Diabetes mellitus （DM） is a metabolic disease caused by absolute or relative insulin deficiency and reduced insulin sensitivity in peripheral cells， posing a serious threat to global health. Chronic complications arising in the later stages of DM can lead to the decline or even loss of function in multiple organs， including the eyes， heart， liver， kidneys， nerves， and feet， making them the primary cause of mortality in DM patients. Although modern medicine has made some progress in the treatment of these complications， challenges such as high costs and adverse drug reactions remain. Thus， identifying highly effective drugs with minimal adverse effects has become a top priority. Astragalus membranaceus is a shining gem in the treasure trove of Chinese medicine. Numerous studies have shown that its primary active component， astragaloside Ⅳ， possesses various biological activities， including anti-inflammatory， antioxidant， and antiviral effects， as well as benefits for cardiac and cerebral function， nerve conduction， and myocardial protection. Meanwhile， the phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway plays a crucial role in regulating oxidative stress， inflammatory responses， apoptosis， and autophagy. Extensive research has highlighted the significant role of this pathway in various DM complications， leading to widespread studies on its interaction with astragaloside Ⅳ. This review summarizes research findings on how astragaloside Ⅳ alleviates pancreatic cytotoxicity in DM patients by modulating the PI3K/Akt pathway. Additionally， it highlights its protective effects on basic cardiac function， inhibition of retinal cell damage， improvement of cerebral nerve dysfunction， reduction of chronic kidney and liver damage， and mitigation of neurovascular toxicity in the lower limbs. These insights provide a valuable reference for the clinical application of A. membranaceus and its active monomer， astragaloside Ⅳ， in the treatment of DM and its complications.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Sophorae Flavescentis Radix is one of the commonly used traditional Chinese medicine in China, and a large amount of pharmaceutical residue generated during its processing and production is discarded as waste, which not only wastes resources but also pollutes the environment. Therefore, elucidating the chemical composition of the residue of Sophorae Flavescentis Radix and the differences between the residue and Sophorae Flavescentis Radix itself is of great significance for the comprehensive utilization of the residue. This study, based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) technology combined with multivariate statistical methods, provides a thorough characterization, identification, and differential analysis of the overall components of Sophorae Flavescentis Radix and its residue. Firstly, 61 compounds in Sophorae Flavescentis Radix were rapidly identified based on their precise molecular weight, fragment ions, and compound abundance, using a self-constructed compound database. Among them, 41 compounds were found in the residue, mainly alkaloids and flavonoids. Secondly, through principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA), 15 key compounds differentiating Sophorae Flavescentis Radix from its residue were identified. These included highly polar alkaloids, such as oxymatrine and oxysophocarpine, which showed significantly reduced content in the residue, and less polar flavonoids, such as kurarinone and kuraridin, which were more abundant in the residue. In summary, this paper clarifies the overall composition, structure, and content differences between Sophorae Flavescentis Radix and its residue, suggesting that the residue of Sophorae Flavescentis Radix can be used as a raw material for the extraction of its high-activity components, with promising potential for development and application in cosmetics and daily care. This research provides a scientific basis for the future comprehensive utilization of Sophorae Flavescentis Radix and its residue.
Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Mass Spectrometry/methods* ; Sophora/chemistry* ; Flavonoids/chemistry* ; Alkaloids/chemistry*

Data space, as an innovative data management and sharing model, is emerging in the medical and health sectors. This study expounds on the conceptual connotation of data space and delineates its key technologies, including distributed data storage, standardization and interoperability of data sharing, data security and privacy protection, data analysis and mining, and data space assessment. By analyzing the real-world cases of data spaces within medicine and health, this study compares the similarities and differences across various dimensions such as purpose, architecture, data interoperability, and privacy protection. Meanwhile, data spaces in these fields are challenged by the limited computing resources, the complexities of data integration, and the need for optimized algorithms. Additionally, legal and ethical issues such as unclear data ownership, undefined usage rights, risks associated with privacy protection need to be addressed. The study notes organizational and management difficulties, calling for enhancements in governance framework, data sharing mechanisms, and value assessment systems. In the future, technological innovation, sound regulations, and optimized management will help the development of the medical and health data space. These developments will enable the secure and efficient utilization of data, propelling the medical industry into an era characterized by precision, intelligence, and personalization.
Humans ; Computer Security ; Information Dissemination ; Data Management ; Information Storage and Retrieval ; Data Mining

The development of novel point-to-point drugs targeting resistance mechanisms is a critical and popular research field; nevertheless, success remains challenging. Therefore, given the short survival time and heightened expectations of patients with advanced NSCLC, the design of various combination therapy strategies––integrating preclinical, clinical, and real-world evidence (such as radiotherapy, chemotherapy, targeted therapy, antibody–drug conjugates, oncolytic viruses, and cell therapy)––may be a wise and practical choice to address the disease. Resistance to immunotherapy involves almost all cell types in the body, primarily cancer cells and T cells involved in immune surveillance. As a result of space limitations, this article focuses on the progress and challenges of various combined strategies for directly eliminating cancer cells. We also emphasize the realignment of treatment goals, shifting from primarily focusing on eliminating cancer cells (via chemotherapy and radiotherapy) to fully utilizing immune regulation to overcome resistance to immune checkpoint inhibitors.

italic>Salvia apiana Jepson, commonly known as white sage, is a perennial sub-shrub of the Salvia genus in the Lamiaceae family with a long medicinal history. In this study, the complete chloroplast genome of S. apiana was sequenced using PacBio HiFi third-generation sequencing technology. The physical map of the genome was constructed, and the sequence structure features, codon preference, and repetitive sequences were analyzed. Furthermore, a comparative analysis of the chloroplast genome and phylogenetic evolution with closely related species within the same genus was conducted. The chloroplast genome of S. apiana was found to have a length of 151 701 bp (GenBank accession number: OR389048), with a typical quadripartite structure and a GC content of 38.06%. A total of 132 genes were annotated, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Among them, 17 genes contained introns, and 18 genes were present in duplicate copies. Codon preference analysis revealed a preference for codons ending with A or U. Analysis of repetitive structures in the S. apiana chloroplast genome identified 170 simple sequence repeat (SSR) sites and 65 scattered repeat sequences, with the majority of SSR sites composed of A and T. Phylogenetic analysis of the complete chloroplast genomes of 21 species within the same genus showed that S. apiana is most closely related to Salvia hispanica Ettling. ex Willk. & Lange, Salvia leucantha Cav., and Salvia tiliifolia Vahl. Comparative analysis of the chloroplast genomes revealed slight contraction and expansion of the inverted repeat (IR) boundaries in S. apiana, as well as multiple highly variable regions in the chloroplast genome sequence. This study establishes a method for de novo assembling the chloroplast genome of S. apiana using third-generation sequencing data and provides a comprehensive analysis of its chloroplast genome, which can serve as a theoretical basis for studies on chloroplast genetic engineering, genetic diversity analysis, molecular breeding, and species identification.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective:To investigate the relationship between mutated genes and clinical features in patients with essential thrombocythemia(ET).Methods:The clinical data of 69 patients with ET from October 2018 to March 2022 were retrospectively analyzed.According to driver mutation type,patients were divided into JAK2 group,CALR group and triple-negative group.The sex,age,cardiovascular risk factors,thrombosis,splenomegaly,routine blood test and coagulation status of patients in three groups were analyzed.Results:Among 69 ET patients,46 cases were associated with JAK2 mutation,14 cases with CALR mutation,8 cases with triple-negative mutation,and one with MPL gene mutation.There were no significant differences in age and sex among the three groups(P＞0.05).The highest thrombotic rate was 26.09％(12/46)in JAK2 group,then 12.5％(1/8)in triple-negative group,while no thrombotic events occurred in CALR group.The incidence of splenomegaly was the highest in JAK2 group(34.78％),while no splenomegaly occurred in triple-negative group.The white blood cell(WBC)count in JAK2 group was(9.00±4.86)× 109/L,which was significantly higher than(6.03±2.32)× 109/L in CALR group(P＜0.05).The hemoglobin(Hb)and hematocrit(HCT)in JAK2 group were(148.42±18.79)g/L and(0.44±0.06)％,respectively,which were both significantly higher than(131.00±15.17)g/L and(0.39±0.05)％in triple-negative group(P＜0.05).The platelet(PLT)in JAK2 group was(584.17±175.77)× 109/L,which was significantly lower than(703.07±225.60)× 109/L in CALR group(P＜0.05).The fibrinogen(Fg)in JAK2 and triple-negative group were(2.64±0.69)g/L and(3.05±0.77)g/L,respectively,which were both significantly higher than(2.24±0.47)g/L in CALR group(P＜0.05,P＜0.01).The activated partial thromboplastin time(APTT)in triple-negative group was(28.61±1.99)s,which was significantly decreased compared with(31.45±3.35)s in CALR group(P＜0.05).Conclusions:There are differences in blood cell count and coagulation status among ET patients with different driver gene mutations.Among ET patients,JAK2 mutation is most common.Compared with CALR group,the thrombotic rate,WBC and Fg significantly increase in JAK2 group,while PLT decrease.Compared with triple-negative group,the incidence of splenomegaly and HCT significantly increase.Compared with CALR group,Fg significantly increases but APTT decreases in triple-negative group.

Objective:To investigate the application effect of 3D printed fetal heart model based on ultrasound data combined with case-based learning (CBL) in prenatal ultrasound teaching of complex heart malformations in standardized residency training of ultrasound medicine.Methods:A total of 60 students majoring in ultrasound imaging who received standardized residency training in Ultrasonography Center of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, from September 2020 to August 2022 were enrolled as subjects and divided into experimental group and control group, with 30 students in each group. The students in the experimental group received teaching with 3D printed fetal heart model and CBL teaching, and those in the control group received teaching with hand-painted heart diagram and CBL teaching. The two groups were compared in terms of the score of theoretical examination, the degree of satisfaction with teaching, and the self-rated score of the understanding of each disease before and after teaching, and the correlation of the increase in score with case complexity was also analyzed. MedCalc software was used to perform the t-test and the linear regression analysis. Results:The experimental group had a significantly higher score of theoretical examination than the control group [(85.70±8.70) vs. (71.40±9.50)]. The questionnaire survey showed that the experimental group had better feedbacks than the control group in the aspects such as the degree of satisfaction with teaching ( P<0.05). After the implementation of this teaching model, compared with the control group, the experimental group had significantly higher self-rated scores of the understanding of case 2, case 3, case 4, and case 5 ( P<0.05). The increase in score after teaching was positively correlated with the complexity score of abnormal cases ( R2=0.90, P=0.010; R2=0.94, P=0.010), and the experimental group tended to have a greater regression coefficient. Conclusions:The reasonable application of 3D printed fetal heart model combined with CBL teaching in fetal heart teaching in standardized residency training of ultrasound medicine can help the students to understand and enhance the knowledge of cardiac anatomy, improve the learning experience of fetal echocardiography, and deepen the understanding and awareness of complex congenital heart disease.

Objective:To evaluate the characteristics of vaginal flora between normal and abnormal pregnant women throughout pregnancy.Methods:Vaginal swab specimens were collected from pregnant women in the first (<14 gestation weeks, GW), second (14~28 GW) and third trimester (>28 GW) in Anqing, Anhui Province from February 2018 to February 2020. Pregnant women were divided into normal and abnormal groups according to all clinical diagnosis. The sequences of 16S rRNA gene (V3-V4) from vaginal swabs were analyzed using QIIME2 platform. The differences in the dominance of Lactobacillus, community state type (CST) transition, Alpha diversity and Beta diversity were analyzed. Diversity data after log transition were used in the analysis of linear mixed model. Results:A total of 34 pregnant women (10 normal and 24 abnormal) with 102 samples were included for analysis. The composition of vaginal flora between two groups: the relative abundance of Lactobacillus was the highest at the genus level and Lactobacillus crispatus and Lactobacillus iners was the top two species with high relative abundance. The dominance of Lactobacillus, Alpha diversity and transition of CST were also similar. Both groups had a gradually decreased trend of Alpha diversity with GW, and the Chao1, Observed species and Faith′s PD indexes′ were different in different GW ( P<0.05). All Beta diversity metrics in normal group had descending trend, with lower value of the index of first distance which implied a higher microbiota stability, while Bray-Curtis, Weighted UniFrac distance had ascending trend in abnormal group, indicating lower stability. Jaccard distance′s first distance was statistically differed among GW and Unweighted UniFrac distance′s differed between normal and abnormal groups. Conclusions:The first distance of Unweighte UniFrac distance in abnormal pregnant women is higher than that of normal pregnant women and the vaginal flora in abnormal group has lower stability.