ObjectiveTo investigate the metabolic alterations of serum short chain fatty acids （SCFAs） in pediatric patients with atopic dermatitis （AD） and their correlation with different clinical phenotypes using targeted metabolomics. MethodsThis study enrolled 87 AD patients and 67 healthy controls （HC）. Serum levels of eight SCFAs were quantified by ultra-high-performance liquid chromatography-mass spectrometry. The associations between SCFAs and AD were assessed using various statistical methods. ResultsCompared with the HC group， levels of acetic acid （AA）， propionic acid （PA）， and caproic acid （CA） （P=0.002，P=0.002，P=0.043） decreased in the AD group. Logistic regression analysis identified AA （OR=0.449， 95% CI： 0.289–0.698） and PA （OR = 0.487， 95% CI： 0.324–0.732） as protective factors against AD. The combination of AA and PA yielded an area under the curve （AUC） greater than 0.7， indicating good diagnostic efficacy. Age-stratified analysis revealed that AA reduction was predominant in childhood， whereas PA reduction was predominant in adolescence. Pathway enrichment analysis showed significant enrichment of fatty acid biosynthesis （FDR=0.341， P=0.003） and vitamin K metabolism （FDR=1， P=0.039） pathways. Furthermore， subgroup analyses based on disease severity， personal/family history of atopy， and sex revealed no significant differences in SCFAs levels among the groups. ConclusionDifferential serum SCFAs and their enriched metabolic pathways may be implicated in the pathogenesis of AD.

Objective:To investigate differences in serum lipid profiles between patients with dermatomyositis (DM) and healthy controls.Methods:A retrospective analysis was conducted on the clinical data and serum samples collected from 51 patients with DM who visited the First Affiliated Hospital, Anhui Medical University from September 2020 to January 2022. Serum samples were also collected from 66 healthy controls during the same period. Serum lipid profiles were analyzed using ultra-performance liquid chromatography-mass spectrometry in both groups. Differential lipids were screened using principal component analysis and orthogonal partial least squares-discriminant analysis. The predictive value of these differential lipids for DM was evaluated by receiver operating characteristic (ROC) curve analysis, and their correlations with clinical indicators were also evaluated.Results:A total of 51 patients with DM were enrolled, including 27 males and 24 females, with ages ( M[ Q1, Q3]) of 55.00 (47.00, 66.00) years and body mass index (BMI) values of 22.64 (19.79, 24.75) . The control group included 66 healthy individuals (33 males and 33 females) , with ages of 51.00 (43.75, 56.00) years and BMI values of 23.60 (21.18, 25.19) . No significant differences were observed between the two groups in terms of sex, age, or BMI (all P > 0.05) . A total of 341 lipid metabolites were identified, and 16 lipid metabolites such as ceramides (Cer) , sphingomyelins, phosphatidylcholines (PC) , phosphatidylethanolamines, lysophosphatidylcholines (LPC) , and triglycerides (TG) significantly differed between the DM group and the control group, of which 8 were upregulated and 8 were downregulated in the DM group. ROC curve analysis identified 7 differential lipids with area under the curve (AUC) values of > 0.9, of which 2 were Cer, 3 were TG, 1 was phosphatidylethanolamine, and 1 was LPC. In the DM patients, serum LPC (22∶1) levels were negatively correlated with creatine kinase isoenzyme MB levels ( r = -0.276, P < 0.05) , serum PC (15∶1/16∶0) levels were negatively correlated with aspartate aminotransferase levels ( r = -0.305, P < 0.05) , and serum Cer (d18∶1/18∶0) levels were positively correlated with C-reactive protein levels ( r = 0.283, P < 0.05) . Significant differences in serum lipid levels were observed between some DM subgroups (all P < 0.05) : sphingomyelin (d24∶0) levels significantly differed between anti-Sj?gren syndrome type A/Ro52 antibody-positive and -negative DM patients; LPC (17∶1) levels significantly differed between anti-PM-SCL75 antibody-positive and -negative DM patients; LPC (20∶0) and PC (32∶1p) levels significantly differed between anti-Mi-2 antibody-positive and -negative DM patients; LPC (22∶1) and TG (9∶0/9∶0/9∶0) levels significantly differed between anti-TIF1-γ antibody-positive and -negative DM patients; Cer (d18∶1/18∶0) levels significantly differed between DM patients with and without Heliotrope's sign. Conclusion:Lipid profiles were significantly altered in DM patients compared with healthy controls, and some lipids showed potential diagnostic value for DM.

Objective:To construct an indicator system for a nursing science and technology innovation curriculum guided by innovation competence, in order to provide a reference for cultivating innovation ability in nursing students.Methods:The overall research period was from March to December 2024. A nursing innovation curriculum indicator framework was initially developed through literature analysis and brainstorming. From October to December 2024, 19 experts from nine hospitals or universities across five provinces and cities were selected via purposive sampling to participate in two rounds of Delphi consultation. Revisions were made based on expert feedback.Results:Both rounds of expert consultation achieved a 100% response rate. The authority coefficient of the experts was 0.92. The final indicator system included four curriculum elements: course content, course objectives, teaching methods, and assessment, encompassing 14 first-level indicators and 40 second-level indicators.Conclusions:The innovation-oriented indicator system for nursing science and technology education demonstrates good scientific validity and reliability. It offers a foundational framework for advancing innovation-focused nursing education and curriculum design.

Objective:To construct an indicator system for a nursing science and technology innovation curriculum guided by innovation competence, in order to provide a reference for cultivating innovation ability in nursing students.Methods:The overall research period was from March to December 2024. A nursing innovation curriculum indicator framework was initially developed through literature analysis and brainstorming. From October to December 2024, 19 experts from nine hospitals or universities across five provinces and cities were selected via purposive sampling to participate in two rounds of Delphi consultation. Revisions were made based on expert feedback.Results:Both rounds of expert consultation achieved a 100% response rate. The authority coefficient of the experts was 0.92. The final indicator system included four curriculum elements: course content, course objectives, teaching methods, and assessment, encompassing 14 first-level indicators and 40 second-level indicators.Conclusions:The innovation-oriented indicator system for nursing science and technology education demonstrates good scientific validity and reliability. It offers a foundational framework for advancing innovation-focused nursing education and curriculum design.

Objective:To investigate differences in serum lipid profiles between patients with dermatomyositis (DM) and healthy controls.Methods:A retrospective analysis was conducted on the clinical data and serum samples collected from 51 patients with DM who visited the First Affiliated Hospital, Anhui Medical University from September 2020 to January 2022. Serum samples were also collected from 66 healthy controls during the same period. Serum lipid profiles were analyzed using ultra-performance liquid chromatography-mass spectrometry in both groups. Differential lipids were screened using principal component analysis and orthogonal partial least squares-discriminant analysis. The predictive value of these differential lipids for DM was evaluated by receiver operating characteristic (ROC) curve analysis, and their correlations with clinical indicators were also evaluated.Results:A total of 51 patients with DM were enrolled, including 27 males and 24 females, with ages ( M[ Q1, Q3]) of 55.00 (47.00, 66.00) years and body mass index (BMI) values of 22.64 (19.79, 24.75) . The control group included 66 healthy individuals (33 males and 33 females) , with ages of 51.00 (43.75, 56.00) years and BMI values of 23.60 (21.18, 25.19) . No significant differences were observed between the two groups in terms of sex, age, or BMI (all P > 0.05) . A total of 341 lipid metabolites were identified, and 16 lipid metabolites such as ceramides (Cer) , sphingomyelins, phosphatidylcholines (PC) , phosphatidylethanolamines, lysophosphatidylcholines (LPC) , and triglycerides (TG) significantly differed between the DM group and the control group, of which 8 were upregulated and 8 were downregulated in the DM group. ROC curve analysis identified 7 differential lipids with area under the curve (AUC) values of > 0.9, of which 2 were Cer, 3 were TG, 1 was phosphatidylethanolamine, and 1 was LPC. In the DM patients, serum LPC (22∶1) levels were negatively correlated with creatine kinase isoenzyme MB levels ( r = -0.276, P < 0.05) , serum PC (15∶1/16∶0) levels were negatively correlated with aspartate aminotransferase levels ( r = -0.305, P < 0.05) , and serum Cer (d18∶1/18∶0) levels were positively correlated with C-reactive protein levels ( r = 0.283, P < 0.05) . Significant differences in serum lipid levels were observed between some DM subgroups (all P < 0.05) : sphingomyelin (d24∶0) levels significantly differed between anti-Sj?gren syndrome type A/Ro52 antibody-positive and -negative DM patients; LPC (17∶1) levels significantly differed between anti-PM-SCL75 antibody-positive and -negative DM patients; LPC (20∶0) and PC (32∶1p) levels significantly differed between anti-Mi-2 antibody-positive and -negative DM patients; LPC (22∶1) and TG (9∶0/9∶0/9∶0) levels significantly differed between anti-TIF1-γ antibody-positive and -negative DM patients; Cer (d18∶1/18∶0) levels significantly differed between DM patients with and without Heliotrope's sign. Conclusion:Lipid profiles were significantly altered in DM patients compared with healthy controls, and some lipids showed potential diagnostic value for DM.

Background::In the clinic, practitioners encounter many patients with an abnormal pattern of dense punctate magnetic resonance imaging (MRI) signal in the basal ganglia, a phenomenon known as "cheese sign". This sign is reported as common in cerebrovascular diseases, dementia, and old age. Recently, cheese sign has been speculated to consist of dense perivascular space (PVS). This study aimed to assess the lesion types of cheese sign and analyze the correlation between this sign and vascular disease risk factors.Methods::A total of 812 patients from Peking Union Medical College Hospital (PUMCH) dementia cohort were enrolled. We analyzed the relationship between cheese sign and vascular risk. For assessing cheese sign and defining its degree, the abnormal punctate signals were classified into basal ganglia hyperintensity (BGH), PVS, lacunae/infarctions and microbleeds, and counted separately. Each type of lesion was rated on a four-level scale, and then the sum was calculated; this total was defined as the cheese sign score. Fazekas and Age-Related White Matter Changes (ARWMC) scores were used to evaluate the paraventricular, deep, and subcortical gray/white matter hyperintensities.Results::A total of 118 patients (14.5%) in this dementia cohort were found to have cheese sign. Age (odds ratio [OR]: 1.090, 95% confidence interval [CI]: 1.064-1.120, P <0.001), hypertension (OR: 1.828, 95% CI: 1.123-2.983, P = 0.014), and stroke (OR: 1.901, 95% CI: 1.092-3.259, P = 0.025) were risk factors for cheese sign. There was no significant relationship between diabetes, hyperlipidemia, and cheese sign. The main components of cheese sign were BGH, PVS, and lacunae/infarction. The proportion of PVS increased with cheese sign severity. Conclusions::The risk factors for cheese sign were hypertension, age, and stroke. Cheese sign consists of BGH, PVS, and lacunae/infarction.

Objective:We aimed to develop a novel visualized model based on nomogram to predict postoperative overall survival.Methods:This was a multicenter, retrospective, observational cohort study, including participants with histologically confirmed gastric and colorectal cancer who underwent radical surgery from 11 medical centers in China from August 1, 2015 to June 30, 2018. Baseline characteristics, histopathological data and nutritional status, as assessed using Nutrition Risk Screening 2002 (NRS 2002) score and the scored Patient-Generated Subjective Global Assessment, were collected. The least absolute shrinkage and selection operator regression and Cox regression were used to identify variables to be included in the predictive model. Internal and external validations were performed.Results:There were 681 and 127 patients in the training and validation cohorts, respectively. A total of 188 deaths were observed over a median follow-up period of 59 (range: 58 to 60) months. Two independent predictors of NRS 2002 and Tumor-Node-Metastasis (TNM) stage were identified and incorporated into the prediction nomogram model together with the factor of age. The model's concordance index for 1-, 3- and 5-year overall survival was 0.696, 0.724, and 0.738 in the training cohort and 0.801, 0.812, and 0.793 in the validation cohort, respectively.Conclusions:In this study, a new nomogram prediction model based on NRS 2002 score was developed and validated for predicting the overall postoperative survival of patients with gastric colorectal cancer. This model has good differentiation, calibration and clinical practicability in predicting the long-term survival rate of patients with gastrointestinal cancer after radical surgery.

The ApoE gene is a genetic risk determinant for sporadic Alzheimer′s disease (AD). The ApoEε4 allele increases the risk of developing AD relative to the common ApoEε3 allele, whereas the ApoEε2 allele decreases the risk of developing the disease. The 3 alleles encode ApoE2, ApoE3, and ApoE4 protein isoforms, respectively. ApoE4 contributes to the pathogenesis of AD by regulating β-amyloid protein, tau protein, transactive response DNA-binding protein-43, neuroinflammation, and cerebral vascular function. The pathways associated with ApoE also offer new opportunities for the treatment of AD. In addition, studies have shown that ApoE4 also plays a toxic role in other neurological disorders. This article described the biological characteristics of ApoE, as well as the impact of ApoE4 on AD and related dementias, aiming to enhance clinical doctors′ understanding of the involvement of ApoE4 in the pathogenesis of AD and related dementia.