ObjectiveTo investigate the anti-Alzheimer's disease （AD） effect of Dipsacus asper（DA） in the Caenorhabditis elegans model， and decipher the underlying mechanism via the peroxisome proliferator-activated receptor α （PPARα）/transcription factor EB （TFEB） pathway. MethodsFirst， transgenic AD C. elegans individuals were assigned into the blank control， model， positive control （WY14643， 20 µmol·L^-1）， and low-， medium-， and high-dose （100， 200， and 400 mg·L^-1， respectively） DA groups. The amyloid β-42 （Aβ₄₂） formation in the muscle cells， the paralysis time， and the deposition of amyloid β-protein （Aβ） in the head were detected. The lysosomal autophagy in the BV2 cell model was examined by Rluc-LC3wt/G120A. The expression levels of lysosomal autophagy-related proteins LC3Ⅱ， LC3I， LAMP2， and TFEB were detected by Western blot. Real-time quantitative polymerase chain reaction （Real-time PCR） was employed to determine the mRNA levels of autophagy-related genes beclin1 and Atg5 and lysosome-related genes LAMP2 and CLN2 downstream of PPARα/TFEB. A reporter gene assay was used to detect the transcriptional activities of PPARα and TFEB. Immunofluorescence was used to detect the fluorescence intensity of PPARα， and the active components of the ethanol extract of DA were identified by UPLC-MS. RCSB PDB， Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， and Autodock were used to analyze the binding between the active components and PPARα-ligand-binding domain （LBD）. ResultsCompared with the model group， the positive control group and 200 and 400 mg·L^-1 DA groups showed prolonged paralysis time （P<0.05）， and all the treatment groups showed decreased Aβ deposition in the head （P<0.01）. DA within the concentration range of 50-500 mg·L^-1 did not affect the viability of BV2 cells. In addition， DA enhanced the autophagy flux （P<0.05）， up-regulated the mRNA levels of beclin1， Atg5， LAMP2， and CLN2 （P<0.05， P<0.01）， promoted the nuclear translocation of TFEB （P<0.05）， increased LAMP2 expression and autophagy flux （P<0.05， P<0.01）， and enhanced the transcriptional activities of PPARα and TFEB （P<0.01）. The positive control group and 200 and 400 mg·L^-1 DA groups showed enhanced fluorescence intensity of PPARα in the BV2 nucleus （P<0.01）. UPLC-MS detected nine known compounds of DA， from which 8 active components of DA were screened out. The docking results suggested that a variety of components in DA could bind to PPARα-LBD and form stable hydrogen bonds. ConclusionDA may reduce the pathological changes in AD by regulating the PPARα-TFEB pathway.

Objective To investigate the status of feeding intolerance in patients with enteral nutrition after lung transplantation and analyze its influencing factors,to provide a reference for formulating a reasonable enteral nutrition plan and improving patients'nutritional status.Methods Convenient sampling method was used to retrospectively collect the clinical data of 115 patients who received enteral nutrition support after lung transplantation and were hospitalized in the ICU of a tertiary hospital in Guangdong Province from August 2022 to November 2023.According to the occurrence of feeding intolerance during ICU hospitalization,the patients were divided into a feeding tolerance group and a feeding intolerance group.Univariate and logistic regression analysis were used to analyze the influencing factors of feeding intolerance patients with enteral nutrition after lung transplantation.Results Within 7 days of initiating enteral nutrition,a total of 63 patients developed feeding intolerance,with an incidence of 54.78％.Among them,the incidence of feeding intolerance was relatively high within 1 to 3 days after initiating enteral feeding.The clinical manifestations of feeding intolerance were diarrhea,bloating,gastric retention,vomiting/regurgitation,among which the diarrhea was the highest incidence(87.30％).Logi-stic regression analysis showed that intraoperative net balance volume(OR=0.999),intraoperative blood transfusion(OR=1.001)volume and diabetes history(OR=0.170)were independent influencing factors for feeding intolerance in patients with enteral nutrition after lung transplantation(P＜0.05).Conclusion There was a high incidence of feed-ing intolerance in patients with enteral nutrition after lung transplantation.Patients undergoing lung transplantation who have a high net intraoperative fluid balance,receive a low volume of intraoperative blood transfusions,and have a history of diabetes are at a lower risk of developing feeding intolerance when receiving postoperative enteral nutrition.When starting enteral nutrition,medical staff should dynamically evaluate the risk factors of feeding intolerance,screen high-risk patients as early as possible,and formulate reasonable enteral nutrition programs to improve the nutritional status of patients and promote their rehabilitation.

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

Objective To investigate the diagnostic value of combined detection of serum secreted frizzled-related protein 5(SFRP5),fibroblast growth factor-21(FGF-21)and kidney injury molecule-1(KIM-1)in di-abetic nephropathy(DN).Methods Patients with DN(n=53)who were treated in Jingnan Medical District,General Hospital of the People's Liberation Army from December 2021 to December 2023 were selected as the study group,and patients with simple diabetes(n=53)were selected as the control group.The levels of ser-um SFRP5,FGF-21 and KIM-1 were detected by enzyme-linked immunosorbent assay.Multivariate Logistic regression analysis was used to analyze the factors affecting the occurrence of DN.The receiver operating char-acteristic(ROC)curve was drawn to analyze the efficacy of serum SFRP5,FGF-21 and KIM-1 levels in the di-agnosis of occurrence of DN.Results Compared with the control group,the levels of fasting blood glucose,u-rine albumin/urine creatinine,urine microalbumin,FGF-21 and KIM-1 in the study group were significantly increased(P<0.05),while the levels of glomerular filtration rate and SFRP5 were significantly decreased(P<0.05).The area under the curve(AUC)of serum SFRP5,FGF-21 and KIM-1 in the diagnosis of occur-rence of DN was 0.977,which was larger than that of each index alone(Zthree combination-SFRP5=2.759,P=0.006,Zthree combination-FGF-21=2.936,P=0.003,Zthree combination-KIM-1=3.104,P=0.002).The sensitivity of combined diagno-sis was 96.23%,the specificity was 88.68%,and the Youden index was 0.849.SFRP5,FGF-21,KIM-1,fast-ing blood glucose,glomerular filtration rate,urine albumin/urine creatinine,urine microalbumin were the in-fluencing factors of occurrence of DN(P<0.05).Conclusion The serum SFRP5 level is decreased and FGF-21 and KIM-1 levels are increased in DN patients.The combination of the three has the best diagnostic effi-ciency for occurrence of DN.

Objective To investigate the status of feeding intolerance in patients with enteral nutrition after lung transplantation and analyze its influencing factors,to provide a reference for formulating a reasonable enteral nutrition plan and improving patients'nutritional status.Methods Convenient sampling method was used to retrospectively collect the clinical data of 115 patients who received enteral nutrition support after lung transplantation and were hospitalized in the ICU of a tertiary hospital in Guangdong Province from August 2022 to November 2023.According to the occurrence of feeding intolerance during ICU hospitalization,the patients were divided into a feeding tolerance group and a feeding intolerance group.Univariate and logistic regression analysis were used to analyze the influencing factors of feeding intolerance patients with enteral nutrition after lung transplantation.Results Within 7 days of initiating enteral nutrition,a total of 63 patients developed feeding intolerance,with an incidence of 54.78％.Among them,the incidence of feeding intolerance was relatively high within 1 to 3 days after initiating enteral feeding.The clinical manifestations of feeding intolerance were diarrhea,bloating,gastric retention,vomiting/regurgitation,among which the diarrhea was the highest incidence(87.30％).Logi-stic regression analysis showed that intraoperative net balance volume(OR=0.999),intraoperative blood transfusion(OR=1.001)volume and diabetes history(OR=0.170)were independent influencing factors for feeding intolerance in patients with enteral nutrition after lung transplantation(P＜0.05).Conclusion There was a high incidence of feed-ing intolerance in patients with enteral nutrition after lung transplantation.Patients undergoing lung transplantation who have a high net intraoperative fluid balance,receive a low volume of intraoperative blood transfusions,and have a history of diabetes are at a lower risk of developing feeding intolerance when receiving postoperative enteral nutrition.When starting enteral nutrition,medical staff should dynamically evaluate the risk factors of feeding intolerance,screen high-risk patients as early as possible,and formulate reasonable enteral nutrition programs to improve the nutritional status of patients and promote their rehabilitation.

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia features effectively under limited abnormal sample supervision is an urgent issue to address. This paper proposed an arrhythmia classification algorithm based on an adaptive multi-feature fusion network. The algorithm extracted RR interval features from ECG signals, employed one-dimensional convolutional neural network (1D-CNN) to extract time-domain deep features, employed Mel frequency cepstral coefficients (MFCC) and two-dimensional convolutional neural network (2D-CNN) to extract frequency-domain deep features. The features were fused using adaptive weighting strategy for arrhythmia classification. The paper used the arrhythmia database jointly developed by the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH) and evaluated the algorithm under the inter-patient paradigm. Experimental results demonstrated that the proposed algorithm achieved an average precision of 75.2%, an average recall of 70.1% and an average F ₁-score of 71.3%, demonstrating high classification accuracy and being able to provide algorithmic support for arrhythmia classification in wearable devices.
Humans ; Arrhythmias, Cardiac/diagnosis* ; Algorithms ; Electrocardiography/methods* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Deep Learning ; Classification Algorithms

Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.