AIM:To investigate the biological functions and molecular mechanisms of long noncoding RNA LINC01615 in head and neck squamous cell carcinoma(HNSCC)cells.METHODS:Transcriptome sequencing data from The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases were used to analyze the expres-sion level of LINC01615 in HNSCC cells and its correlation with patient survival.RT-qPCR was used to detect the expres-sion levels of LINC01615 in HNSCC and normal control cells.An siRNA-mediated LINC01615 knockdown HNSCC cell model was established,and high-content screening cell counting,ATP and CCK8 assays were performed to analyze cell proliferation.Transwell assays were conducted to assess cell migration and invasion.Bioinformatics analysis was em-ployed to predict potential target genes of LINC01615 and the biological processes and signaling pathways involved.RT-qPCR and Western blot were used to validate the regulatory effect of LINC01615 on the candidate target gene TEAD2.Transcriptome data from TCGA and GEO databases were analyzed to determine the expression pattern of TEAD2 in HN-SCC.Functional cell experiments were performed to investigate the impact of TEAD2 knockdown on HNSCC proliferation,migration,and invasion.Rescue experiments were conducted to examine whether LINC01615 influenced the malignant phenotypes(proliferation,migration,and invasion)of HNSCC cells by regulating TEAD2 expression.RESULTS:The expression levels of LINC01615 were significantly higher in HNSCC tissues and cells than those in normal control tissues and cells,respectively(P<0.01).Knockdown of LINC01615 significantly inhibited HNSCC proliferation,migration,and invasion(P<0.01).Bioinformatics analysis identified 134 candidate target genes of LINC01615,which were primarily en-riched in tumor-related biological processes and signaling pathways,including angiogenesis,regulation of endothelial cell proliferation,regulation of cell migration,HPV infection,Hippo signaling pathway,and PI3K-Akt signaling pathway.Knockdown of LINC01615 led to a significant decrease in TEAD2 expression in HNSCC cells(P<0.01).Functional cell studies demonstrated that TEAD2 knockdown suppressed HNSCC proliferation,migration,and invasion,whereas TEAD2 overexpression reversed the inhibitory effects of LINC01615 knockdown on these malignant phenotypes.CONCLUSION:LINC01615 is upregulated in HNSCC tissues and cells,functioning as an oncogene.Mechanistic studies reveal that LINC01615 promotes HNSCC proliferation,migration,and invasion by upregulating TEAD2,a key transcription factor in the Hippo signaling pathway.These findings may provide a novel potential biomarker for the clinical diagnosis and treat-ment of HNSCC.

Objective To evaluate the modeling characteristics and predictive performance of models for predicting post-stroke neurological deterioration(ND)published in existing literatures.Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidance for scoping reviews,a comprehensive search was conducted in PubMed,CINAHL,Cochrane Library,Embase,Web of Science,Scopus,CNKI,Wanfang Data,and VIP databases from inception to December 15,2024.The search strategy combined Medical Subject Headings(MeSH)and free-text terms,with key words including"Stroke""Ischemic Stroke""Neurological Deterioration""Nomograms""Risk Prediction""Predictive Models""卒中""脑梗死""脑出血""神经功能恶化"and"预测模型".Base on the data extraction checklist and critical appraisal,data extraction covered three domains:(1)basic characteristics,including author,publication year,country,study design(retrospective,prospective,registry-based),sample source(single-center,multicenter),stroke subtypes(acute ischemic stroke[AIS]-conservative therapy,AIS-intravenous thrombolysis[IVT],AIS-endovascular therapy[EVT],intracerebral hemorrhage[ICH]),ND time windows(acute[≤72 h],subacute[≤ 7 d],long-term[≤90 d]),and outcome types(single/composite endpoints);(2)model evaluation metrics,including missing data handling(complete-case analysis,multiple imputation),model development methodologies(multivariate Logistic regression,least absolute shrinkage and selection operator regression,machine learning),presentation formats(nomograms,web calculators,risk prediction tool),discrimination(area under the curve,C-index),calibration(Hosmer-Lemeshow test,calibration curve and slope),clinical utility(decision curve analysis[DCA],global metrics Brier score,R2,AIC),sample size(training set,internal validation set,external validation set),sample size requirements(events per variable[EPV]≥10 to mitigate overfitting),and validation(internal/external);(3)predictor features,including selection strategies(prior knowledge-driven,univariate analysis),quantity,and attributes(demographics,medical history,physical examination,treatment intervention information,imaging/laboratory indicators).Predictive models that meet exclusion criteria from prior literature were analyzed by their discrimination,calibration,clinical utility and global metrics.Forest plots were utilized to visualize discrimination(evaluated via difference in area under the curve)of the extracted models.The prediction model risk of bias assessment tool(PROBAST)was applied to assess bias risk and clinical applicability.Occurrence frequencies of the post-stroke neurological deterioration predictors were ranked and the top 6 high-frequency predictors were extracted.Results(1)Among 3 728 screened studies,25 were included based on the inclusion and exclusion criteria.(2)Basic characteristics:retrospective(72％[18/25])and single-center(64％[16/25])designs dominated.With most models targeted on AIS(92％[23/25]),and the rest(8％[2/25])on ICH.ND was primarily defined by neurological scale changes(60％[15/25];e.g.,National Institutes of Health stroke scale[NIHSS]score increase or Glasgow coma scale[GCS]score decrease),with time windows categorized as acute(36％[9/25]),subacute(48％[12/25]),or long-term(16％[4/25]).(3)Model evaluation:multivariate Logistic regression(96％[24/25])and nomograms(88％[22/25])were predominant.Only 24％(6/25)explicitly addressed missing data handling methods,and 52％(13/25)with EPV≥10.The median area under the curve was 0.865(range:0.650-0.981).44％(11/25)of the studies reported calibration curves,and 4％(1/25)reported calibration slopes.All studies utilized DCA to validate their clinical applicability,84％(21/25)of the studies conducted internal validation,while only 32％(8/25)conducted external validation.PROBAST evaluation revealed low overall bias risk in 8％(2/25;no error across participant,predictor,outcome,or analysis domains)and low clinical applicability risk in 44％(11/25;alignment with target populations,accessible predictors,and clinically relevant outcomes)of the studies.(4)Predictors:64％(16/25)of the predictor were screened predominantly through the prior knowledge-driven based strategy.The top 6 high-frequency predictors are NIHSS score(64％[16/25]),age(36％[9/25]),blood glucose/diabetes(36％[9/25]),blood pressure/hypertension(32％[8/25]),the Alberta stroke program early CT score(20％[5/25]),and neutrophil-to-lymphocyte ratio(20％[5/25]).AIS-ND predictors emphasized readily available metrics,such as NIHSS(65％[15/23]),age(35％[8/23]),while ICH-ND primarily relied on imaging markers(e.g.,baseline hematoma volume[2/2],location[1/2]).Conclusion Current post-stroke ND predictive models demonstrate satisfactory performance on discrimination and multimodal integration,but their practical application are hindered by insufficient calibration quantification,high bias risk,and limited clinical translatability.

AIM:To investigate the biological functions and molecular mechanisms of long noncoding RNA LINC01615 in head and neck squamous cell carcinoma(HNSCC)cells.METHODS:Transcriptome sequencing data from The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases were used to analyze the expres-sion level of LINC01615 in HNSCC cells and its correlation with patient survival.RT-qPCR was used to detect the expres-sion levels of LINC01615 in HNSCC and normal control cells.An siRNA-mediated LINC01615 knockdown HNSCC cell model was established,and high-content screening cell counting,ATP and CCK8 assays were performed to analyze cell proliferation.Transwell assays were conducted to assess cell migration and invasion.Bioinformatics analysis was em-ployed to predict potential target genes of LINC01615 and the biological processes and signaling pathways involved.RT-qPCR and Western blot were used to validate the regulatory effect of LINC01615 on the candidate target gene TEAD2.Transcriptome data from TCGA and GEO databases were analyzed to determine the expression pattern of TEAD2 in HN-SCC.Functional cell experiments were performed to investigate the impact of TEAD2 knockdown on HNSCC proliferation,migration,and invasion.Rescue experiments were conducted to examine whether LINC01615 influenced the malignant phenotypes(proliferation,migration,and invasion)of HNSCC cells by regulating TEAD2 expression.RESULTS:The expression levels of LINC01615 were significantly higher in HNSCC tissues and cells than those in normal control tissues and cells,respectively(P<0.01).Knockdown of LINC01615 significantly inhibited HNSCC proliferation,migration,and invasion(P<0.01).Bioinformatics analysis identified 134 candidate target genes of LINC01615,which were primarily en-riched in tumor-related biological processes and signaling pathways,including angiogenesis,regulation of endothelial cell proliferation,regulation of cell migration,HPV infection,Hippo signaling pathway,and PI3K-Akt signaling pathway.Knockdown of LINC01615 led to a significant decrease in TEAD2 expression in HNSCC cells(P<0.01).Functional cell studies demonstrated that TEAD2 knockdown suppressed HNSCC proliferation,migration,and invasion,whereas TEAD2 overexpression reversed the inhibitory effects of LINC01615 knockdown on these malignant phenotypes.CONCLUSION:LINC01615 is upregulated in HNSCC tissues and cells,functioning as an oncogene.Mechanistic studies reveal that LINC01615 promotes HNSCC proliferation,migration,and invasion by upregulating TEAD2,a key transcription factor in the Hippo signaling pathway.These findings may provide a novel potential biomarker for the clinical diagnosis and treat-ment of HNSCC.

Objective To conduct a rapid health technology assessment(rHTA)of the efficacy,safety,and cost-effectiveness of tirzepatide for the treatment of type 2 diabetes mellitus(T2DM),and to provide evidence for clinical medication.Methods PubMed,Web of Science,Embase,Cochrane Library,WanFang Data,CNKI databases,and health technology assessment(HTA)websites were searched to collect systematic reviews/Meta-analysis,pharmacoecomic literature and HTA reports of tirzepatide in the treatment of T2DM from inception to February 28,2025.Two researchers independently conducted literature screening,data extraction,and quality assessment,and then summarized and analyzed the results.Results A total of 13 articles were included,comprising 2 HTA reports,8 systematic reviews/Meta-analyses,and 3 pharmacoeconomic studies.In terms of efficacy,tirzepatide outperformed placebo or other antidiabetic drugs in reducing glycated hemoglobin(HbA1c),increasing the rate of HbA1c＜7％,lowering blood glucose,and reducing weight.The antihyperglycemic and weight-loss effects of tirzepatide were dose-dependent,and it also had certain advantages in reducing the risk of cardiovascular events and renal composite endpoint events.Regarding safety,the incidence of gastrointestinal adverse events in the tirzepatide group was higher than that in the placebo group and the insulin group,mainly manifested as diarrhea,nausea,and vomiting.However,it did not increase the risk of serious gastrointestinal adverse events,nor did it increase the risk of hypoglycemia and pancreatitis.In terms of cost-effectiveness,tirzepatide had cost-utility and cost-effectiveness advantages compared with semaglutide and other antidiabetic drugs.Conclusion Compared with other antidiabetic drugs,tirzepatide has better efficacy,safety,and cost-effectiveness in the treatment of T2DM.

Objective To conduct a rapid health technology assessment(rHTA)of the efficacy,safety,and cost-effectiveness of tirzepatide for the treatment of type 2 diabetes mellitus(T2DM),and to provide evidence for clinical medication.Methods PubMed,Web of Science,Embase,Cochrane Library,WanFang Data,CNKI databases,and health technology assessment(HTA)websites were searched to collect systematic reviews/Meta-analysis,pharmacoecomic literature and HTA reports of tirzepatide in the treatment of T2DM from inception to February 28,2025.Two researchers independently conducted literature screening,data extraction,and quality assessment,and then summarized and analyzed the results.Results A total of 13 articles were included,comprising 2 HTA reports,8 systematic reviews/Meta-analyses,and 3 pharmacoeconomic studies.In terms of efficacy,tirzepatide outperformed placebo or other antidiabetic drugs in reducing glycated hemoglobin(HbA1c),increasing the rate of HbA1c＜7％,lowering blood glucose,and reducing weight.The antihyperglycemic and weight-loss effects of tirzepatide were dose-dependent,and it also had certain advantages in reducing the risk of cardiovascular events and renal composite endpoint events.Regarding safety,the incidence of gastrointestinal adverse events in the tirzepatide group was higher than that in the placebo group and the insulin group,mainly manifested as diarrhea,nausea,and vomiting.However,it did not increase the risk of serious gastrointestinal adverse events,nor did it increase the risk of hypoglycemia and pancreatitis.In terms of cost-effectiveness,tirzepatide had cost-utility and cost-effectiveness advantages compared with semaglutide and other antidiabetic drugs.Conclusion Compared with other antidiabetic drugs,tirzepatide has better efficacy,safety,and cost-effectiveness in the treatment of T2DM.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To evaluate the modeling characteristics and predictive performance of models for predicting post-stroke neurological deterioration(ND)published in existing literatures.Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidance for scoping reviews,a comprehensive search was conducted in PubMed,CINAHL,Cochrane Library,Embase,Web of Science,Scopus,CNKI,Wanfang Data,and VIP databases from inception to December 15,2024.The search strategy combined Medical Subject Headings(MeSH)and free-text terms,with key words including"Stroke""Ischemic Stroke""Neurological Deterioration""Nomograms""Risk Prediction""Predictive Models""卒中""脑梗死""脑出血""神经功能恶化"and"预测模型".Base on the data extraction checklist and critical appraisal,data extraction covered three domains:(1)basic characteristics,including author,publication year,country,study design(retrospective,prospective,registry-based),sample source(single-center,multicenter),stroke subtypes(acute ischemic stroke[AIS]-conservative therapy,AIS-intravenous thrombolysis[IVT],AIS-endovascular therapy[EVT],intracerebral hemorrhage[ICH]),ND time windows(acute[≤72 h],subacute[≤ 7 d],long-term[≤90 d]),and outcome types(single/composite endpoints);(2)model evaluation metrics,including missing data handling(complete-case analysis,multiple imputation),model development methodologies(multivariate Logistic regression,least absolute shrinkage and selection operator regression,machine learning),presentation formats(nomograms,web calculators,risk prediction tool),discrimination(area under the curve,C-index),calibration(Hosmer-Lemeshow test,calibration curve and slope),clinical utility(decision curve analysis[DCA],global metrics Brier score,R2,AIC),sample size(training set,internal validation set,external validation set),sample size requirements(events per variable[EPV]≥10 to mitigate overfitting),and validation(internal/external);(3)predictor features,including selection strategies(prior knowledge-driven,univariate analysis),quantity,and attributes(demographics,medical history,physical examination,treatment intervention information,imaging/laboratory indicators).Predictive models that meet exclusion criteria from prior literature were analyzed by their discrimination,calibration,clinical utility and global metrics.Forest plots were utilized to visualize discrimination(evaluated via difference in area under the curve)of the extracted models.The prediction model risk of bias assessment tool(PROBAST)was applied to assess bias risk and clinical applicability.Occurrence frequencies of the post-stroke neurological deterioration predictors were ranked and the top 6 high-frequency predictors were extracted.Results(1)Among 3 728 screened studies,25 were included based on the inclusion and exclusion criteria.(2)Basic characteristics:retrospective(72％[18/25])and single-center(64％[16/25])designs dominated.With most models targeted on AIS(92％[23/25]),and the rest(8％[2/25])on ICH.ND was primarily defined by neurological scale changes(60％[15/25];e.g.,National Institutes of Health stroke scale[NIHSS]score increase or Glasgow coma scale[GCS]score decrease),with time windows categorized as acute(36％[9/25]),subacute(48％[12/25]),or long-term(16％[4/25]).(3)Model evaluation:multivariate Logistic regression(96％[24/25])and nomograms(88％[22/25])were predominant.Only 24％(6/25)explicitly addressed missing data handling methods,and 52％(13/25)with EPV≥10.The median area under the curve was 0.865(range:0.650-0.981).44％(11/25)of the studies reported calibration curves,and 4％(1/25)reported calibration slopes.All studies utilized DCA to validate their clinical applicability,84％(21/25)of the studies conducted internal validation,while only 32％(8/25)conducted external validation.PROBAST evaluation revealed low overall bias risk in 8％(2/25;no error across participant,predictor,outcome,or analysis domains)and low clinical applicability risk in 44％(11/25;alignment with target populations,accessible predictors,and clinically relevant outcomes)of the studies.(4)Predictors:64％(16/25)of the predictor were screened predominantly through the prior knowledge-driven based strategy.The top 6 high-frequency predictors are NIHSS score(64％[16/25]),age(36％[9/25]),blood glucose/diabetes(36％[9/25]),blood pressure/hypertension(32％[8/25]),the Alberta stroke program early CT score(20％[5/25]),and neutrophil-to-lymphocyte ratio(20％[5/25]).AIS-ND predictors emphasized readily available metrics,such as NIHSS(65％[15/23]),age(35％[8/23]),while ICH-ND primarily relied on imaging markers(e.g.,baseline hematoma volume[2/2],location[1/2]).Conclusion Current post-stroke ND predictive models demonstrate satisfactory performance on discrimination and multimodal integration,but their practical application are hindered by insufficient calibration quantification,high bias risk,and limited clinical translatability.

Objective To establish a highly sensitive and specific method for detecting human DNA based on real time quantitative PCR(qPCR)technique for the rapid detection of potential DNA con-tamination sources in DNA laboratories.Methods Primers and probes were designed with Primer Ex-pressTM software using the reference sequence of human 18S rRNA gene as a template,and the opti-mal prime-probe combination was screened by matrix method.The PCR products of the target se-quence of human 18S rRNA gene were used to construct the plasmid,and a plasmid standard was used to draw the standard curve of the qPCR system.According to the Minimum Information for Pub-lication of Quantitative Real-time PCR Experiments(MIQE)guidelines,the specificity,sensitivity,re-peatability and application effect of the qPCR system were evaluated.Results The sensitivity of the qPCR system established in this study was 5.3×10-5 ng/μL,which showed good specificity for human DNA samples.The correlation coefficient of the qPCR system was-0.999,and amplification efficiency was 100％.Both the intra-batch and inter-batch variation coefficients were less than 2％.Conclusion The established human DNA detection method based on qPCR technique has good specificity,high sen-sitivity,and robust stability.It can be used for rapid detection of DNA contamination and daily moni-toring of the accumulated human DNA in the laboratory environment.

The small-molecule alkaloid halofuginone(HF)is obtained from febrifugine.Recent studies on HF have aroused widespread attention owing to its universal range of noteworthy biological activities and therapeutic functions,which range from parasite infections and fibrosis to autoimmune diseases.In particular,HF is believed to play an excellent anticancer role by suppressing the proliferation,adhesion,metastasis,and invasion of cancers.This review supports the goal of demonstrating various anticancer effects and molecular mechanisms of HF.In the studies covered in this review,the anticancer molecular mechanisms of HF mainly included transforming growth factor-β(TGF-β)/Smad-3/nuclear factor erythroid 2-related factor 2(Nrf2),serine/threonine kinase proteins(Akt)/mechanistic target of rapa-mycin complex 1(mTORC1)/wingless/integrated(Wnt)/β-catenin,the exosomal microRNA-31(miR-31)/histone deacetylase 2(HDAC2)signaling pathway,and the interaction of the extracellular matrix(ECM)and immune cells.Notably,HF,as a novel type of adenosine triphosphate(ATP)-dependent inhibitor that is often combined with prolyl transfer RNA synthetase(ProRS)and amino acid starvation therapy(AAS)to suppress the formation of ribosome,further exerts a significant effect on the tumor microenvironment(TME).Additionally,the combination of HF with other drugs or therapies obtained universal attention.Our results showed that HF has significant potential for clinical cancer treatment.

The innate immune sensor NLRP3 inflammasome overactivation is involved in the pathogenesis of ulcerative colitis. PGAM5 is a mitochondrial phosphatase involved in NLRP3 inflammasome activation in macrophages. However, the role of PGAM5 in ulcerative colitis and the mechanisms underlying PGAM5 regulating NLRP3 activity remain unknown. Here, we show that PGAM5 deficiency ameliorates dextran sodium sulfate (DSS)-induced colitis in mice via suppressing NLRP3 inflammasome activation. By combining APEX2-based proximity labeling focused on PGAM5 with quantitative proteomics, we identify NEK7 as the new binding partner of PGAM5 to promote NLRP3 inflammasome assembly and activation in a PGAM5 phosphatase activity-independent manner upon inflammasome induction. Interfering with PGAM5-NEK7 interaction by punicalagin inhibits the activation of the NLRP3 inflammasome in macrophages and ameliorates DSS-induced colitis in mice. Altogether, our data demonstrate the PGAM5-NEK7 interaction in macrophages for NLRP3 inflammasome activation and further provide a promising therapeutic strategy for ulcerative colitis by blocking the PGAM5-NEK7 interaction.