Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Objective To explore the predictive value of ultra-sound(US)combined with multi-sequence MRI in a clinical-deep learning radiomics nomogram(DLRN)for the short-term efficacy of neoadjuvant chemotherapy(NAC)in patients with triple-negative breast cancer(TNBC).Methods A total of 122 TNBC patients from five hospitals were retrospectively analyzed,and divided into training group(72 cases)and validation group(50 cases).The clinical and pathological data,NAC regimens,and imaging data were collected.The lesions and its surrounding 10-unit voxels from US and MRI images were retained as the region of interest(ROI).Pyradiomics software and a ResNet152 convolutional neural network(CNN)framework were used to extract radiomics and deep learning features to construct a clinical-DLRN with outcome dimension fusion.The receiver operating characteristic(ROC)curve and calibration curve were plotted,and five-fold cross-validation decision curve were used to verify the model's clinical effec-tiveness.Results The clinical-DLRN constructed by US combined with multi-sequence MRI showed that area under the curve(AUC)was 0.967[95％confidence interval(CI)0.782-0.967]and accuracy(ACC)was 0.900,respectively.The five-fold cross-validation decision curve showed good generalization,with the highest clinical net benefit between risk thresholds of 0.72 and 0.96.Conclusion The clinical-DLRN integrating US and multi-sequence MRI has the best efficacy in predicting the short-term efficacy of NAC in TNBC patients,which offering potential guidance for personalized TNBC treatment.

Objective The purpose of writing the"expert consensus on humanistic care for patients in hospice care"(hereinafter referred to as the"consensus")aims to standardize the practice of humanistic care in the field of hospice care,ensuring that humanistic care is integrated throughout the entire service process for hospice care patients and their families.Methods A systematic search was conducted in domestic and foreign databases for literature related to hospice care and humanistic care,including guidelines,expert consensuses,systematic reviews or Meta-analyses,and evidence summaries.High-quality evidence was evaluated,extracted,and summarized to form the initial draft of the"consensus".From June to October 2024,20 experts from the fields of hospice care,nursing humanities,and evidence-based nursing were invited to participate in 1 round of expert consultation.Among them,13 experts were selected for 2 rounds of expert demonstration meetings.After collating and analyzing the experts' opinions,the initial draft was revised and refined,ultimately resulting in the final version of the"consensus".Results The effective response rate of the consultation questionnaire was 100％,with expert authority coefficient of 0.880,judgment coefficient of 0.935,and familiarity level of 0.825.The Kendall harmony coefficient of the expert consultation was 0.134(P＜0.05).The"consensus"consisted of 13 aspects,including the targets and objectives,principles,institutional guarantees,environmental requirements,etc.Conclusion This"consensus"possesses strong scientific rigor and practicality,which can provide guidance and references for the practice of humanistic care in the field of hospice care,promoting the standardization and humanization of hospice care services.

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 To evaluate the impact of slow-freezing process on human ovarian tissue with the standard cryopreservation-thawing protocol of Fertility Protection Center of Beijing Obstetrics and Gynecology Hospital,Capital Medical University.Methods Ovarian tissues of 12 patients were divided into fresh ovarian tissue group(fresh group)and freezing-thawing ovarian tissue group(F-T group).The freezing-thawing protocol was the standard protocol in our center.The number and activity of follicle were examined with Hematoxylin-eosin(HE)staining and calcein-AM(calcein acetoxymethylester)staining,and the proliferation and apoptosis was evaluated with the immunohistochemical staining of Ki-67 and caspase-3.The expressions of apoptosis-related proteins such as caspase-3,bax and FasL between the two groups were compared with Western blotting.Results There were no statistically significant differences in follicle counting and follicle activity in ovarian tissues pre-and post-freezing-thawing(P>0.05),and the positive rate of Ki-67 in ovarian tissues after freezing-thawing was significantly lower than that in fresh ovarian tissues(P<0.05),and there was no statistically significant difference in the positive rate of caspase-3 between the two groups(P>0.05).The expression of caspase-3 protein in ovarian tissues after freezing-thawing was significantly higher than that in fresh ovarian tissues(P<0.05),while the expressions of other apoptosis-related proteins such as bax and FasL were not significantly different(P>0.05).Conclusion The standard cryopreservation-thawing regimen in our center can effectively maintain the follicle number,morphology,and activity in ovarian tissues.After freezing and thawing,the cell proliferation level is decreased.The expression of apoptosis-related proteins such as bax and FasL are not increased,and the expression of caspase-3 is relatively increased.These results suggest our freezing-thawing regimen is good for human ovarian tissue.

Female infertility is recognized as a global public health issue by the World Health Organization.Female fertility remodeling includes ovarian function reconstruction and uterus/endometrium reconstruction,etc.It is emerging as a hot technology since it is ready to prepare autologous platelet-rich concentrate and it is safer and more acceptable in autologous application.It plays an important role in regenerative medicine,and it is currently widely applied in maxillofacial and plastic surgery,dermatology and other clinical practices.This article mainly reviews the progresses of the application of autologous platelet-rich concentrate in female fertility remodeling.

This paper reports the clinical data and the diagnosis and treatment of a patient with exogenous insulin autoimmune syndrome(EIAS)induced by long-term use of exogenous insulin(Eucrin 50).For diabetes patients with hyperinsulin-induced hypoglycemia,detection of IAA is helpful for diagnosis EIAS.Due to different test methods affect IAA results,if negative,EIAS cannot be completely excluded.The polyethylene glycol precipitation method can assist in early diagnosis.

Objective To evaluate the diagnostic value of positron emission tomography(PET)/computed tomography(CT)and bone marrow biopsy(BMB)for bone marrow infiltration in common non-Hodgkin lymphoma(NHL).Methods We retrospectively analyzed data from 197 patients with NHL and compared the diagnostic value of PET/CT and BMB for bone marrow infiltration.Differences in PET/CT parameters and serological test results were compared between PET/CT-positive and PET/CT-negative patients as well as between BMB-positive and BMB-negative patients.Results In patients with diffuse large B-cell lymphoma(DLBCL),the sensitivities of PET/CT and BMB for detecting bone marrow infiltration were 90.5%and 66.7%,and the specificities were 95.1%and 100.0%,respectively.In patients with follicular lymphoma(FL),the sensitivities were 63.6%and 81.8%,and the specificities were 98.1%and 100.0%,respec-tively.In patients with T-cell lymphoma(TCL),the sensitivities were 60.0%and 80.0%,and the specificities were 88.0%and 100.0%,respectively.Among patients with DLBCL and TCL,significant differences were observed in platelet count and lactate dehydrogenase levels between PET/CT-positive and PET/CT-negative patients(P<0.05).Conclusion PET/CT showed excellent diagnostic perfor-mance for evaluating bone marrow infiltration in DLBCL.PET/CT had limited sensitivity for FL and TCL and might serve as a supplemen-tary tool for BMB.Platelet count and lactate dehydrogenase levels may aid in the diagnosis of bone marrow infiltration in DLBCL and TCL.

The development of artificial intelligence(AI)technology has provided new avenues for the public to access health information.While both domestic and international research and practical applications of health conversational AI have emerged,there remains a lack of consensus on the key issues surrounding their development.Based on a comprehensive review of domestic and international literature and multiple rounds of expert consultations,the study focuses on six issues:the definition,characteristics,application scenarios,evaluation elements,evaluation methods,as well as prospects and challenges of AI-driven health consultation systems,and develops the practice guideline for health conversational artificial intelligence.The findings aim to provide scientific reference for promoting the innovative application of AI technology in the healthcare field.