This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Objective:To observe the effect of auricular pressure beans(APN)combined with Compound Tung-Leaf Burn Oil(CTBO)on perioperative anxiety and pain in patients undergoing circumcision.Methods:This study included 100 patients undergo-ing circumcision with the disposable circumcision anastomosis stapler in our hospital from August 2023 to November 2023,of whom 50 received routine circumcision nursing care(the control group)and other 50 APN combined with compound CTBO in addition(the ob-servation group).We compared between the two groups the anxiety scores before any intervention,30 minutes before and 24 hours and 10 days after operation,the pain scores 24 hours postoperatively and at the first change of wound dressing,the frequency of 3-day post-operative sleep awakenings,the incidence of complications,and the satisfaction of the patients.Results:Totally,94 patients com-pleted the study,46 in the observation and 48 in the control group.The anxiety scores exhibited no statistically significant difference between the two groups of patients before any intervention(P>0.05),but were markedly lower in the observation than in the control group at 30 minutes before and 24 hours and 10 days after surgery(P<0.05),and so were the pain scores24 hours after surgery and at the first change of wound dressing(P<0.05),and the frequency of 3-day postoperative sleep awakenings(P<0.05).The satis-faction rate of the patients was remarkably higher(P<0.05)while the incidence of complications significantly lower in the observation group than in the control(P<0.05).Conclusion:Auricular pressure beans combined with Compound Tung-Leaf Burn Oil can ef-fectively alleviate perioperative anxiety,reduce postoperative pain and improve satisfaction of the patients undergoing circumcision.

Pulmonary disease is one of the major threats to human health. However, the current clinical treatment drugs for lung diseases generally have problems such as low lung delivery efficiency, fast clearance rate and obvious toxic side effects. Recently, membrane biomimetic nanocarriers have attracted more and more attention. Due to their advantages of high targeting, long cycle time, good biocompatibility and strong immune escape ability, membrane biomimetic nanocarriers have become a major research hotspot in targeted therapy of lung diseases. In this review, we discuss the main preparation methods of membrane biomimetic nanoparticles, the characteristics of membrane biomimetic nanocarriers from different cell sources and their application in the targeted therapy of lung diseases. At the same time, according to the characteristics of different membranes, the shortcomings, current technical limitations and future prospects are discussed. This review is expected to provide references for the design of membrane biomimetic nanocarriers and their potential applications in the treatment of lung diseases.

Objective:This study aims to explore the synergistic effects of DIP and other medical insurance supply-side policies.Method:City A that has piloted DIP reform was set as the treatment group,and City B without reform was set as the control group.A total of 1 120 public medical institution samples from 2019 to 2022 were collected.The total medical expenses during hospitalization and some structural expenses were analyzed using DID method.Result:DIP had a significant inhibitory effect on the medical expenses,and the expenses of checkups and examinations during hospitalization in city A,but had no impact on the drug and the material expenses during hospitalization.Conclusion:DIP played a significant cost control role and effectively controlled the total medical expenses during hospitalization.The synergistic effects of price adjustment of medical services policy and national centralized drug/material procurement policy on cost control were insufficient.DIP synergized with other supply-side policies to promote rational medical cost structure.It is suggested that medical insurance departments should focus on the synergistic effects of medical insurance supply-side policies to jointly improve the efficiency of medical insurance fund utilization.

Objective To study the changes in serum homocysteine (Hcy) and matrix metalloproteinase-9 (MMP-9) levels and risk factors in patients with coronary heart disease (CHD) complicated with Helicobacter pylori (HP) infection in Chengdu area, and to provide a theoretical basis for the prevention of HP infection in patients with coronary heart disease. Methods A total of 348 CHD patients admitted to our hospital in Chengdu from 2019 to 2021 were selected. Hp infection status was detected by C¹⁴ urea breath test. Patients were classified into control group (n=197) and HP infection group (n=151) according to the detection results. Data including gender, age, body mass index and peptic ulcer history were collected, and univariate analysis and logistic regression were used to screen the risk factors affecting the occurrence of HP infection in patients with CHD. Results The prevalence rate of HP infection was 43.39% (151/348) among the selected CHD patients. Serum levels of Hcy and MMP-9 were notably elevated in HP infection group compared with control group (P<0.05). The proportion of patients with age ≥60 years old, hyperlipidemia, proton pump inhibitor use history, and frequent consumption of out-of-home food and spicy food in HP infection group was obviously larger than that in control group (P<0.05). Hyperlipidemia (OR=3.719), history of proton pump inhibitor use (OR=3.254) and frequent consumption of out-of-home food (OR=2.721) were independent risk factors for HP infection in CHD patients (P<0.05). Conclusion CHD patients in Chengdu suffer a prevalence rate of HP infection, and have elevated levels of serum Hcy and MMP-9. Furthermore, the intervention measures for patients with hyperlipidemia, proton pump inhibitor drug use history and frequent consumption of out-of-home food are of vital importance for decreasing the risk of HP infection.