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Abstract The global rise in prediabetes and diabetes, with type 2 diabetes (T2DM) being predominant, highlights the association between T2DM and hypertriglyceridemia (HTG). Patients with both abnormal glucose levels and HTG require increased attention due to higher risks of complications and mortality. Therefore, this study aimed to find the key long non-coding RNA (lncRNA) of HTG in the abnormal glucose metabolism patients. We collected blood samples for RNA sequencing experiments and blood samples for validation in population. We have conducted RNA sequencing, weighted gene co-expression network analysis (WGCNA), quantitative real‐time polymerase chain reaction (qRT-PCR) in a 82-vs-82-sample-size population and insulin induced HepG2, RNA- Fluorescence in situ hybridization (FISH) and Cell Counting Kit-8 (CCK-8). We also explored lipid metabolism related transcription factor and the related protein expression and processed key lncRNA by both interference expression and overexpression, and the related consequences were rescued by its target mRNA. ENST00000540317.5 (LINC317.5) was lower in HTG with abnormal glucose metabolism and was found in both cytoplasm and nucleus in HepG2, inversely regulating the accumulation of TG and its target mRNA TKFC. Relative expression of peroxisome proliferator-activated receptor alpha (PPARα) and peroxisome proliferator-activated receptor gamma (PPARγ) were decreasing, and SREBP-1c (sterol regulatory element-binding protein-1c) was increasing of the interference expression of LINC317.5. Interference expression of LINC317.5 significantly decreased the protein expression of ACADM and CPT1A, whereas increased the protein expression of FAS and ACC1. TKFC partly reduced the triglyceride (TG) accumulation of LINC317.5. In conclusion, we suggested LINC317.5-TKFC as a key for TG accumulation in the HepG2-insulin resistant (IR). These might provide information of non-invasive biomarkers for the HTG with abnormal glucose.

Abstract Background The association between sensory impairment including vision impairment (VI), hearing impairment (HI), dual impairment (DI) and the functional limitations of SCD (SCD-related FL) are still unclear in middle-aged and older people. Methods 162,083 participants from BRFSS in 2019 to 2020 was used in this cross-sectional study. After adjusting the weights, multiple logistic regression was used to study the relationship between sensory impairment and SCD or SCD-related FL. In addition, we performed subgroup analysis on the basis of interaction between sensory impairment and covariates. Results Participants who reported sensory impairment were more likely to report SCD or SCD-related FL compared to those without sensory impairment (p

Abstract Objective To evaluate whether the presence of human papillomavirus (HPV) DNA and p16 might be associated with better prognosis in patients with hypopharyngeal carcinoma (HPC), especially on overall survival (OS) and disease-free survival (DFS). Method PubMed, the Cochrane Library, the Web of Science and EMBASE were searched from inception to April 2021 to search for HPV DNA- and p16-related prognostic articles on HPC. Meta-analysis was performed on the selected articles according to the inclusion and exclusion criteria. Publication bias was assessed for the included studies with Egger’s test. All studies were analyzed by using Stata 16.0 statistical software. Results A total of 18 studies were included, including 12 HPV DNA studies and 11 p16 studies. Meta-analysis showed that HPV DNA positivity was a strong prognostic factor for improved OS in patients with HPC, with a pooled hazard ratio (HR) of 0.61 (95% CI, 0.54–0.69), but there was no statistically significant difference in DFS (HR, 0.60; 95% CI, 0.31–1.16). Patients with p16-positive tumors had better OS (HR, 0.66; 95% CI, 0.49–0.89) and DFS (HR, 0.59; 95% CI, 0.44–0.78) than patients with p16-negative tumors. Conclusions This study suggests that the presence of HPV DNA leads to better OS in patients with HPC, and the presence of p16 also corresponds to better OS and DFS. Our results provide up-to-date evidence to clinicians and researchers. Larger studies adjusting for prognostic factors are needed in subsequent studies.

Abstract Background Hypertriglyceridemia (HTG) is one of the most important comorbidities in abnormal glucose patients. The aim of this study was to identify lncRNAs functional modules and hub genes related to triglyceride (TG) in prediabetes. Methods The study included 12 prediabetic patients: 6 participants with HTG and 6 participants with normal triglyceride (NTG). Whole peripheral blood RNA sequencing was performed for these samples to establish a lncRNA library. WGCNA, KEGG pathways analysis and the PPI network were used to construct co‐expression network, to obtain modules related to blood glucose, and to detect key lncRNAs. Meanwhile, GEO database and qRT-PCR were used to validate above key lncRNAs. Results We found out that the TCONS_00334653 and PVT1, whose target mRNA are MYC and HIST1H2BM, were downregulating in the prediabetes with HTG. Moreover, both of TCONS_00334653 and PVT1 were validated in the GEO database and qRT-PCR. Conclusions Therefore, the TCONS_00334653 and PVT1 were detected the key lncRNAs for the prediabetes with HTG, which might be a potential therapeutic or diagnostic target for the treatment of prediabetes with HTG according to the results of validation in the GEO database, qRT-PCR and ROC curves.

Ground-level ozone (O3) is a well-known atmospheric pollutant aside from particulate matter. China as a global populous country is facing serious surface O3 pollution. To detect the complex spatiotemporal transformation of the population exposure to ambient O3 pollution in China from 2005 to 2019, the Bayesian multi-stage spatiotemporal evolution hierarchy model was employed. To insight the drivers of the population exposure to ambient O3 pollution in China, a Bayesian spatiotemporal LASSO regression model (BST-LASSO-RM) and a spatiotemporal propensity score matching (STPSM) were firstly applied; then, a spatiotemporal causal inference method integrating the BST-LASSO-RM and STPSM was presented. The results show that the spatial pattern of the annual population-weighted ground-level O3 (PWGLO3) concentrations, representing population exposure to ambient O3, in China has transformed since 2014. Most regions (72.2%) experienced a decreasing trend in PWGLO3 pollution in the early stage, but in the late stage, most areas (79.3%) underwent an increasing trend. Some drivers on PWGLO3 concentrations have partial spatial spillover effects. The PWGLO3 concentrations in a region can be driven by this region’s surrounding areas’ economic factors, wind speed, and PWGLO3 concentrations. The major drivers with six local factors in 2005–2014 changed to five local factors and one spatial adjacent factor in 2015–2019. The driving of the traffic and green factors have no spatial spillover effects. Three traffic factors showed a negative driving effect in the early stage, but only one, bus ridership per capita (BRPC), retains the negative driving effect in the late stage. The factor with the maximum driving contribution is BRPC in the early stage, but PM2.5 pollution in the late stage, and the corresponding driving contribution is 17.57%. Green area per capita and urban green coverage rates have positive driving effects. The driving effects of the climate factors intensified from the early to the later stage.

This meta-analysis aimed to systematically investigate whether vitamin D supplementation reduces blood lipid—total cholesterol (TC), LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), and triglyceride (TG)—levels in prediabetic individuals. Pubmed, Web of Science, Cochrane Library, Embase, CNKI, and WANFANG databases were searched for studies published before 13 February 2022 (including 13 February 2022). Five articles were included. The results showed that vitamin D intervention led to a significant reduction in TG compared with control or placebo treatment (−0.42 [−0.59, −0.25], P < 0.001). Subgroup analyses showed that this effect was particularly significant among the studies that included obese subjects (−0.46 [−0.65, −0.28], P < 0.001), the studies that also included men (not only women) (−0.56 [−0.78, −0.34], P < 0.001), and the studies with intervention durations longer than 1 year (−0.46 [−0.65, −0.28], P < 0.001). Both relatively low doses of 2,857 IU/day (−0.65 [−0.92, −0.38], P < 0.001) and relatively high doses of 8,571 IU/day (−0.28 [−0.54, −0.02] P = 0.04) of vitamin D supplementation reduced TG levels, and the effect was observed both in Northern Europe (−0.65 [−0.92, −0.38], P < 0.001) and Asian (−0.25 [−0.48, −0.03], P = 0.03) country subgroups. No significant effects on TC, HDL-C, and LDL-C were shown. In conclusion, vitamin D supplementation might beneficially affect TG levels in individuals with prediabetes. Particularly longer durations of treatment, more than 1 year, with doses that correct vitamin deficiency/insufficiency, can have a beneficial effect. This meta-analysis was registered at www.crd.york.ac.uk/prospero (CRD42020160780).

AimsCognitive impairment is an increasingly urgent global public health challenge. Dietary Inflammatory Index (DII) is a literature-derived score that links diet to inflammation. The relationship between DII and cognitive impairment remains controversial. Therefore, our study aimed to analysis the role of DII on the risk of cognitive impairment by meta-analysis.MethodsPubMed, Cochrane Library, MEDLINE, Web of Science and EMBASE databases were searched up to July 2022. Newcastle–Ottawa scale (NOS) and Joanna Briggs Institute (JBI) Checklist were performed to estimate the quality of studies.ResultsNine observational studies with 19,379 subjects were included. Our study found that higher DII could elevate the risk of cognitive impairment (OR = 1.46, 95%CI = 1.26, 1.69). Meanwhile, the OR of cognitive impairment was 1.49 (95%CI = 1.21, 1.83) for cross-sectional studies and 1.42 (95%CI = 1.12, 1.79) for cohort studies, respectively.ConclusionOur meta-analysis indicated that higher DII (indicating a more pro-inflammatory diet) is related to increased risk of cognitive impairment.

ObjectiveWe aimed to investigate the association between different eating habit patterns and mental health problems among Chinese middle and high school students, and further to estimate the interaction effect of different grouping variables on eating habits.MethodsOne thousand three hundred and forty-eight adolescents from Jilin Province in China were involved in this cross-sectional study. Mental health and eating habits were assessed using General Health Questionnaire and questions on Nutrition Knowledge, Attitude and Practice, respectively. Latent class analysis (LCA) was performed to identify eating habit patterns. Binary logistic regression and generalized linear models were used to explore the association between eating habit patterns, energy-adjusted nutrient intakes and mental health problems. Interaction analysis was performed to analyze the association between eating habits and mental health in different groups.ResultsBased on the LCA results, a 3-class parallel model was identified: 648 adolescents (48.1%) were classified in class-1 “Healthy Eating Behavior/Eating at Home,” 452 adolescents (33.5%) in class-2 “Healthy Eating Behavior/Eating at School” and 248 adolescents (18.4%) in class-3 “Unhealthy Eating Behavior/Random Place.” Compared with class-1, participants in class-2 and class-3 were at higher risk of mental health problems, especially for class-3 (p < 0.05). The energy and nutrient intakes by different latent classes showed that adolescents who ate unhealthy had lower daily intake of energy, protein, carbohydrate, fiber, Vitamins and minerals (p < 0.05). The interaction between age, sleep duration and different eating habits was statistically significant (p for interaction < 0.1).Conclusion“Unhealthy eating behavior/random place pattern” was positively correlated with mental health problems of adolescents. The adolescents with health diet were accompanied by fewer mental health problems, especially for that eating at home. And there were interactions between eating habits and age, sleep duration on the mental health problems.

Non-alcoholic fatty liver disease (NAFLD) has recently become the most common liver disease with a global prevalence of over 25% and is expected to increase. Recently, experts have reached a consensus that “fatty liver disease associated with metabolic dysfunction or MAFLD” may be a more appropriate and inclusive definition than NAFLD. Like the former name NAFLD, MAFLD, as a manifestation of multiple system metabolic disorders involving the liver, has certain heterogeneity in its pathogenesis, clinical manifestations, pathological changes and natural outcomes. We found that there is a delicate dynamic balance among intestinal microflora, metabolites and host immune system to maintain a healthy intestinal environment and host health. On the contrary, this imbalance is related to diseases such as MAFLD. However, there are no clear studies on how dietary nutrients affect the intestinal environment and participate in the pathogenesis of MAFLD. This review summarizes the interactions among dietary nutrients, intestinal microbiota and MAFLD in an attempt to provide evidence for the use of dietary supplements to regulate liver function in patients with MAFLD. These dietary nutrients influence the development and progression of MAFLD mainly through the hepatic-intestinal axis by altering dietary energy absorption, regulating bile acid metabolism, changing intestinal permeability and producing ethanol. Meanwhile, the nutrients have the ability to combat MAFLD in terms of enriching abundance of intestinal microbiota, reducing Firmicutes/Bacteroidetes ratio and promoting abundance of beneficial gut microbes. Therefore, family therapy with MAFLD using a reasonable diet could be considered.

ObjectiveThe purpose of this study was to evaluate the association between triglyceride glucose (TyG) index and new-onset diabetes under different glycemic states and to compare the predictive value of TyG−related parameters, obesity indices, and lipid ratios for new-onset diabetes.MethodsData were collected from the China Health and Retirement Longitudinal Study (CHARLS), consisting of 6,258 participants aged ≥45 years. Participants were grouped according to their glycemic states. Cox proportional hazards models and restricted cubic spline regression were used to explore the association between TyG index and diabetes. Cox proportional hazard models were applied to confirm the predictive value of the optimal marker. Receiver operating characteristic (ROC) curves were used to compare the predictive value.ResultsTyG index was positively correlated with the risk of diabetes (hazard ratio (HR), 1.75; 95% confidence interval (CI), 1.56–1.97), and the linear association existed (p

AimsPrevalence of prediabetes and type 2 diabetes mellitus(T2DM) are increasing worldwide. Key lncRNAs were detected to provide a reference for searching potential biomarkers of prediabetes and T2DM in hypertriglyceridemia patients.MethodsThe study included 18 hypertriglyceridemia patients: 6 newly diagnosed type 2 diabetes patients, 6 samples with prediabetes and 6 samples with normal blood glucose. Weighted gene co-expression network analysis (WGCNA) was conducted to construct co‐expression network and obtain modules related to blood glucose, thus detecting key lncRNAs.ResultsThe green, yellow and yellow module was significantly related to blood glucose in T2DM versus normal controls, T2DM versus prediabetes, prediabetes versus normal controls, respectively. ENST00000503273, ENST00000462720, ENST00000480633 and ENST00000485392 were detected as key lncRNAs for the above three groups, respectively.ConclusionsFor hypertriglyceridemia patients with different blood glucose levels, ENST00000503273, ENST00000462720 and ENST00000480633 could be potential biomarkers of T2DM.

This study explored the roles of epidemic-spread-related behaviors, vaccination status and weather factors during the COVID-19 epidemic in 50 U.S. states since March 2020. Data from March 1, 2020 to February 5, 2022 were incorporated into panel model. The states were clustered by the k-means method. In addition to discussing the whole time period, we also took multiple events nodes into account and analyzed the data in different time periods respectively by panel linear regression method. In addition, influence of cluster grouping and different incubation periods were been discussed. Non-segmented analysis showed the rate of people staying at home and the vaccination dose per capita were significantly negatively correlated with the daily incidence rate, while the number of long-distance trips was positively correlated. Weather indicators also had a negative effect to a certain extent. Most segmental results support the above view. The vaccination dose per capita was unsurprisingly proved to be the most significant factor especially for epidemic dominated by Omicron strains. 7-day was a more robust incubation period with the best model fit while weather had different effects on the epidemic spread in different time period. The implementation of prevention behaviors and the promotion of vaccination may have a successful control effect on COVID-19, including variants' epidemic such as Omicron. The spread of COVID-19 also might be associated with weather, albeit to a lesser extent.

Purpose: To develop a nomogram for predicting the prognosis of T1 esophageal squamous cell carcinoma (ESCC) patients with positive lymph node. Methods: T1 ESCC patients with lymph node metastasis diagnosed between 2010 and 2015 were selected from the Surveillance, Epidemiology, and Final Results (SEER) database. The entire cohort was randomly divided in the ratio of 7:3 into a training group (n=457) and validation group (n=192), respectively. Prognostic factors were identified by univariate and multivariate Cox regression models. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to evaluate the discrimination and calibration of the nomogram. The accuracy and clinical net benefit of the nomogram compared with the 7th AJCC staging system were evaluated using net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Results: The nomogram consisted of eight factors: insurance, T stage, summary stage, primary site, radiation code, chemotherapy, surgery, and radiation sequence with surgery. In the training and validation cohorts, the AUCs exceeded 0.700, and the C-index scores were 0.749 and 0.751, respectively, indicating that the nomogram had good discrimination. The consistency between the survival probability predicted by the nomogram and the actual observed probability was indicated by the calibration curve in the training and validation cohorts. For NRI>0 and IDI>0, the predictive power of the nomogram was more accurate than that of the 7th AJCC staging system. Furthermore, the DCA curve indicated that the nomogram achieved better clinical utility than the traditional system. Conclusions: Unlike the 7th AJCC staging system, the developed and validated nomogram can help clinical staff to more accurately, personally and comprehensively predict the 1-year and 3-year OS probability of T1 ESCC patients with lymph node metastasis.

The emotion-cause pair extraction task is a fine-grained task in text sentiment analysis, which aims to extract all emotions and their underlying causes in a document. Recent studies have addressed the emotion-cause pair extraction task in a step-by-step manner, i.e., the two subtasks of emotion extraction and cause extraction are completed first, followed by the pairing task of emotion-cause pairs. However, this fail to deal well with the potential relationship between the two subtasks and the extraction task of emotion-cause pairs. At the same time, the grammatical information contained in the document itself is ignored. To address the above issues, we propose a deep neural network based on span association prediction for the task of emotion-cause pair extraction, exploiting general grammatical conventions to span-encode sentences. We use the span association pairing method to obtain candidate emotion-cause pairs, and establish a multi-dimensional information interaction mechanism to screen candidate emotion-cause pairs. Experimental results on a quasi-baseline corpus show that our model can accurately extract potential emotion-cause pairs and outperform existing baselines.

This study identified maths motivation profiles in a sample of 878 Chinese secondary school students, and examined the effects of perceived parent/teacher achievement goals on maths motivation profiles and the effects of the latter on academic outcomes. Latent profile analysis conducting on three achievement goals (mastery-approach, performance-approach, and performance-avoidance) and four interest components (emotion, value, knowledge, engagement) identified four profiles: "medium, high all, low, and high mastery-oriented and interest." Students who perceived more parent/teacher mastery-approach and performance-approach goals were more likely to belong to the high all profiles. Students with the high all and the high mastery-oriented and interest profiles showed the highest use of deep and surface learning strategies and maths achievement. The results revealed distinct motivational profiles by integrating achievement goal theory and four-phase interest development theory, and provided preliminary evidence to help parents and teachers enhance students' maths motivation.