Objective To investigate the suitable habitats of Phlebotomus chinensis in Gansu Province, so as provide insights into effective management of mountain-type zoonotic visceral leishmaniasis (MT-ZVL). Methods The geographical coordinates of locations where MT-ZVL cases were reported were retrieved in Gansu Province from 2015 to 2023, and data pertaining to 26 environmental variables were captured, including 19 climatic variables (annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest quarter, mean temperature of the coldest quarter, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, precipitation of the warmest quarter, and precipitation of the coldest quarter), five geographical variables (elevation, annual normalized difference vegetation index, vegetation type, landform type and land use type), and two population and economic variables (population distribution and gross domestic product). Twelve species distribution models were built using the biomod2 package in R project, including surface range envelope (SRE) model, generalized linear model (GLM), generalized additive model (GAM), multivariate adaptive regression splines (MARS) model, generalized boosted model (GBM), classification tree analysis (CTA) model, flexible discriminant analysis (FDA) model, maximum entropy (MaxEnt) model, optimized maximum entropy (MAXNET) model, artificial neural network (ANN) model, random forest (RF) model, and extreme gradient boosting (XGBOOST) model. The performance of 12 models was evaluated using the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS), and Kappa coefficient, and single models with high performance was selected to build the optimal ensemble models. Factors affecting the survival of Ph. chinensis were identified based on climatic, geographical, population and economic variables. In addition, the suitable distribution areas of Ph. chinensis were predicted in Gansu Province under shared socioeconomic pathway 126 (SSP126), SSP370 and SSP585 scenarios based on climatic data during the period from 1991 to 2020, from 2041 to 2060 (2050s), and from 2081 to 2100 (2090s) . Results A total of 11 species distribution models were successfully built for prediction of potential distribution areas of Ph. chinensis in Gansu Province, and the RF model had the highest predictive accuracy (AUC = 0.998). The ensemble model built based on the RF model, XGBOOST model, GLM, and MARS model had an increased predictive accuracy (AUC = 0.999) relative to single models. Among the 26 environmental factors, precipitation of the wettest quarter (12.00%), maximum temperature of the warmest month (11.58%), and annual normalized difference vegetation index (11.29%) had the greatest contributions to suitable habitats distribution of Ph. sinensis. Under the climatic conditions from 1991 to 2020, the potential suitable habitat area for Ph. chinensis in Gansu Province was approximately 5.80 × 10⁴ km², of which the highly suitable area was 1.42 × 10⁴ km², and primarily concentrated in the southernmost region of Gansu Province. By the 2050s, the unsuitable and lowly suitable areas for Ph. chinensis in Gansu Province had decreased by varying degrees compared to that of 1991 to 2020 period, while the moderately and highly suitable areas exhibited expansion and migration. By the 2090s, under the SSP126 scenario, the suitable habitat area for Ph. chinensis increased significantly, and under the SSP585 scenario, the highly suitable areas transformed into extremely suitable areas, also showing substantial growth. Future global warming is conducive to the survival and reproduction of Ph. chinensis. From the 2050s to the 2090s, the highly suitable areas for Ph. chinensis in Gansu Province will be projected to expand northward. Under the SSP126 scenario, the suitable habitat area for Ph. chinensis in Gansu Province is expected to increase by 194.75% and 204.79% in the 2050s and 2090s, respectively, compared to that of the 1991 to 2020 period. Under the SSP370 scenario, the moderately and highly suitable areas will be projected to increase by 164.40% and 209.03% in the 2050s and 2090s, respectively, while under the SSP585 scenario, they are expected to increase by 195.98% and 211.66%, respectively. Conclusions The distribution of potential suitable habitats of Ph. sinensis gradually shifts with climatic changes. Intensified surveillance and management of Ph. sinensis is recommended in central and eastern parts of Gansu Province to support early warning of MT-ZVL.

Objective In order to strengthen the connotation construction of hospitals,promote high-quality develop-ment,improve the quality of medical services,improve operational efficiency,and explore and practice the performance manage-ment mode in combination with the characteristics of the hospital's own development.Methods Take a tertiary children's spe-cialty hospital in Wuxi as an example,optimize the internal performance appraisal management system of the hospital,and con-duct dynamic monitoring and management of the whole appraisal process.Results The sample hospital constructed a multifacet-ed performance management system,and the performance appraisal results of the national tertiary public hospital in 2022 were significantly improved,and the various appraisal indexes,such as the percentage of fourth-level surgery,the intensity of antimi-crobial drug use,the value of CMI,the satisfaction degree of the medical staff,and the satisfaction degree of the outpatients,were kept optimized.Conclusion The continuous optimization of the performance management model has improved the hospital's level of refined management,the efficiency of collaboration between departments,the efficiency of resource allocation,and the efficiency of economic operation,stimulated the work motivation of medical staff,and improved the quality of medical services.

Small cell lung cancer (SCLC) is a highly malignant disease that has garnered significant attention in terms of treatment modalities and course management. Gaining an understanding of the clinical characteristics of SCLC, acquiring proficiency in screening, diagnosis, and treatment methods for this condition, as well as promptly addressing any adverse reactions to treatment are essential foundations for developing a scientific and rational pathological management plan for SCLC. By utilizing an intelligent whole course follow-up management platform, dynamic follow-up, timely warnings, and early interventions can enable high-quality whole life cycle management. This article aims to review the current treatment landscape of SCLC while exploring the challenges associated with implementing a comprehensive process-oriented management approach. The goal is to provide valuable insights for better managing SCLC patients and ultimately improving their quality of life and prognosis.
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Humans ; Small Cell Lung Carcinoma/diagnosis* ; Lung Neoplasms/diagnosis* ; Quality of Life ; Follow-Up Studies

Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.

Objective In order to strengthen the connotation construction of hospitals,promote high-quality develop-ment,improve the quality of medical services,improve operational efficiency,and explore and practice the performance manage-ment mode in combination with the characteristics of the hospital's own development.Methods Take a tertiary children's spe-cialty hospital in Wuxi as an example,optimize the internal performance appraisal management system of the hospital,and con-duct dynamic monitoring and management of the whole appraisal process.Results The sample hospital constructed a multifacet-ed performance management system,and the performance appraisal results of the national tertiary public hospital in 2022 were significantly improved,and the various appraisal indexes,such as the percentage of fourth-level surgery,the intensity of antimi-crobial drug use,the value of CMI,the satisfaction degree of the medical staff,and the satisfaction degree of the outpatients,were kept optimized.Conclusion The continuous optimization of the performance management model has improved the hospital's level of refined management,the efficiency of collaboration between departments,the efficiency of resource allocation,and the efficiency of economic operation,stimulated the work motivation of medical staff,and improved the quality of medical services.

Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.

ObjectiveTo investigate the correlation among the botanical characteristics， biological characteristics， chemical composition， and medicinal properties and efficacy of traditional Chinese medicines （TCM） from latex-containing plants， so as to strengthen the theory of "identifying symptoms for qualities" and provide a reference for the development and utilization of the latex-containing plant resources. MethodStatistics on the meridians for properties and tastes， efficacy， medicinal parts， family and genus， and chemical components of TCM from latex-containing plants were carried out. A total of 53 TCM from latex-containing plants included in the 2020 edition of the Chinese Pharmacopoeia were screened by mining the Chinese Botanical Journal， Chinese Materia Medica， Dictionary of Traditional Chinese Medicines， and related literature. In addition， their meridians for properties and tastes， medicinal parts， chemical components， and TCM classifications were summarized and statistically analyzed by using Excel 2013 and ChiPlot 2023.3.31 software. ResultIt was found that latex-containing plants were mainly distributed in one kingdom， one phylum， two classes， and 20 families， and most of the TCM from latex-containing plants belonged to Dicotyledonaceae under Angiosperms. In terms of properties and tastes， plain>cold>warm>cool>hot and bitter>pungent>sweet>sour>salty. In terms of meridians， liver>lung>kidney>spleen=large intestine=stomach>heart>bladder=gallbladder=small intestines. In terms of medicinal parts， roots （root， rhizomes， tuberous root， and root bark）>resin>seed>whole herb （whole herb and above-ground part）>stem （stem and branch）>fruit>leaf>flower=skin. In terms of research on chemical components， they were mostly glycosides. In terms of TCM classification， they were mostly medicines for activating blood circulation and removing blood stasis. ConclusionThe TCM from latex-containing plants is mainly plain， with a uniform warm and cold distribution. The tastes are mainly bitter and pungent， and the major meridians are the liver and lung. The roots and resins are mainly used as medicines. The components mostly contain glycosides， alkaloids， and volatile oils， and most of them are medicines for activating blood circulation and removing blood stasis， as well as for removing heat and toxins. There is a certain degree of correlation among the growth habits， medicinal parts， chemical components， and the properties， tastes， and efficacy of the TCM from latex-containing plants. It may provide a reference for resource development and utilization of TCM from latex-containing plants.

ObjectiveThe relevant laws among the biological characteristics， medicinal parts， growth environment， and medicinal properties and efficacy of traditional Chinese medicines （TCM） from fungi were excavated， so as to strengthen the theory of distinguishing symptoms for quality and provide a reference for the development and utilization of TCM from fungi. MethodThe medicinal parts， meridians for properties and tastes， heterotrophic mode， and efficacy of commonly used TCM from fungi were summarized. By consulting the Compendium of Materia Medica， Shennong Materia Medica， Flora of China， and literature， the TCM from fungi indexed in the 2020 edition of the Chinese Pharmacopoeia and some local pharmacopeias were checked. ResultA total of 28 common TCM from fungi were selected. Different TCMs from fungi have different meridians for properties and tastes， medicinal parts， habits， and growth environments. The relevant information was counted. Among the four properties， plain>cold>warm. Among the five tastes， sweet>bitter>light>pungent=salty. In terms of medicinal parts， fruiting body>sclerotia>complex>spermia=outer skin=other. In terms of meridians， lung>liver=heart>spleen=kidney>stomach. In terms of habits， parasitism>saprophysis>symbiosis=facultative parasitism=facultative saprophysis. ConclusionTCM from fungi are mainly parasitic and saprophytic， and the plain property and sweet taste the most. The meridians are mostly lung， heart， and liver. Nourishment and diuresis are the main efficacy. There is a certain correlation between the color， habit， medicinal parts， and growth environment of TCM from fungi and their properties， tastes， and efficacy， providing comprehensive literature reference and theoretical basis for their in-depth research， clinical use， and resource development.

ObjectiveTo investigate the functions and characteristics of traditional Chinese medicine （TCM） from plant skin and their Chinese patent medicines and explore the related laws of the medicinal tissue， property， taste， efficacy， and clinical application， so as to strengthen the theory of identifying symptoms for qualities and provide references for the development and utilization of TCM from plant skin and their Chinese patent medicines. MethodBy reviewing the 2020 edition of the Chinese Pharmacopoeia and some local pharmacopeias， TCM from plant skin and their Chinese patent medicines were screened out， and the characteristics， functions， and precautions of TCM from plant skin and their Chinese patent medicines were summarized. Statistical analysis was carried out with Excel. ResultA total of 62 TCM from plant skin were found， mainly distributed in one kingdom， three phyla， and 31 families. In terms of the family genus， Rutaceae>Leguminosae>Cucurbitaceae. In terms of the medicinal tissue， bark>root bark>fruit bark>seed bark. In terms of property and taste， warm>cold>plain>cool>hot， and bitter>sweet=pungent>acidic. In terms of meridians， lung>liver>spleen>heart>colorectal>kidney>stomach=bladder. In terms of TCM classification， most of them belong to the category of heat-clearing medicines. There were 485 types of Chinese patent medicines from plant skin， with the most Chinese patent medicines containing Citri Reticulatae Pericarpium. Among the forms of administration， pills were the most predominant. In terms of the tastes of the medicines， bitter and sweet flavors predominated. In terms of functions， medicines for strengthening the body resistance were the most. For the precautions， contraindications during pregnancy were the most common. ConclusionThere is a correlation among medicinal tissue， property， taste， efficacy， and clinical application of TCM from plant skin. It is also necessary to pay attention to the contraindications of the medicines and rationally choose TCM from plant skin and their Chinese patent medicines under the guidance of TCM theory based on syndrome differentiation and treatment.