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 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.

Objective To investigate the levels of gross α and gross β activities in different water types within a 40-kilometer radius around the Zhangzhou Nuclear Power Plant prior to its operation. Methods In 2018, drinking water samples were collected from the area surrounding the nuclear power plant during both the wet and dry seasons, including source water, treated water, tap water, and well water. The gross α and gross β activity concentrations were measured using a low-background α/β counter, followed by statistical analysis. Results A total of 80 water samples from different sources around the Zhangzhou Nuclear Power Plant were collected. The average gross α and gross β activity concentrations during the wet season were (0.110 ± 0.036) Bq/L and (0.643 ± 0.028) Bq/L, respectively, while those during the dry season were (0.124 ± 0.032) Bq/L and (0.624 ± 0.026) Bq/L, respectively. There were no significant differences in the gross α and gross β activity concentrations between the wet and dry seasons for the overall sample set (P > 0.05). However, there were statistically significant differences in the gross α and gross β activity concentrations between the wet and dry seasons for source water and well water (Z_wet = −2.005, −2.123; Z_dry = −1.943, −3.090; P < 0.05). Conclusion The radioactivity levels in different water types within various ranges around the Zhangzhou Nuclear Power Plant before its operation were determined. The measured activity concentrations were at the same level as those from previous investigations in other regions of Fujian Province.

BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is the predominant form of chronic liver disease worldwide. This study was designed to investigate the proportion and characteristics of MAFLD within the general Chinese population and to identify the contributory risk factors for liver fibrosis among MAFLD individuals. METHODS: The participants were recruited from a cohort undergoing routine health evaluations at the Third Hospital of Hebei Medical University between May 2019 and March 2023. The diagnosis of MAFLD was based on the established clinical practice guidelines. The fibrosis-4 index score (FIB-4) was employed to evaluate hepatic fibrosis, with a FIB-4 score of ≥1.3 indicating significant fibrosis. Binary logistic regression analyses were used to determine risk factors associated with significant hepatic fibrosis in MAFLD. RESULTS: A total of 22,970 participants who underwent comprehensive medical examinations were included in the analysis. The overall proportion of MAFLD was 28.77% (6608/22,970), with 16.87% (1115/6608) of these patients showing significant fibrosis as assessed using FIB-4. Independent risk factors for significant liver fibrosis in MAFLD patients were male (odds ratio [OR] = 0.676, 95% confidence interval [CI]: 0.558-0.821), hepatitis B surface antigen (HBsAg) positivity (OR = 2.611, 95% CI: 1.557-4.379), body mass index ≥23.00 kg/m 2 (OR = 0.632, 95% CI: 0.470-0.851), blood pressure ≥130/85 mmHg (OR = 1.885, 95% CI: 1.564-2.272), and plasma glucose ≥5.6 mmol/L (OR = 1.815, 95% CI: 1.507-2.186) (all P <0.001). CONCLUSIONS The proportion of MAFLD in an urban Chinese population is 28.77%. About 16.87% of MAFLD patients presented with significant liver fibrosis. Independent risk factors for significant liver fibrosis in MAFLD patients should be noticed.
Humans ; Male ; Female ; Liver Cirrhosis/pathology* ; Middle Aged ; Risk Factors ; Adult ; Fatty Liver/pathology* ; Aged ; China/epidemiology* ; Logistic Models ; Urban Population ; East Asian People

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

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*

Objective To investigate the radioactivity levels of gross α and gross β in foods around Zhangzhou nuclear power plant, China before operation. Methods Forty-nine samples from 33 kinds of foods in 5 categories of daily food around Zhangzhou nuclear power plant were collected, pretreated, dried, and ashed. The radioactivity levels of gross α and gross β were measured by the low-background α and β measuring instrument. The atomic absorption technique was employed to measure the level of potassium (K), and the radioactivity level of gross β (subtracting ⁴⁰K) was calculated with K concentrations in different foods consulted from the nutritional dietary system. Results The radioactivity levels of gross α in vegetables and fruits, grain, poultry and livestock, aquatic products, and tea around Zhangzhou nuclear power plant were < minimum detectable level (MDL)-7.97, < MDL-6.82, < MDL, < MDL-20.76, and 11.90-23.08 Bq/kg, respectively; the radioactivity levels of gross β were 34.56-122.81, 13.05-188.96, 56.00-108.34, 17.86-169.01, and 123.74-171.63 Bq/kg, respectively; the radioactivity levels of gross β (subtracting ⁴⁰K) were not detected (ND)-14.27, ND-27.86, ND-48.72, ND-45.85, and 6.69-13.79 Bq/kg, respectively. Conclusion The radioactivity of gross α and gross β in foods around Zhangzhou nuclear power plant before operation is basically at the same level as that in other areas of China.

BACKGROUND:Pulsed electromagnetic fields,as an important physical therapy,are exactly effective in the treatment of osteoarthritis,but the mechanism has not been fully clarified. OBJECTIVE:To observe the effect of pulsed electromagnetic field on the degeneration of knee joint cartilage in aged rats. METHODS:Eight 6-month-old Sprague-Dawley rats were selected as the young group and were subjected to normal diet with no treatment.Sixteen 22-month-old Sprague-Dawley rats were randomly divided into old group(n=8)and pulsed electromagnetic field group(n=8).The rats in the pulsed electromagnetic field group were subjected to a pulsed electromagnetic field intervention,once a day,5 days per week for continuous 8 weeks.The rats in the old group were given no treatment.All rats were anesthetized and executed after 8 weeks for the detection of relevant indexes. RESULTS AND CONCLUSION:Compared with the young group,serum type Ⅱ collagen C-terminal peptide level was increased in the old group(P<0.05);compared with the old group,serum type Ⅱ collagen C-terminal peptide level was decreased in the pulsed electromagnetic field group(P<0.05).Micro-CT showed that the bone volume fraction,bone mineral density,and number of bone trabeculae decreased(P<0.05)and the trabecular separation increased(P<0.05)in the tibia of rats in the aged group compared with the young group;and the bone volume fraction,bone density,and number of trabeculae increased(P<0.05)and the trabecular separation decreased(P<0.05)in the tibia of rats in the pulsed electromagnetic field group compared with the aged group.The tibial plateau Safranin O-fast green staining showed that the articular cartilage structure of rats in the aged group was disorganized,and the number of chondrocytes was obviously reduced,and the tidal line could not be distinguished.The above results were improved in the pulsed electromagnetic field group.RT-qPCR and western blot assay showed that the mRNA and protein expression levels of matrix metalloproteinase 1,matrix metalloproteinase 13,P53 and P21 in the articular cartilage and subchondral bone of rats were elevated in the aged group compared with the young group(P<0.05)and decreased in the pulsed electromagnetic field group compared with the old group(P<0.05).To conclude,pulsed electromagnetic fields may improve osteoarthritis in aged rats by inhibiting chondrocyte senescence,alleviating articular cartilage degradation and inhibiting subchondral bone osteoporosis through suppressing the expression of P53/P21.