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 evaluate the effects of fasting and high-fat diet on the pharmacokinetics of rabeprazole sodium enteric-coated tablets in healthy Chinese subjects.Methods A single-center,randomized,open,two-agent,two-sequence,four-cycle,fully repeated crossover,single-dose trial design was used in this study,healthy subjects were assigned to receive single dose of rabeprazole sodium enteric-coated tablets 0.1 g in either fasting or high-fat diet state,and blood samples were taken at different time points,respectively.The concentrations of rabeprazole sodium enteric-coated in plasma were determined by liquid chromatography-tandem mass spectrometry(LC-MS/MS),the model method of the non-compartmental was used to calculate the pharmacokinetic parameters by Phoenix WinNonlin 8.2.Results The main pharmacokinetic parameters of rabeprazole sodium enteric-coated tablets in fasting state and high-fat diet state were as follows:Cmax were(339.63±156.47)and(318.86±132.13)ng·mL-1;t1/2 were(2.34±0.68)and(3.60±2.40)h;AUC0_t were(556.62±251.65)and(528.50±201.78)ng·mL-1·h;AUC0-∞ were(563.39±255.69)and(535.15±203.24)ng·mL-1·h;tmax were 3.65 and 6.99 h.After high-fat diet,the Cmax and AUC of rapeprazole sodium after high-fat and high-calorie diet decreased,Cmax decreased by 6.12％,AUC0-t decreased by 5.05％,AUC0-∞ decreased by 5.01％,andtmaxwas delayed by about 3.34 h.Cmax,AUC0-t and AUC0-∞ 90％confidence interval were 73.13％-115.10％,83.22％-112.28％and 83.40％-112.13％,respectively.Neither was between 85.00％-125.00％.Conclusion High-fat diet affects the absorption rate and degree of rabeprazole sodium enteric-coated,so it is suitable to be administered on an empty stomach.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

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 evaluate the effects of fasting and high-fat diet on the pharmacokinetics of rabeprazole sodium enteric-coated tablets in healthy Chinese subjects.Methods A single-center,randomized,open,two-agent,two-sequence,four-cycle,fully repeated crossover,single-dose trial design was used in this study,healthy subjects were assigned to receive single dose of rabeprazole sodium enteric-coated tablets 0.1 g in either fasting or high-fat diet state,and blood samples were taken at different time points,respectively.The concentrations of rabeprazole sodium enteric-coated in plasma were determined by liquid chromatography-tandem mass spectrometry(LC-MS/MS),the model method of the non-compartmental was used to calculate the pharmacokinetic parameters by Phoenix WinNonlin 8.2.Results The main pharmacokinetic parameters of rabeprazole sodium enteric-coated tablets in fasting state and high-fat diet state were as follows:Cmax were(339.63±156.47)and(318.86±132.13)ng·mL-1;t1/2 were(2.34±0.68)and(3.60±2.40)h;AUC0_t were(556.62±251.65)and(528.50±201.78)ng·mL-1·h;AUC0-∞ were(563.39±255.69)and(535.15±203.24)ng·mL-1·h;tmax were 3.65 and 6.99 h.After high-fat diet,the Cmax and AUC of rapeprazole sodium after high-fat and high-calorie diet decreased,Cmax decreased by 6.12％,AUC0-t decreased by 5.05％,AUC0-∞ decreased by 5.01％,andtmaxwas delayed by about 3.34 h.Cmax,AUC0-t and AUC0-∞ 90％confidence interval were 73.13％-115.10％,83.22％-112.28％and 83.40％-112.13％,respectively.Neither was between 85.00％-125.00％.Conclusion High-fat diet affects the absorption rate and degree of rabeprazole sodium enteric-coated,so it is suitable to be administered on an empty stomach.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

Objective To explore the diagnostic efficacy of serum 14-3-3β protein combined with fractional exhaled nitric oxide(FeNO)and conventional ventilatory lung function parameters in diagnosing bronchial asthma(referred to as"asthma")in children.Methods A prospective study included 136 children initially diagnosed with asthma during an acute episode as the asthma group,and 85 healthy children undergoing routine health checks as the control group.The study compared the differences in serum 14-3-3β protein concentrations between the two groups,analyzed the correlation of serum 14-3-3β protein with clinical indices,and evaluated the diagnostic efficacy of combining 14-3-3β protein,FeNO,and conventional ventilatory lung function parameters for asthma in children.Results The concentration of serum 14-3-3β protein was higher in the asthma group than in the control group(P<0.001).Serum 14-3-3β protein showed a positive correlation with the percentage of neutrophils and total serum immunoglobulin E,and a negative correlation with conventional ventilatory lung function parameters(P<0.05).Cross-validation of combined indices showed that the combination of 14-3-3β protein,FeNO,and the percentage of predicted value of forced expiratory flow at 75%of lung volume had an area under the curve of 0.948 for predicting asthma,with a sensitivity and specificity of 88.9%and 93.7%,respectively,demonstrating good diagnostic efficacy(P<0.001).The model had the best extrapolation.Conclusions The combination of serum 14-3-3β protein,FeNO,and the percentage of predicted value of forced expiratory flow at 75%of lung volume can significantly improve the diagnostic efficacy for asthma in children.

Combined radiation and burn injury (CRBI) is a severe syndrome, which is induced by the simultaneous or successive radiation and burn; but no appropriate clinical therapies are available. Loong oil (LO) is a traditional Chinese medicine oil composed of the oil extracts of cuttlebone, safflower, walnut oil, and rapeseed oil, which has been demonstrated to own anti-radiation and tissue healing functions. In this study, glyceryl monostearate (GMO) was used for the preparation of lyotropic liquid crystals that loaded LO to obtain Loong oil-lyotropic liquid crystals (LOL) for the treatment of skin CRBI. The hexagonal phase structure of LOL was proved by small X-ray scattering (SAXS) analysis with an approximate 7:9:11 ratio of peaks and under the polarizing microscope with the birefringence phenomenon. LOL had a high LO loading capacity (4%) and good bio-adhesive force, favoring skin administration. Animal experiments were approved by the Ethics Committee of the Beijing Institute of Radiation Medicine, Academy of Military Medical Sciences and the experiments were conducted in accordance with relevant guidelines and regulations (approval number: IACUC-DWZX-2022-834). Compared to triethanolamine creams, LOL had higher skin permeability with total skin penetration within 1 h, benefiting the treatment of deep CRBI. A deep II degree burn CRBI mouse model was established after whole-body irradiation with 5 Gy ⁶⁰Co γ-ray and the next 6-second 100 ℃ burn injury. LOL promoted LO skin penetration, improved epithermal cell proliferation and the formation of hair follicles, accelerated wound healing, and inhibited scarring, which benefitted the therapy of CRBI. In this study, LO application fields are expanded and LO is a promising medication for the treatment of CRBI.