Malignant tumors represent a major threat to global health. Conventional anti-tumor pharmacotherapy often encounters challenges such as drug resistance, highlighting an urgent need for the development of novel therapeutic strategies. Fatty acid synthase (FASN), the key enzyme catalyzing de novo fatty acid synthesis, is subject to precise regulation at multiple levels, including transcriptional control, various post-translational modifications such as ubiquitination and phosphorylation, as well as modulation by diverse signaling pathways. Recent studies have revealed that FASN is aberrantly overexpressed in various malignant tumors and is closely associated with tumor progression and poor patient prognosis. FASN is a homodimer composed of seven functional domains that catalyzes the NADPH-dependent condensation of acetyl-CoA and malonyl-CoA to generate saturated fatty acids, primarily palmitic acid. Its stability is regulated by multiple ubiquitin ligases and deubiquitinating enzymes. Additionally, FASN is subject to upstream regulation via neural precursor cell-expressed developmentally downregulated 8 (Nedd8) modification and the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, thereby establishing a metabolic-signaling positive feedback loop. As a core executor of metabolic reprogramming, FASN promotes tumorigenesis through dual mechanisms. First, its fatty acid synthesis product, palmitate, participates in membrane phospholipid synthesis, lipid raft formation, and protein palmitoylation, thereby activating several key oncogenic signaling pathways, including PI3K/AKT/mTOR, wingless-type MMTV integration site family member (Wnt)/β‑catenin, and signal transducer and activator of transcription 3 (STAT3)/matrix metalloproteinase (MMP), leading to tumor development and progression. Second, FASN plays a pivotal role in modulating the anti-tumor functions of immune cells and remodeling the tumor immune microenvironment. Specifically, FASN enhances immune checkpoint inhibition by inducing programmed death-ligand 1 (PD-L1) palmitoylation, suppresses the activation of cytotoxic T lymphocytes and natural killer cells, and promotes the polarization of M2-type macrophages, consequently facilitating tumor immune evasion and malignant progression. Precisely due to its significant overexpression in tumor cells, its critical functional role, and its differential expression compared to normal cells, FASN has emerged as a highly promising target for anti-tumor drug development. Highly selective small-molecule inhibitors, notably represented by TVB-2640, have advanced to clinical trial stages and demonstrated favorable anti-tumor activity. Furthermore, the combination of FASN inhibitors with other chemotherapeutic agents or targeted drugs can overcome the limitations of monotherapy through synergistic effects or by resensitizing tumor cells to conventional drugs, achieving a “1+1>2” therapeutic outcome. With the advancement of modern traditional Chinese medicine (TCM), numerous active ingredients derived from TCM have been confirmed to exert anti-tumor effects by modulating FASN-related pathways. This integrated approach leverages the precision of Western medicine while simultaneously harnessing the holistic regulatory benefits of TCM to alleviate the side effects of radiotherapy and chemotherapy. Despite the promising prospects of FASN-targeted therapies, challenges remain, including tumor cell metabolic plasticity, tumor context-dependent responses, and heterogeneity. This review systematically summarizes the molecular structure, physiological functions, and mechanisms of FASN in tumorigenesis, as well as recent advances in targeted therapies. Future directions—including the precise identification of responsive patient populations using spatial transcriptomics, the development of novel combination regimens, and the active exploration of integrative strategies combining traditional Chinese and Western medicine—will facilitate the clinical translation of FASN-targeted therapies and open new avenues for improving the quality of life and prognosis of cancer patients.

Objective To analyze the risk factors of type 2 diabetes mellitus (T2DM) with metabolic-associated fatty liver disease (MAFLD) and explore their relationship with BMI management. Methods A retrospective analysis was conducted of 310 patients with type 2 diabetes who underwent physical examinations at the 363 hospital between March 2023 and March 2025. Among these patients, those with MAFLD were counted. The risk factors of T2DM with MAFLD were analyzed by logistic regression analysis. The relationship between T2DM with MAFLD and BMI management was explored by Spearman correlation coefficient analysis. Results Compared with the non-MAFLD group, the levels of alanine aminotransferase (ALT), fasting insulin (I₀), fasting blood glucose (G₀), BMI, triglyceride (TG), aspartate aminotransferase (AST), and serum uric acid (SUA) were higher while the level of high-density lipoprotein cholesterol (HDL-C) was lower in the MAFLD group (P<0.05). Logistic regression analysis showed that BMI, SUA, I₀, ALT, G₀, and BMI control scale score were risk factors of T2DM with MAFLD (P<0.05). The score of BMI control scale of patients in the MAFLD group was higher than that in the non-MAFLD group (P<0.05). Correlation analysis indicated that T2DM with MAFLD was negatively correlated with BMI management (P<0.05). Conclusion BMI, SUA, I₀, ALT, and G₀ are all risk factors of T2DM with MAFLD. BMI management is negatively correlated with T2DM with MAFLD. Patients with T2DM should control BMI and blood glucose to reduce the occurrence of MAFLD.

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 To analyze the predictive value of different obesity indicators on acute cerebral infarction in patients with transient ischemic attack (TIA). Methods A total of 310 patients with TIA admitted to Tangdu Hospital of Air Force Medical University from March 2022 to September 2025 were selected and classified into non-event group (276 cases) and cerebral infarction group (34 cases) based on acute cerebral infarction within 90 days. The basic data and obesity-related indicators [body mass index (BMI), waist-to-hip ratio, body adiposity index (BAI), conicity index (C-index) and a body shape index (ABSI were compared. Multivariate logistic regression analysis was utilized to screen the independent influencing factors. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive efficiency. Results The age, proportions of concurrent hypertension and concurrent diabetes mellitus, ABCD2 score, waist-to-hip ratio, ABSI, C-index, BMI and BAI in the cerebral infarction group were older or higher than those in the non-event group, and the symptoms duration was longer (P<0.05). The above indicators were all related factors for acute cerebral infarction in patients with TIA within 90 days (P<0.05), and ABSI and ABCD² score were independent influencing factors (P<0.05). The prediction model was manifested as Logit (P)=− 4.205 + 0.482 × ABCD² score + 1.120 × ABSI × 100. ABSI and ABCD2 score had predictive value on the occurrence of acute cerebral infarction (P<0.05), and the predictive efficiency of combined model was higher than that of single indicator (P<0.05). Conclusion Among different obesity indicators, ABSI has the highest value on predicting recent acute cerebral infarction in TIA. The prediction model based on ABSI and ABCD2 score exhibits the best predictive efficiency.

Objective To observe the effects of wheat grain moxibustion on the hippocampal ERK/CREB-BDNF/TrkB signaling pathway and neurotransmitters in rats with perimenopausal depressive disorder(PDD);To explore its mechanism in treating PDD.Methods Totally 24 female SD rats were randomly divided into sham-operation group,model group,Western medicine group and wheat grain moxibustion group,with 6 rats in each group.The PDD rat model was established by bilateral ovariectomy and chronic unpredictable mild stress.The wheat grain moxibustion group received moxibustion at the"Zhongwan","Xiawan","Qihai","Guanyuan"acupoints,with a conical moxa cone for intervention,6 cones per acupoint;the Western medicine group was given fluoxetine hydrochloride solution 1.8 mg/kg by gavage,once a day,for consecutive 21 d.Before and after modeling and after intervention,the body mass,sucrose water preference rate and immobility time in the forced swimming test of the rats were recorded;Transmission electron microscopy was used to observe the synaptic structure in hippocampal tissue;ELISA was used to detect the expressions of 5-HT,GABA and Glu in hippocampal tissue;Western blot was used to detect the expressions of ERK,p-ERK,CREB,p-CREB,BDNF and TrkB proteins in hippocampal tissue.Results Compared with the sham-operation group,the body mass and sucrose water preference rate of the model group decreased,and the immobility time in the forced swimming test was prolonged(P<0.01);the number of synaptic vesicles in hippocampus decreased,the thickness of the postsynaptic density decreased,the aggregation of transduction-related proteins decreased,the synaptic cleft increased;the contents of 5-HT and GABA in hippocampal tissue decreased,the content of Glu increased,and the expressions of p-ERK,p-CREB,BDNF and TrkB proteins decreased(P<0.01).Compared with the model group,the body mass and sucrose water preference rate of the rats in Western medicine group and wheat grain moxibustion group increased,and the immobility time in the forced swimming test was shortened(P<0.01);the area of the postsynaptic density in the hippocampus increased,the synaptic cleft reduced,the contents of 5-HT and GABA in hippocampal tissue increased,the content of Glu decreased,and the expressions of p-ERK,p-CREB,BDNF and TrkB proteins increased(P<0.01).Conclusion Wheat grain moxibustion can effectively alleviate depressive-like behavior in PDD rats,and its mechanism may be related to regulating neurotransmitter expressions and mediating the ERK/CREB-BDNF/TrkB signaling pathway,thereby regulating hippocampal neuroplasticity.

Objective:This study investigated the expression level of phosphatidylserine-specific phospholipase A1(PLA1A)in colorectal can-cer(CRC)and analyzed its correlations with clinicopathological features,prognosis,and immune infiltration.Methods:The expression level of PLA1A in CRC was screened,and the influence of this expression level on patient prognosis was analyzed using bioinformatics methods.A cohort of 192 patients diagnosed with CRC at Shanxi Province Cancer Hospital from January to December 2020 were selected.The PLA1A ex-pression level in those with CRC was determined using immunohistochemistry(IHC)and real-time quantitative reverse transcription PCR(RT-qPCR).The relationship between PLA1A level and the clinicopathological features of the patients with CRC was analyzed using the chi-square test.The expression levels of immune cell markers CD4 and CD8 as well as immunosuppressive checkpoints PD-1,TIM-3,and CTLA-4 in CRC were detected via IHC,and their correlations with PLA1A level were analyzed using the chi-square test.Results:The results of bioinformatics analysis showed that the expression level of PLA1A in CRC tissue was higher than paracancerous tissue,which correlated with overall surviv-al(OS)(P<0.05).The IHC and RT-qPCR results showed that PLA1A expression level was significantly upregulated in CRC tissiue(P<0.05).High PLA1A level was closely associated with the TNM stage,degree of differentiation,and lymph node metastasis(P<0.05).The IHC results demonstrated that PLA1A positively correlated with the infiltrating CD8+T cell level(P<0.05).In addition,the elevated PLA1A levels upregu-lated the expressions of immunosuppressive checkpoints PD-1,TIM-3,and CTLA-4(P<0.05).Conclusions:PLA1A is highly expressed in CRC,which is closely related to immune infiltrating cells and immunosuppressive checkpoints,suggesting that PLA1A plays an important role in immune infiltration in CRC,a finding that provides guidance in the treatment of CRC.

OBJECTIVE To evaluate the clinical value of dose-escalated postoperative radiotherapy(PORT)in improving local control and survival outcomes for head and neck adenoid cystic carcinoma(ACC)patients.METHODS This retrospective study analyzed 336 ACC patients treated with surgery plus PORT at Beijing Tongren Hospital from January 2015 to January 2021.Cohort stratification compared high-dose(>60 Gy,n=146)and conventional-dose(≤60 Gy,n=190)regimens.Survival analysis employed Kaplan-Meier estimates with log-rank testing,complemented by multivariate Cox regression for risk adjustment.RESULTS The cohort demonstrated 39.29%(132/336)cumulative local failure rate.The overall survival rates at 1,3,and 5 years after surgery were 98.81%,94.05%,and 90.48%,respectively.Dose-response relationships revealed:1.Significantly reduced local recurrence with high-dose PORT(28.08%vs.47.89%,P<0.001),corresponding to 41.37%lower recurrence risk(a HR=0.59,95%CI=0.38-0.91;P=0.041);2.Superior progression-free survival in the high-dose group(3-year:86.99%vs.76.32%;5-year:82.19%vs.66.32%,all P<0.05);3.Comparable overall survival between groups(median OS:200 vs.160 months,P=0.292).CONCLUSION Dose escalation beyond 60 Gy significantly enhances locoregional control and progression-free survival in head and neck ACC without conferring overall survival advantage,likely reflecting the disease's characteristic indolent metastatic progression.These results establish>60 Gy as an optimal dose threshold for PORT in high-risk ACC management.

As a serine protease,thrombin can convert soluble fibrinogen into insoluble fibrin and plays a pivotal role in the coagulation cascade.Therefore,the accurate quantitative assay of thrombin levels is of great value in the evaluation of coagulation function,clinical screening and prognostic monitoring of coagulation-related diseases,and screening of drugs for targeted therapy.Existing methods for thrombin detection can be divided into two categories,e.g.,the assay of concentration levels using nucleic acid aptamers as the affinity elements and the assay of activity levels based on the hydrolytic cleavage of substrate peptides.In recent years,electrochemical biosensors have attracted much attention in thrombin detection due to high sensitivity,high selectivity,simple instrument,fast response,and good portability.In this review,the latest research progress in methods for electrochemical detection of thrombin was summarized,focusing on the detection principles and the applied signal amplification strategies of related electrochemical biosensors.In addition,the challenges with respect to the practical use of electrochemical thrombin biosensors and the prospects were discussed.

Objective To explore the application value of different deep learning models in predicting the lung cancer spread through air spaces(STAS).Methods A total of 203 patients with stage Ⅰ—Ⅱ primary lung cancer were included,of which 74 were STAS-positive and 129 were STAS-negative.Patients were randomly divided into training set(142 cases)and test set(61 cases)at a 7∶3 ratio.Region of interest(ROI)was outlined using ITK-SNAP software,facilitating the extraction of tumor and peritumoral images.The Resnet18,Inception_v3,and Vision Transformer(Vit)were employed for model training and feature extraction.Feature selection was performed by the least absolute shrinkage and selection operator(LASSO)algorithm and Spearman correlation coefficient,followed by the establishment of a predictive model using the Naive Bayes machine learning algorithm.The receiver operating characteristic(ROC)curve was drawn to compare the prediction performance of each model.The assessment of calibration was performed using calibration curves,and the evaluation of clinical application value was conducted using decision curve analysis(DCA).Results The area under the curve(AUC)for the training and test sets were as follows:the training set Resnet18 0.849-0.930,Inception_v3 0.848-0.888,Vit 0.747-0.842;and the test set Resnet18 0.796-0.846,Inception_v3 0.783-0.804,Vit 0.690-0.796.In tumor-peritumoral images,Resnet18 had a higher calibration and better clinical net benefit,while Vit showed superior calibration and clinical net benefit when only tumor tissue was considered.Conclusion Deep learning models can effectively predict lung cancer STAS,providing more decision support for the preoperative diagnosis and treatment of stages Ⅰ—Ⅱ lung cancer.

In recent years,the incidence and mortality of heatstroke have been increasing annually alongside global warming,with a marked rise in cases exhibiting atypical symptoms.To address the increasingly complex challenges in heatstroke prevention and treatment,Heatstroke Prevention and Treatment Research Center of Chinese PLA,Expert Group of Heatstroke Prevention and Treatment of Chinese PLA,and Chinese PLA Professional Committee of Critical Care Medicine have jointly developed this guideline(2025 edition).Utilizing the Grading of Recommendations Assessment,Development and Evaluation(GRADE)system,Appraisal of Guidelines for Research and Evaluation(AGREE)criteria,and Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards,and based on the 2015 draft"Expert Consensus on the Standardized Diagnosis and Treatment of Heatstroke"and the 2019"Chinese Expert Consensus on the Diagnosis and Treatment of Heatstroke",this guideline has been crafted.This guideline provides 25 evidence-based recommendations to guide the prevention,treatment and research of heatstroke,which thoroughly covers 8 critical domains:clinical classification,pathophysiological mechanisms,clinical manifestations,diagnostic criteria,differential diagnosis,treatment protocols,rehabilitation and return to work,and prevention.