ObjectiveBased on whole-animal mass spectrometry imaging technology， spatial metabolomics was used to characterize in situ the metabolic alteration patterns in the lungs and brain of a rat model of lung heat-induced cough and asthma， as well as after treatment with Xiebai San. MethodsNine Sprague-Dawley （SD） rats were randomly divided into a blank group （physiological saline）， a model group （physiological saline）， and a Xiebai San group （9 g·kg^-1）， with three rats in each group. The model group and the Xiebai San group were both induced using lipopolysaccharide-ovalbumin （LPS-OVA） to establish an asthma rat model. After treatment with Xiebai San， the animals were euthanized on day 21 and rapidly frozen in liquid nitrogen to preserve morphology. Whole-animal tissue sections were prepared using a cryomicrotome， and imaging was performed using the Air-flow-assisted Desorption Electrospray Ionization Mass Spectrometry Imaging （AFADESI-MSI） platform. Based on the corresponding optical images， ion data of metabolites from the lung and brain tissues of each group were extracted. Differential metabolites were analyzed using SIMCA and GraphPad Prism 9.0 software. Metabolites were identified using the HMDB （https：//hmdb.ca/） and LipidMAPS^® （https：//www.lipidmaps.org/） databases， and metabolic changes in the lungs and brain were analyzed. ResultsMass spectrometry imaging showed that， after Xiebai San intervention， components such as neoglycyrrhizin and glycyrrhizin from Glycyrrhizae Radix et Rhizoma， as well as palmitamide from Lycii Cortex， were significantly distributed in the lung and brain tissues of rats. Lung analysis indicated that substances with anti-inflammatory effects， such as citric acid， were significantly decreased （P0.01）， while lipid metabolites such as lysophosphatidylethanolamine （LPE 17：1）， LPE （22：4）， and LPE （19：0） （P0.01） were significantly increased， showing a marked inflammatory response in the model group. After Xiebai San intervention， these conditions were notably improved. Analysis of metabolic changes in brain tissue showed that， compared with the blank group， amino acid and fatty acid metabolic pathways in the model group exhibited restricted alterations. Among them， levels of aspartic acid， glutamic acid， fatty acid （FA 18：5）， hydroxy fatty acids （FAHFA 36：0；O）， FA （6：1；O6）， and LPE （18：1） increased， whereas FA （16：0） and FA （20：4） significantly decreased. Administration of Xiebai San improved these metabolic abnormalities in the brain. Systematic analysis of lung and brain metabolic changes in rats with lung heat-induced cough and asthma showed that antioxidant unsaturated phospholipid substances were significantly decreased in the model group， suggesting oxidative stress and inflammation-related lung-brain axis responses after the onset of lung heat-induced cough and asthma. ConclusionUsing whole-animal mass spectrometry imaging combined with spatial metabolomics revealed the in vivo distribution of Xiebai San constituents， characterized the metabolic alterations in the lungs and brain caused by lung heat-induced cough and asthma， and systematically demonstrated the lung-brain axis inflammatory responses and the regulatory effects of Xiebai San. These findings provide valuable information for the study of Chinese medicine in lung heat-induced cough and asthma.

Retinitis pigmentosa （RP） is the most common hereditary blinding eye disease in clinical practice， with the pathogenesis remaining unclear. Patients experience progressive apoptosis of retinal photoreceptor cells， accompanied by degeneration of retinal pigment epithelium （RPE） cells. Current Western medical treatments mainly focus on gene therapy and stem cell transplantation， showing limited efficacy. In contrast， clinical observations have confirmed the therapeutic effects of traditional Chinese medicine （TCM） treatments. Establishing an RP animal model that aligns with the diagnostic features of both TCM and Western medicine could help combine the strengths of both approaches， thereby broadening the treatment options for RP. This study categorizes and summarizes the existing RP animal models in terms of classification， types， inheritance patterns， and alignment with clinical manifestations. It is found that current RP models are primarily derived from natural animal models such as RD mice and RCS rats， transgenic animal models like RPE-65 knockout mice and rhodopsin gene knockout mice， and chemically induced models such as those created by monochromatic light exposure or N-ethyl-N-nitrosourea （ENU） administration. These three categories of models focus more on detecting RP-related histopathological， molecular biological， and cellular immunological indicators， but offer limited observation of the overall characteristics of the disease and lack insight into syndrome differentiation. Although RP is a congenital genetic disease， its progression is influenced by acquired factors such as environment， constitution， emotions， and care. Current models do not fully capture the characteristics of this disease. Therefore， establishing an RP animal model based on the diagnostic features of both TCM and Western medicine will have significant implications for future experimental and clinical research.

ObjectiveBased on whole-animal mass spectrometry imaging technology， spatial metabolomics was used to characterize in situ the metabolic alteration patterns in the lungs and brain of a rat model of lung heat-induced cough and asthma， as well as after treatment with Xiebai San. MethodsNine Sprague-Dawley （SD） rats were randomly divided into a blank group （physiological saline）， a model group （physiological saline）， and a Xiebai San group （9 g·kg^-1）， with three rats in each group. The model group and the Xiebai San group were both induced using lipopolysaccharide-ovalbumin （LPS-OVA） to establish an asthma rat model. After treatment with Xiebai San， the animals were euthanized on day 21 and rapidly frozen in liquid nitrogen to preserve morphology. Whole-animal tissue sections were prepared using a cryomicrotome， and imaging was performed using the Air-flow-assisted Desorption Electrospray Ionization Mass Spectrometry Imaging （AFADESI-MSI） platform. Based on the corresponding optical images， ion data of metabolites from the lung and brain tissues of each group were extracted. Differential metabolites were analyzed using SIMCA and GraphPad Prism 9.0 software. Metabolites were identified using the HMDB （https：//hmdb.ca/） and LipidMAPS^® （https：//www.lipidmaps.org/） databases， and metabolic changes in the lungs and brain were analyzed. ResultsMass spectrometry imaging showed that， after Xiebai San intervention， components such as neoglycyrrhizin and glycyrrhizin from Glycyrrhizae Radix et Rhizoma， as well as palmitamide from Lycii Cortex， were significantly distributed in the lung and brain tissues of rats. Lung analysis indicated that substances with anti-inflammatory effects， such as citric acid， were significantly decreased （P0.01）， while lipid metabolites such as lysophosphatidylethanolamine （LPE 17：1）， LPE （22：4）， and LPE （19：0） （P0.01） were significantly increased， showing a marked inflammatory response in the model group. After Xiebai San intervention， these conditions were notably improved. Analysis of metabolic changes in brain tissue showed that， compared with the blank group， amino acid and fatty acid metabolic pathways in the model group exhibited restricted alterations. Among them， levels of aspartic acid， glutamic acid， fatty acid （FA 18：5）， hydroxy fatty acids （FAHFA 36：0；O）， FA （6：1；O6）， and LPE （18：1） increased， whereas FA （16：0） and FA （20：4） significantly decreased. Administration of Xiebai San improved these metabolic abnormalities in the brain. Systematic analysis of lung and brain metabolic changes in rats with lung heat-induced cough and asthma showed that antioxidant unsaturated phospholipid substances were significantly decreased in the model group， suggesting oxidative stress and inflammation-related lung-brain axis responses after the onset of lung heat-induced cough and asthma. ConclusionUsing whole-animal mass spectrometry imaging combined with spatial metabolomics revealed the in vivo distribution of Xiebai San constituents， characterized the metabolic alterations in the lungs and brain caused by lung heat-induced cough and asthma， and systematically demonstrated the lung-brain axis inflammatory responses and the regulatory effects of Xiebai San. These findings provide valuable information for the study of Chinese medicine in lung heat-induced cough and asthma.

Retinitis pigmentosa （RP） is the most common hereditary blinding eye disease in clinical practice， with the pathogenesis remaining unclear. Patients experience progressive apoptosis of retinal photoreceptor cells， accompanied by degeneration of retinal pigment epithelium （RPE） cells. Current Western medical treatments mainly focus on gene therapy and stem cell transplantation， showing limited efficacy. In contrast， clinical observations have confirmed the therapeutic effects of traditional Chinese medicine （TCM） treatments. Establishing an RP animal model that aligns with the diagnostic features of both TCM and Western medicine could help combine the strengths of both approaches， thereby broadening the treatment options for RP. This study categorizes and summarizes the existing RP animal models in terms of classification， types， inheritance patterns， and alignment with clinical manifestations. It is found that current RP models are primarily derived from natural animal models such as RD mice and RCS rats， transgenic animal models like RPE-65 knockout mice and rhodopsin gene knockout mice， and chemically induced models such as those created by monochromatic light exposure or N-ethyl-N-nitrosourea （ENU） administration. These three categories of models focus more on detecting RP-related histopathological， molecular biological， and cellular immunological indicators， but offer limited observation of the overall characteristics of the disease and lack insight into syndrome differentiation. Although RP is a congenital genetic disease， its progression is influenced by acquired factors such as environment， constitution， emotions， and care. Current models do not fully capture the characteristics of this disease. Therefore， establishing an RP animal model based on the diagnostic features of both TCM and Western medicine will have significant implications for future experimental and clinical research.

In recent years， traditional Chinese medicine （TCM） has achieved significant progress in the treatment of inflammatory bowel disease （IBD）. A comprehensive literature search was conducted covering the period from January 1， 2010， to December 30， 2024， across Chinese databases including China National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP China Science and Technology Journal Database， and the Chinese Biomedical Literature Service System， as well as international databases such as PubMed， Web of Science， and Embase. The clinical applications and mechanistic studies of TCM in IBD were systematically reviewed. The current status of TCM research on the etiology and pathogenesis of IBD， innovative clinical practices， and multimodal therapeutic approaches， including Chinese herbal formulas， single herbs or active compounds， acupuncture， herbal retention enema， and acupoint application， were summarized， together with their synergistic effects when combined with western medical treatments. The development and application of Chinese patent medicines for IBD are undergoing a profound transition from efficacy validation to mechanistic exploration. Mechanistic studies on the effects of TCM in IBD mainly focus on regulating gut microbiota homeostasis， repairing the intestinal mucosal barrier， and modulating intestinal immune balance. Furthermore， future research directions for TCM-based IBD management are proposed， including the establishment of TCM diagnostic and treatment models， expanding integrated applications of external and internal TCM therapies， innovating personalized treatment strategies， and advancing drug development. These efforts aim to provide insights for the standardized and precision-oriented development of TCM in the diagnosis and treatment of IBD.

Objective To explore factors affecting the postoperative renal function and surgical complications in recipients of living donor kidney transplantation. Methods A retrospective analysis was conducted on medical records of 119 patients who underwent living donor kidney transplantation at Beijing Friendship Hospital Affiliated to Capital Medical University, from January 2020 to September 2024. The severity of surgical complications was evaluated using the Clavien-Dindo score. Spearman correlation analysis was used to analyze the correlation between preoperative general data, surgical data, preoperative laboratory data and the Clavien-Dindo score. Multiple linear regression analysis was performed on the correlated factors. Univariate and multivariate logistic regression analyses were used to analyze the factors affecting the occurrence of delayed graft function (DGF) after surgery. Results The body mass index, history of hypertension, cold ischemia time, the first warm ischemia time, the second warm ischemia time, prothrombin activity and international normalized ratio were all correlated with the Clavien-Dindo score. Multiple linear regression analysis showed that the longer the second warm ischemia time and the first warm ischemia time were, the higher the Clavien-Dindo score was, and the more severe the postoperative surgical complications were (all P<0.05). Multivariate logistic regression analysis showed that long the first warm ischemia time and long dialysis time were independent risk factors for the occurrence of DGF after surgery (all P<0.05). Conclusions Prolonged the second warm ischemia time and the first warm ischemia time may increase the severity of surgical complications in recipients after living donor kidney transplantation. Long the first warm ischemia time and long dialysis time are independent risk factors for the occurrence of DGF after surgery.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

In July 2024， the European Association for the Study of the Liver released the latest edition of EASL Clinical Practice Guidelines on liver transplantation. The purpose of the EASL guidelines presented here is not to cover all aspects of liver transplantation， but to focus on important advances since the release of the 2016 edition of EASL guidelines. This article gives an excerpt of the recommendations in the guidelines.

During the career life cycle, workers may face various health problems such as occupational injuries, occupational diseases, and work-related diseases. How to comprehensively protect the health of workers is a crucial scientific issue that needs to be solved urgently. Workers show the characteristics of co-exposure to multiple occupational risks or co-existence of multiple health conditions in their occupational activities. Occupational injuries are closely related to occupational diseases and work-related diseases. To carry out prevention and control of occupational injuries in the context of "big health", we should further strengthen the systematic approach and highlight the concept of "overall process" and "all-round". That is to establish an occupational injury surveillance system covering the whole process of surveillance-assessment-intervention and the evaluation of intervention effects, and to set up the joint prevention and control strategy of occupational injuries, occupational diseases, and work-related diseases. This will promote the implementation of efficient and intensive health management at government, society, employers, workers and other levels to achieve all-round protection of workers' health. When exploring the possible effects of job burnout, occupational stress, comorbidity, and other factors on occupational injuries, the introduction of machine learning methods provides a new approach to identifying and analyzing the influencing factors of occupational injuries and to exploring potential underlying mechanisms.

Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels: individual, equipment, management, and environment in past 12 months. Data balancing was performed using resampling, and LASSO regression was used to select factors of non-fatal occupational injuries. The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable, where variables with estimated coefficients > 0 are risk factors, and those <0 are protective factors. The area under the receiver operating characteristic (ROC)curve (AUC) was used to test the performance of the model, with an AUC value > 0.7 indicating good model performance. Results Among the 2243 frontline workers, males accounted for 77.7% (1742 out of 2243), with the main age range being 40-49 years old, representing 29.5% (661 out of 2243), 82.7% of the workers (1854 out of 2243) were married, and 55.6% (1248 out of 2243) had a junior middle school education level. The average monthly income for 51.0% (1144 out of 2243) of the workers was between 5000 and 6999 Chinese Yuan. The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4% (189/2243) in the past 12 months. Among the 22 factors associated with the occurrence of non-fatal occupational injuries (P<0.05), 10 were individual-level factors, including gender, smoking, alcohol consumption, colleague relationships, average exercise duration, job burnout, work fatigue, musculoskeletal disorders, cardiovascular diseases, and neurological and sensory organ diseases; 3 were equipment-level factors, including equipment operability, hazardous workpieces, and safety hazards; 5 were environmental-level factors, including low temperatures, special operations, noise, workspace size, and dirty and disorderly environment; and 4 were management-level factors, including daily working hours, weekly working days, overtime, and pre-job technical training. The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables. Among them, there were 7 risk factors for non-fatal occupational injuries (coefficient > 0), including safety hazards, musculoskeletal disorders, dangerous workpieces, job burnout, dirty and disorderly environment, smoking, and male gender; and 3 protective factors (coefficient < 0), including pre-job technical training, good colleague relationship, and long working days per week. Conclusion Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interventions for non-fatal occupational injuries by controlling potential safety hazards, providing pre-job technical training, reducing dangerous workpieces, rectifying working environment, and reasonably arranging working hours.