Objective:To analyze the population structure, quantity of rodents, fleas and epidemiological characteristics of animal plague in the plague foci of Erenhot in Inner Mongolia Autonomous Region, and to provide a basis for scientific prevention and control of plague.Methods:The descriptive epidemiological method was used to analyze the surveillance and epidemic data of plague in Erenhot from 2013 to 2023 (from the plague prevention and control management information system of the Chinese Center for Disease Control and Prevention, and the summary of plague surveillance data in Inner Mongolia Autonomous Region from 2013 to 2023), including rat density, nocturnal rat capture, flea infection of rodents, bacteriological and serological detection, etc.Results:From 2013 to 2023, a total of 418 hm 2 of plague foci were investigated in Erenhot, 1 054 rats were caught, and the density of rats was 2.52/hm 2, among which Meriones unguiculatus was the dominant species ( n = 480), and the density was 1.15/hm 2. The capture rate of nocturnal rodents was 6.38% (1 291/20 250). The flea infestation rate of rodents was 35.53% (1 491/4 197), with a flea index of 1.25. Xenopsylla conformity is the dominant flea species ( n = 1 886). Animal plague outbreaks occurred in 7 years, with 11 positive rodents and 10 groups of positive fleas identified by the bacteriology tests, and a total of 21 strains of Yersinia pestis isolated. Eleven positive sera samples were detected by serology. Conclusion:The rodent density in the plague foci of Erenhot is relatively low, but the flea index is high, the animal epidemic is active, facing a significant risk of imported human and animal plague epidemics.

Objective To evaluate the quality of Uncaria Hook(UH)in the market.Methods Twenty-nine batches of UH were tested by legal standards(character,identification,inspection,and extract detection).The TLC method was used to explore the identification of the control herbs,pilocarcinine,dehydropilocarcinine,pilocarcinine and isocarcinine.The HPLC method was used to establish the characteristic spectrum of UH.Then cluster analysis,PCA-X,and OPLS-DA analysis methods were used to perform statistical analysis on the common peak area of unguttine,and determine the contents of heicoside,iso-dehydrounguttine,iso-unguttine,iso-unguttine,and unguttine,to screen out the key quality control components of UH and evaluate their quality.Results Among the 29 batches of samples,23 batches were qualified,and the qualified rate was 79.31％.The results of the TLC analysis showed that the chemical constituents of different base sources were very different.No pilocarcinine was detected in Uncaria macrophylla no hydropilocarcinine was detected in Uncaria sinensis,and four components were not detected in Uncaria hirsuta.Only the samples with the base source of the plant showed corresponding spots in the chromatographic position with the control drug and the control substance.The results of HPLC showed that the chemical composition and content of different base sources of UH were very different.No hydrouncinine and pilocarcinine were detected in Uncaria macrophylla.No iso-dehydrouncinine,dehydrouncinine,and dehydropilocarcinine were detected in Uncaria sinensis.And only heicoside was detected in Uncaria sinensis,and the content of heicoside was low.Based on statistical analysis,there were differences among different batches of UH,and three key quality control ingredients,iso-dehydrounguocarcinoma,dehydrounguocarcinoma,and iso-unguocarcinoma that may lead to quality differences of unguocarcinoma were found.Conclusions Overall,the UH is of poor quality,the current processing standards and testing standards can not ensure the quality of the product,affecting the safety and effectiveness of clinic use.The chemical composition categories and contents of different base sources of UH are very different,which increases the difficulty of formulating a unified quality standard.

Bronchiectasis is one of the most common and refractory lower respiratory tract diseases in clinic practice.Pseudomonas aeruginosa is the most common frequently isolated pathogen in adults with bronchiectasis complicated by infection.The complex relationship among inflammation,immunity,infection and structural damage in the airway of patients has been described as a"vicious circle"model,but the specific mechanism of different pathological links in this model and their intricate interactions are still not fully understood.The theory of"Strengthening fire eating qi"first appeared in Su Wen·Yin Yang Ying Xiang Da Lun,and provides simply explain the"qi"damage to"shape"damage of patients'airway from the perspective of"fire"and"qi"in traditional Chinese medicine,and provide new ideas for explaining the pathological mechanism connotation of bronchiectasis combined with Pseudomonas aeruginosa infection.The exploration of pathological mechanism is the fundamental source of understanding disease progression and discovering new treatment ideas.At present,the clinical treatment of Western medicine for patients with bronchiectasis mainly focuses on anti-infection and symptomatic treatment.Although etiological targeted therapies and targeted drugs are constantly explored and developed,they are still rarely applied in clinical practice.As a treasure of Chinese culture,traditional Chinese medicine has the advantage of taking both specimens into consideration,and its clinical efficacy and pharmacological value are worthy of further study.Based on the classical theory of"Strengthening fire eating qi",this review aims to understand and summarize the modern pathological mechanism of bronchiectasis combined with Pseudomonas aeruginosa infection and highlights current research hotspots in both Chinese and Western medicine treatment,in order to provide clinical thinking.

Objective:To establish machine learning models to predict visual improvement and anatomical response after anti-vascular endothelial growth factor (VEGF) treatment in patients with diabetic macular edema (DME).Methods:A multi-algorithm machine learning predictive modeling study based on retrospective clinical data was conducted.A total of 225 patients with DME who received their first intravitreal anti-VEGF injection at Fuzhou University Affiliated Provincial Hospital were enrolled between January 2023 and April 2025.According to data completeness, 204 cases were included in the visual recovery prediction model and 201 cases were included in the anatomical response prediction model.Baseline data included optical coherence tomography (OCT) features and blood biomarkers.The primary outcomes were defined as an improvement of ≥1 line in visual acuity and a reduction of ≥20% in central retinal thickness (CRT) after anti-VEGF treatment.Feature selection was performed using univariate logistic regression and Lasso regression.Four machine learning algorithms, logistic regression (LR), decision tree, multilayer perceptron, and random forest, were trained and validated.Model performance was evaluated using accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and decision curve analysis.The best-performing model was further interpreted using SHAP analysis, and a nomogram was constructed for clinical application.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Fuzhou University Affiliated Provincial Hospital (No.K2025-03-064).Written informed consent was obtained from each subject.Results:Among the 37 baseline variables, five key predictors were identified for the outcome of ≥20% CRT reduction: baseline CRT, baseline CRT ≥400 μm, presence of subretinal fluid (SRF), disorganization of the retinal inner layers (DRIL), and integrity of the ellipsoid zone (EZ).Among the four models, the LR model had the best performance, with an accuracy of 0.88, sensitivity of 0.94, specificity of 0.70, and an AUC of 0.94 (95% confidence interval [ CI]: 0.87-1.00).SHAP analysis showed that baseline CRT ≥400 μm, DRIL, SRF, and baseline CRT contributed positively to the outcome, while EZ integrity was a negative predictor for CRT reduction.For the outcome of ≥1-line visual improvement, two key predictors were identified: baseline best corrected visual acuity (BCVA) and EZ integrity.Both baseline BCVA and EZ integrity were negative predictors for ≥1-line visual improvement.The LR model also had the best performance in the internal validation cohort, with an accuracy of 0.71, sensitivity of 0.67, specificity of 0.75, and an AUC of 0.76 (95% confidence interval [ CI]: 0.61-0.91).A visual nomogram was developed based on the selected predictors and the best-performing model.By converting patient-specific clinical characteristics into scores, clinicians can calculate a total score and estimate the probability of achieving a reduction of ≥20% in CRT and a ≥1-line improvement in visual acuity after anti-VEGF therapy. Conclusions:Machine learning-based model building can effectively predict visual and anatomical response following anti-VEGF treatment in DME patients.Logistic regression shows robust predictive performance for both outcomes.Identification of key predictors, especially OCT features such as EZ integrity, SRF, and DRIL, may aid in guiding treatment expectation assessment and personalized intervention strategies.Nomogram constructed in this study shows good clinical applicability and may serve as a decision-support tool to improve the precision of DME management.

Objective To investigate the predictive value of serum lipoprotein-associated phospholipase A2(Lp-PLA2)and homocysteine(Hcy)combined with white matter hyperintensities(WMH)for cognitive impairment in patients with cerebral small vessel disease(CSVD).Methods A total of 240 patients with CSVD were selected.According to the Montreal Cognitive Assessment(MoCA)scale,all subjects were divided into the non-cognitive impairment group(MoCA≥26 points,120 cases)and the cognitive impairment group(MoCA＜26 points,120 cases).Paraventricular white matter high signal(PWMHs)and deep white matter high signal(DWMHs)were scored by Fazekas scale.The sum of the two parts was the total score,and the severity of DWMHs was graded by the score.The basic information,serum Lp-PLA2,Hcy level and severity of WMH were compared between the two groups.Logistic regression was applied to analyze influencing factors of cognitive impairment in CSVD patients.The predictive value of serum level of Lp-PLA2 and Hcy and WMH for cognitive impairment in CSVD patients was analyzed by receiver operating characteristic(ROC)curve.Results Compared with the non-cognitive impairment group,patients of the cognitive impairment group were older,had higher serum levels of Lp-PLA2 and Hcy,and had more severe of WMH(P＜0.05).Results of Logistic regression analysis showed that serum Lp-PLA2,Hcy levels and severity of WMH were influencing factors for cognitive impairment of patients with CSVD(P＜0.05).The results of ROC curve analysis showed that the area under the curve of serum Lp-PLA2,Hcy level combined with severity of WMH predicting cognitive impairment in patents with CSVD was 0.812,the sensitivity was 81.7%and the specificity was 71.7%(P＜0.05).Conclusion Patients with cognitive impairment caused by CSVD have higher serum levels of Lp-PLA2 and Hcy,and more severe WMH.The combination of the three has a relatively high predictive value for cognitive impairment in patents with CSVD.

The intervertebral disc is a complex structure composed of the central nucleus pulposus, the peripheral annulus fibrosus, and the cartilaginous endplates located at the top and bottom. This unique arrangement effectively isolates the nucleus pulposus from the host’s immune system. Additionally, specific substances within the intervertebral disc exhibit inhibitory effects on the infiltration of immune cells and cytokines, which has led to the recognition of the intervertebral disc as an immune-privileged tissue. However, during intervertebral disc degeneration (IDD), the physical barriers that maintain this immune privilege are compromised. As a result, the nucleus pulposus may be perceived as a foreign antigen by the immune system. Simultaneously, inflammatory cytokines released by the degenerating disc attract a significant influx of immune cells, disrupting the delicate immunological balance within the nucleus pulposus and exacerbating the progression of IDD. Recent studies have confirmed the infiltration of immune cells such as macrophages and mast cells into the degenerative intervertebral disc, and the phenotypic characteristics and quantitative changes of these immune cells are closely related to the process of IDD. In terms of treatment strategies, biological agents such as mesenchymal stem cell therapy, gene therapy and growth factors that regulate the immune microenvironment of degenerative intervertebral discs have entered the stage of animal experiments. At the same time, small molecule drugs have shown unique regulatory potential in restoring the immune-privileged status of intervertebral discs.

Objective:To establish machine learning models to predict visual improvement and anatomical response after anti-vascular endothelial growth factor (VEGF) treatment in patients with diabetic macular edema (DME).Methods:A multi-algorithm machine learning predictive modeling study based on retrospective clinical data was conducted.A total of 225 patients with DME who received their first intravitreal anti-VEGF injection at Fuzhou University Affiliated Provincial Hospital were enrolled between January 2023 and April 2025.According to data completeness, 204 cases were included in the visual recovery prediction model and 201 cases were included in the anatomical response prediction model.Baseline data included optical coherence tomography (OCT) features and blood biomarkers.The primary outcomes were defined as an improvement of ≥1 line in visual acuity and a reduction of ≥20% in central retinal thickness (CRT) after anti-VEGF treatment.Feature selection was performed using univariate logistic regression and Lasso regression.Four machine learning algorithms, logistic regression (LR), decision tree, multilayer perceptron, and random forest, were trained and validated.Model performance was evaluated using accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and decision curve analysis.The best-performing model was further interpreted using SHAP analysis, and a nomogram was constructed for clinical application.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Fuzhou University Affiliated Provincial Hospital (No.K2025-03-064).Written informed consent was obtained from each subject.Results:Among the 37 baseline variables, five key predictors were identified for the outcome of ≥20% CRT reduction: baseline CRT, baseline CRT ≥400 μm, presence of subretinal fluid (SRF), disorganization of the retinal inner layers (DRIL), and integrity of the ellipsoid zone (EZ).Among the four models, the LR model had the best performance, with an accuracy of 0.88, sensitivity of 0.94, specificity of 0.70, and an AUC of 0.94 (95% confidence interval [ CI]: 0.87-1.00).SHAP analysis showed that baseline CRT ≥400 μm, DRIL, SRF, and baseline CRT contributed positively to the outcome, while EZ integrity was a negative predictor for CRT reduction.For the outcome of ≥1-line visual improvement, two key predictors were identified: baseline best corrected visual acuity (BCVA) and EZ integrity.Both baseline BCVA and EZ integrity were negative predictors for ≥1-line visual improvement.The LR model also had the best performance in the internal validation cohort, with an accuracy of 0.71, sensitivity of 0.67, specificity of 0.75, and an AUC of 0.76 (95% confidence interval [ CI]: 0.61-0.91).A visual nomogram was developed based on the selected predictors and the best-performing model.By converting patient-specific clinical characteristics into scores, clinicians can calculate a total score and estimate the probability of achieving a reduction of ≥20% in CRT and a ≥1-line improvement in visual acuity after anti-VEGF therapy. Conclusions:Machine learning-based model building can effectively predict visual and anatomical response following anti-VEGF treatment in DME patients.Logistic regression shows robust predictive performance for both outcomes.Identification of key predictors, especially OCT features such as EZ integrity, SRF, and DRIL, may aid in guiding treatment expectation assessment and personalized intervention strategies.Nomogram constructed in this study shows good clinical applicability and may serve as a decision-support tool to improve the precision of DME management.

Objective:To analyze the population structure, quantity of rodents, fleas and epidemiological characteristics of animal plague in the plague foci of Erenhot in Inner Mongolia Autonomous Region, and to provide a basis for scientific prevention and control of plague.Methods:The descriptive epidemiological method was used to analyze the surveillance and epidemic data of plague in Erenhot from 2013 to 2023 (from the plague prevention and control management information system of the Chinese Center for Disease Control and Prevention, and the summary of plague surveillance data in Inner Mongolia Autonomous Region from 2013 to 2023), including rat density, nocturnal rat capture, flea infection of rodents, bacteriological and serological detection, etc.Results:From 2013 to 2023, a total of 418 hm 2 of plague foci were investigated in Erenhot, 1 054 rats were caught, and the density of rats was 2.52/hm 2, among which Meriones unguiculatus was the dominant species ( n = 480), and the density was 1.15/hm 2. The capture rate of nocturnal rodents was 6.38% (1 291/20 250). The flea infestation rate of rodents was 35.53% (1 491/4 197), with a flea index of 1.25. Xenopsylla conformity is the dominant flea species ( n = 1 886). Animal plague outbreaks occurred in 7 years, with 11 positive rodents and 10 groups of positive fleas identified by the bacteriology tests, and a total of 21 strains of Yersinia pestis isolated. Eleven positive sera samples were detected by serology. Conclusion:The rodent density in the plague foci of Erenhot is relatively low, but the flea index is high, the animal epidemic is active, facing a significant risk of imported human and animal plague epidemics.

Purpose To investigate the sex differences of white matter damage in Alzheimer's disease(AD)and their association with cognitive impairment.Materials and Methods This retrospective study included 88 AD patients(48 females),71 amnestic mild cognitive impairment(aMCI)patients(39 females),and 95 healthy controls(63 females)recruited from the Memory Disorder Clinic at the First Affiliated Hospital of Anhui Medical University from September 2017 to July 2024.High-resolution three-dimensional T1 structure images and diffusion tensor imaging images were all obtained from each participant.The mean diffusivity(MD)and fractional anisotropy(FA)values of each white matter region were obtained,and the two-way ANOVA analysis was conducted to investigate brain regions with interaction effects between groups and sexes,those brain regions were then chosen as regions of interest for further correlation analysis with a series of cognitive scale scores.Results In terms of FA values,the right posterior corona radiata,right anterior limb of the internal capsule and left corticospinal tract showed interaction between sexes and cognitive groups(F=4.764,3.812,5.937,all P<0.05).The FA value of AD group was significantly lower than that of healthy control and aMCI group(all P<0.05),but there was no significant difference between healthy control and aMCI group(except the right anterior limb of the internal capsule,P=0.018).In AD group,FA values were significantly higher in women than in men in the previously described brain regions(all P<0.05),while there was no significant difference in FA values between male and female in healthy control and aMCI groups(except the left corticospinal tract,P<0.001).In terms of MD values,the right anterior limb of the internal capsule,right superior corona radiata and left external capsule showed interaction effect between sexes and cognitive groups(F=8.581,3.680,7.218,all P<0.05).The MD value of AD group was significantly higher than that of aMCI group(P<0.001),and aMCI group was higher than that of healthy control group(all P<0.05).In AD group,the MD values in the above brain regions were significantly higher in males than those in females(all P<0.01),while no significant difference was found between males and females in healthy control and aMCI groups(except for the left external capsule,P<0.05).For correlation analysis,the AD group was dimidiated into two groups by sex,the scores of the Montreal cognitive assessment,the Mini Mental state examination and the verbal fluency test of the female patient group were positively correlated with the FA values of the right posterior corona radiate(r=0.372,P=0.009;r=0.345,P=0.016;r=0.383,P=0.007),while the Mini Mental state examination and the verbal fluency test scores of female AD patient group were negatively correlated with the MD values of the right superior corona radiata(r=-0.360,P=0.012;r=-0.360,P=0.003).Conclusion Compared to the healthy control and MCI groups,white matter damage in AD patients shows sex differences and is associated with general cognitive and language functions impairment in female AD patients.

Emerging evidences have indicated the role of ferroptosis in the progression of metabolic-associated fatty liver disease (MAFLD); thus, inhibiting ferroptosis is a promising strategy for the development of MAFLD therapeutics. Recent studies have demonstrated the antioxidative effect of the gut commensal bacterium Akkermansia muciniphila (A. muc); however, whether it can alleviate ferroptosis remains unclear. The current study indicates A. muc intervention efficiently reversed high-fat high-fructose diet (HFHFD)-induced lipid peroxidation and ferroptosis in the liver. These beneficial effects were mediated by activation of the hepatic AMPK/SIRT1/PGC-1α axis, as evidenced by the finding that AMPK deficiency abrogated the amelioration of lipid peroxidation in vitro and in vivo. Furthermore, the short-chain fatty acids (SCFAs) were enriched upon A. muc treatment, and acetate was identified as a key activator of hepatic AMPK signalling. Mechanistically, microbiota-derived acetate was transported to the liver and metabolized to adenosine monophosphate (AMP), which triggered AMPK activation. Furthermore, a colonization assay in germ-free mice confirmed that A. muc mediated antiferroptotic effects in the absence of other microbes. These data indicated that A. muc exerts antiferroptotic effects against MAFLD, at least partially by producing acetate, which activates the hepatic AMPK/SIRT1/PGC-1α axis to alleviate ferroptosis via the inhibition of polyunsaturated fatty acid (PUFA) synthesis.