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.

Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

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.

Objective To explore latent classes of behavioural and psychological symptoms in the patients with Alzheimer's disease(AD)and to identify the factors influencing the latent classes and provide a basis for fomulating personalized nursing measures.Methods Convenience sampling was employed to recruit 361 AD inpatients from our hospital between November 2023 and May 2024 for this cross-sectional study.A general data questionnaire,the neuropsychiatric inventory questionnaire,Monteria cognitive assessment scale,activity of daily life scale,and mini-nutritional assessment scale were used in the survey.Latent class analysis was conducted to analyse the data acquired from the survey.Univariate analysis and multiple Logistic regression analysis were used to identify the factors influencing latent classes.Results Toally 346 patients finished the study.It was found that a 72.5%of AD patients developed behavioural and psychological symptoms.The symptoms were categorised into three classes:low symptom-apathy,middle symptom-emotional disturbance and high symptom-behaviour disorder.The course of disease,cognitive function,daily living ability and nutritional status were identified as the factors that influenced the latent classes(all P<0.05).Conclusion AD patients with low cognitive function,poor daily living ability,malnutrition and a course of disease over 5 years are at high risks of behavioural and psychological symptoms which are heterogeneous.Care providers are advised to propose personalised care strategies to improve the behavioural and psychological symptoms.

Objective:To investigate the effects of TP53 genetic status(wild-type/mutated/null)on the drug resistance of decitabine(DAC)in myelodysplastic syndromes(MDS)and identify key resistance-associated genes.Methods:Two myeloid cell lines with distinct TP53 status(M-07e:wild-type;SKM-1:mutated;)were treated with gradient DAC concentrations(0-10 μmol/L)for 0-72 h.Cell viability was detected by CCK-8 assay.RNA-Seq transcriptomics,and methylation profiling were integrated to analyze differentially expressed genes.Results:Decitabine(DAC)treatment induced time-and dose-dependent inhibition of cell viability in CCK-8 assays,with SKM-1 cells exhibiting the highest resistance(IC50=5 μmol/L vs M-07e=0.5 μmol/L,P＜0.01).Transcriptomic analysis revealed 662 upregulated and 452 downregulated genes in DAC-treated M-07e cells,while SKM-1 cells showed 515 upregulated and 73 downregulated genes.By proteomic profiling,117 upregulated and 136 downregulated proteins were identified in M-07e cells,while 91 upregulated and 46 downregulated proteins were identified in SKM-1 cells following DAC exposure.Through integrated analysis of upregulated genes and proteins expression profiles,181 candidate genes were screened out,while methylation studies identified 884 hypomethylated genes with high-sensitivity loci and CpG density.Notably,31 genes overlapped between these datasets,and functional annotation indicated these drug-resistance-associated genes are primarily involved in positive regulation of cell differentiation,negative regulation of binding processes,and negative regulation of cellular component organization.Conclusion:TP53 mutations drive DAC resistance via epigenetic reprogramming.Targeting these genes may improve outcomes in TP53-mutated MDS.

The incidence of age-related macular degeneration(AMD)is rising with the intensifying aging trend,be-coming a critical challenge that demands urgent solutions.Dry AMD(dAMD)accounts for approximately 80％of all AMD cases,and there is currently a lack of highly effective treatment options.In recent years,traditional Chinese medicine(TCM)has been proven to effectively treat dAMD through actions such as antioxidation,anti-apoptosis,anti-inflammation,and lipid-lowering.By reviewing domestic and international literature,this article discusses TCM monomers,extracts,and compound formulations for dAMD,analyzing their various mechanisms.Based on traditional TCM efficacy theories and in-tegrated with modern mechanisms of action,it targets the active components of TCM to elucidate the connection between effective medicinal targets of TCM and dAMD,thereby clarifying the efficacy and scientific basis of TCM monomers,com-pounds,and extracts in treating dAMD.The aim is to provide new perspectives for the prevention and clinical treatment of dAMD.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

Objective:To establish a stable rat model of sequelae of pelvic inflammatory disease(SPID)with clinical characteristics,and to provide a reliable experimental model for the study of the pharmcological effect and mechanism of SPID.Methods:Twenty-four 7-week-old SD rats were divided into sham operation group,model-A(108 cfu/mL mixed bacterial solution,0.2 mL),model-B(109 cfu/mL mixed bacterial solution 0.2 mL),and model-C(108 cfu/mL E.coli 0.2 mL).The weight of the rat's uterine was weighed and the uterine index was calculated.The automatic hematology analyzer was used to detect the blood routine;hematoxylin-eosin staining(HE)and masson staining were used to detect uterine pathlogical changes in rats.Enzyme-linked immunosorbent assay(ELISA)was used to detect interleukin-1β(IL-1β),interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in rat uterine tissue homogenates.Western blot was used to detect the expression of proteins related to NF-κB signaling pathway.Results:Compared with the sham operation group,the uterine index of model-A,model-B,and model-C were significantly increased(P＜0.05,P＜0.01).The levels of WBC and NE in the model-A increased significantly(P＜0.01).The level of LY in model-B decreased significantly(P＜0.01).The levels of IL-1β,TNF-α in model-A,model-B,and model-C were significantly increased(P＜0.01).The levels of IL-6 in model-A and model-B were significantly increased(P＜0.05,P＜0.01).The collagen volume fraction of model-A and model-B were significantly increased(P＜0.01).Mechanism study indicates that the expression levels of p-IKKβ/IKKβ,p-IκBα/IκBα and p-p65/p65 in model-A were significantly increased(P＜0.01),and the expression levels of IκBα/β-actin were significantly decreased(P＜0.01).The expression level of p-IKKβ/IKKβ in model-B was significantly increased(P＜0.01).Conclusions:A stable rat model of SPID that conforms to clinical characteristics can be successfully constructed by combining 0.2 mL of mixed bacterial solution with a concentration of 108 cfu/mL and mechanical injury.This modeling method intervened in the expression of the NF-κB inflammatory signaling pathway.