 matching cases,50 patients with schizophrenia in the same period were selected as the reference group.Reference group received quetiapine treatment,while study group was treated with Shumian capsules on the basis of the reference group.Negative symptom scale(SANS),positive and negative symptom scale(PANSS),Pittsburgh sleep quality index(PSQI),social-skills for psychiatric inpatients(SSPI),treatment emergent symptom scale(TESS),self-rating anxiety scale SAS),self-rating depression scale(SDS)score,neurotransmitter levels[γ-aminobutyric acid(GABA),brain-derived neurotrophic factor(BDNF),glutamic acid(Glu)and the occurrence of adverse reactions were compared between the two groups.Results:The scores of SANS,PANSS,PSQI,TESS,SAS,SDS and Glu levels decreased 4 weeks and 8 weeks after treatment in both groups,and study group were lower than those in reference group,SSPI score and GABA and BDNF levels increased,and study group were higher than those in the reference group(P＜0.05).There was no significant difference in the incidence of adverse reactions between the two groups(P＞0.05).Conclusion:Shumian Capsules combined with quetiapine can effectively improve negative symptoms,sleep quality and neurotransmitters in patients with schizophrenia,and have good safety.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Objective To evaluate the efficacy and safety of enteric-coated metformin hydrochloride capsules(Junlida?)in patients with T2DM and poor glycemic control under lifestyle interventions.Methods In this study,419 patients with T2DM were recruited from 15 research centers from July 2020 to March 2022,and randomly divided into observation(Obs)group(n=209)and control group(Con,n=210)using a multicenter,randomized,double-blind,non-inferiority trial design.Patients in the Obs group were treated with enteric-coated Metformin hydrochloride capsules(Junlida?),and patients in the Con group were treated with Metformin hydrochloride tablets(Glucophage?).The optimal effective dose of 2 g/d was achieved within 4 weeks,and the reasonable dose was maintained until the end of treatment.The treatment period was 24 weeks.HbA1c and its compliance rate,FPG,and body weight were compared between the two groups in full analysis set(FAS)and protocol set(PPS).Safety and adverse events(AE)were evaluated in safety set(SS).Results A total of 414 participants were randomized(207 cases in Obs group and 207 cases in Con group).414 cases in FAS population(207 cases in Obs group and 207 cases in Con group),and 328 cases in PPS population(164 cases in Obs group and 164 cases in Con group),and 414 cases in SS population(207 cases in Obs group and 207 cases in Con group).After treatment,HbA1c,FPG and body weight were lower in both groups(P<0.05)in FAS and PPS.HbA1c compliance rate was not significantly different between the two groups in FAS and PPS(P>0.05).The results of non-inferiority test showed that the lower limit was>-0.4%in both FAS(-0.154,95%CI-0.384～0.069)and PPS(-0.139,95%CI-0.390～0.112),and the Obs group reached non-inferiority end point.The achievement rate,compliance rate,safety index and incidence of AE were not significantly different between the two groups(P>0.05).Conclusions Junlida? demonstrated non-inferiority to Glucophage? in glycemic control and can be safely and effectively used in patients with diabetes.

Objective:This prospective study is conducted to explored the influence of Shumian Capsules combine with quetiapine on negative symptoms,sleep quality and neurotransmitters in patients with schizophrenia.Methods:50 patients with schizophrenia admitted to Fuzhou Gulou District Hospital of Fujian Province from April 2022 to May 2024 were retrospectively selected as the study group.According to the principle of 1∶1 matching cases,50 patients with schizophrenia in the same period were selected as the reference group.Reference group received quetiapine treatment,while study group was treated with Shumian capsules on the basis of the reference group.Negative symptom scale(SANS),positive and negative symptom scale(PANSS),Pittsburgh sleep quality index(PSQI),social-skills for psychiatric inpatients(SSPI),treatment emergent symptom scale(TESS),self-rating anxiety scale SAS),self-rating depression scale(SDS)score,neurotransmitter levels[γ-aminobutyric acid(GABA),brain-derived neurotrophic factor(BDNF),glutamic acid(Glu)and the occurrence of adverse reactions were compared between the two groups.Results:The scores of SANS,PANSS,PSQI,TESS,SAS,SDS and Glu levels decreased 4 weeks and 8 weeks after treatment in both groups,and study group were lower than those in reference group,SSPI score and GABA and BDNF levels increased,and study group were higher than those in the reference group(P＜0.05).There was no significant difference in the incidence of adverse reactions between the two groups(P＞0.05).Conclusion:Shumian Capsules combined with quetiapine can effectively improve negative symptoms,sleep quality and neurotransmitters in patients with schizophrenia,and have good safety.

Objective To investigate the feasibility and safety of transoral transgastric natural orifice transluminal endoscopic surgery(TG-NOTES)cholecystectomy in miniature pigs.Methods A total of 11 miniature pigs were selected as the experimental subjects and underwent TG-NOTES cholecystectomy.These pigs were divided into the Group A and Group B according to the surgical procedures.Among them,7 miniature pigs in the Group A underwent endoscopic cholecystectomy without dissecting the gallbladder triangle,while 4 miniature pigs in the Group B underwent endoscopic cholecystectomy after dissecting the gallbladder triangle.The success rate of surgery,the time of each stage of surgery,the incidence of complications,the success rate of cholecystectomy and the survival rate of miniature pigs in the two groups were counted.One miniature pig in the Group A and 4 miniature pigs in the Group B were selected for survival experiments.After surviving for 1 week,they were killed and dissected to observe the healing of incision and incidence of complications.Results The surgical survival rate of experimental animals was 100%,and the success rate of cholecystectomy was 100%.There was no significant difference in the surgical time,time of cut the stomach into the abdomen,time of gallbladder exploration or time of gallbladder removal of miniature pigs between the two groups(P>0.05).The time of ligating gallbladder artery of miniature pigs in the Group B was longer than that in the Group A,and the time of isdating gallbladder was shorter than that in the Group A,with statistically significant differences(P<0.05).There was no significant difference in the average number of complications of miniature pigs between the two groups(P>0.05).The dissection of animals after survival experiments revealed that the incisions healed well without serious complications.Conclusion This study successfully establishes the surgical model of TG-NOTES cholecystectomy,and confirms the safety and feasibility of TG-NOTES cholecystectomy.

Objective To construct a nomogram prediction model for predicting hemoglobin A1c(HbA1c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021 to January 2022 were selected as the research objects and divided into the non-standard group(HbA1c≥7%,n=801)and the standard group(HbA1c<7%,n=135).Univariate analysis was used to screen the related factors of HbA1c failure.Logistic regression multivariate model was used to analyze the influencing factors of HbA1c failure in T2DM patients.The R language was used to construct a nomogram,and the area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the predictive ability of the model.The C-index and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model.Results There were statistically significant differences in triglyceride(TG),low-density lipoprotein cholesterol,direct bilirubin,urinary albumin/creatinine ratio(UACR),self-monitoring of blood glucose(SMBG),meat and vegetable pairing,hot pot,whole grain and animal viscera consumption between the two groups(P<0.05).Logistic regression analysis showed that TG(OR 1.699,95%CI 1.298～2.222),UACR(OR 1.003,95%CI 1.001～1.005),SMGB(OR 0.480,95%CI 0.313～0.735),more meat and less vegetables(OR 1.432,95%CI 1.062～1.931)were the influencing factors of HbA1c failure.The AUC of the nomogram prediction model based on the influencing factors was 0.711,with C-index 0.710(95%CI 0.663～0.758)and good calibration(χ2=11.185,P=0.191).Conclusions The nomogram prediction model for HbA1c failure in T2DM patients established based on TG,UACR,SMGB,meat and vegetarian mix has good discrimination and calibration,which can provide certain reference value for warning of poor blood glucose control.