ObjectiveTo construct a risk prediction model for frequent acute exacerbations of chronic obstructive pulmonary disease （COPD） under disease-syndrome combination， thus providing decision support for precise clinical intervention. MethodsA total of 2 029 patients with acute exacerbations of COPD admitted to the First Affiliated Hospital of Anhui University of Chinese Medicine from January 2020 to August 2024 were retrospectively included. These patients were classified into groups of frequent acute exacerbations （≥2 times/year） and infrequent acute exacerbations （<2 times/year） according to the hospitalization times per year. Risk factors were screened by LASSO regression combined with logistic regression， and a nomogram model was constructed. The model performance was assessed based on the area under the curve （AUC）， calibration curves， and decision curve analysis （DCA）. ResultsThe differences in baseline characteristics between the frequent acute exacerbations group （1 196 cases） and infrequent acute exacerbations group （833 cases） were not statistically significant. LASSO regression combined with multivariate logistic regression screened the following independent risk factors： body mass index （BMI）， hospitalization days， number of smoking years， place of residence， use of noninvasive ventilators， oxygen-demanding therapy， liver cirrhosis， use of systemic glucocorticosteroids， and traditional Chinese medicine syndrome （phlegm and stasis obstructing the lung）. The nomogram model showed good discrimination and calibration in both the training set （AUC=0.748） and validation set （AUC=0.774）. ConclusionThe risk prediction model for frequent acute exacerbations of COPD， integrating traditional Chinese medicine syndrome， constructed in this study has high accuracy. It can provide a scientific basis for early clinical identification of high-risk patients and individualized intervention.

Objective Objective To analyze the potential spatial factors affecting the genetic differentiation of Oncomelania hupensis robertsoni in Yunnan Province. Methods A total of 13 administrative villages were selected from schistosomiasis-endemic areas of Yunnan Province as O. hupensis snail sampling sites. At least 200 snails were collected in each site, and the spatial variable data of each site were recorded, including longitude, latitude and altitude. Thirty active and Schistosoma japonicum uninfected O. hupensis snails were selected from each sampling site by means of the crawling method and the cercarial shedding method. Genomic DNA was extracted from O. hupensis snails. Following PCR amplification, purification of PCR amplification products and sequencing, the gene sequences of O. hupensis snail samples were spliced and edited using the DNAstar software and the NCBI database to yield the complete mitochondrial sequences of O. hupensis snails at each sampling site, and the mitochondrial genetic distance matrix of O. hupensis robertsoni was calculated at each sampling site. The geographical coordinates of each sampling site were marked using the software ArcGIS 10.2, and the straight-line geographical distance between each sampling site was calculated. The altitude difference, longitude difference and latitude difference between each sampling site were calculated using the Excel software, and the correlation between the mitochondrial genetic distance matrix of O. hupensis robertsoni and each spatial variable matrix was examined by using the Mantel test at 13 sampling sites in Yunnan Province. Results Among the 13 O. hupensis snail sampling sites in Yunnan Province, the largest mitochondrial genetic distance of O. hupensis robertsoni snail populations was seen between Anding Village, Nanjian Yi Autonomous County and Caizhuang Village, Midu County (26.244 2), and the largest geographical distance was seen between Dongyuan Village, Gucheng District and Cangling Village, Chuxiong County (272.64 km). The highest altitude difference was seen between Anding Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1 086.10 m), and the largest longitude difference was found between Qiandian Village, Eryuan County and Cangling Village, Chuxiong County (1.86°), while the largest latitude difference was measured between Leqiu Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1.81°). In addition, the mitochondrial genetic distance of O. hupensis robertsoni snail populations was positively correlated with altitude at 13 snail sampling sites in Yunnan Province (r = 0.542 8, P < 0.001), and showed no significant correlations with geographical distance (r = 0.093 4, P > 0.05), longitude (r = −0.199 5, P > 0.05) or latitude (r = 0.205 7, P > 0.05). Conclusion Altitude may be a potential spatial factor affecting the genetic differentiation of O. hupensis robertsoni in Yunnan Province.

Objective To investigate the distribution characteristics of Oncomelania hupensis snails in Yunnan Province fol-lowing interruption of schistosomiasis transmission, so as to provide the evidence for assessing the risk of schistosomiasis transmission and scientifically formulating the schistosomiasis surveillance program. Methods According to the requirements of the National Schistosomiasis Surveillance Scheme (2020 Edition), O. hupensis snail surveillance data were collected from 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province from 2020 to 2024, including area of snail survey, area of snail habitats, area of re-emerging snail habitats, number of frames surveyed, number of frames with O. hupensis snails, number of O. hupensis snails captured, and number of living snails, and the occurrence of frames with snails and mean density of living snails were calculated. Changes in snail status over the 5-year period from 2020 to 2024 and the differences in snail distributions specified by epidemic intensity, environmental type, and vegetation type were analyzed. Results The areas of snail survey increased from 1 727.96 hm² in 2020 to 3 894.45 hm² in 2024 (peak) across 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province during the period from 2020 through 2024. The areas of snail habitats increased from 70.36 hm² in 2020 to a peak in 2023 (172.04 hm²), followed by a reduction to 132.36 hm² in 2024, and the areas of re-emerging snail habitats increased from 42.71 hm² in 2020 to a peak in 2022 (78.43 hm²), followed by a reduction to 40.21 hm² in 2024. The occurrence of frames with snails and mean density of living snails increased from 1.24% (3 025/244 404) and (0.033 2 ± 0.038 7) snails/0.1 m² in 2020 to peaks at 2.03% (6 231/307 563) and (0.066 9 ± 0.068 4) snails/0.1 m² in 2023, followed by reductions to 1.04% (5 829/559 941) and (0.032 6 ± 0.057 7) snails/0.1 m² in 2024, respectively. There was a significant difference in the occurrence of frames with snails over the 5-year study period (χ² = 1 962.95, P < 0.05), and the occurrence of frames with snails reduced by 48.71% in 2024 relative to in 2023 (χ² = 1 411.05, P < 0.005); however, there was no significant difference in the mean density of living snails over the 5 years (H = 5.310, P > 0.05). There were significant differences in the occurrence of frames with snails (χ² = 481.27, P < 0.05) and mean density of living snails (H = 6.872, P < 0.05) in schistosomiasis-endemic areas with different epidemic intensities. The occurrence of frames with snails (χ² = 25.32 and 38.70, both P values < 0.017) and mean density of living snails (Z = 28.55 and 49.96, both P values < 0.017) were higher in schistosomiasis transmission-interrupted and eliminated areas with snails than in schistosomiasis-eliminated areas without snails, and the occurrence of frames with snails (χ² = 453.54, P < 0.017) and mean density of living snails (Z = −56.97, P < 0.017) were higher in schistosomiasis-eliminated areas with snails than in schistosomiasis transmission-interrupted areas with snails. O. hupensis snails were mainly distributed in paddy fields, dry farmlands and ditches; however, the occurrence of frames with snails (13.40%, 424/3 164) and mean density of living snails [(0.252 8 ± 0.158 7) snails/0.1 m²] were higher in ponds/weirs than in other types of environments (both P values < 0.05). Rice, dry farmland crops and weeds were main vegetations in which O. hupensis snails were distributed, and the occurrence of frames with snails (2.29%, 7 111/310 140) and mean density of living snails [(0.072 3 ± 0.018 9) snails/0.1 m²] were higher in weeds than in other types of environments (both P values < 0.05). Conclusions O. hupensis snails have been effectively controlled in Yunnan Province following implementation of integrated schistosomiasis control measures; however, there are still risk factors for schistosomiasis transmission, including reduced attention to schistosomiasis control and snail re-emergence. Improved control efforts and surveillance system construction and timely identification of risk factors of snail status and timely management are recommended to ensure the achievement of the target of schistosomiasis elimination as scheduled.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Objective The aim of this study is to discuss the causal relationship between periodontal disease(PD)and prostate cancer(PCa).Methods A two-sample bidirectional Mendelian randomization(MR)analysis based on publicly statistical data from genome-wide association studies(GWAS)was conducted.MR Egger,weighted medium,simple mode and weighted mode were supplemented,while inverse variance weighted analysis(IVW)was the main method of analysis.Heterogeneity testing,pleiotropy testing and leave-one-out testing were used to assess the sensitivity and stabili-ty.Results The results of MR analysis showed that PD had no significant impact on the occurrence of PCa:East Asian(IVW,PD:OR=1.07,P=0.48);European(IVW,PD:OR=1.00,P=0.37,periodontitis:OR=1.03,P=0.14,chronic gingivitis:OR=0.99,P=0.37,chronic periodontitis:OR=1.03,P=0.22).The reverse MR analysis also did not show a causal relationship between PCa and PD:East Asian(IVW,PD:OR=0.97,P=0.22);European(IVW,PD:OR=0.84,P=0.44,periodontitis:OR=1.01,P=0.75,chronic gingivitis:OR=0.93,P=0.23,chronic periodontitis:OR=0.99,P=0.80).The results of other analysis were consistent with those of IVW analysis.Conclusions The results of our two-sample bidirectional MR analysis do not support a causal relationship between PD and PCa.

Objective This review aims to investigate the application of eye tracking(ET)in patients with speech impairment in the ICU.The review summarizes the current status and prospects of ET technology applications.Methods Following the scoping reviews framework,a systematic search was conducted across Web of Science,PubMed,Cochrane Library,Embase,CINAHL,CNKI,Wanfang Data,Chinese Medical Database,and Chinese biomedical database.The search covered publications from the inception of each database to October 29th,2024.The included studies were comprehensively analyzed.Results A total of 12 pieces of the literature were included,including 4 prospective cohort studies,4 experimental studies,3 prospective observational studies,and 1 randomized controlled trial.The application population of ET in the ICU mainly includes patients on mechanical ventilation,those at high risk of delirium,patients with spinal cord injury,etc.The types of integrated ET system equipment are mainly head-mounted and fixed;the types of ET involve gaze,blinking,etc.;the functions include standardized scale assessment,free interaction,and eye-movement model recognition.The main outcome indicators of the research are feasibility,physical symptoms and social-psychological status.Conclusion ET is applicable to a specific group of ICU patients with aphasia,and has shown good feasibility and effectiveness in the expression of patients'basic needs,self-assessment of symptoms and improvement of psychosocial status.

Aim To study the protective effect of the silibinin derivative Sil-1 on acute myocardial ischemia in SD rats and its mechanism of action.Methods Af-ter 18 hours of oxygen-glucose deprivation and treat-ment of H9c2 cells,the protective effect of Sil-1 on rat cardiomyocytes was examined.SD rats were treated 30 minutes before surgery,followed by 24 h ligation of the left anterior descending coronary artery.The cardiopro-tective effects of Sil-1 and its mechanisms for improving myocardial ischemic injury were investigated using pro-teomics technology.Results In vitro,compared with the control group,the activity of H9c2 cells in the mod-el group showed reduced cell viability,increased dead cells,elevated ROS and higher levels of LDH and in-flammatory cytokines TNF-α,IL-1β and IL-6 in the culture medium.Sil-1 could improve the above condi-tions to different degrees.In vivo,compared with the control group,rats in the model group showed signifi-cantly higher T waves on electrocardiogram,significant ischemic areas in the heart section,disorganized ar-rangement of cardiomyocytes,increased inflammatory factor infiltration and elevated CK,CK-MB,LDH and inflammatory factors TNF-α,IL-6 and IL-1β.Besides,NF-κB phosphorylation levels in myocardial tissue in-creased.Sil-1 improved the above conditions to varying degrees.The results of proteomics showed that 90 pro-teins were found between the control vs model group and the Sil-1 vs model group,and KEGG enrichment a-nalysis showed that MAPK,chemokines,VEGF and other signaling pathways were abundant.Western blot results showed that Sil-1 blocked the phosphorylation of ERK,JNK and p38 MAPK.Conclusions Sil-1 inhib-its the MAPK pathway by blocking the phosphorylation of JNK,ERK,and p38 MAPK,and achieves a protec-tive effect on rats with acute myocardial infarction.

Objective:To establish a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the determination of N-desalkylquetiapine, hydroxybupropion, N-desmethyl clozapine, N-desmethyl clomipramine, O-desmethyvenlafaxine and dehydro aripiprazole in human plasma.Methods:In June 2023, plasma samples were treated with methanol-acetonitrile (volume ratio of 1∶1) for protein precipitation and then detected by LC-MS/MS. It was separated by C18 column and eluted with 5 mmol/L ammonium acetate water and 5 mmol/L ammonium acetate methanol solution as mobile phase gradient. The metabolites of six psychotropic drugs were qualitatively and quantitatively by using electrospray positive ion multi-reactive ion monitoring scanning mode (MRM) .Results:The linear relationships of six psychotropic drug metabolites were good in the concentration range of 2-100 μg/L. The linear correlation coefficients were 0.9971-0.9999, the limits of quantification of the method were 0.10-6.00 μg/L, and the inter-and intra-day precision were 4.6%-9.8% and 1.5%-8.6%, with the recoveries of the spiked standards ranged from 90.0% to 106.1%.Conclusion:The LC-MS/MS method for the determination of metabolites of six psychotropic drugs in human plasma is simple, rapid and sensitive, and can be used for the qualitative and quantitative determination of metabolites in plasma samples of patients suspected of psychotropic drug poisoning.

Objective:To establish a high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for the fast determination of maduramicin ammonium (MAD) in rat serum.Methods:In February 2024, rat serum samples were selected and directly injected after extraction and purification with methanol: acetonitrile (1: 1), separated on a C18 chromatographic column, and gradient-eluted using 0.1% formic acid aqueous solution -0.1% formic acid methanol solution as the mobile phase. Under optimized instrument conditions, electrospray positive ion multiple reaction monitoring (MRM) mode was employed for quantification using the external standard method, followed by methodological validation of the established approach.Results:The linearity of MAD in serum was good in the concentration range of 0.5-100 μg/L, and the correlation coefficient was 0.9997. The mean recoveries of MAD from spiked samples were 86.0%-109.6%, with the relative standard deviations were less than 10%. The limit of detection was 0.23 μg/L, The limit of detection was 0.75 μg/L.Conclusion:This method is high sensitive and reliable, which is suitable for the determination of MAD in in mouse serum.