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.

AIM: To observe the preoperative and postoperative clinical efficacy of comprehensive dry eye treatment in cataract patients complicated with diabetes mellitus, with a focus on comparing the differences between the two groups in terms of postoperative dry eye symptoms, tear film function, visual recovery, and complication rates, aiming to provide an effective protocol for the perioperative management and long-term prognosis improvement in this patient population.METHODS:Patients diagnosed with both cataract and diabetes mellitus and presenting with varying degrees of dry eye symptoms, scheduled for cataract surgery at the hospital from May 2023 to December 2024, were enrolled as study subjects. They were divided into two groups using a random number method: the control group received sodium hyaluronate eye drops alone, and the experimental group underwent comprehensive preoperative dry eye treatment(sodium hyaluronate eye drops+warm compress+meibomian gland cleaning and massage+Chinese herbal fumigation+health guidance). Tear film breakup time(BUT), corneal fluorescein staining(FL), Ocular Surface Disease Index(OSDI)score, tear meniscus height(TMH), and non-invasive first tear film breakup time(NIBUT)were compared between the two groups before and after 4 wk of treatment. Meibomian gland loss, tear film lipid layer thickness, and basic ocular symptoms were also assessed.RESULTS:This study included 60 eyes of 60 patients, with a control group of 30 eyes of 30 patients(aged 56.24±10.24 y, 13 males and 17 females)and an experimental group of 30 eyes of 30 patients(aged 58.01±9.79 y, 15 males and 15 females).After 4 wk of preoperative treatment, the BUT in the experimental group increased from 4.09±1.13 s to 10.35±1.46 s, and from 4.15±1.05 s to 8.26±1.36 s in the control group, showing a significant intergroup difference(t=5.737, P<0.001). The FL score in the experimental group decreased from 6.83±0.46 points to 2.86±0.38 points, whereas in the control group it decreased from 6.79±0.39 points to 5.32±0.43 points(t=23.480, P<0.001). After 4 wk of treatment, the NIBUT in the experimental group increased from 5.19±1.12 s to 9.36±1.47 s, compared to an increase from 5.21±1.04 s to 7.18±1.25 s in the control group(t=6.188,P<0.001). The proportion of patients with a thin tear film lipid layer was significantly higher in the experimental group than in the control group(all P<0.01). Ocular clinical symptoms decreased after treatment in both groups, with the experimental group showing lower scores than the control group(all P<0.001).CONCLUSION:Preoperative comprehensive dry eye treatment can multi-dimensionally improve dry eye symptoms and tear film stability in cataract patients with diabetes mellitus, providing an effective strategy for the perioperative management of cataract patients.

OBJECTIVES: To investigate the effect of Qianggu Kangshu Formula (QGKSF) for alleviating osteoclast differentiation in rheumatoid arthritis and the underlying mechanism. METHODS: RAW264.7 cells cultured under hypoxic conditions were treated with RANKL to induce osteoclast differentiation and incubated with normal rat serum or sera from rats medicated with methotrexate (MTX) or QGKSF at low and high doses. Cell viability, TRAP-positive multinucleated cells and F-actin ring formation in the treated cells were assessed with CCK-8 assay, TRAP staining and Phalloidin staining, respectively. Autophagy and autophagosomes in the cells were observed with MDC staining and transmission electron microscopy. ELISA was used to measure IL-6 and TNF-α levels in the culture supernatant, and the expressions of HIF-1α, BNIP3, Bcl-2, Beclin1, LC3-I, LC3-II, P62 and TRAP mRNAs and proteins were analyzed using RT-qPCR and Western blotting. RESULTS: In hypoxia- and RANKL-induced RAW264.7 cells treated with normal rat serum, significant increments of TRAP-positive cells and F-actin ring formation were observed with an enhanced autophagic fluorescence intensity and increased autophagosomes. Treatment of the induced cells with rat sera medicated with MTX and low- and high-dose QGKSF obviously reduced the TRAP-positive cells, F-actin rings and autophagosomes as well as the autophagic fluorescence intensity. RANKL treatment significantly increased IL-6 and TNF-α levels in RAW264.7 cells, which were obviously decreased by treatment with MTX- and QGKSF-medicated sera. RANKL also significantly increased the mRNA and protein expression levels of HIF-1α, BNIP3, Bcl-2, Beclin1, LC3 and TRAP and lowered P62 expressions, and these changes were effectively reversed by treatment with MTX- and QGKSF-medicated sera. CONCLUSIONS QGKSF attenuates RANKL-induced osteoclast differentiation in hypoxic RAW264.7 cells by inhibiting the HIF-1α/BNIP3 autophagy signaling pathway, suggesting its potential for treatment of bone destruction in rheumatoid arthritis.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Osteoclasts/drug effects* ; Autophagy/drug effects* ; Mice ; Signal Transduction/drug effects* ; Rats ; Cell Differentiation/drug effects* ; Arthritis, Rheumatoid/pathology* ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; RAW 264.7 Cells ; Membrane Proteins/metabolism* ; Mitochondrial Proteins

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective:to investigate age-related changes in high-sensitivity cardiac troponin T(hs-cTnT)levels among middle-aged and elderly individuals, and to establish reference values for the 99th percentile upper reference limit(99th URL)of hs-cTnT within this demographic.Methods:This research is designed as a cross-sectional study.Hs-cTnT test results were collected from outpatients at Beijing Hospital between January 2018 and December 2023.The final sample included 5, 677 outpatients aged 45 to 85 years(65±10), all of whom were free from cardiovascular diseases and other chronic heart-related conditions.Multiple linear regression was utilized to assess the impact of gender and age group on hs-cTnT concentrations within the middle-aged and elderly populations.Furthermore, a generalized additive model for location, scale, and shape(GAMLSS)was employed to generate percentile curves of hs-cTnT by gender in this cohort, with the aim of determining the 99th URLs for both middle-aged and elderly individuals.Results:Multiple linear regression analyses indicated that both gender and age significantly influenced hs-cTnT levels in middle-aged and elderly populations( β60-69 years=1.399, β≥70 years=5.306, βgender=-2.650, all Pvalues<0.001).The hs-cTnT data for both males and females conformed to Box-Cox-Cole-Green(BCCG)distributions, with percentile curves fitted at the 25th, 50th, 75th, and 99th percentiles according to gender.The percentile values of hs-cTnT in both males and females demonstrated a progressive increase with advancing age.Notably, males exhibited higher 99th percentile values than females across all age groups. Conclusions:The GAMLSS approach is employed to establish continuous reference intervals for hs-cTnT in the middle-aged and elderly population.This effort aims to provide a theoretical foundation for reference values specific to this demographic in China and to offer guidance for clinical 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.

This study analyzed the clinical characteristics,diagnosis,treatment,and outcomes of disseminated Tsalaromycosis marneffei(DTSM)in non-HIV-infected patients.A retrospective analysis was conducted on 20 cases of non-HIV-infected DTSM treated at Guangzhou Chest Hospital between January 2015 and December 2021.Clinical data,including demographic characteris-tics,time to diagnosis,clinical manifestations,comorbidities,treatment details,and outcomes,were collected and analyzed.Among the 20 cases,9 were in males,and 11 were in females;the median age was 46(range:1-70)years.The median time from symptom onset to definitive diagnosis was 12(range:1-24)months,and 16 cases were initially misdiagnosed with mycobacterial disease.More than half the patients exhibited four major clinical features:fever,lymphadenopathy,skin lesions,and bone lesions.Pulmonary imag-ing abnormalities were observed in 19 cases,and an average of(3.6±1.6)lung lobes were involved.The positive detection rate of multi-sample cultures(70%,14/20)was significantly higher than that identified through histopathological examination(25%,5/20)(χ2=8.120,P=0.004).Findings for all five patients with positive next-generation sequencing(NGS)results were further confirmed through pathogen culture or histopathology.After antifungal treatment,14 patients showed clinical improvement and were discharged.In conclusion,non-HIV-infected DTSM is characterized by complex clinical manifestations and extensive pulmonary involvement,thus leading to frequent misdiagnosis and diagnostic delays.Pathogen detection methods,such as multi-sample cultures and NGS,demonstrate superior diagnostic accuracy to histopathological examination.Early identification and standardized antifungal therapy are critical factors in determining patient outcomes.

Objective:To analyze the epidemiological characteristics, spatial clustering, and correlation between dental fluorosis detection rates and meteorological factors in children aged 8 - 12 years old in 37 counties (cities, districts, hereinafter referred to as counties) affected by coal-burning-borne endemic fluorosis in Guizhou Province, and to provide a scientific basis for prevention and control of the disease.Methods:Monitoring data on dental fluorosis in children aged 8 - 12 years old from 2019 to 2022 were collected from the National Health Security Information System for Endemic Diseases. Meteorological data, including annual average temperature, annual average precipitation, annual sunshine hours, and annual average relative humidity, were obtained from the Guizhou Provincial Bureau of Statistics. Descriptive epidemiology, analytical epidemiology, and spatial correlation analysis methods were used to analyze the data. Visual maps were created based on the clustering levels of annual dental fluorosis detection rates (high-high, low-low, high-low, low-high). Spatial autocorrelation and meteorological factors were used to analyze the epidemiological characteristics, spatial clustering, and the impact of meteorological factors on dental fluorosis.Results:From 2019 to 2022, a total of 3 649 161 children aged 8 - 12 in the counties affected by coal-burning-borne endemic fluorosis were monitored, and 115 793 children were diagnosed with dental fluorosis, with a detection rate of 3.17%. The detection rates were 4.73% (45 093/954 338) in 2019, 3.35% (31 424/938 445) in 2020, 2.86% (21 727/760 195) in 2021, and 1.76% (17 549/996 183) in 2022, respectively. The dental fluorosis indices were 0.09, 0.07, 0.06, and 0.03, respectively. The number of counties with detection rates > 6% was 7, 5, 5, and 0 in 2019 - 2022, respectively. Dafang County consistently had the highest detection rates, with rates of 10.06% (6 783/67 408), 10.07% (1 955/19 421), 13.54% (4 017/29 667), and 4.83% (3 284/76 206) in 2019 - 2022, respectively. The Moran's I indices for dental fluorosis detection rates were 0.45, 0.53, 0.53, and 0.53 in 2019 - 2022, with Z = 4.29, 5.07, 5.31, and 5.10, respectively ( P < 0.05), indicating global spatial autocorrelation (positive) and spatial clustering of dental fluorosis detection rates. The number of counties with "high-high" clustering of detection rates was 7, 7, 6, and 7 in 2019 - 2022, mainly concentrated in the northwestern region, including Qixingguan District, Nayong County, Dafang County, Zhijin County, and Jinsha County of Bijie City. "Low-high" clustering areas were distributed in Zhongshan District of Liupanshui City in 2019, 2020, and 2022. The detection rate of dental fluorosis was associated with local annual average temperature (°C) and annual precipitation (mm) ( r = - 0.393, - 0.337, P = 0.016, 0.041). Conclusions:From 2019 to 2022, the detection rate of dental fluorosis in children aged 8 - 12 in coal-burning-borne endemic fluorosis areas in Guizhou Province has been decreasing year by year, and it shows spatial clustering. The high clustering area is in the northwest of Guizhou Province, which should be regarded as a key prevention and control area for coal-burning-borne fluorosis in the future. At the same time, areas with lower temperatures and precipitation should also strengthen prevention and control efforts.

Objective:To analyze the epidemiological characteristics, spatial clustering, and correlation between dental fluorosis detection rates and meteorological factors in children aged 8 - 12 years old in 37 counties (cities, districts, hereinafter referred to as counties) affected by coal-burning-borne endemic fluorosis in Guizhou Province, and to provide a scientific basis for prevention and control of the disease.Methods:Monitoring data on dental fluorosis in children aged 8 - 12 years old from 2019 to 2022 were collected from the National Health Security Information System for Endemic Diseases. Meteorological data, including annual average temperature, annual average precipitation, annual sunshine hours, and annual average relative humidity, were obtained from the Guizhou Provincial Bureau of Statistics. Descriptive epidemiology, analytical epidemiology, and spatial correlation analysis methods were used to analyze the data. Visual maps were created based on the clustering levels of annual dental fluorosis detection rates (high-high, low-low, high-low, low-high). Spatial autocorrelation and meteorological factors were used to analyze the epidemiological characteristics, spatial clustering, and the impact of meteorological factors on dental fluorosis.Results:From 2019 to 2022, a total of 3 649 161 children aged 8 - 12 in the counties affected by coal-burning-borne endemic fluorosis were monitored, and 115 793 children were diagnosed with dental fluorosis, with a detection rate of 3.17%. The detection rates were 4.73% (45 093/954 338) in 2019, 3.35% (31 424/938 445) in 2020, 2.86% (21 727/760 195) in 2021, and 1.76% (17 549/996 183) in 2022, respectively. The dental fluorosis indices were 0.09, 0.07, 0.06, and 0.03, respectively. The number of counties with detection rates > 6% was 7, 5, 5, and 0 in 2019 - 2022, respectively. Dafang County consistently had the highest detection rates, with rates of 10.06% (6 783/67 408), 10.07% (1 955/19 421), 13.54% (4 017/29 667), and 4.83% (3 284/76 206) in 2019 - 2022, respectively. The Moran's I indices for dental fluorosis detection rates were 0.45, 0.53, 0.53, and 0.53 in 2019 - 2022, with Z = 4.29, 5.07, 5.31, and 5.10, respectively ( P < 0.05), indicating global spatial autocorrelation (positive) and spatial clustering of dental fluorosis detection rates. The number of counties with "high-high" clustering of detection rates was 7, 7, 6, and 7 in 2019 - 2022, mainly concentrated in the northwestern region, including Qixingguan District, Nayong County, Dafang County, Zhijin County, and Jinsha County of Bijie City. "Low-high" clustering areas were distributed in Zhongshan District of Liupanshui City in 2019, 2020, and 2022. The detection rate of dental fluorosis was associated with local annual average temperature (°C) and annual precipitation (mm) ( r = - 0.393, - 0.337, P = 0.016, 0.041). Conclusions:From 2019 to 2022, the detection rate of dental fluorosis in children aged 8 - 12 in coal-burning-borne endemic fluorosis areas in Guizhou Province has been decreasing year by year, and it shows spatial clustering. The high clustering area is in the northwest of Guizhou Province, which should be regarded as a key prevention and control area for coal-burning-borne fluorosis in the future. At the same time, areas with lower temperatures and precipitation should also strengthen prevention and control efforts.