ObjectiveAge-related macular degeneration （AMD） is one of the leading causes of low vision and blindness in people over 50 years old， and dry AMD （dAMD） is one type for which there is currently no clear treatment. On the basis of the diagnosis and clinical characteristics of dAMD in traditional Chinese and Western medicine， this paper evaluated the fitting degrees of existing animal models of dAMD with clinical characteristics according to the evaluation methods of animal models， and put forward suggestions and prospects. MethodsLiterature on animal models of dAMD was searched against database， and the characteristics of the models were assigned according to the diagnosis criteria of diseases and syndromes of traditional Chinese and Western medicine， and the fitting degrees of the models with clinical characteristics were analyzed and evaluated. ResultsAt present， the animal models of dAMD are mainly established targeting complement factors， chemokines， oxidative damage， lipid/glucose metabolism， and natural strains. Most of the models can simulate the major pathological changes of dAMD， showing the fitting degree of 25%-50% with clinical characteristics in Western medicine. However， the evaluation of traditional Chinese medicine （TCM） syndromes， especially the evaluation of secondary syndromes， is missing， and the models present low fitting degrees with the clinical characteristics in TCM. ConclusionExisting animal models of dAMD are mostly established under the guidance of Western diagnostic standards， which reproduce the main disease characteristics of Western medicine and lack observation of TCM syndromes. Future studies can pay attention to the intervention factors and evaluation systems of spleen deficiency Qi deficiency and liver-kidney Yin deficiency syndrome and build the animal model of dAMD with integration of disease and syndrome based on clinical characteristics of traditional Chinese and Western medicine.

ObjectiveAge-related macular degeneration （AMD） is one of the leading causes of low vision and blindness in people over 50 years old， and dry AMD （dAMD） is one type for which there is currently no clear treatment. On the basis of the diagnosis and clinical characteristics of dAMD in traditional Chinese and Western medicine， this paper evaluated the fitting degrees of existing animal models of dAMD with clinical characteristics according to the evaluation methods of animal models， and put forward suggestions and prospects. MethodsLiterature on animal models of dAMD was searched against database， and the characteristics of the models were assigned according to the diagnosis criteria of diseases and syndromes of traditional Chinese and Western medicine， and the fitting degrees of the models with clinical characteristics were analyzed and evaluated. ResultsAt present， the animal models of dAMD are mainly established targeting complement factors， chemokines， oxidative damage， lipid/glucose metabolism， and natural strains. Most of the models can simulate the major pathological changes of dAMD， showing the fitting degree of 25%-50% with clinical characteristics in Western medicine. However， the evaluation of traditional Chinese medicine （TCM） syndromes， especially the evaluation of secondary syndromes， is missing， and the models present low fitting degrees with the clinical characteristics in TCM. ConclusionExisting animal models of dAMD are mostly established under the guidance of Western diagnostic standards， which reproduce the main disease characteristics of Western medicine and lack observation of TCM syndromes. Future studies can pay attention to the intervention factors and evaluation systems of spleen deficiency Qi deficiency and liver-kidney Yin deficiency syndrome and build the animal model of dAMD with integration of disease and syndrome based on clinical characteristics of traditional Chinese and Western medicine.

The lacrimal gland organoids are innovative in vitro cultured tissue model that mimics the lacrimal gland, retaining its original histological and molecular biological properties. This model can more accurately reproduce the physiological environment of the lacrimal gland, including its ductal system and tear film protein secretion. It offers a new platform for studying the physiopathological basis of the lacrimal gland, establishing disease models, conducting regenerative medicine applications, and performing drug screening. Currently, organoids technology is continuously evolving, with ongoing updates to the methods for in vitro culturing of the lacrimal gland. These advancements gradually address challenges related to cultivation complexity, cost, and time, demonstrating a wide range of application potential. In this paper, we summarize the latest progress in lacrimal gland organoids research both domestically and internationally, exploring the development of lacrimal gland organoids, 3D construction technologies, and their potential for clinical applications, in order to provide new insights for clinical research on lacrimal gland-related diseases and to promote broader application of lacrimal gland organoids in drug development and personalized diagnosis and treatment.

The lacrimal gland organoids are innovative in vitro cultured tissue model that mimics the lacrimal gland, retaining its original histological and molecular biological properties. This model can more accurately reproduce the physiological environment of the lacrimal gland, including its ductal system and tear film protein secretion. It offers a new platform for studying the physiopathological basis of the lacrimal gland, establishing disease models, conducting regenerative medicine applications, and performing drug screening. Currently, organoids technology is continuously evolving, with ongoing updates to the methods for in vitro culturing of the lacrimal gland. These advancements gradually address challenges related to cultivation complexity, cost, and time, demonstrating a wide range of application potential. In this paper, we summarize the latest progress in lacrimal gland organoids research both domestically and internationally, exploring the development of lacrimal gland organoids, 3D construction technologies, and their potential for clinical applications, in order to provide new insights for clinical research on lacrimal gland-related diseases and to promote broader application of lacrimal gland organoids in drug development and personalized diagnosis and treatment.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To assess the efficacy and safety of pain control nursing for burn patients.Methods:Databases including CNKI, Wanfang Data Knowledge Service Platform, Weipu Database, China Biomedical Literature Database, Web of Science and Cochrane Library were searched to collect the literature on pain control nursing of burn patients from their inception to December 31, 2024. Literature screening, data extraction and quality assessment were performed independently by 2 researchers based on inclusion and exclusion criteria. Meta-analysis of the included studies was performed by applying RevMan 5.4 software. The efficacy of pain control care was assessed in terms of improving care satisfaction, alleviating negative emotions, reducing pain, and decreasing infection rate. Publication bias was analyzed on the related studies.Results:A total of 9 papers were included, all of which were randomized controlled trial (RCT) studies, involving 791 burn patients, with 392 in the pain control nursing group and 399 in the conventional care group. Meta-analysis showed that compared with the conventional care, pain control nursing significantly increased satisfaction of care ( OR=0.28, 95% CI 0.22, 0.34), improved negative emotions ( SMD=-3.06, 95% CI -4.65, -1.47), reduced pain ( SMD=-2.49, 95% CI -3.41, -1.58), and effectively reduced the incidence of infection ( OR=0.13, 95% CI 0.05, 0.34). The studies related to negative emotions were at the risk of publication bias. Conclusion:Compared with conventional care, pain control nursing can significantly increase care satisfaction, alleviate negative emotions, reduce pain, and lower infection risk in burn patients.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To assess the efficacy and safety of pain control nursing for burn patients.Methods:Databases including CNKI, Wanfang Data Knowledge Service Platform, Weipu Database, China Biomedical Literature Database, Web of Science and Cochrane Library were searched to collect the literature on pain control nursing of burn patients from their inception to December 31, 2024. Literature screening, data extraction and quality assessment were performed independently by 2 researchers based on inclusion and exclusion criteria. Meta-analysis of the included studies was performed by applying RevMan 5.4 software. The efficacy of pain control care was assessed in terms of improving care satisfaction, alleviating negative emotions, reducing pain, and decreasing infection rate. Publication bias was analyzed on the related studies.Results:A total of 9 papers were included, all of which were randomized controlled trial (RCT) studies, involving 791 burn patients, with 392 in the pain control nursing group and 399 in the conventional care group. Meta-analysis showed that compared with the conventional care, pain control nursing significantly increased satisfaction of care ( OR=0.28, 95% CI 0.22, 0.34), improved negative emotions ( SMD=-3.06, 95% CI -4.65, -1.47), reduced pain ( SMD=-2.49, 95% CI -3.41, -1.58), and effectively reduced the incidence of infection ( OR=0.13, 95% CI 0.05, 0.34). The studies related to negative emotions were at the risk of publication bias. Conclusion:Compared with conventional care, pain control nursing can significantly increase care satisfaction, alleviate negative emotions, reduce pain, and lower infection risk in burn patients.

Objective This paper analyzed the characteristics and changes in the disease spectrum of internal medicine inpatients of a tertiary hospital in Zhongshan City.It aimed to explore the evolving trends in disease ranking and treatment charac-teristics to provide a scientific basis for enhancing hospital management.Methods This paper selected 26 053 patients dis-charged from the internal medicine department of the tertiary hospital in Zhongshan City between January 1,2018,and December 31,2022.A retrospective analysis was used to classify these patients by ages,hospitalization date,and relative weight.Results In the past five years,those discharged patients showed no significant increase in the number,but a significant increase in age and ase Mix Index(CMI).Conclusion Since the outbreak of COVID-19,intractable inpatients in the hospital has steadily in-creased in number each year,while the diseases spectrum remains stable.The CMI of circulatory system,respiratory system,and nervous system diseases is relatively high.As key tricky components of internal medicine,these sub-specialties should concentrate on enhancing diagnostic and treatment capabilities as well as service quality to offer improved healthcare services to the public.

Objective:The study aimed to quantify the contents of peimine and peiminine in huangshi xiangsheng pills using a nano quantity analyte detector(NQAD)and compare the results with the evaporative light scattering detector(ELSD).Methods:Analytical separation was conducted utilizing a CAPCELL PAK MG Ⅲ C18 column(4.6 mm ×250 mm,5 μmi)as the stationary phase.The mobile phase consisted of a mixture of acetonitrile-water-diethylamine(65∶35∶0.03),with a flow rate set at 1.0 mL·min-1 and the column maintained at a temperature of 25℃.Results:NQAD analysis revealed a robust linear correlation between the concentration and the peak area for peimine within a concentration range of 2.450 to 1.470 μg·mL-1,achieving a correlation coefficient of 0.999 3.The limit of detection(LOD)and recovery rate for peimine were determined to be 14.70 ng and 99.50％(n=9),respectively.Similarly,a linear relationship was observed for peiminine between the concentration and the peak area,spanning a range of 3.657 to 1.170 μg·mL-1,with a correlation coefficient of 0.999 1.The LOD and recovery rate for peiminine were 21.94 ng and 100.5％(n=9),respectively.In contrast,ELSD yielded LOD of 24.50 ng for peimine and 36.57 ng for peiminine,with linear range of double logarithmic fitting was 4.900 to 490.0 μg·mL-1 and 7.314 to 585.1 μg·mL-1,respectively.Conclusion:NQAD outperforms ELSD in the quantification of peimine and peiminine,offering superior accuracy,precision,and sensitivity,along with an extended dynamic linear range.By enabling direct content calculation via linear regression,it streamlines the process,bypassing the complex double logarithmic calculations.This approach not only boosts the efficiency of data handling but also substantially simplifies the computational steps,addressing the detection and analysis needs for peimine and peiminine in huangshi xiangsheng pills.