The rapid and sensitive on-site detection of the methicillin resistance gene (mecA) is crucial for monitoring antimicrobial resistance in dairy products. Herein, we developed a novel, fully integrated detection platform by coupling light-driven (LD) recombinase polymerase amplification (RPA) with strand displacement amplification (SDA) and a photothermal lateral flow test strip (LFTS), mediated by copper selenide (CS) nanomaterials. This cascade system leverages the excellent photothermal conversion property of CS, which under 808 nm laser irradiation provide localized heating to drive both RPA and SDA isothermally, eliminating the need for conventional temperature control equipment. The dual-amplification strategy significantly enhanced sensitivity, with the LD system achieving a 1.9-fold higher efficiency than water-bathed amplification within 30 min. Amplicons were quantitatively detected using a gold-modified CS-based photothermal LFTS, where captured nanoparticles generated a measurable temperature increase (ΔT). The assay demonstrated a wide linear range from 3.9 to 3.9 × 106 copies/μL with a limit of detection of 0.43 copies/μL, exhibited high specificity against non-target antibiotic resistance genes (sul1, sul2, nuc), and showed good storage stability. When applied to spiked raw milk samples, recovery rates ranged from 84.7% to 112.3%, correlating well with qPCR results. The entire workflow from amplification to readout was completed within 35 min in a closed-tube format, offering a powerful, rapid, and equipment-free strategy for on-site monitoring of drug-resistant genes in complex food matrices.

Prediabetes is highly prevalent in China and often remains undetected in primary-care settings where fasting plasma glucose (FPG) alone may miss individuals with impaired glucose tolerance (IGT). Early identification of metabolic deterioration requires practical, biochemically informed identification tools. This study aimed to develop and evaluate a multifactorial model for identifying prediabetes among Chinese adults. We conducted a retrospective case-control study including 296 adults undergoing routine health examinations at Pingshan Hospital between August 2023 and December 2024. Based on WHO 2019 criteria and 2010 ADA standards, 123 individuals with prediabetes and 173 normoglycemic controls were enrolled. Clinical and biochemical variables—including adiponectin (ADPN), non-esterified fatty acids (NEFA), lipid parameters, and the triglyceride-to-HDL-cholesterol (TG/HDL-C) ratio—were measured. Multivariable logistic regression analysis was performed using the enter method, with variables selected based on clinical relevance and prior evidence. Model performance was evaluated using receiver operating characteristic (ROC) analysis. Age, ADPN, NEFA, and TG/HDL-C were incorporated into the final model. ADPN was inversely associated with prediabetes risk, whereas age showed a positive association, TG/HDL-C and NEFA demonstrated a borderline positive association. The model demonstrated moderate discriminative ability, with an area under the curve (AUC) of 0.736 (95

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection induces profound immune dysregulation during the acute phase; however, the extent and characteristics of immune remodeling after recovery remain incompletely understood. This study aimed to comprehensively characterize transcriptional, clonal, and immune-receptor repertoire alterations in SARS-CoV-2 convalescent individuals at single-cell resolution. Methods Peripheral blood mononuclear cells (PBMCs) from five SARS-CoV-2 convalescent healthcare workers and six uninfected controls were analyzed using single-cell RNA sequencing integrated with full-length T-cell receptor (TCR) and B-cell receptor (BCR) repertoire profiling. Immune-cell composition, transcriptional programs, clonal expansion, repertoire diversity, and differentiation trajectories were systematically evaluated. Results Convalescent individuals exhibited reduced circulating natural killer (NK) cells and a distinct interferon-responsive NK-cell subset enriched for interferon-stimulated genes. CD8⁺ effector and proliferative T cells displayed marked clonal expansion, reduced TCR diversity, and biased TRAV/TRBV usage. Persistent interferon-responsive transcriptional signatures were also detected in subsets of CD4⁺ naïve and CD8⁺ effector T cells. B-cell repertoires showed increased diversity without dominant clonal expansion, while an interferon-responsive neutrophil subset was enriched after recovery. Conclusion SARS-CoV-2 convalescence is associated with coordinated remodeling of both innate and adaptive immunity, characterized by persistent interferon-responsive immune states, altered TCR repertoires, and increased BCR diversity. These findings suggest that immune reconstitution after viral clearance may remain incomplete and could contribute to long-term immune adaptation. However, the small single-center cohort, cross-sectional design, and lack of functional validation limit mechanistic interpretation and generalizability. Larger longitudinal studies are warranted.

Extracellular vesicles (EVs) have emerged as promising tools for early cancer detection, therapeutic monitoring, and drug delivery in oncology. Artificial intelligence (AI), particularly machine learning and deep learning, offers new analytical tools and computational approaches for EV research. This review summarizes recent advances in the application of AI to EV isolation, characterization, diagnosis, and drug delivery, with particular emphasis on its potential to enhance tumor detection sensitivity, diagnostic accuracy, and the rational design of delivery platforms. Special attention is given to the roles and recent applications of AI models in integrating multimodal features, characterizing EV heterogeneity, supporting diagnostic classification, and modeling in vivo behavior. Moreover, we examine the integration of AI with EV-based microfluidic isolation, surface-enhanced Raman spectroscopy (SERS), fluorescence imaging, and multiomics analysis. Among these areas, AI-assisted EV diagnostic applications are comparatively closer to clinical translation, with several studies incorporating patient-derived samples and AI-assisted diagnostic platforms, whereas AI-guided therapeutic EV design strategies remain largely exploratory. With the continued accumulation of multicenter, cross-platform EV datasets, improvements in algorithmic robustness, and closer integration of computational and experimental workflows, AI may support further clinical evaluation of EV-based diagnostics and the systematic optimization of therapeutic EV platforms.

BACKGROUND:Non-alcoholic fatty liver disease (NAFLD) and its advanced form, non-alcoholic steatohepatitis (NASH), significantly contribute to the increasing incidence of liver cancer due to NASH (NALC), emphasizing the urgent need to address the associated global health burden. METHODS:Using the Global Burden of Disease 2021 dataset, we analyzed the incidence, mortality, and disability-adjusted life year (DALY) rates of NALC and NAFLD from 1990 to 2021 across 204 countries. The Joinpoint model, age-period-cohort modeling, decomposition analysis, and frontier analysis were used to assess trends, identify contributing factors, and evaluate health inequities. Projections for future incidence were made using Nordpred and Bayesian age-period-cohort models. RESULTS:The global incidence and mortality rates of NALC have increased significantly. Incidence rose from 14,413.92 cases (95% CI 11,470.95-17,854.24) in 1990 to 42,291.37 (95% CI 34,032.64-51,129.45) in 2021. This trend was particularly evident in low-middle SDI countries, while high SDI countries exhibited declining mortality rates despite rising incidence. Population growth was a primary driver of the increased burden in most regions. Projections suggest that NALC incidence may reach 43,525.53 (95% CI 14,169.28-72,881.77) by 2039, particularly among the elderly, highlighting the serious future risks associated with NALC globally. CONCLUSION:The findings highlight the growing global burden of NALC driven by NAFLD, especially in low- to middle-income regions. Targeted interventions, alongside a deeper understanding and better resource allocation, are essential to mitigate the rising incidence and address the health disparities associated with this expanding public health challenge.

Accurate stratification of recurrence risk after curative resection remains a critical challenge in the management of hepatocellular carcinoma (HCC). Dysregulated ceramide (CER) metabolism has been implicated in HCC progression and relapse. This paper evaluates whether preoperative plasma CER profiling coupled with machine learning (ML) enhances the risk prediction of HCC recurrence. In this retrospective study, 257 HCC patients undergoing curative resection participated. Preoperative plasma CERs were quantified by targeted Lipidomics. Independent predictors were identified via multivariate Cox regression and incorporated into ten ML models. Using an internal 20

This study investigates the effects of fat emulsion-based early parenteral nutrition in patients following hemihepatectomy, addressing a critical gap in clinical knowledge regarding parenteral nutrition after hemihepatectomy. We retrospectively analysed clinical data from 274 patients who received non-fat emulsion-based parenteral nutrition (non-fatty nutrition group) and 297 patients who received fat emulsion-based parenteral nutrition (fatty nutrition group) after hemihepatectomy. Fat emulsion-based early parenteral nutrition significantly reduced levels of post-operative aspartate aminotransferase, total bilirubin and direct bilirubin, while minor decreases in red blood cell and platelet counts were observed in the fatty nutrition group. Importantly, fat emulsion-based early parenteral nutrition shortened lengths of post-operative hospital stay and fasting duration, but did not affect the incidence of short-term post-operative complications. Subgroup analyses revealed that the supplement of n-3 fish oil emulsions was significantly associated with a reduced inflammatory response and risk of post-operative infections. These findings indicate that fat emulsion-based early parenteral nutrition enhances short-term post-operative recovery in patients undergoing hemihepatectomy.

BACKGROUND:Circulating ceramides (CERs) are associated with liver diseases and dysfunction. The utility of plasma CERs in predicting post-hepatectomy liver failure (PHLF) remains unclear. This study aimed to evaluate the clinical utility of preoperative plasma CERs for predicting clinically relevant PHLF (CR-PHLF). METHODS:This study included 736 patients who underwent hepatectomy across four independent hospitals in China. The training set included 392 patients from 2019 to 2021, and the prospective internal and external validation sets included 195 patients from 2022 to 2024 and 149 patients from 2023 to 2025, respectively. Preoperative plasma CERs were measured using targeted lipidomics. Grade B/C PHLF was classified by the criteria of the International Study Group of Liver Surgery and defined as CR-PHLF. Predictors for CR-PHLF were identified by least absolute shrinkage and selection operator logistic regression and receiver operating characteristic analysis. The study is registered on ClinicalTrials.gov (NCT03598465) and the Research Registry (Identifier: researchregistry11253). RESULTS:Plasma CER(d18:1/20:1) demonstrated a positive correlation with preoperative liver dysfunction and superior predictive power for CR-PHLF, with an area under the receiver-operating characteristic curve (AUROC) of 0.837 (95% confidence interval [CI]: 0.782-0.892; P < 0.001). Major hepatectomy, direct bilirubin, and CER(d18:1/20:1) were identified as independent PHLF predictors and integrated into an innovative CR-PHLF prediction model (Hpx-CER model). The model exhibited commendable discrimination in the training set (AUROC = 0.896; 95% CI: 0.851-0.941; P < 0.001), and the prospective internal (AUROC = 0.907; 95% CI: 0.845-0.970; P < 0.001) and external validation sets (AUROC = 0.862; 95% CI: 0.707-1.000; P < 0.001). Across all high-risk subgroups of CR-PHLF, including major hepatectomy, difficult hepatectomy, cirrhosis, malignant liver diseases, and preoperative liver dysfunction, our model consistently outperformed conventional models in predicting CR-PHLF. CONCLUSION:Plasma CER(d18:1/20:1) is a novel predictor of CR-PHLF. The Hpx-CER model performs commendably in predicting CR-PHLF and provides reliable preoperative risk estimations.

Bovine Mastitis (BM) adversely impacts the health of dairy cows and the quality of milk. Rapid and precise detection to miRNA-146a, a biomarker of BM for early diagnosis, is therefore crucial for the safety of dairy products. Herein, a high-efficiency method for the detection of miRNA-146a was developed, integrating photothermal Cu2-xSe nanoparticles (CS NPs), strand displacement amplification (SDA) and lateral flow assay (LFA). The core innovation utilizes photothermal materials for dual functionality: (1) CS NPs as a photothermal nanomaterial enables rapid photocontrolled SDA (pSDA) under 808 nm laser irradiation, achieving target amplification within 20 min-2.3 times faster than conventional water-bathed SDA; and (2) Au coated Cu2-xSe nanoparticles (CSA NPs) facilitates quantitative detection within a specifically designed photothermal LFA (pLFA). This pLFA measures temperature changes (ΔT) in the test zone via infrared thermal imaging to quantify the single-labeled amplicons. The integrated pSDA-pLFA method achieves an excellent balance of speed and sensitivity, featuring a detection limit of 28.6 fM and a wide linear range of 1.0 × 102 fM to 1.0 × 108 fM (R2 = 0.9907). Validation using spiked milk samples demonstrated strong consistency with quantitative PCR (qPCR) results, confirming the establishment of a novel, rapid, and quantitative pSDA-pLFA platform for miR-146a detection. This approach holds significant promise for enhancing dairy industry bio-surveillance and ensuring food safety.

Background:Chyle leaks (CL) is a significant postoperative complication following lymph node dissection in cancer patients. Persistent CK is related to a series of adverse outcomes. Nutritional management is considered an effectively strategy that treat CL. However, the existing evidence on nutritional management for this patient cohort fails to provide actionable clinical guidance. Aim:This study was aimed to establish an evidence-based framework for nutritional management, offering reliable basis for clinical nursing practice. Methods:Utilizing the "6S" mode, we conducted a systematic search of UpToDate, BMJ, Best Practice, Cochrane Library, Joanna Briggs Institute (JBI) Center for Evidence-Based Health Care Database, National Guideline Clearinghouse (NGC), Guidelines International Network (GIN), National Institute for Health and Care Excellence (NICE), Scottish Intercollegiate Guidelines Network (SIGN), Registered Nurses' Association of Ontario (RNAO), World Health Organization, Medlive, American Society for Parenteral and Enteral Nutrition (ASPEN), European Society for Clinical Nutrition and Metabolism (ESPEN), Web of Science, PubMed, Embase, CINAHL, China Biology Medicine (CBM), and China National Knowledge Infrastructure (CNKI) for all evidence on the nutritional management of postoperative coeliac leakage in cancer patients. This search included guidelines, evidence summaries, expert consensus, clinical decision-making, recommended practices, systematic evaluations or Meta-analyses, randomized controlled trials (RCTs), and class experiments. The search timeframe was from the library's establishment to June 2024. Quality assessment of the literature was completed independently by two researchers with professional evidence-based training and expert advice, and evidence was extracted and summarized for those that met the quality criteria. Results:A total of 13 articles were included in the analysis, comprising two expert consensus, one guideline, one class of experimental studies, seven systematic evaluations, and two clinical decisions. We summarized 22 pieces of evidence across five categories: nutritional screening, assessment, and monitoring, timing of nutritional therapy, methods and approaches to nutritional therapy, nutrient requirements, and dietary modification strategies. Conclusion:This study presents key evidence for nutritional management in cancer patients with CL post-surgery, emphasizing nutritional screening, assessment, timing and methods of therapy, and dietary adjustment strategies. It emphasized the necessity of thorough screening tools for the assessment of nutritional condition, and the benefits of early enteral feeding. A multidisciplinary team approach is vital for conducting personalized dietary, while sustained nutritional support, dietary fat restrictions, and medium-chain triglycerides enhance nutrient absorption. Consistent monitoring of chylous fluid output and timely dietary adjustments are crucial for improving patient outcomes and recovery. Systematic review registration:http://ebn.nursing.fudan.edu.cn/registerResources, identifier ES20244732.

Colorectal cancer (CRC) is a prevalent malignancy affecting the human digestive tract. Triptonide has been shown to have some anticancer activity, but its effect in CRC is vague. Herein, we examined the effect of triptonide on CRC. In this study, the results of bioinformatics analysis displayed that triptonide may regulate ferroptosis in CRC by modulating GPX4 and SLC7A11. In HCT116 and LoVo cells, the expression levels of GPX4 and SLC7A11 were significantly reduced after triptonide management versus the control group. Triptonide inhibited proliferation, but promoted ferroptosis in CRC cells. SLC7A11 upregulation overturned the effects of triptonide on proliferation and ferroptosis in CRC cells. Triptonide inhibited activation of the PI3K/AKT/Nrf2 signaling in CRC cells. Activation of the PI3K/AKT signaling or Nrf2 upregulation overturned the effects of triptonide on proliferation and ferroptosis in CRC cells. Triptonide suppressed CRC cell growth in vivo by modulating SLC7A11 and GPX4. In conclusion, Triptonide repressed proliferation and facilitated ferroptosis of CRC cells by repressing the SLC7A11/GPX4 axis through inactivation of the PI3K/AKT/Nrf2 signaling.

Background: Non -small cell lung cancer (NSCLC) represents the predominant pathological subtype of lung cancer in China. Amidst the advent of precision medicine, immunotherapy has emerged as a pivotal approach in managing malignant neoplasms, substantially improving patient prognosis and survival rates. However, the efficacy of immunotherapy remains limited, primarily attributed to the development of resistance among advanced -stage patients. This study used bioinformatics methodologies to analyze and identify potential key genes governing immune resistance in NSCLC, offering novel insights into therapeutic avenues. Methods: Gene expression datasets (GSE126044 and GSE135222) encompassing NSCLC cases with immunotherapy resistance and control groups were retrieved from the Gene Expression Omnibus (GEO) repository. Differential gene expression analysis was conducted using Gene Expression Omnibus 2 R (GEO2R) with criteria set at |log FC (fold change)| >= 1 and p < 0.05. Subsequent analyses involved Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Ontology (GO) functional annotation, Protein -Protein Interaction (PPI) network construction, and Gene Set Enrichment Analysis (GSEA). The findings were visualized through volcano plots and box plots in the R program. Candidate genes were cross -validated with Genecard database entries and scrutinized against existing literature for clinical relevance. The association between key genes, immune cells, and immune -associated gene expressions was analyzed using the Tumor Immune Estimation Resource (TIMER) database. Immunohistochemistry assays were employed to assess the differentially expressed genes (DEGs) in lung cancer tissues. Results: Sixty-four upregulated DEGs were obtained from datasets GSE126044 and GSE135222. PPI network analysis identified one cluster and twelve candidate genes, further corroborated through module examination of common DEGs. Integration with Genecard database entries and literature confirmed Fas Ligand (FASLG) as a pivotal gene. KEGG and GSEA pathway analyses unveiled potential mechanisms predominantly related to the interaction between immune cell functions and cytokines, especially T cells. Analysis in the TIMER database revealed a significant positive correlation between FASLG expression and six types of infiltrating immune cells, as well as specific immune cell subsets, alongside three immune checkpoint -associated molecules: Cluster of Differentiation 274 (CD274), Cytotoxic T -Lymphocyte -Associated protein 4 (CTLA-4), and Programmed Cell Death Protein 1 (PDCD1) (p -value < 0.05). Furthermore, in The Cancer Genome Atlas (TCGA) database, FASLG was strongly associated with T cell gene markers and regulatory factors associated with T cell exhaustion, demonstrating statistical significance (p -value < 0.05). Immunohistochemical results preliminarily confirmed the significant upregulation of FASLG in lung cancer tissues. Conclusion: The identification of key genes and associated signaling cascades deepens our understanding of the molecular mechanisms governing immunotherapy resistance in NSCLC. Notably, FASLG is a potential facilitator of immune escape in NSCLC tumor cells by promoting T cell exhaustion, highlighting NSCLC as a viable target for anticancer interventions.

BACKGROUND & AIMS: The machinery that prevents colorectal cancer liver metastasis (CRLM) in the context of liver regeneration (LR) remains elusive. Ceramide (CER) is a potent anti-cancer lipid involved in intercellular interaction. Here, we investigated the role of CER metabolism in mediating the interaction between hepatocytes and metastatic colorectal cancer (CRC) cells to regulate CRLM in the context of LR. METHODS: Mice were intrasplenically injected with CRC cells. LR was induced by 2/3 partial hepatectomy (PH) to mimic the CRLM in the context of LR. The alteration of corresponding CER-metabolizing genes was examined. The biological roles of CER metabolism in vitro and in vivo were examined by performing a series of functional experiments. RESULTS: Induction of LR augmented apoptosis but promoted matrix metalloproteinase 2 (MMP2) expression and epithelial-mesenchymal transition (EMT) to increase the invasiveness of metastatic CRC cells, resulting in aggressive CRLM. Upregulation of sphingomyelin phosphodiesterase 3 (SMPD3) was determined in the regenerating hepatocytes after LR induction and persisted in the CRLM-adjacent hepatocytes after CRLM formation. Hepatic Smpd3 knockdown was found to further promote CRLM in the context of LR by abolishing mitochondrial apoptosis and augmenting the invasiveness in metastatic CRC cells by up-regulating MMP2 and EMT through promoting the nuclear translocation of beta-catenin. Mechanistically, we found that hepatic SMPD3 controlled the generation of exosomal CER in the regenerating hepatocytes and the CRLM-adjacent hepatocytes. The SMPD3-produced exosomal CER critically conducted the intercellular transfer of CER from the hepatocytes to metastatic CRC cells and impeded CRLM by inducing mitochondrial apoptosis and restricting the invasiveness in metastatic CRC cells. The administration of nanoliposomal CER was found to suppress CRLM in the context of LR substantially. CONCLUSIONS: SMPD3-produced exosomal CER constitutes a critical anti-CRLM mechanism in LR to impede CRLM, offering the promise of using CER as a therapeutic agent to prevent the recurrence of CRLM after PH.

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Pyroptosis is an inflammatory form of programmed cell death closely related to tumor formation and development. However, the functional role and significance of pyroptosis in HCC remain unclear. Methods RNA-sequencing and clinical data for HCC patients were obtained from TCGA and GEO databases. We first explored the 49 pyroptosis-related genes (PRGs) expression patterns in HCC. The univariate Cox regression analysis and consensus clustering by PRGs were then performed to divide TCGA-HCC patients into two subtypes, C1 and C2. Based on prognostic PRGs, the LASSO Cox regression method was employed to construct a prognostic model. The predictive value was evaluated by generated nomogram and decision curve analysis (DCA). GSEA and immune infiltration analysis evaluated immune status. Additionally, regulating networks of prognostic PRGs were predicted with Networkanalyst online tools. Finally, the expression of the prognostic genes was validated by qRT-PCR. Results HCC patients in subtype C2 exhibited a larger proportion of grade III-IV, higher immune scores, more genetic mutations, and increased expression of immune factors. A prognostic model was developed based on four prognostic PRGs and classified HCC patients into high- and low-risk groups. Patients in the low-risk group showed better prognostic survival. The risk score of this model was an independent prognostic factor and had a good predictive ability. Besides, immune status showed a difference between the two risk groups. We drew the regulating networks between the mRNA of 4 prognostic PRGs and TFs, miRNAs, or chemicals. The qRT-PCR results demonstrated PRGs highly expressed in paracancerous tissues and lowly expressed in carcinoma. Conclusions The prognostic model based on four PRGs has significant implications for prognosis assessment and provides a new idea for HCC treatment.

INTRODUCTION: Endoscopic evaluation is crucial for predicting the invasion depth of esophagus squamous cell carcinoma (ESCC) and selecting appropriate treatment strategies. Our study aimed to develop and validate an interpretable artificial intelligence–based invasion depth prediction system (AI-IDPS) for ESCC. METHODS: We reviewed the PubMed for eligible studies and collected potential visual feature indices associated with invasion depth. Multicenter data comprising 5,119 narrow-band imaging magnifying endoscopy images from 581 patients with ESCC were collected from 4 hospitals between April 2016 and November 2021. Thirteen models for feature extraction and 1 model for feature fitting were developed for AI-IDPS. The efficiency of AI-IDPS was evaluated on 196 images and 33 consecutively collected videos and compared with a pure deep learning model and performance of endoscopists. A crossover study and a questionnaire survey were conducted to investigate the system's impact on endoscopists' understanding of the AI predictions. RESULTS: AI-IDPS demonstrated the sensitivity, specificity, and accuracy of 85.7%, 86.3%, and 86.2% in image validation and 87.5%, 84%, and 84.9% in consecutively collected videos, respectively, for differentiating SM2-3 lesions. The pure deep learning model showed significantly lower sensitivity, specificity, and accuracy (83.7%, 52.1% and 60.0%, respectively). The endoscopists had significantly improved accuracy (from 79.7% to 84.9% on average, P = 0.03) and comparable sensitivity (from 37.5% to 55.4% on average, P = 0.27) and specificity (from 93.1% to 94.3% on average, P = 0.75) after AI-IDPS assistance. DISCUSSION: Based on domain knowledge, we developed an interpretable system for predicting ESCC invasion depth. The anthropopathic approach demonstrates the potential to outperform deep learning architecture in practice.

BACKGROUND:The effects of postoperative adjuvant therapy for high-risk recurrent hepatocellular carcinoma (HCC) in immunotherapy are still under investigation. This study evaluated the preventive effects and safety of postoperative adjuvant therapy, including atezolizumab, and bevacizumab, against the early recurrence of HCC with high-risk factors. METHODS:The complete data of HCC patients who underwent radical hepatectomy with or without postoperative adjuvant therapy after two-year follow-up were analyzed retrospectively. The patients were divided into high-risk or low-risk groups based on HCC pathological characteristics. High-risk recurrence patients were divided into postoperative adjuvant treatment and control groups. Due to the difference in approaches in postoperative adjuvant therapies, they were divided into transarterial chemoembolization (TACE), atezolizumab, and bevacizumab (T + A), and combination (TACE+T + A) groups. The two-year recurrence-free survival rate (RFS), overall survival rate (OS), and associated factors were analyzed. RESULTS:The RFS in the high-risk group was significantly lower than that in the low-risk group (P = 0.0029), and the two-year RFS in the postoperative adjuvant treatment group was significantly higher than that in the control group (P = 0.040). No severe complications were observed in those who received atezolizumab and bevacizumab or other therapy. CONCLUSION:Postoperative adjuvant therapy was related to two-year RFS. TACE, T + A, and the combination of these two approaches were comparable in reducing the early recurrence of HCC without severe complications.

CONTEXT:A wide variety of malignancies common to humans display abnormal constitutive expression of nuclear factor kappa beta (NF-κβ). The study of NF-κβ can increase understanding of its role in cancer, especially in lung-tumor formation.OBJECTIVE:This review intended to examine the research on the impact of the NF-κβ signaling pathway on the development of malignancies of the lungs and the advances in the regulation of that pathway to mitigate and provide treatment for lung carcinoma.DESIGN:The research team performed a narrative review by searching the PubMed, EMBASE, and Web of Science databases. The search used the keywords NF-κB or NF-kappa B or nuclear factor kappa B and non-small-cell lung cancer or non-small-cell lung carcinoma or NSCLC or lung cancer or lung adenocarcinoma or lung squamous carcinoma.SETTING:This study were conducted at Department of Respiratory and Critical Care Medicine, Qingxian People's Hospital, Cangzhou City, Hebei Province, People's Republic of China.RESULTS:As a major cell survival signal, nuclear factor-kappaB (NF-kappaB) is involved in multiple steps in carcinogenesis and in cancer cell's resistance to chemo- and radio-therapy. Recent studies with animal models and cell culture systems have established the links between NF-kappaB and lung carcinogenesis, highlighting the significance of targeting NF-kappa signaling pathway for lung cancer treatment and chemoprevention.CONCLUSIONS:While no convincing evidence exists that survival of lung cancer cells is dependent on NF-κβ, inhibition of NF-κβ is a potent supporting therapy for enhancing the therapeutic effects of chemotherapy and radiotherapy. Constitutive and therapeutically induced activation of NF-κβ reduces the tumor-massacre effect of treatment, so inhibiting NF-κβ might increase antitumor activity.

Objective Evaluate the quality of implementation of Traditional Chinese Medicine (TCM)/Integrated Traditional Chinese and Western Medicine (IM) clinical guidelines and expert con-sensus published at home and abroad using the “Clinical Practice Guideline (CPG) implementation evaluation tool”, understand the implementation of TCM/IM CPGs and expert consensus, provide a ref-erence for TCM/IM guidelines implementation and promotion.Methods CNKI, Wanfang Data, PubMed, and Medive databases were systematically searched, to collect original TCM/IM guidelines/consensus. The “CPG implementation evaluation tool” was applied to evaluate the implementation of the included TCM/IM guidelines.Results A total of 231 guidelines/consensus were included, consisting of 119 guidelines and 112 expert consensus. In general, the implementation quality of most TCM/IM guide-lines/consensus is low (90.91%).Conclusion The implementation of TCM/TCM CPGs/expert consen-sus still needs to be improved. Incorporating implementation science into the guideline formulation process, managing and guiding formulation from the source, and optimizing the presentation and dis-semination strategies of the guidelines can promote the implementation of guidelines/consensus appli-cation.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Emerging evidence indicates that the NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome is activated, which results in a cytokine storm at the late stage of COVID-19. Autophagy regulation is involved in the infection and replication of SARS-CoV-2 at the early stage and the inhibition of NLRP3 inflammasome-mediated lung inflammation at the late stage of COVID-19. Here, we discuss the autophagy regulation at different stages of COVID-19. Specifically, we highlight the therapeutic potential of autophagy activators in COVID-19 by inhibiting the NLRP3 inflammasome, thereby avoiding the cytokine storm. We hope this review provides enlightenment for the use of autophagy activators targeting the inhibition of the NLRP3 inflammasome, specifically the combinational therapy of autophagy modulators with the inhibitors of the NLRP3 inflammasome, antiviral drugs, or anti-inflammatory drugs in the fight against COVID-19.