Traditional Chinese medicine （TCM）， through its multi-target and systematic regulatory effects， has demonstrated unique advantages in the treatment of gastric precancerous lesions （GPL）. At present， TCM theoretical research on GPL is mainly reflected in three aspects， the integration of macroscopic syndrome differentiation， the inflammation-carcinoma transformation mechanism， as well as the systematization and scientization of theoretical inheritance from famous TCM practitioners. High-quality evidence-based research findings serve as the foundation for clinical practice guidelines on GPL， and TCM has gained international academic recognition in the field of GPL prevention and treatment. Research on TCM mechanisms has yielded a series of important outcomes in the aspects of signaling pathways， gene expression regulation， cellular epigenetics， histone modification， and intestinal microecology. It is proposed that future research on GPL should focus on four key directions， establishing multi-omics data， exploring targeted intervention strategies on key regulatory nodes， advancing the standardization process of integrated traditional Chinese and western medicine prevention and treatment technologies， and constructing stratified screening and intervention platforms. The in-depth integration of TCM microcosmic mechanism of action with its macroscopic syndrome differentiation and treatment system， coupled with interdisciplinary research， will provide valuable references for the clinical treatment and scientific research of GPL.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

ObjectiveTo observe the effect of M1 bone marrow-derived macrophages （M1-BMDM） with Wnt5a knockdown on liver fibrosis and regeneration in a rat model of liver cirrhosis， and to investigate its gain-of-function effect compared with unmodified M1-BMDM. MethodsPrimary bone marrow-derived macrophages were isolated from rats and were polarized to M1 phenotype to construct M1-BMDM^Wnt5a-KD cells. A rat model of liver cirrhosis induced by CCl₄/2-AAF was established， and at the end of week 8， rats were randomly divided into model group， M1-BMDM group， M1-BMDM Wnt5a-knockdown empty vector group （M1-BMDM^KD-EV group）， and M1-BMDM Wnt5a-knockdown group （M1-BMDM^Wnt5a-KD group）， with 6 rats in each group. On the first day of week 9， the rats in each group were given a single injection of the corresponding cells via the caudal vein， along with an intraperitoneal injection of a CCR2 inhibitor. Six rats without any treatment were used as normal control group. Samples were collected at the end of week 12 to assess liver histopathology， serum liver function parameters， hepatic stellate cell activation， and the expression levels of mature hepatocyte markers. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the model group， all cell treatment groups had significant alleviation of liver inflammatory response and significant reductions in the activities of alanine aminotransferase and aspartate aminotransferase （AST） in serum （all P<0.01）， and the M1-BMDM^Wnt5a-KD group had a significantly lower serum level of AST than the M1-BMDM group （P<0.05）. The semi-quantitative analysis based on immunohistochemical staining showed that compared with the model group， all cell treatment groups had a significant reduction in the percentage of CD68-positive area （all P<0.05）， and compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had a significant reduction in the percentage of CD68-positive area and a significant increase in the percentage of CD163-positive area （both P<0.05）. Compared with the model group， all cell treatment groups had significant reductions in the mRNA expression levels of CD68 and tumor necrosis factor-α （all P<0.05） and the protein expression level of CD68 （all P<0.01）； compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had significant increases in the protein and mRNA expression levels of CD163 （both P<0.05）， significant reductions in the protein and mRNA expression levels of CD68 （both P<0.05）， and a significant reduction in the protein expression level of tumor necrosis factor-α （P<0.01）. Sirius Red collagen staining and alpha-smooth muscle actin （α-SMA） immunohistochemical staining showed that compared with the model group， all cell treatment groups had significant alleviation of liver collagen deposition and α-SMA-positive area， with the most significant changes in the M1-BMDM^Wnt5a-KD group， and compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had significantly smaller Sirius Red-positive area and α-SMA-positive area and a significantly lower content of hydroxyproline in liver tissue （all P<0.05）. Compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had significant reductions in the protein and mRNA expression levels of α-SMA and the mRNA expression level of COL-I and TGF-β （all P<0.05）. Compared with the model group， all cell treatment groups had a significant increase in the protein expression level of HNF-4α in liver tissue （all P<0.05）， and the M1-BMDM^Wnt5a-KD group had significantly higher protein and mRNA expression levels of HNF-4α and hepatocyte specific antigen than the M1-BMDM^KD-EV group （both P<0.05）. The M1-BMDM^Wnt5a-KD group had a significantly higher serum level of albumin than the M1-BMDM^KD-EV group （P<0.01）. Immunofluorescence co-staining showed that compared with the model group， all cell treatment groups had a significant increase in the number of cells stained positive for HNF and HNF-4α and Ki67 （all P<0.01）， and the M1-BMDM^Wnt5a-KD group had a significantly higher number of such cells than the M1-BMDM^KD-EV group （P<0.05）. ConclusionInhibition of Wnt5a expression enhances the therapeutic effect of M1-BMDM on rats with liver cirrhosis induced by CCl₄/2-AAF， which provides new ideas for enhancing the anti-cirrhotic effect of M1-BMDM through genetic modification.

Objective To evaluate the effectiveness of a preventive workflow in participatory observation based on healthcare failure mode and effect analysis(HFMEA)in reducing intraoperative acquired pressure injury(IAPI)in patients undergoing spinal surgery,and to provide evidences for prospective nursing management.Methods A preventive workflow of participatory observation-based HFMEA was established,which included defining HFMEA topic,forming a multidisciplinary team,creating a process map(through participatory observation),conducting failure mode and hazard analysis(using a Hazard scoring matrix and decision tree analysis,and identifying the causes of key failure through Pareto chart analysis),implementing improvement actions,and tracking effectiveness.Ultimately,11 high-risk failure modes were identified for further improvement:poor design of form/information system,heavy workload and fast pace,lack of departmental regulations,risk factors of IAPI,and unclear duty and responsibility in a multidisciplinary team.A series measures for improvement were developed and implemented based on the identified key causes.A pre-and post-control study was carried out.A total of 180 patients who received spinal surgery between November and April 2024 and received traditional preventive methods were assigned to a control group.While further 218 patients who received spinal surgery between May and December 2023 were assigned to the trial group with the participatory observation on the basis of HFMEA prevention workflow.IAPI incidence rate and severity were compared between the two groups,as well as the completion rate of preoperative IAPI risk assessment in the trial group.Results The trial group demonstrated significantly lower IAPI incidence and severity compared with those in the control group(P<0.05).In the trial group,178 patients(98.92%)completed the preoperative IAPI risk assessment,and 172 patients(95.47%)completed the intraoperative assessment.Conclusion The participatory observation based HFMEA prevention workflow can effectively reduce an incidence and severity of IAPI in patients undergoing spinal surgery,ensure patient safety and thereby enhance the quality of nursing management.

Objective:To analyze the predictive role of WT1 expression levels pre-and early post-transplantation on relapse and overall survival(OS)in patients with acute myeloid leukemia(AML)undergoing allogeneic hematopoietic stem cell transplantation(allo-HSCT)during their first complete remission(CR1).Methods:A retrospective analysis was conducted on the clinical data of 107 adult AML patients who underwent allo-HSCT during their CR1 at our center between May 2012 and December 2021.The predictive role of bone marrow WT1 expression levels before transplantation and at 3 and 6 months post-transplantation on relapse and OS was explored in combination with relevant clinical factors.Results:The median follow-up time for the 107 patients was 70(range:11-117)months.Among the patients,15 cases died.Kaplan-Meier survial analysis showed that the 3-year overall survival(OS)rate was 85.0％.20 patients experienced relapse,with a median time to relapse of 8(range:0.5-44)months and a l-year cumulative relapse rate of 13.1％.The overall median value of WT1 before transplantation,3 months after transplantation,and 6 months after transplantation was 0.26％(range:0％-23.64％),with an upper quartile value of 0.74％.No statistically significant differences in WT1 expression levels were observed among the pre-transplantation,3-month post-transplantation,and 6-month post-transplantation time points(P=0.227).Univariate analysis showed that patients with WT1 levels＞0.74％at 3 months post-transplantation had a higher 1-year relapse rate(P=0.029)and lower 3-year OS rate(P＜0.001)compared to patients with WT1 levels ≤0.74％.Other significant factors affecting 1-year relapse included stem cell source(P=0.041)and chronic graft-versus-host disease(cGVHD)(P=0.013).For 3-year OS,additional influencing factors were genetic high risk(P=0.048)and stem cell source(P=0.016).Multivariate analysis revealed that WT1 level＞0.74％at 3 months post-transplantation had a trend to affect 1-year relapse rate(HR=3.309,95％CI:0.958-11.431,P=0.058),while the absence of cGVHD was an independent risk factor for 1-year relapse(HR=3.473,95％CI:0.749-16.100,P=0.037).Only WT1 level＞0.74％at 3 months post-transplantation was an independent risk factor for 3-year OS(HR=6.886,95％CI:2.402-19.738,P＜0.001).Conclusion:High WT1 expression level at 3 months post-transplantation in AML patients undergoing allo-HSCT during CR1 affects the 1-year relapse rate and 3-year OS,and is an independent risk factor affecting 3-year OS.These findings suggest that dynamic monitoring of WT1 expression levels has certain value in prognostic assessment of AML patients who received allo-HSCT during CR1.

Objective:To investigate the clinical application of ultrasound-guided cervical plexus block combined with superior laryngeal nerve block in tracheotomy for burn patients.Methods:A total of 88 burn patients who underwent tracheotomy from January 2022 to December 2022 were divided into observation group(44 cases)and matched group(44 cases).The matched group received conventional general anesthesia,while the observation group underwent ultrasound-guided cervical plexus block combined with superior laryngeal nerve block.The operation time,anesthetic effect,intraoperative hemodynamic parameters,postoperative complications,and patient satisfaction were compared.Results:The surgery time in the observation group was shorter than that in the matched group(P＜0.05).The anesthetic effect in the observation group was superior to that in the matched group,with more stable intraoperative hemodynamics,and smaller fluctuations in heart rate and mean arterial pressure(P＜0.05).The incidence of postoperative cough reflex,hoarseness,postoperative pain score,and respiratory complications in the observation group were lower than those in the matched group(P＜0.05).Patient satisfaction in the observation group was higher than that in the matched group(P＜0.05).Conclusion:Ultrasound-guided cervical plexus block combined with superior laryngeal nerve block for tracheotomy in burn patients can effectively improve anesthetic effect,reduce operation time,stabilize intraoperative hemodynamics,reduce postoperative complications,and improve patient satisfaction,which is worthy of clinical application.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.

Objective To explore the potential profile of body image and its influencing factors among head and neck cancer patients.Methods Convenience sampling was employed to investigate 335 head and neck cancer patients in a tertiary hospital in Shandong Province from October 2023 to May 2024.Data was collected using the patient's general information questionnaire,Body Image Scale,Medical Coping Modes Questionnaire,Perceived Social Support Scale,Comprehensive Score for Financial Toxicity based on the Patient-Reported Outcome Measures.Latent profile analysis and multivariate Logistic regression analysis were used to explore distinct profiles and influencing factor of body image in head and neck patients.Results A total of 335 valid questionnaires were collected in this study,and 95.4％of the valid questionnaires were included.Body image of patients with head and neck cancer could be divided into 3 latent profiles:body emotional stability(41.5％),body cognitive dissatisfaction(33.7％)and social behavior avoidance(24.8％).Age,location of cancer onset,stage of cancer,surgical treatment,medical coping style(facing coping,yielding coping),social support and economic toxicity were the factors influencing the latent profiles of body image in patients with head and neck cancer(P＜0.05).Conclusion There is heterogeneity in body image of patients with head and neck cancer.Medical staff should implement targeted management strategies based on the influencing factors of different profiles to reduce the body image disorders in patients with head and neck cancer,and to promote patients to better return to society.

Objective To analyze the association between lifestyle and the risk of type 2 diabetes(T2D)among adult residents.Methods The data was sourced from the Shanghai Suburban Adult Cohort and Biobank.A total of 42 096 adult residents who had not developed T2D were recruited from four districts of Shanghai(Songjiang,Jiading,Minhang,and Xuhui)between 2016 and 2019.The follow-up ended on Feb 28,2023.A structured questionnaire was used to collect information on six lifestyle-related items,including smoking,alcohol consumption,BMI,waist circumference(WC),physical activity,and diet.The unhealthy lifestyle scores(UHLS)were calculated by counting the number of all the unhealthy lifestyle items,with a range of 0-6.New-onset T2D events diagnosed by physicians were obtained through the medical information system.Cox proportional hazards regression model and restricted cubic spline model were utilized to evaluate the association between unhealthy lifestyles and the risk of T2D incidence.Results About 28.1%of the participants led 4-6 unhealthy lifestyles.A total of 1 752 new T2D cases were identified during 218 513.4 person-years of follow-up.Analysis of single unhealthy lifestyle showed that abnormal WC(HR=1.5,95%CI:1.4-1.7)and abnormal BMI(HR=1.3,95%CI:1.2-1.5)were associated with an increased risk of T2D.Compared with individuals with a UHLS of 0-1,those with a UHLS of 3 and 4-6 had 30%(95%CI:1.1-1.6)and 50%(95%CI:1.2-1.8)higher risks of T2D,respectively.Each additional unhealthy lifestyle was associated with a 10%increase in T2D incidence risk(HR=1.1,95%CI:1.1-1.2).Conclusion The risk of T2D in adult residents increases with the cumulative number of unhealthy lifestyles.Adult residents with abnormal WC or BMI,or have three or more unhealthy lifestyles accumulated,will increase the risk of new-onset T2D.