ObjectiveTo evaluate the clinical efficacy and safety of Xiaozhen Formula （消疹方） in preventing skin toxicity induced by epidermal growth factor receptor inhibitors （EGFRIs） in patients with EGFR-mutant non-small cell lung cancer （NSCLC）. MethodsA randomized， double-blind， placebo-controlled， multicenter clinical study was conducted. A total of 120 patients with EGFR-mutant NSCLC from seven centers were enrolled and randomly assigned to a treatment group （60 cases） or a control group （60 cases）. On the basis of EGFRI-targeted therapy， patients in the treatment group received Xiaozhen Formula granules， whereas those in the control group received Xiaozhen Formula placebo granules， both at 10 g twice daily for 4 consecutive weeks. The primary outcomes were the grading of skin toxicity evaluated using the National Cancer Institute Common Terminology Criteria for Adverse Events （NCI-CTCAE） version 5.0 and the incidence of rash. Secondary outcomes included the time to onset and time to resolution of the highest-grade rash， the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 （EORTC QLQ-C30） scores， the Hospital Anxiety and Depression Scale （HADS） scores， and disease control rate， together with safety assessments. ResultsBased on the full analysis set （FAS）， the incidence of skin toxicity in the treatment group was 18.33% （11/60）， significantly lower than 45.00% （27/60） in the control group （P＜0.01）， with the highest severity of skin toxicity in both groups was grade 2. Among patients who developed rash， the resolution rate in the treatment group was 90.91% （10/11）， higher than that 33.33% （9/27） in the control group. The median time to resolution was 15 days （95%CI： 8-17 days） in the treatment group and it was not reached in the control group； the distribution of time to resolution differed significantly between groups （P＜0.001）. After treatment， the treatment group had higher EORTC QLQ-C30 functional scale and global health status/quality-of-life scores， and lower symptom scale， single-item scores， as well as HADS-A， and HADS-D scores than the control group （P＜0.05）. In the FAS analysis， the disease control rate （DCR） was 85.0% （51/60） in the treatment group， lower than 100.0% （60/60） in the control group （P=0.003）， whereas no significant between-group difference was observed in the per-protocol set （PPS） analysis （P=0.464）. The incidence of adverse events did not differ significantly between the two groups （P＞0.05）， and no definite safety signals related to the investigational drug were observed. ConclusionXiaozhen Formula can reduce the incidence of EGFRI-induced skin toxicity， and improve the outcome of rash regression， the patients' quality of life and psychological status in EGFR-mutant NSCLC patients.

BackgroundPatients with depressive disorder often exhibit impaired decision-making functions. However， the relationship between decision-making abilities and depressive and anxiety symptoms in these patients remains unclear. ObjectiveTo explore the characteristics of decision-making behavior in patients with depressive disorder， and to analyze its relationship with clinical symptoms. MethodsA total of 48 patients diagnosed with depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were recruited from the Department of Psychosomatic Medicine of the Affiliated Hospital of Southwest Medical University from October 2020 to May 2023. Concurrently， 52 healthy individuals matched for age and gender were recruited from Luzhou as the control group. Beck Depression Inventory （BDI） and Beck Anxiety Inventory （BAI） were used for assessment， and decision-making behavior was evaluated using Probabilistic Reversal Learning （PRL） task. Indicators assessed included the number of trials to criterion， perseverative errors， win-stay rate and lose-shift rate. Spearman correlation analysis was used to assess the correlation between BDI and BAI scores and PRL task indicators. ResultsThe depression group showed a significantly higher lose-shift rate compared with the control group （t=3.684， P<0.01）. There were no statistically significant differences between two groups in trials to criterion， perseverative errors and win-stay rate （t=0.329， 0.132， 0.609， P>0.05）. In depression group， BDI and BAI scores were positively correlated with the win-stay rate（r=0.450， 0.398， P<0.01）. ConclusionPatients with depressive disorder are more likely to change their decision-making strategies following negative outcomes. Furthermore， the severity of depressive and anxiety symptoms is associated with a greater propensity to maintain existing decisions after receiving positive feedback. ［Funded by 2019 Joint Project of Luzhou Science and Technology Bureau-Southwest Medical University （number， 2019LZXNYDJ39］

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.

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.

Objective:To explore the spatial correlation between gray matter volume (GMV) changes and neurotransmitter receptors/transporters in patients with first-episode schizophrenia (FES) .Methods:Fifty-four FES patients(FES group) and fifty-nine healthy controls (HC group) were selected from June 2014 to May 2020 in the Psychiatry Department of Renmin Hospital of Wuhan University. Structural magnetic resonance imaging (sMRI) was conducted on all subjects. Differences of GMV were compared across 400 cortical regions and 32 subcortical regions. Based on the positron emission tomography(PET) data from Neuromaps, which provides the density of 19 different neurotransmitter receptors and transporters, Spearman correlation analysis was performed to evaluate the spatial correlation between GMV changes and neurotransmitter systems.Results:Compared to the HC group, FES group exhibited significant GMV reductions in widespread cortical (90/400) and subcortical (6/32) regions (all FDR-corrected P<0.05). The effect size of GMV reduction (Cohen’s d) showed significant positive correlations with the density of 5-hydroxytryptamine 1a(5HT1a) ( r=0.400, Pspin=0.002), γ-aminobutyric acid type A receptor(GABA A)( r=0.307, Pspin=0.002), and metabotropic glutamate receptor 5(mGluR5) ( r=0.275, Pspin=0.020) receptors (all FDR-corrected P<0.05). Conclusion:GMV reductions in a wide range of brain regions existed in patients with FES. There are significant correlations between 5HT1a, GABA A and mGluR5 receptors and gray matter reduction in patients with FES. The disorder of these neurotransmitter receptors may be the potential neurobiological mechanism of gray matter structural abnormalities in the early stage of schizophrenia.

Objective:To summarize the clinical characteristics of congenital chylothorax (CC) in neonates, and to analyze the effects of conservative treatment and the prognosis.Methods:A case control study was conducted.Clinical data of neonates with CC treated in the Department of Neonatal Surgical Intensive Care Unit, Guangzhou Women and Children′s Medical Center Guangzhou Medical University, from January 2015 to April 2023 were collected.The patients were divided into a survival group and a death group according to the outcome.SPSS 26.0 software was used for statistical analysis, and binary Logistic regression was used for the analysis of risk factors for death.Results:A total of 55 patients were included in this study, including 35 males and 20 females.The gestational age at birth and birth weight were 37.1 (34.7, 38.7) weeks and 3 250 (2 640, 3 540) g, respectively.Among the patients included, 30 cases had bilateral pleural effusion, 25 cases had unilateral pleural effusion, and 22 cases had hydrops fetalis; 50 cases were prenatally diagnosed with pleural effusion, with the mean gestational age at diagnosis being 31.0(26.0, 34.6) weeks.Additionally, 21 cases had polyhydramnios, and 18 cases had mediastinal displacement.Ten cases received intrauterine treatment and 17 cases were treated with octreotide.The maximum daily amount of pleural effusion was 31.7(12.0, 62.5) mL/kg, and pleural effusion resolved within 14 (6, 22) days.The length of hospital stay was 23 (12, 36) days.Forty-four cases survived, while 11 cases died.The differences in polyhydramnios, gestational age, bilateral pleural effusion, hydrops fetalis and Apgar score were significant between the survival and death groups (all P<0.05).Binary Logistic regression analysis revealed that bilateral pleural effusion and a low 5-minute Apgar score were independent risk factors for early death in neonates with CC (all P<0.05).A total of 38 children were followed up at the age of 2.30 (1.24, 3.46) years.There was 1 case of recurrence, and none of the patients experienced recurrent respiratory infections. Conclusions:CC is most common in full-term infants and has a predominantly bilateral effusion, its long-term prognosis with conservative treatment is promising.However, neonates with CC who present with bilateral pleural effusion or low 5-minute Apgar scores have an increased risk of early mortality.

Gastric cancer is a common tumor in China, and lymph node metastasis (LNM) is an independent prognostic factor for it. Accurately determining the risk of LNM in gastric cancer can help to formulate the treatment plan and estimate its staging and prognosis preoperatively. Existing means for evaluating LNM in gastric cancer have shortcomings such as low accuracy and high subjectivity. In recent years, artificial intelligence (AI) has begun to be used in medical research and clinical fields, which is of great significance in the era of precise individualized medicine. Combined with multimodal data including clinical, imaging, pathomics and molecular information, AI can improve the accuracy of LNM diagnosis and assist clinical decision-making, which has made significant progress recently. The aim of this review is to provide an overview of the history and status of AI for LNM prediction in gastric cancer, and to discuss the challenges and development directions.

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.

Gastric cancer is a common tumor in China, and lymph node metastasis (LNM) is an independent prognostic factor for it. Accurately determining the risk of LNM in gastric cancer can help to formulate the treatment plan and estimate its staging and prognosis preoperatively. Existing means for evaluating LNM in gastric cancer have shortcomings such as low accuracy and high subjectivity. In recent years, artificial intelligence (AI) has begun to be used in medical research and clinical fields, which is of great significance in the era of precise individualized medicine. Combined with multimodal data including clinical, imaging, pathomics and molecular information, AI can improve the accuracy of LNM diagnosis and assist clinical decision-making, which has made significant progress recently. The aim of this review is to provide an overview of the history and status of AI for LNM prediction in gastric cancer, and to discuss the challenges and development directions.

This study applied the grading of recommendations assessment, development and evaluation(GRADE) system and the integrated evidence chain-based effectiveness evaluation of traditional Chinese medicine(Eff-iEC) to evaluate the evidence for 12 commonly used Chinese patent medicines for the treatment of osteoporosis, which are frequently recommended in guidelines or expert consensuses. The results showed that Xianling Gubao Capsules/Tablets were rated as C(low-level evidence) according to the GRADE system, and as BA~+B~+(intermediate evidence) according to the Eff-iEC system. Jintiange Capsules were rated as C(low-level evidence) by the GRADE system, and as AA~+B(high-level evidence) by the Eff-iEC system. Gushukang Granules/Capsules were rated as C(low-level evidence) by GRADE system, and as BA~+B~+(intermediate evidence) by Eff-iEC system. Zuogui Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Qianggu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B~+(high-level evidence) by Eff-iEC system. Zhuanggu Zhitong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BA~+B(intermediate evidence) by Eff-iEC system. Jingui Shenqi Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B(high-level evidence) by Eff-iEC system. Quanduzhong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AD~+B~+(low-level evidence) by Eff-iEC system. Epimedium Total Flavones Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AAB~+(high-level evidence) by Eff-iEC system. Yougui Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~(++)B~(+ )(high-level evidence) by Eff-iEC system. Qigu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BB~+B(intermediate evidence) by Eff-iEC system. Liuwei Dihuang Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Overall, the Eff-iEC system provides a more comprehensive assessment of the effectiveness evidence for traditional Chinese medicine(TCM) than the GRADE system. However, it still has certain limitations that hinder its wider promotion and application. In terms of clinical evidence evaluation, both the Eff-iEC and GRADE systems reflect that the current clinical research quality on Chinese patent medicines for the treatment of osteoporosis is generally low. High-quality clinical trials are still needed in the future to further validate clinical efficacy.
Drugs, Chinese Herbal/therapeutic use* ; Osteoporosis/drug therapy* ; Humans ; Nonprescription Drugs/therapeutic use* ; Evidence-Based Medicine ; Medicine, Chinese Traditional