Based on the etiology and clinical diagnostic criteria of type 2 diabetes mellitus （T2DM）， identification and typing of treatment from the perspective of traditional Chinese and western medicine， the criteria for evaluating the clinical compatibility of traditional Chinese and western medicine in animal models of T2DM were set up. The literature was reviewed to sort out and analyze the existing commonly used modeling methods， summarize the mechanism， compare the advantages and disadvantages， and calculate the consistency between the animal model and the clinical symptoms， syndromes， and indicators from the perspective of traditional Chinese and western medicine. The authors found that spontaneous animal models and high-fat diets combined with multiple low-dose streptozotocin （STZ） induction models were more in line with modern medical pathogenesis of T2DM. However， it fails to form some special syndromes required for traditional Chinese medicine （TCM） research. In addition， there are many methods of combining the etiology and pathogenesis of TCM， which can be divided into three categories： intervention carried out by drug administration， behavioral stimulation， or environmental changes according to TCM， or use of hormones according to clinical evidence and combination of the two methods mentioned above. All of them can successfully establish different types of animal models. However， different methods of establishing syndrome models have their own advantages and disadvantages， and there is no unified standard for the stability and evaluation of syndrome models. As for the clinical consistency criteria of traditional Chinese and western medicine established in this paper， the animal model with 100% consistency has not been calculated due to the conditions of incomplete symptoms and syndromes described in the studies and different selection indicators. Consequently， the establishment of a simple， easy-to-use， and affordable T2DM animal model with both traditional Chinese and western medicine disease characteristics and the improvement of the Chinese and western medicine evaluation system for different evidence types are of great significance for the future development of TCM research on T2DM.

Based on the etiology and clinical diagnostic criteria of type 2 diabetes mellitus （T2DM）， identification and typing of treatment from the perspective of traditional Chinese and western medicine， the criteria for evaluating the clinical compatibility of traditional Chinese and western medicine in animal models of T2DM were set up. The literature was reviewed to sort out and analyze the existing commonly used modeling methods， summarize the mechanism， compare the advantages and disadvantages， and calculate the consistency between the animal model and the clinical symptoms， syndromes， and indicators from the perspective of traditional Chinese and western medicine. The authors found that spontaneous animal models and high-fat diets combined with multiple low-dose streptozotocin （STZ） induction models were more in line with modern medical pathogenesis of T2DM. However， it fails to form some special syndromes required for traditional Chinese medicine （TCM） research. In addition， there are many methods of combining the etiology and pathogenesis of TCM， which can be divided into three categories： intervention carried out by drug administration， behavioral stimulation， or environmental changes according to TCM， or use of hormones according to clinical evidence and combination of the two methods mentioned above. All of them can successfully establish different types of animal models. However， different methods of establishing syndrome models have their own advantages and disadvantages， and there is no unified standard for the stability and evaluation of syndrome models. As for the clinical consistency criteria of traditional Chinese and western medicine established in this paper， the animal model with 100% consistency has not been calculated due to the conditions of incomplete symptoms and syndromes described in the studies and different selection indicators. Consequently， the establishment of a simple， easy-to-use， and affordable T2DM animal model with both traditional Chinese and western medicine disease characteristics and the improvement of the Chinese and western medicine evaluation system for different evidence types are of great significance for the future development of TCM research on T2DM.

Hematological malignancies are a serious disease with a high risk of mortality and a high tendency to recur. The current mainstream treatment methods mainly include chemotherapy, targeted therapy, supportive therapy, and hematopoietic stem cell transplantation. Immune cell therapy can induce the function of immune cells and accurately kill tumors and pathogens. For those refractory patients who experience relapse or have poor response to traditional treatments, the immune cell therapy has good clinical efficacy. This article reviews the latest advances in immune cell therapy for hematological malignancies.

Proteolysis-targeting chimeras (PROTACs) represent a promising class of drugs that can target disease-causing proteins more effectively than traditional small molecule inhibitors can, potentially revolutionizing drug discovery and treatment strategies. However, the links between in vitro and in vivo data are poorly understood, hindering a comprehensive understanding of the absorption, distribution, metabolism, and excretion (ADME) of PROTACs. In this work, ¹⁴C-labeled vepdegestrant (ARV-471), which is currently in phase III clinical trials for breast cancer, was synthesized as a model PROTAC to characterize its preclinical ADME properties and simulate its clinical pharmacokinetics (PK) by establishing a physiologically based pharmacokinetics (PBPK) model. For in vitro-in vivo extrapolation (IVIVE), hepatocyte clearance correlated more closely with in vivo rat PK data than liver microsomal clearance did. PBPK models, which were initially developed and validated in rats, accurately simulate ARV-471's PK across fed and fasted states, with parameters within 1.75-fold of the observed values. Human models, informed by in vitro ADME data, closely mirrored postoral dose plasma profiles at 30 mg. Furthermore, no human-specific metabolites were identified in vitro and the metabolic profile of rats could overlap that of humans. This work presents a roadmap for developing future PROTAC medications by elucidating the correlation between in vitro and in vivo characteristics.

ObjectiveTo investigate the features of liver histopathological damage in patients with indeterminate phase of chronic HBV infection， as well as the timing for initiating antiviral therapy in such patients. MethodsA retrospective screening was performed for the patients with chronic HBV infection who were hospitalized in The Fifth Medical Center of Chinese PLA General Hospital and underwent liver biopsy from March 2018 to April 2022， among whom the patients who met the criteria for indeterminate phase defined in Chinese guidelines for chronic hepatitis B prevention and treatment （2022 edition） were enrolled， and their clinical data were collected. Liver histopathological stage was determined using the Scheuer scoring system， with stages 0 — 4 for inflammation grade （G） and stages 0 — 4 for fibrosis degree （S）， and the patients were divided into groups based on the presence of significant necroinflammation （≥G2） and significant liver fibrosis （≥S2）. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. A Spearman’s rank correlation analysis was used to investigate the correlation between liver histopathology and clinical factors， and the Logistic regression model was used to identify the independent influencing factors for significant necroinflammation and liver fibrosis. ResultsA total of 271 patients with indeterminate phase of chronic HBV infection were enrolled， among whom 61 （22.5%） had significant necroinflammation （≥G2） and 124 （45.8%） had significant liver fibrosis （≥S2）. The Logistic regression analysis showed that alanine aminotransferase ≥30 U/L （for male patients） or ≥19 U/L （for female patients） （odds ratio ［OR］=2.69， 95% confidence interval ［CI］： 1.39 — 5.21， P=0.003）， HBV DNA ≥2 000 IU/mL （OR=2.75， 95%CI： 1.38 — 5.48， P=0.004）， and liver stiffness measurement （LSM） ≥6.0 kPa （OR=4.57， 95%CI： 2.17 — 9.62， P<0.001） were independent risk factors for significant inflammation. HBV DNA ≥2 000 IU/mL （OR=1.82， 95%CI： 1.01 — 3.32， P=0.049） and LSM ≥6.0 kPa （OR=2.06， 95%CI： 1.23 — 3.43， P=0.006） were independent influencing factors for significant liver fibrosis. ConclusionAmong the patients with indeterminate phase of chronic HBV infection， a substantial proportion of patients have significant liver histopathological damage. Antiviral therapy should be initiated in a timely manner for patients with high-risk factors.

As an important strategy in antiviral drug development, nucleoside analogs (NAs) have attracted considerable attention due to their unique mechanisms of action and favorable safety profile. This review systematically summarizes recent advances in the mechanisms of action of NAs, focusing on the following four aspects: (1) Targeting viral polymerases, inhibiting viral replication through mechanisms such as non-absolute termination, delayed chain termination and induction of viral RNA mutations in addition to classical chain termination, which has been newly discovered; (2) Regulating RNA methylation modifications—for instance, competitively inhibiting methyltransferases, which significantly reduces viral replication efficiency; (3) Depleting nucleotide pools—by affecting host cell purine nucleotide synthesis pathways, thereby indirectly inhibiting viral replication; and (4) Immunomodulatory functions—including activation of the STING pathway to promote interferon production. Furthermore, this review systematically discusses the breakthrough progress in prodrug technologies for addressing key clinical challenges such as drug resistance and off-target toxicity of NAs. These advances provide crucial technical support for the clinical translation of NAs. These advances provide key technical support for the clinical translation of NAs. This review clarifies the multi-target action rules of NAs and provides a theoretical framework for the design of next-generation broad-spectrum antiviral agents.

DeepSeek,a domestically developed generative artificial intelligence(AI)tool,is experiencing rapid growth within China's technological landscape.With its core advantages of open-source accessibility,cost-efficiency,vertical scenario specialization,and Chinese linguistic contextualization,it has been reconfiguring medical education.This development brings nu-merous innovative opportunities to postgraduate medical education,particularly in standardized training of resident physicians.On one hand,DeepSeek creates new possibilities for participants in residency training regarding knowledge acquisition,assisted learning,and teaching methodologies.On the other hand,its implementation raises concerns such as inadequate development of higher-order thinking skills,lack of realistic doctor-patient communication simulations,and diminished roles of clinical instruc-tors.Hospitals with a resident physician training base should promptly adapt to the new situation and move embrace intelligent de-velopment.By addressing the challenges posed by DeepSeek while fully utilizing emerging technologies,they can drive the high-quality development of standardized resident physician training.

Emotions are an integral part of animal welfare.Facial expressions are increasingly used as a non-invasive method for assessing the emotional state of animals.Dogs(Canis familiaris)are closely related to humans,and facial expressions are crucial for interspecies communication and emotional expression.This paper reviews the neurobiological mechanisms of facial expressions and the anatomical structure of the facial muscles and their evolution in dogs,the analogy between dog and human facial expressions,and the expression of various parts of the dog's face under different emotions.These studies demonstrate that dog's facial expressions can be used as a potential indicator of animal welfare,and that dogs can be used as a model animal for studying interspecies facial emotional communication.The use of dog's facial expressions to assess emotions will aid multidisciplinary research,including in the fields of neuroscience,psychopharmacology,animal behavior,and animal welfare.

As an important setting for the administration of vaccinations, the reasonable setting up and standardized management of vaccination clinics will enhance immunization service quality, public satisfaction, and improve the vaccination rate to protect people′s health. In recent years, various provinces in China are continuously promoting the standardized construction and management of vaccination clinics. However, the level of standardization management remains unbalanced, and the capacity of vaccination services needs to be further improved. This paper reviews the standardized management process of vaccination clinics, summarizes the practice and achievements in various regions, and analyzes the challenges and issues during these processes, to provide reference for improving the standardized management level of vaccination clinics in the future.

Objective:To develop an artificial intelligence-based model for automated recognition of serum indices using machine vision and deep learning.Methods:This study was a cross-sectional study.Serum sample images were collected fromWest China Hospital of Sichuan University from September 21, 2020 to January 20, 2023 using the imaging device of the fully automated sample pre-processing system. A computer random number generator was used to randomly select one whole hour each day, and all serum sample images processed within that hour were included. After excluding samples with unqualified images and missing serum index results, a total of 5, 534 samples were included. These were divided into a training set and a test set in an 8∶2 ratio using Python random shuffle function, and 4, 458 samples were in the training set and 1, 076 samples were in the test set. After manual inspection, the serum regions were annotated using the MATLAB Image Labeler tool and converted into YOLO format, and a YOLO v5-based model was constructed for automatic serum region extraction. The actual values of lipemia index (L-index), hemolysis index (H-index), and icterus index (I-index) were measured using the automatic biochemical analyzerwith matched reagent kits. A serum index regression model was constructed based on the MobileNet v2 network using the PyTorch 1.10.0 framework. The grading performance of the model was evaluated using accuracy, Kappa coefficient, sensitivity, specificity, positive predictive value, and negative predictive value. Regression performance was assessed using root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and Bland-Altman analysis.Results:The overall accuracy rates for grading L-index, H-index, and I-index were 98.88%, 95.26%, and 92.47%, respectively, with Kappa coefficients of 0.72, 0.72, and 0.59. For L-index, MAE was 5.11, RMSE was 9.77, and R2 was 0.78. For H-index, MAE was 5.18, RMSE was 8.99, and R2 was 0.89. For I-index, MAE was 1.13, RMSE was 3.01, and R2 was 0.71. Bland-Altman analysis showed that 95.5%, 95.1%, and 95.7% of the data points fell within the consistency intervals for L-index, H-index, and I-index, respectively.Conclusion:The study developed an artificial intelligence-based serum index regression modelto estimate serum indices with high efficiency and accuracy. It shows great potential for reducing laboratory costs, improving clinical testing efficiency, and promoting intelligent development in laboratory medicine.