ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

Objective To evaluate the in vitro effect of combinations of 5 β-lactam antibiotics with different β-lac-tamase inhibitors on the activity of multidrug-resistant Mycobacterium tuberculosis(MDR-TB),and identify the most effective combination of β-lactam antibiotics and β-lactamase inhibitors against MDR-TB.Methods MDR-TB strains collected in Henan Province Antimicrobial Resistance Surveillance Project in 2021 were selected.The mini-mum inhibitory concentrations(MIC)of 5 β-lactam antibiotics or combinations with different β-lactamase inhibitors on clinically isolated MDR-TB strains were measured by MIC detection method,and the blaC mutation of the strains was analyzed by polymerase chain reaction(PCR)and DNA sequencing.Results A total of 105 strains of MDR-TB were included in the analysis.MIC detection results showed that doripenem had the highest antibacterial activity against MDR-TB,with a MIC50 of 16 μg/mL.MIC values of most β-lactam antibiotics decreased significantly after combined with β-lactamase inhibitors.A total of 13.33％(n=14)strains had mutations in blaC gene,mainly 3 nu-cleotide substitution mutations,namely AGT333AGG,AAC638ACC and ATC786ATT.BlaC proteins Ser111 Arg and Asn213Thr enhanced the synergistic effect of clavulanic acid/sulbactam and meropenem on MDR-TB compared with synonymous single-nucleotide mutation.Conclusion The combination of doripenem and sulbactam has the strongest antibacterial activity against MDR-TB.Substitution mutations of BlaC protein Ser111 Arg and Asn213Thr enhances the sensitivity of MDR-TB to meropenem through the synergy with clavulanic acid/sulbactam.

Objective:In order to construct a multisectoral cooperation evaluation index system for chronic disease prevention and control in the Healthy China strategy,so as to provide a reference for the evaluation and improvement of multisectoral cooperation work.Methods:The initial indicator system was constructed based on D'Amour's cooperative structure model.Fifteen public health experts were selected to refine the evaluation indicators through two rounds of expert consultation using the Delphi method.Then weights of indicators were assigned according to AHP.Results:Experts'positive coefficient,level of authority and coordination of opinions were confirmed.The finalized evaluation index system for multisectoral cooperation in chronic disease prevention and control contains 5 first-level indicators,12 second-level indicators and 34 third-level indicators.According to the weight,the indicators in first level were Shared Goals and Vision(0.222 8),Internalization(0.158 7),Formalization(0.252 3),Governance(0.154 5)and Cooperation effects(0.211 8).Conclusions:The evaluation index system applicable to multisectoral cooperation in the prevention and control of chronic diseases in counties(cities/districts)is preliminarily established,which is highly scientific and operable,and lays the foundation for the next step of application and promotion.

Aim To investigate the regulatory role and mechanism of resveratrol in inhibiting autophagy and promoting apoptosis in choroidal melanoma cells. Methods Choroidal melanoma cells (MUM2B) were divided into control and experimental groups, and treated with different concentrations of resveratrol (0, 10, 20,40,60,80 μmol ·L

Objective     To construct a radiomics model for identifying clinical high-risk carotid plaques. Methods     A retrospective analysis was conducted on patients with carotid artery stenosis in China-Japan Friendship Hospital from December 2016 to June 2022. The patients were classified as a clinical high-risk carotid plaque group and a clinical low-risk carotid plaque group according to the occurrence of stroke, transient ischemic attack and other cerebrovascular clinical symptoms within six months. Six machine learning models including eXtreme Gradient Boosting, support vector machine, Gaussian Naive Bayesian, logical regression, K-nearest neighbors and artificial neural network were established. We also constructed a joint predictive model combined with logistic regression analysis of clinical risk factors. Results    Finally 652 patients were collected, including 427 males and 225 females, with an average age of 68.2 years. The results showed that the prediction ability of eXtreme Gradient Boosting was the best among the six machine learning models, and the area under the curve (AUC) in validation dataset was 0.751. At the same time, the AUC of eXtreme Gradient Boosting joint prediction model established by clinical data and carotid artery imaging data validation dataset was 0.823. Conclusion     Radiomics features combined with clinical feature model can effectively identify clinical high-risk carotid plaques.

Important forensic diagnostic indicators of sudden death in coronary atherosclerotic heart dis-ease,such as acute or chronic myocardial ischemic changes,sometimes make it difficult to locate the ischemic site due to the short death process,the lack of tissue reaction time.In some cases,the de-ceased died of sudden death on the first-episode,resulting in difficulty for medical examiners to make an accurate diagnosis.However,clinical studies on coronary instability plaque revealed the key role of coronary spasm and thrombosis caused by their lesions in sudden coronary death process.This paper mainly summarizes the pathological characteristics of unstable coronary plaque based on clinical medi-cal research,including plaque rupture,plaque erosion and calcified nodules,as well as the influencing factors leading to plaque instability,and briefly describes the research progress and technique of the atherosclerotic plaques,in order to improve the study on the mechanism of sudden coronary death and improve the accuracy of the forensic diagnosis of sudden coronary death by diagnosing different patho-logic states of coronary atherosclerotic plaques.

italic>Lamiophlomis rotata is an important medicinal plant species endemic to the Tibetan Plateau, which is prone to strong climate change impacts on its habitable range due to the high sensitivity of the Tibetan Plateau to climate change. Accurate quantification of species vulnerability to climate change is essential for assessing species extinction risk and developing effective conservation strategies. Therefore, we carried out the α-shape analysis to determine the habitat of L. rotata. We then carried out the climate-niche factor analysis (CNFA) to assess the vulnerability of L. rotata to climate change based on five climate variables (i.e., mean diurnal range, temperature seasonality, mean temperature of warmest quarter, precipitation of driest month and precipitation of warmest quarter) in the context of two shared socioeconomic pathways (i.e., SSP126 and SSP585) and three global climate models (CMCC-ESM2: Centro Euro-Mediterraneo sui Cambiamenti Climatici-Earth System Model version 2; HadGEM3-GC31-LL: Hadley Global Environment Model version 3-Global Coupled configuration 3.1; IPSL-CM6A-LR: Institut Pierre Simon Laplace-Climate Model version 6) during two different periods (2041-2060 and 2081-2100). The vulnerability of L. rotata to climate change was calculated by integrating the sensitivity and exposure indices of L. rotata to five climate variables. The results showed that L. rotata had the highest vulnerability to the precipitation of warmest quarter. Its vulnerability within its habitat range generally showed a spatial pattern of high value in the southern region and low in the northern region, high in the western region and low in the eastern region. In general, the vulnerability of L. rotata under the SSP585 scenario was higher than that under the SSP126 scenario. The climate data of different global climate models have some influence on the results, while the resulted uncertainty can be reduced by data integration methods. As a result of climate change, the pressure on the survival of L. rotata in the future will be intensified in the low-altitude areas such as the Yarlung Zangbo River, Yigongzangbu River, Zayu River, and Jiaomuzu River, etc., while the highly weathered scree flats or stony alpine meadows in the high-altitude zones, such as the eastern Tanggula Mountain Range, the northern part of Hengduan Mountain Range, and the western part of the Qinling Mountains, may become its refuge. It is necessary to focus on and strengthen the protection and management of L. rotata resources in these vulnerble and critical areas.

AIM To study the flavonoids from the leaves of Cinnamomum camphora(L.)Presl.and their antioxidant activities.METHODS The 95％ethanol extraction from the leaves of C.camphora was isolated and purified by liquid-liquid extraction,macroporous adsorption resin chromatography,HW-40C gel column chromatography,molecular exclusion chromatography and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH method.RESULT Ten flavonoids were isolated and identified as(2R,3S)-7-methoxy-5-O-β-D-glucopyranosyl-afzelechin(1),quercetin-3-O-sambubioside(2),quercetin-3-O-β-D-apiosyl-(1→2)-β-D-glucoside(3),quercetin-3-O-robibioside(4),kaempferol-3-O-β-D-rutinoside-7-O-β-D-glucoside(5),kaempferol-3-O-α-L-rhamnoside-7-O-β-D-glucoside(6),5,3'-di-O-methyl-epicatechin(7)、cinchonain Ⅱb(8)、quercetin-3,4'-di-O-β-D-glucoside(9)、(-)-epicatechin(10).The IC50 value of compound 8 scavenging DPPH free radical was 4.8 μg/mL.CONCLUSION Compound 1 is a new compound,and compound 2-6 are obtained from Cinnamomum genus for the first time,compound 7-9 are first isolated from this plant.Compound 8 shows good antioxidant activities..