Objective: To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control. Methods: Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence. Results: A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk. Conclusions SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.

The inflammatory microenvironment is closely associated with the initiation and progression of osteoarthritis （OA）， specifically manifesting as macrophage activation， dysregulation of inflammatory cytokines， and redox imbalance. Following an overview of the pathological characteristics of the OA inflammatory microenvironment， this paper reviews the research progress on the mechanism of traditional Chinese medicine （TCM） intervening in OA by modulating the inflammatory microenvironment. It has been found that TCM monomers/active ingredients （such as total alkaloids from Strychnos nux-vomica ， quercetin， triptolide， etc.）， herb pairs （e.g. Angelica pubescens - Gentiana macrophylla ， Carthami Flos-Lycopodii Herba）， and TCM formulas （such as Zhuanggu jianxi formula， Duhuo jisheng decoction and Rongjin niantong formula， etc.） can inhibit macrophage activation， reduce the release of proinflammatory cytokines and the generation of reactive oxygen species by inhibiting multiple signaling pathways， including nuclear factor-κB， Wnt/ β -catenin， and mitogen-activated protein kinase， thereby alleviating the articular inflammatory microenvironment， restoring local joint homeostasis， and slowing the progression of OA.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

This paper systematically elaborates on the key points of diagnosis and differential diagnosis of salivary gland tumors characterized by a substantial amount of extracellular mucus as a main or prominent feature, and clarifies the core differential features. The term "mucus-rich" specifically denotes that mucus is a major component of the tumor, rather than a focal or minor one. This phenomenon is associated with distinct histogenetic mechanisms: it may result from specific genetic mutations (e.g., AKT1 E17K in mucinous adenocarcinoma) that drive ductal epithelial differentiation into mucus-secreting cells, or from myoepithelial cells secreting glycosaminoglycans that form a myxoid stroma. Salivary gland tumors with abundant extracellular mucus include mucinous cystadenoma, sialadenoma papilliferum-like intraductal papillary tumors, mucinous myoepithelioma, pleomorphic adenoma with mucin-rich stroma, mucinous adenocarcinoma, low-grade mucoepidermoid carcinoma, mucin-rich salivary duct carcinoma and intestinal-type adenocarcinoma. The diagnosis of these tumors is complicated by the dual nature of extracellular mucus: while it is a defining feature of some entities, it can also obscure key diagnostic architectural features in others, leading to histological overlap and inconspicuous diagnostic areas. Given the frequent histological morphological overlap among these tumors, immunohistochemical findings and molecular characteristics have emerged as crucial differential diagnostic criteria. Core differential diagnostic points include the following: histologically, there must be meticulous identification of typical structures obscured by mucin (such as squamoid cells in mucoepidermoid carcinoma and apocrine features in salivary duct carcinoma); in immunohistochemical staining, CK20 is useful for distinguishing intestinal-type adenocarcinoma (positive) from mucinous adenocarcinoma (negative), while androgen receptor aids in differentiating salivary duct carcinoma (positive) from mucoepidermoid carcinoma (negative); and molecular testing plays a critical role in definitive diagnosis (e.g., the AKT1 E17K mutation for mucinous adenocarcinoma, MAML2 rearrangement for mucoepidermoid carcinoma, and MEF2C::SS18 fusion for microsecretory adenocarcinoma). This paper systematically summarizes the core pathological features and differential diagnostic points of mucin-rich salivary gland tumors, aiming to provide a practical reference for clinical pathological diagnosis.

ObjectiveTo evaluate the clinical efficacy and safety of acupuncture in treating severe Bell's palsy and to explore its potential mechanism by investigating the effect on serum levels of glial cell line-derived neurotrophic factor （GDNF） and nerve growth factor （NGF）. MethodsA randomized， subject-blinded， sham-acupuncture controlled trial was conducted. A total of 130 patients with severe Bell's palsy were randomly allocated into a treatment group or a control group at a 1∶1 ratio. Both groups received conventional western medicine. In addition， the treatment group received acupuncture， while the control group received sham acupuncture， with each session lasting 30 minutes. The treatment course lasted 8 weeks for both groups， followed by a follow-up assessment at week 12. The primary outcome was the proportion of patients achieving House-Brackmann （H-B） grade Ⅱ or lower at week 8. Secondary outcomes included Sunnybrook facial grading system scores at week 0， 4， 8， and 12， the time to satisfactory recovery（the time required to achieve H-B grade≤Ⅱ）， distribution of H-B grades and facial disability index （FDI） scores including the physical function subscale （FDIP） and social/well-being function subscale （FDIS） scores at week 0， 4， 8， and 12， and serum GDNF and NGF levels at week 0， 4， and 8. Adverse events and participants' self-assessments of treatment efficacy were also recorded. ResultsA total of 122 participants completed the study， including 62 in the treatment group and 60 in the control group. An intention-to-treat （ITT） analysis was performed， and missing data were handled using the last observation carried forward （LOCF） method. The proportion of patients achieving H-B grade ≤grade Ⅱ at week 8 was 78.5% （51/65） in the treatment group， significantly higher than 49.2% （32/65） in the control group （P＜0.05）. The Sunnybrook scores， FDIP and FDIS scores increased， while H-B grades decreased at week 4， 8， and 12 in both groups compared to week 0； moreover， improvements in all outcome measures were significantly greater in the treatment group than in the control group （P＜0.05）. The median time to satisfactory recovery was 6 weeks （95%CI： 5.697-6.303） in the treatment group， significantly shorter than 12 weeks （95%CI： 8.314-15.686） in the control group （P＜0.05）. Serum levels of GDNF and NGF were significantly higher in the treatment group at weeks 4 and 8 （P＜0.05）. No serious acupuncture-related adverse events occurred in either group. Adverse events were reported in 5 patients （7.69%） in the treatment group and 4 patients （6.15%） in the control group， with no statistically significant difference between groups （P＞0.05）. Patients' self-assessment of treatment efficacy after 8 weeks treatment was significantly better in the treatment group （P＜0.05）. ConclusionAcupuncture can effectively improve facial nerve function and shorten recovery time in patients with severe Bell's palsy， with a favorable safety profile. The therapeutic mechanism may be associated with the upregulation of serum GDNF and NGF levels.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

This study reports a new species of Culicoides(Avaritia)isolated from Xunke County, Heilongjiang Province, China. The new species, Culicoides(Avaritia)dongshanensis Liu et Wang, sp. nov., was identified and illustrated based on female adults. Its diagnostic characteristics are as follows: eyes contiguous over a short distance, with short interfacetal hair, antennal ratio(AR)of 1.20, palpal ratio(PR)of 2.16, wing length of 0.83 mm, mandible with 15 teeth, one pale spot in base cell M1, one pale spot in cell M4, two pale spots in cell A, and two unequal spermathecae. Type specimens were deposited at the Center for Disease Control and Prevention of the Northern Theater Command.

Neurodegenerative diseases (NDs), particularly Alzheimer’s disease (AD) and Parkinson’s disease (PD), and cardiovascular diseases (CVDs), including heart failure (HF) and coronary artery disease (CAD), are major chronic disorders associated with population aging. Their frequent coexistence in clinical practice suggests that they may not progress independently, but may instead be linked through bidirectional pathological communication within the brain-heart axis. Epidemiological evidence underscores this clinical burden: systematic reviews and meta-analyses have reported pooled relative risks for dementia of approximately 1.27 among individuals with a history of CAD and 1.60 among those with HF, while the pooled prevalence of cognitive impairment and dementia in patients with HF has been estimated at approximately 41.42% and 19.79%, respectively. This review synthesizes current evidence on the mechanistic links, disease-state manifestations, biomarkers, and potential therapeutic strategies involved in the comorbidity between NDs and CVDs from the perspective of the brain-heart axis. The brain and heart communicate through autonomic, neuroendocrine, neuroimmune, vascular, and humoral pathways. Sympathetic activation, parasympathetic withdrawal, vagal dysfunction, cerebral hypoperfusion, endothelial injury, blood-brain barrier (BBB) alterations, peripheral immune activation, and circulating inflammatory mediators may jointly contribute to cross-organ pathological signaling. Oxidative stress and inflammatory response are not specific to the brain-heart axis; rather, they may act as candidate amplifying processes within this network. Mitochondrial dysfunction and NADPH oxidase activation can increase the generation of reactive oxygen species and reactive nitrogen species, which may activate nuclear factor-κB, the NLRP3 inflammasome, and mitogen-activated protein kinase/c-Jun N-terminal kinase signaling. These pathways can promote the release of interleukin-1β, interleukin-6, tumor necrosis factor‑α, and other inflammatory mediators, which may in turn aggravate mitochondrial injury, endothelial dysfunction, immune cell activation, and further oxidant generation. Cytokines, chemokines, oxidized lipids, mitochondrial DNA, damage-associated molecular patterns, and extracellular vesicles may transmit these signals between the cardiovascular and central nervous systems, whereas autonomic reflexes provide an additional route for bidirectional amplification. Distinct disease states illustrate different manifestations of this network. The association between AD and CVDs may involve vascular risk factors, impaired amyloid-β clearance, abnormal cholesterol homeostasis, cerebral microvascular injury, neuroinflammation, and endothelial dysfunction. HF-related cognitive impairment may be linked to reduced cardiac output, recurrent cerebral hypoperfusion, hypoxia-related signaling, BBB dysfunction, circulating inflammation, and impaired autonomic feedback. In PD, cardiovascular autonomic dysfunction and abnormalities in heart rate and blood pressure regulation may interact with vascular injury, reduced cerebral perfusion, inflammation, and oxidative stress. However, the relationship between PD and CAD remains heterogeneous and may be modified by age, ethnicity, medication use, metabolic factors, and coexisting diseases. Biomarker evaluation should therefore move beyond isolated indicators. Traditional markers, including malondialdehyde, superoxide dismutase, glutathione, C-reactive protein, and interleukin-6, reflect systemic oxidative or inflammatory burden but lack sufficient specificity to distinguish primary neurodegeneration, cardiovascular injury, or a comorbid state involving both. Greater clinical value may be obtained from cross-system panels that combine oxidative stress and inflammatory markers with cardiac stress or injury biomarkers, such as N-terminal pro-B-type natriuretic peptide; glial or neuronal biomarkers, such as glial fibrillary acidic protein and neurofilament light chain; BBB- or endothelial injury-related biomarkers; and omics-derived candidates, including microRNAs, long non-coding RNAs, DNA methylation signatures, metabolites, and proteins. Multi-omics integration and artificial intelligence-assisted analysis may support risk stratification, disease monitoring, and prediction of treatment response. However, these approaches require standardized analytical platforms, validation in independent cohorts, and careful distinction between associative findings and causal mechanisms. Potential interventions include antioxidant, anti-inflammatory, mitochondria-targeted, and multi-target combination strategies, together with emerging approaches such as nanodelivery, CRISPR/Cas9- or CRISPR/dCas9-based regulation, mesenchymal stem cell-mediated mitochondrial transfer, and ergothioneine supplementation. Nevertheless, most available evidence is indirect, preclinical, or derived from other disease indications, and no single drug or technology can currently be regarded as specific to brain-heart axis comorbidity. The clinical relevance of these strategies will depend on whether they can be matched to dominant pathological phenotypes and improve both neurological and cardiovascular outcomes. Overall, comorbidity between NDs and CVDs is more appropriately understood as a heterogeneous cross-organ regulatory network than as a disorder driven by a single pathway. Future research should prioritize multicenter longitudinal cohorts, standardized clinical phenotyping, validation of cross-system biomarker panels, and mechanism-guided interventions in clearly defined patient subgroups, with integrated assessment of cognitive function, cardiovascular events, quality of life, long-term safety, and treatment response.

ObjectiveTo screen for and validate key differentially expressed proteins in serum of patients with metabolic dysfunction‑associated fatty liver disease （MAFLD）， and to provide a basis for identifying diagnostic biomarkers and developing intervention strategies for this disease. MethodsA total of 20 patients who were diagnosed with MAFLD in the third affiliated hospital of Chengdu University of Traditional Chinese Medicine from December 2024 to January 2025 were enrolled as MAFLD group， and 20 healthy controls were enrolled as HC group. Demographic data and serum biochemical parameters were collected from both groups. Data-independent acquisition （DIA） quantitative proteomics was used to measure the relative expression levels of serum proteins， and related methods were used to obtain significantly differentially expressed proteins， including the gene ontology functional enrichment analysis， the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis， protein-protein interaction （PPI） network， Hub node interaction， and weighted gene co-expression network analysis （WGCNA）. Rats were given a high-fat diet to establish a model of MAFLD， and randomly assigned to the control group and model group. Serum biochemical parameters and inflammatory factors were measured， liver histopathological changes were observed， and the protein expression levels of MER proto-oncogene tyrosine kinase （MERTK） and matrix metalloproteinase-9 （MMP-9） in liver tissue were verified. The independent-samples t test was used for comparison of normally distributed continuous data between groups， while the Mann-Whitney U test was used for comparison of non-normally distributed continuous data or data with heterogeneity of variance between groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsCompared with the HC group， the MAFLD group had significant increases in the serum levels of aspartate aminotransferase （t=-7.348， P<0.05）， alanine aminotransferase （Z=5.088， P<0.05）， alkaline phosphatase （t=-3.943， P<0.05）， triglyceride （Z=2.070， P<0.05）， and high-density lipoprotein cholesterol （t=3.867， P<0.05）. A total of 3 559 proteins were identified by DIA serum proteomics， among which 160 differentially expressed proteins were mainly enriched in pathways including metabolic disorders， immune inflammatory response， and extracellular matrix remodeling. The PPI network and the Hub node analysis showed that serpin family E member 1， MMP-9， and intercellular cell adhesion molecule-1 were core regulatory proteins. WGCNA showed that the MEyellow module was significantly positively correlated with MAFLD phenotype （cor=0.55， P<0.001）， which was functionally enriched in the efferocytosis pathway. MERTK （P<0.001） and MMP-9 （P<0.001） showed the most significant differential expression in this module. A rat model of MAFLD was successfully established using a high-fat diet， and compared with the control group， the model group had enlarged， yellowish， and greasy liver and disordered structure of hepatic lobules， hepatocyte fatty degeneration， and inflammatory cell infiltration based on HE staining， as well as massive lipid droplet deposition based on oil red O staining， while no obvious fibrous cords were observed in Masson staining. Compared with the control group， the model group had significant increases in the serum levels of aspartate aminotransferase （t=-5.148， P<0.05）， alanine aminotransferase （t=-5.663， P<0.05）， total bilirubin （t=-13.061， P<0.05）， triglyceride （Z=-2.722， P<0.05）， total cholesterol （t=3.588， P<0.05）， and tumor necrosis factor-α （t=-16.741， P<0.05）， as well as significant increases in the protein expression levels of MERTK （t=-11.448， P<0.001） and MMP-9 （t=-10.875， P<0.001） in liver tissue. ConclusionMMP-9 and MERTK are abnormally expressed in MAFLD and may be used as potential diagnostic biomarkers for this disease.