Background and Aims:Patients with end-stage liver disease(ESLD)frequently experience persistent pruritus,which significantly impairs their quality of life.Although relief of pruritus after liver transplantation is often attributed to the normalization of bilirubin levels,the role of skin microbiota in developing pruritus remains unclear.This study aimed to investigate the dynamic changes in skin microbiota during the perioperative period of liver transplantation in ESLD patients and to explore their association with pruritic symptoms.Methods:Fifteen ESLD patients treated in the Third Xiangya Hospital between 2022 and 2023 were enrolled and skin swabs were collected from the anterior tibial region at three time points:before liver transplantation and on postoperative days 7 and 30.Skin samples from 15 age-matched healthy controls were collected at the same anatomical site.Microbial composition was analyzed using 16S rRNA sequencing.Meanwhile,pruritus severity was assessed using a visual analogue scale(VAS),and multiple serological indicators were measured to evaluate correlations between microbiota changes,pruritus severity,and liver function parameters.Results:Compared with healthy controls,ESLD patients exhibited significantly altered β-diversity in skin microbiota and an increased relative abundance of Staphylococcus(LDA>4),which was strongly correlated with VAS scores for pruritus(r=0.93,Padj=3.08×10?1?).On postoperative day 7,α-diversity decreased,and Staphylococcus abundance peaked,then gradually normalized by day 30 as pruritus improved.Further analysis revealed that Staphylococcus abundance was positively correlated with alanine aminotransferase,aspartate aminotransferase,total bilirubin,direct bilirubin,total bile acids,and international normalized ratio,and negatively correlated with albumin(all Padj<0.05).Notably,Staphylococcus levels were significantly higher in patients with moderate to severe pruritus(VAS score>5).Conclusion:ESLD patients demonstrate marked dysbiosis of the skin microbiota during the perioperative period of liver transplantation,characterized by an abnormal proliferation of Staphylococcus,which may contribute to the development and exacerbation of pruritus.Targeting the skin microbiome,particularly interventions against Staphylococcus,may offer a novel therapeutic strategy for alleviating pruritus in ESLD patients.

With the rapid development of medical big data and artificial intelligence,Clinical Prediction Models(CPMs)have become pivotal tools for disease prevention,diagnosis,and treatment.Current research predominantly focuses on the economic analysis of pharmacological or public health interventions,yet a comprehensive methodological framework for the economic evaluation of CPMs has been notably absent.The Guidelines for Economic Evaluation of Clinical Prediction Models(hereafter the Guidelines),jointly initiated by the Chinese Research Hospital Association and Peking University,Tsinghua University,and Capital Medical University,adheres to the WHO Handbook for Guideline Development and the Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards.A multidisciplinary collaboration,including a steering committee,expert panel,secretariat,and external review group,was established to develop the guideline following evidence-based principles and procedures.Consensus recommendations were formulated through the Delphi method.It describes the background,objectives,target group,and the development methodology and process,ensuring the entire compilation process of the Guidelines is transparent and standardized.Through comprehensive evidence retrieval,systematic evidence appraisal,and a scientific approach to forming recommendations,the scientific rigor and validity of the Guidelines were further enhanced.

Objective To explore the feasibility of a deep learning model based on early fundus lesions without manual segmentation in pan-retinal images for predicting diabetic kidney disease(DKD)and evaluating the enhancing effects of different binocular fusion strategies.Methods A retrospective cohort of 353 patients with type 2 diabetes mellitus(T2DM)admitted to the Endocrinology Department of Jiangdu People's Hospital Affiliated to Yangzhou University between December 2022 and March 2024 was analyzed.Patients were divided into DKD(n=114)and non-diabetic kidney disease(NDKD)(n=239)group based on the presence of DKD.First,a U-Net-based pre-trained automatic segmentation model was developed to process panoramic fundus retinal images.Subsequently,left and right eye deep learning models were constructed using ResNet152 under a five-fold cross-validation framework(70%training,30%validation).Three binocular fusion strategies were implemented:result fusion,feature fusion,and image fusion models.Model performance was evaluated using the area under the receiver operating characteristic(ROC)curve(AUC).DeLong test was used to compare AUC differences among models,while net reclassification index(NRI)and decision curve analysis(DCA)were used to assess clinical utility.Results Six prediction models were developed:clinical parameter model,left fundus model,right fundus model,binocular image fusion model,binocular result fusion model,and binocular feature fusion model.The Transformer-based binocular feature fusion model achieved the highest AUC in both training and validation sets(0.864 and 0.658,respectively).DeLong tests revealed significant AUC superiority of the Transformer model over the other five models in the training set(all P<0.001),though no significant differences were observed in the validation set(all P>0.05).NRI analysis showed negative values for all comparisons with the Transformer model(training set:-0.255,-0.244,-0.289,-0.426,-0.163;validation set:-0.060,-0.016,-0.028,-0.105,-0.033,respectively),indicating its optimal predictive performance.DCA further demonstrated greater net benefit for the Transformer-based fusion model.Conclusions The deep learning model constructed using early fundus lesions without manual segmentation in pan-retinal images can predict DKD.The Transformer-based fusion strategy present the best performance,providing a novel approach for further optimization and development of tools to predict DKD in the future.

OBJECTIVE: To investigate the hepatotoxicity of alkaloids from Euodiae Fructus combined with berberine (BBR) in Zuojin Pill, and to preliminarily explore the possible detoxification mechanism of the combination components. METHODS: The combination ratio of components was determined by the maximum concentration (Cmax) of the chemical components in Zuojin Pill. HepG2 cell model was used to investigate the combined toxicity of the hepatotoxic components from Euodiae Fructus, such as evodiamine (EVO) or dehydroevodiamine (DHED), with BBR for 48 h. The experimental groups were set as follows: the vehicle control group, the EVO group, the DHED group, the BBR group, and the combination group of EVO or DHED with BBR. The cell counting kit-8 (CCK-8) method was used to determine the cell viability, and the combination index (CI) was used to determine the combined toxicity of the components. The alanine transaminase (ALT), aspartate aminotransferase (AST), lactate dehydroge-nase (LDH), and alkaline phosphatase (ALP) activities as well as total bilirubin (TBIL) content in the cell culture supernatant were detected. The protein expression levels of bile acid transporters, such as bile salt export pump (BSEP) and multidrug resistance-associated protein 2 (MRP2), were detected by Western blot. The intracellular malondialdehyde (MDA) content and superoxide dismutase (SOD) activity in HepG2 cells were detected. RESULTS: Compared with EVO or DHED group, the combination of EVO 1 μmol/L with BBR 10 μmol/L or DHED 50 μmol/L with BBR 35 μmol/L significantly increased cell viability of HepG2 cells (P < 0.01), with CI values of 77.89 or 4.49, respectively, much greater than 1. Significant decreases in the activities of ALT, AST, LDH, ALP, and TBIL content in the cell culture supernatant were found in both combination groups (P < 0.05, P < 0.01). Compared with the EVO group, the combination of EVO with BBR upregulated the protein expression levels of BSEP and MRP2. Compared with the DHED group, the combination of DHED with BBR significantly downregulated the protein expression levels of BSEP and MRP2 (P < 0.01). Compared with EVO or DHED group, the combination of EVO or DHED with BBR significantly reduced the MDA content in HepG2 cells (P < 0.05, P < 0.01). CONCLUSION A certain ratio of BBR combined with EVO or DHED had an antagonistic effect on HepG2 cytotoxicity, which might be related to regulating the expression of bile acid transpor-ters, and reducing lipid peroxidation damage.
Humans ; Hep G2 Cells ; Berberine/pharmacology* ; Drugs, Chinese Herbal/toxicity* ; Evodia/chemistry* ; Alkaloids/pharmacology* ; Cell Survival/drug effects* ; Multidrug Resistance-Associated Proteins/metabolism* ; Multidrug Resistance-Associated Protein 2 ; Quinazolines

Objective The aim is to understand the common scenarios of non-medical use of prescription opioids(NMUPO)and analyze the potential facilitating and hindering factors in the regulatory process of NMUPO from the perspective of healthcare professionals.Methods Healthcare professionals in local hospitals were surveyed through a two-stage purposive sampling from June to August 2022 in Ningbo,China.The survey was conducted using a semi-structured questionnaire on topics,and thematic analysis were used to identify and summarise key themes and patterns.Results A total of 75 participants were included,the average age was(43.9±7.2)years,and 54(72.0%)were male.The most common NMUPO scenarios involved middle-aged males pretending acute severe pain to obtain injectable opioids.The facilitating and hindering factors related to the regulation of NMUPO can be categorized into three types:institutional governance,technical support,and individual behaviors.At the institutional level,facilitating factors included strict national prescribing policies and local"narcotic drug card"systems,while barriers comprised incomplete lists of controlled substances.At the technological support level,facilitating factors included the establishment of regional health information platforms,while barriers included the lack of standardized prescription guidelines and diagnostic decision-support tools.At the individual level,facilitating factors included the public's cautious attitude toward drug misuse,while barriers included strained doctor-patient relationships.Conclusion China still faces significant challenges in addressing NMUPO and urgently needs to improve the existing regulatory system.It is recommended that reforms be carried out in areas such as pharmaceutical control mechanisms,drug treatment and rehabilitation services,preventive health education activities,and the optimized use of health information systems.

Background and Aims:Patients with end-stage liver disease(ESLD)frequently experience persistent pruritus,which significantly impairs their quality of life.Although relief of pruritus after liver transplantation is often attributed to the normalization of bilirubin levels,the role of skin microbiota in developing pruritus remains unclear.This study aimed to investigate the dynamic changes in skin microbiota during the perioperative period of liver transplantation in ESLD patients and to explore their association with pruritic symptoms.Methods:Fifteen ESLD patients treated in the Third Xiangya Hospital between 2022 and 2023 were enrolled and skin swabs were collected from the anterior tibial region at three time points:before liver transplantation and on postoperative days 7 and 30.Skin samples from 15 age-matched healthy controls were collected at the same anatomical site.Microbial composition was analyzed using 16S rRNA sequencing.Meanwhile,pruritus severity was assessed using a visual analogue scale(VAS),and multiple serological indicators were measured to evaluate correlations between microbiota changes,pruritus severity,and liver function parameters.Results:Compared with healthy controls,ESLD patients exhibited significantly altered β-diversity in skin microbiota and an increased relative abundance of Staphylococcus(LDA>4),which was strongly correlated with VAS scores for pruritus(r=0.93,Padj=3.08×10?1?).On postoperative day 7,α-diversity decreased,and Staphylococcus abundance peaked,then gradually normalized by day 30 as pruritus improved.Further analysis revealed that Staphylococcus abundance was positively correlated with alanine aminotransferase,aspartate aminotransferase,total bilirubin,direct bilirubin,total bile acids,and international normalized ratio,and negatively correlated with albumin(all Padj<0.05).Notably,Staphylococcus levels were significantly higher in patients with moderate to severe pruritus(VAS score>5).Conclusion:ESLD patients demonstrate marked dysbiosis of the skin microbiota during the perioperative period of liver transplantation,characterized by an abnormal proliferation of Staphylococcus,which may contribute to the development and exacerbation of pruritus.Targeting the skin microbiome,particularly interventions against Staphylococcus,may offer a novel therapeutic strategy for alleviating pruritus in ESLD patients.

With the rapid development of medical big data and artificial intelligence,Clinical Prediction Models(CPMs)have become pivotal tools for disease prevention,diagnosis,and treatment.Current research predominantly focuses on the economic analysis of pharmacological or public health interventions,yet a comprehensive methodological framework for the economic evaluation of CPMs has been notably absent.The Guidelines for Economic Evaluation of Clinical Prediction Models(hereafter the Guidelines),jointly initiated by the Chinese Research Hospital Association and Peking University,Tsinghua University,and Capital Medical University,adheres to the WHO Handbook for Guideline Development and the Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards.A multidisciplinary collaboration,including a steering committee,expert panel,secretariat,and external review group,was established to develop the guideline following evidence-based principles and procedures.Consensus recommendations were formulated through the Delphi method.It describes the background,objectives,target group,and the development methodology and process,ensuring the entire compilation process of the Guidelines is transparent and standardized.Through comprehensive evidence retrieval,systematic evidence appraisal,and a scientific approach to forming recommendations,the scientific rigor and validity of the Guidelines were further enhanced.

Objective To explore the feasibility of a deep learning model based on early fundus lesions without manual segmentation in pan-retinal images for predicting diabetic kidney disease(DKD)and evaluating the enhancing effects of different binocular fusion strategies.Methods A retrospective cohort of 353 patients with type 2 diabetes mellitus(T2DM)admitted to the Endocrinology Department of Jiangdu People's Hospital Affiliated to Yangzhou University between December 2022 and March 2024 was analyzed.Patients were divided into DKD(n=114)and non-diabetic kidney disease(NDKD)(n=239)group based on the presence of DKD.First,a U-Net-based pre-trained automatic segmentation model was developed to process panoramic fundus retinal images.Subsequently,left and right eye deep learning models were constructed using ResNet152 under a five-fold cross-validation framework(70%training,30%validation).Three binocular fusion strategies were implemented:result fusion,feature fusion,and image fusion models.Model performance was evaluated using the area under the receiver operating characteristic(ROC)curve(AUC).DeLong test was used to compare AUC differences among models,while net reclassification index(NRI)and decision curve analysis(DCA)were used to assess clinical utility.Results Six prediction models were developed:clinical parameter model,left fundus model,right fundus model,binocular image fusion model,binocular result fusion model,and binocular feature fusion model.The Transformer-based binocular feature fusion model achieved the highest AUC in both training and validation sets(0.864 and 0.658,respectively).DeLong tests revealed significant AUC superiority of the Transformer model over the other five models in the training set(all P<0.001),though no significant differences were observed in the validation set(all P>0.05).NRI analysis showed negative values for all comparisons with the Transformer model(training set:-0.255,-0.244,-0.289,-0.426,-0.163;validation set:-0.060,-0.016,-0.028,-0.105,-0.033,respectively),indicating its optimal predictive performance.DCA further demonstrated greater net benefit for the Transformer-based fusion model.Conclusions The deep learning model constructed using early fundus lesions without manual segmentation in pan-retinal images can predict DKD.The Transformer-based fusion strategy present the best performance,providing a novel approach for further optimization and development of tools to predict DKD in the future.

Objective The aim is to understand the common scenarios of non-medical use of prescription opioids(NMUPO)and analyze the potential facilitating and hindering factors in the regulatory process of NMUPO from the perspective of healthcare professionals.Methods Healthcare professionals in local hospitals were surveyed through a two-stage purposive sampling from June to August 2022 in Ningbo,China.The survey was conducted using a semi-structured questionnaire on topics,and thematic analysis were used to identify and summarise key themes and patterns.Results A total of 75 participants were included,the average age was(43.9±7.2)years,and 54(72.0%)were male.The most common NMUPO scenarios involved middle-aged males pretending acute severe pain to obtain injectable opioids.The facilitating and hindering factors related to the regulation of NMUPO can be categorized into three types:institutional governance,technical support,and individual behaviors.At the institutional level,facilitating factors included strict national prescribing policies and local"narcotic drug card"systems,while barriers comprised incomplete lists of controlled substances.At the technological support level,facilitating factors included the establishment of regional health information platforms,while barriers included the lack of standardized prescription guidelines and diagnostic decision-support tools.At the individual level,facilitating factors included the public's cautious attitude toward drug misuse,while barriers included strained doctor-patient relationships.Conclusion China still faces significant challenges in addressing NMUPO and urgently needs to improve the existing regulatory system.It is recommended that reforms be carried out in areas such as pharmaceutical control mechanisms,drug treatment and rehabilitation services,preventive health education activities,and the optimized use of health information systems.

In order to understand nurses’ willingness to participate in humanistic nursing training and its influencing factors, and provide reference for managers to understand the current situation and improve nurses’ enthusiasm for humanistic nursing training. The convenience sampling method was used to investigate 23 707 nurses in 28 provinces (autonomous regions and municipalities directly under the central government) through a self-designed questionnaire distributed on the Internet. The results showed that 98.1% of nurses thought that participating in humanistic nursing related training was helpful to clinical work, but only 88.6% of the respondents were willing to participate in humanistic nursing training. Thirty factors were analyzed from four aspects of basic characteristics of individuals, cognitive relevant experience and organizational atmosphere. Fifteen factors had significant significance in binary Logistic regression analysis (P<0.05). Among them, the factors that had a positive impact on training willingness were: marriage, education, professional title, post establishment, agree with humanistic care is the basic duty of a nurse praised, experience of being praised at work, family support, rapport with patients, passion of colleagues to participate in training, sustained high-quality care demonstration activities, join the humanistic care related organization, hospital reimbursement of training expenses (OR value of 6.559~1.113, P<0.001). The OR value of humanistic nursing as a nurse’s responsibility was 6.559 and the 95%CI was 5.585~7.702. The factors that hindered nurses from participating in training were: work occupied most of time and energy, think humanistic nursing is abstract and difficult to understand, think the mastered humanistic knowledge and skills meet the needs of work (OR value of 0.657~0.722, P<0.001). Through the analysis, it is considered that nurses have a extremely consistent high recognition of the significance of humanistic nursing training, but their willingness to receive training is affected by many factors such as individual experience, cognitive attitude and organizational atmosphere. In order to realize nurses’ high recognition of humanistic nursing training to high enthusiasm of behavior, the aspects of individual cognition and organizational atmosphere must be discussed.