ObjectiveHistorically documented Zhejiang Atractylodis Macrocephalae Rhizoma（Baizhu） possesses premium characteristics such as phoenix-like head and crane-like neck， pronounced sweetness， and fragrant aroma. However， its current market circulation is low， and the processed products with Zhejiang-style characteristics are at the risk of being lost. This study aims to preserve the ancient Zhejiang-style processing techniques and evaluate them using modern scientific methods. MethodsMultidimensional intelligent sensory evaluation was used to digitally characterize the "quality-structure" of the external appearance of nine-steamed and nine-processed Baizhu medicinal materials（intermediate processed products） and the "odor-taste" of the internal quality of its decoction pieces（slices）， and the appearance parameters were digitally characterized by colorimeter， texture analyzer， electronic nose and electronic tongue， the chemical composition was analyzed via ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）. Then， cluster analysis on the differences in odor between the medicinal materials（intermediate processed products） and decoction pieces（slices） of nine-steamed and nine-processed Baizhu was conducted， as well as the differences in taste between water-soluble and alcohol-soluble extracts of the decoction pieces（slices）， and the correlation analysis of chroma value-alcohol-soluble extract content-component response value. ResultsThe nine-steamed and nine-processed Baizhu had a dark brown to black epidermis， a brownish-yellow to brownish-gray cross-section， a slightly tough texture， a faint odor， and a slightly sweet， bitter and pungent taste. Texture analyzer measurements revealed minimal adhesion and maximum recovery in the middle section of the characteristic processed Baizhu， consistent with the processing endpoint of thorough steaming and cooking. The head section showed the highest internal hardness， elasticity and chewiness， indicating a denser texture in this area. The electronic nose sensor could clearly distinguish the difference between the medicinal materials and its decoction pieces， with a more significant clustering effect at 60 ℃ for 30 minutes compared to ambient temperature headspace for 2 hours， highlighting the significant impact of the baking degree before slicing on the quality. The electronic tongue taste signal map clearly distinguished the differences between water-soluble and alcohol-soluble extracts of nine-steamed and nine-processed Baizhu decoction pieces， and the addition of auxiliary materials during processing could enhance its alcohol-soluble extract content. A total of 82 chemical components were identified in the characteristic processed Baizhu. After processing， the contents of 58 components increased， while 24 components decreased. Correlation analysis revealed significant negative correlations（P<0.01） between ethanol-soluble extract content and colorimetric values of brightness（L^*）， yellow-bule value（b^*）， and total color difference（E^*_ab）. E^*_ab showed marked negative correlations（P<0.05） with the response values of isochlorogenic acid A and C. ConclusionThis study establishes a modern intelligent sensory evaluation model for multidimensional holographic characterization of nine-steamed and nine-processed Baizhu， clarifying the correlation between increased isochlorogenic acid content and the visual color appearance after different steaming cycles， as well as its intrinsic alcohol-soluble extracts. This provides a reference for quality evaluation and processing standards of the Zhejiang-style characteristic processed products.

Despite therapy with potent antiviral agents, chronic hepatitis B (CHB) patients remain at high risk of hepatocellular carcinoma (HCC). While metabolites have been rediscovered as active drivers of biological processes including carcinogenesis, the specific metabolites modulating HCC risk in CHB patients are largely unknown. Here, we demonstrate that baseline plasma from CHB patients who later developed HCC during follow-up exhibits growth-promoting properties in a case-control design nested within a large-scale, prospective cohort. Metabolomics analysis reveals a reduction in long-chain acylcarnitines (LCACs) in the baseline plasma of patients with HCC development. LCACs preferentially inhibit the proliferation of HCC cells in vitro at a physiological concentration and prevent the occurrence of HCC in vivo without hepatorenal toxicity. Uptake and metabolism of circulating LCACs increase the intracellular level of acetyl coenzyme A, which upregulates histone H3 Lys14 acetylation at the promoter region of KLF6 gene and thereby activates KLF6/p21 pathway. Indeed, blocking LCAC metabolism attenuates the difference in KLF6/p21 expression induced by baseline plasma of HCC/non-HCC patients. The deficiency of circulating LCACs represents a driver of HCC in CHB patients with viral control. These insights provide a promising direction for developing therapeutic strategies to reduce HCC risk further in the antiviral era.

The interest in covalent drugs has resurged in recent decades, spurring the development of numerous specialized computational docking tools to facilitate covalent ligand design and screening. Herein, we present CarsiDock-Cov, a new paradigm distinguishing itself as the first deep learning (DL)-guided approach for covalent docking. CarsiDock-Cov retains the core components of its non-covalent predecessor, leveraging a DL model pretrained on millions of docking complexes to predict protein-ligand distance matrices, along with a dedicated-designed geometric optimization procedure to convert these distances into refined binding poses. Additionally, it incorporates several key enhancements specifically tailored to optimize the protocol for covalent docking applications. Our approach has been extensively validated on multiple public datasets regarding the docking and screening of covalent ligands, and the results indicate that our approach not only achieves comparably improved applicability compared to its non-covalent predecessor, but also exhibits competitive performance against various state-of-the-art covalent docking tools. Collectively, our approach represents a significant advance in covalent docking methodology, offering an automated and efficient solution that shows considerable promise for accelerating covalent drug discovery and design.

Strengthening the construction of platforms,talents,and disciplines is a crucial strategy to enhance the core competitiveness and promote the high-quality development of national regional medical centers.It outlines the theoretical framework and implementation path for building the"Platform-Talent(Team)-Discipline"develop-ment system during the establishment of the National Regional Medical Center at Henan Children's Hospital Zheng-zhou Children's Hospital.By creating a collaborative innovation platform integrating medical services,education,and research,implementing talent development programs,optimizing mechanisms for talent recruitment,cultivation,and retention,and advancing discipline development projects,the center has achieved significant progress in its core competencies.This exploration provides valuable insights and references for the development of national regional medical centers and the high-quality growth of public hospitals.

Hereditary hemorrhagic telangiectasia (HHT) is a rare autosomal dominant genetic disease characterized by hemorrhage and arteriovenous malformations of the lungs, liver, and nervous system caused by telangiectasias. Here we report an elderly female patient with constipation, fatigue and anemia admitted to the characteristic medical center of the Chinese People's Armed Police Force. Imaging findings showed pulmonary vascular malformations, formation of multiple venous fistulas, liver arteriovenous malformations, splenic varicose veins, gastrointestinal telangiectasias, iron deficiency anemia, and multiple organ involvement, which were very rare in HHT patients.

OBJECTIVE To standardize the strategies for prevention and control of Chikungunya(CHIK)in healthcare in-stitutions so as to reduce the risk of transmission in the institutions.METHODS A working group comprising the ex-perts in hospital infection control,infectious diseases,and microbiology systematically reviewed domestic and international evidence and current guidelines,integrated China's vector ecology and healthcare realities,conducted two rounds of Delphi to achieve expert consensus,and graded the evidence and recommendation strength using the Oxford Centre for Evidence Based Medicine system.RESULTS The consensus issues 18 actionable recommendations on triage,patient mosquito-proof isolation,integrated vector control,protection of susceptible populations,environmental cleaning and disinfection,specimen management,medical textile handling,and outbreak emergency response,with each statement assigned an evi-dence level and recommendation strength.CONCLUSION This consensus is for the first time in China to provide evidence-graded strategies for control of CHIK in healthcare institutions,offering work flow-oriented,implementable guidance for clinicians,laboratorians,and infection-control personnel under different risk scenarios and enhancing the comprehensive coping capacity of the healthcare institutions.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

OBJECTIVE To analyze the biological characteristics and genomic features of highly lytic bacteriopha-ges isolated from sewage in tropical hospitals and provide references for the hospital-associated infection prevention and control of multidrug-resistant Acinetobacter baumannii(MDR-Ab).METHODS With MDR-Ab as the host bacterium,bacteriophages were isolated from sewage.Transmission electron microscopy was employed to observe their morphology,and determine the optimal multiplicity of infection(MOI),one-step growth curve and environ-mental stability.Whole-genome sequencing and bioinformatics analysis were conducted to annotate functional genes and construct a phylogenetic tree.RESULTS A virulent bacteriophage,HN_Aba_01,was isolated.Elec-tron microscopy revealed that it belonged to the Myoviridae family,with a head diameter of 50 nm and a tail length of 90 nm.This bacteriophage exhibited strong lytic activity,with an optimal MOI of 0.000 000 1,a latent period of 5 minutes and a lysis yield of 15 PFU/cell.It remained stable at temperatures ranging from 4 ℃ to 60 ℃and pH values from 3 to 10.Genomic analysis identified 85 ORFs,including lyase,perforin and depolymerase genes.It shared 98.12％identity with the bacteriophage AbP2 genome(reference genome)and was classified into the Obolenskvirus genus.CONCLUSIONS The bacteriophage isolated from tropical hospital sewage,with high lyt-ic activity and good environmental adaptability,can be used for the hospital-associated infection prevention and control of MDR-Ab.

Objective:To explore the demographic composition of type 2 diabetes mellitus (T2DM) with metabolic associated fatty liver disease (MAFLD) and the role of energy metabolism in the progression of MAFLD in order to provide theoretical support for improving the prognosis of MAFLD.Methods:A cross-sectional study was conducted. Ninety-four cases with T2DM combined with MAFLD admitted to the Endocrinology Department of Tianjin Third Central Hospital from July 2014 to July 2019 were selected. Patients were divided into three groups: non-metabolic associated steatohepatitis (MASH) group (25 cases), borderline MASH group (49 cases), and MASH group (20 cases) according to the non-alcoholic fatty liver disease activity score (NAS). Patients were further divided into two groups: non/mild fibrosis (F0-1) group (74 cases) and the significant fibrosis (F2-4) group (20 cases) in accordance with liver fibrosis scores. The differences in general clinical and biochemical indicators, body composition, and energy metabolism indicators among the groups were compared. Binary logistic regression analysis was conducted to explore factors affecting liver inflammation and fibrosis severity degree in patients with MAFLD.Results:The visceral fat area (VFA) and body fat percentage (PBF) were significantly higher in the MASH group than in the non-MASH group ( P<0.05), while the skeletal muscle mass index and body mass index (SMI-BMI) were significantly lower in the MASH group than in the marginal MASH group ( P<0.05) during the comparison of body composition and substrate metabolism at different stages of MASH. Alanine aminotransferase (ALT) and homeostasis model assessment of insulin resistance (HOMA-IR) were significantly higher in the fibrotic group than in those in the no/mild fibrosis group ( P<0.05) when comparing clinical and biochemical indicators, body composition, and substrate metabolism at different stages of fibrosis. The skeletal muscle mass (SMM), SMI-BMI, SMM-Weight, resting energy expenditure (REE), and fat oxidation rate (FAT OXR) were significantly lower in the fibrotic group than those in the no/mild fibrosis group ( P<0.05). The respiratory quotient and carbohydrate functional ratio (%CHO) were significantly higher in the fibrotic group than in the no/mild fibrosis group ( P<0.05). Correlation analysis indicated a positive correlation between the NAS score, reflecting the severity of liver inflammatory lesions, with VFA and PBF ( r=0.258 and 0.323, P<0.05); while the F score was positively correlated with the respiratory quotient, %CHO, and VFA ( r=0.292, 0.303, and 0.239, P<0.05), and negatively correlated with REE, the energy ratio from fat, FAT OXR, SMM, SMI-Weight, and SMI-BMI ( r=-0.209, -0.214, -0.333, -0.240, -0.250, and -0.305, P<0.05). Logistic regression analysis indicated that SMI-Weight and FAT OXR were independent factors affecting the progression of liver fibrosis. Conclusion:The reduction of skeletal muscle, particularly because of energy metabolism, is a factor affecting the progression of fibrosis in MAFLD.

Occupational noise-induced hearing loss (NIHL) is an irreversible sensorineural hearing loss that severely endangers workers’ health, making early screening crucial. This article reviewed the research progress on early screening methods for occupational NIHL, introduced the testing mechanisms of three core screening methods—tympanometry, otoacoustic emissions, and extended high-frequency audiometry —and summarized their clinical application advantages and limitations. It is proposed that multimodal combined detection (e.g., the combination of tympanometry, otoacoustic emissions, and extended high-frequency audiometry) can significantly improve the accuracy and comprehensiveness of early screening. Meanwhile, future studies with prospective cohort design are encouraged to verify the long-term monitoring value of each method and to strengthen the joint development of screening technologies with cutting-edge approaches such as machine learning, in order to further improve screening efficiency and provide stronger protection for workers’ hearing health.