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Background: Carotid plaque and triglyceride-glucose (TyG) index are associated with insulin resistance. However, a highly debated question is whether there is an association between the TyG index and carotid plaque incidence. Thus we performed an in-depth longitudinal study to investigate the relationship between carotid plaque occurrence and the TyG index among Chinese individuals. Methods: Two thousand and three hundred seventy subjects (1381 males and 989 females) were enrolled and followed up for three years. The subjects were stratified into four groups based on the quartile of the TyG index at baseline. Univariate and multivariate Cox proportional hazard models were conducted to examine the role of TyG played in the carotid plaque. The strength of association was expressed as hazard ratio (HR) and 95% confidence interval (CI). Results: After three years of follow-up, 444 subjects were detected with newly formed carotid plaque. The overall 3-year cumulative carotid plaque incidence was 18.7%, and the risk of carotid plaque increased with elevated TyG index (p < 0.001). The Cox regression analysis showed that males (HR: 1.33, 95% CI: 1.10–1.61), and people with higher systolic blood pressure (HR:1.01, 95% CI: 1.01–1.02), lower high-density lipoprotein cholesterol (HR: 0.68, 95% CI: 0.50–0.93), diabetes (HR: 2.21, 95% CI: 1.64–2.97), and hypertension (HR:1.49, 95% CI: 1.23–1.81) had a significantly increased risk for the carotid plaque formation. Similar results remained in the sensitivity analysis. Conclusions: The TyG index can be used as a dose-responsive indicator of carotid plaque in the Chinese population. Elderly males with dyslipidemia, diabetes, or hypertension should be more vigilant about their TyG index since they are susceptible to developing carotid plaque. Physicians are encouraged to monitor the TyG index to help identify and treat patients with carotid plaque at an early stage. [ABSTRACT FROM AUTHOR]

Background: Ulcerative colitis (UC) is a chronic and recurrent disease without satisfactory treatment strategies. Dental pulp stem cell (DPSC) transplantation has been proposed as a potential therapy for UC. This study aimed to investigate the therapeutic effects of the rat hepatocyte growth factor (HGF) gene transduced into DPSCs for UC. Methods: The therapeutic effects of HGF-DPSCs transplanted intravenously into a rat model of UC induced by 5% dextran sulphate sodium (DSS) were compared with the other treatment groups (LV-HGF group, DPSCs group and GFP-DPSCs group). Immunofluorescence and immunohistochemistry were used to observe the localization and proliferation of HGF-DPSCs at the site of colon injury. The expression levels of inflammatory factors were detected by real-time quantitative PCR (RT-PCR) and western blotting. The oxidative stress markers were detected by ELISA. DAI scores and body weight changes were used to macroscopically evaluate the treatment of rats in each group. Results: Immunofluorescence and immunohistochemistry assays showed that HGF-DPSCs homed to colon injury sites and colocalized with intestinal stem cell (ISC) markers (Bmi1, Musashi1 and Sox9) and significantly promoted protein expression (Bmi1, Musashi1, Sox9 and PCNA). Anti-inflammatory cytokine (TGF-β and IL-10) expression was the highest in the HGF-DPSCs group compared with the other treatment groups, while the expression of pro-inflammatory cytokines (TNF-α and INF-γ) was the lowest. Additionally, the oxidative stress response results showed that malondialdehyde (MDA) and myeloperoxidase (MPO) expression decreased while superoxide dismutase (SOD) expression increased, especially in the HGF-DPSCs group. The DAI scores showed a downward trend with time in the five treatment groups, whereas body weight increased, and the changes were most prominent in the HGF-DPSCs group. Conclusions: The study indicated that HGF-DPSCs can alleviate injuries to the intestinal mucosa by transdifferentiating into ISC-like cells, promoting ISC-like cell proliferation, suppressing inflammatory responses and reducing oxidative stress damage, which provides new ideas for the clinical treatment of UC. [ABSTRACT FROM AUTHOR]

Background: Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC. Methods: We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth. Results: NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%). Conclusions: By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace [ABSTRACT FROM AUTHOR]

Background: Domains of unknown function (DUF) proteins are a number of uncharacterized and highly conserved protein families in eukaryotes. In plants, some DUFs have been predicted to play important roles in development and response to abiotic stress. Among them, DUF568-containing protein family is plant-specific and has not been described previously. A basic analysis and expression profiling was performed, and the co-expression and interaction networks were constructed to explore the functions of DUF568 family in rice. Results: The phylogenetic tree showed that the 8, 9 and 11 DUF568 family members from rice, Arabidopsis and maize were divided into three groups. The evolutionary relationship between DUF568 members in rice and maize was close, while the genes in Arabidopsis were more distantly related. The cis-elements prediction showed that over 82% of the elements upstream of OsDUF568 genes were responsive to light and phytohormones. Gene expression profile prediction and RT-qPCR experiments revealed that OsDUF568 genes were highly expressed in leaves, stems and roots of rice seedling. The expression of some OsDUF568 genes varied in response to plant hormones (abscisic acid, 6-benzylaminopurine) and abiotic stress (drought and chilling). Further analysis of the co-expression and protein–protein interaction networks using gene ontology showed that OsDUF568 − related genes were enriched in cellular transports, metabolism and processes. Conclusions: In summary, our findings suggest that the OsDUF568 family may be a vital gene family for the development of rice roots, leaves and stems. In addition, the OsDUF568 family may participate in abscisic acid and cytokinin signaling pathways, and may be related to abiotic stress resistance in these vegetative tissues of rice. [ABSTRACT FROM AUTHOR]

Background: To estimate the global disease burden of uncorrected refractive error (URE) among adolescents and assess the contributions of various risk factors to disability-adjusted life-years (DALYs) due to URE.Methods: Global, regional and country-level DALY numbers and rates due to URE among adolescents were acquired from the Global Burden of Disease Study 2019 database. Human Development Index (HDI), Socio-Demographic Index (SDI) and other country-level data were obtained from other open databases as potential indicators. Regression analysis was used to evaluate associations between DALY rates among adolescents and potential predictors.Results: Global DALYs due to URE among adolescents rose by 8% between 1990 and 2019 but moderately decreased by 4.8% during this period after adjusting for population size. Female adolescents showed higher DALY rates. DALY rates sharply increased from 5 to 9 years of age, then rose more slowly, reaching a plateau before 20 years of age. Country-level DALY rates in 2019 were positively associated with HDI, SDI, and urbanization rates but negatively correlated with primary school dropout rates. Higher disease burden of adolescents visually impaired from URE was associated with lower primary school dropout rates (β = - 0.257, 95% CI - 0.376 to - 0.138, P < 0.001) and higher urbanization rates (β = 0.257, 95% CI 0.067 to 0.256, P = 0.001).Conclusions: Higher socioeconomic status, urbanization rates and education levels are associated with a heavier disease burden of URE among adolescents. The findings of this study can provide a reference for policy making on resource allocation for URE prevention and control in teenagers. [ABSTRACT FROM AUTHOR]

Background: Liver cancer remains the leading cause of cancer death globally, and the treatment strategies are distinct for each type of malignant hepatic tumors. However, the differential diagnosis before surgery is challenging and subjective. This study aims to build an automatic diagnostic model for differentiating malignant hepatic tumors based on patients' multimodal medical data including multi-phase contrast-enhanced computed tomography and clinical features. Methods: Our study consisted of 723 patients from two centers, who were pathologically diagnosed with HCC, ICC or metastatic liver cancer. The training set and the test set consisted of 499 and 113 patients from center 1, respectively. The external test set consisted of 111 patients from center 2. We proposed a deep learning model with the modular design of SpatialExtractor-TemporalEncoder-Integration-Classifier (STIC), which take the advantage of deep CNN and gated RNN to effectively extract and integrate the diagnosis-related radiological and clinical features of patients. The code is publicly available at https://github.com/ruitian-olivia/STIC-model. Results: The STIC model achieved an accuracy of 86.2% and AUC of 0.893 for classifying HCC and ICC on the test set. When extended to differential diagnosis of malignant hepatic tumors, the STIC model achieved an accuracy of 72.6% on the test set, comparable with the diagnostic level of doctors' consensus (70.8%). With the assistance of the STIC model, doctors achieved better performance than doctors' consensus diagnosis, with an increase of 8.3% in accuracy and 26.9% in sensitivity for ICC diagnosis on average. On the external test set from center 2, the STIC model achieved an accuracy of 82.9%, which verify the model's generalization ability. Conclusions: We incorporated deep CNN and gated RNN in the STIC model design for differentiating malignant hepatic tumors based on multi-phase CECT and clinical features. Our model can assist doctors to achieve better diagnostic performance, which is expected to serve as an AI assistance system and promote the precise treatment of liver cancer. [ABSTRACT FROM AUTHOR]

Background: Although studies indicate that social support is related to emotional exhaustion, depression symptoms, and anxiety symptoms, the underlying mechanism between those variables remains unknown. Methods: Based on a sample of 254 residents in standardized residency training programs, two mediation models were tested in which emotional exhaustion served as a mediator in the relationship between social support and anxiety symptoms/depression symptoms. We used the following self-reported questionnaires as instruments to collect data: zung self-rating depression scale, zung self-rating anxiety scale, social support rating scale, and emotional exhaustion scale. Results: In the final study sample, the mean age of the residents was 25.92 years old (SD =1.88), and a total of 41.3% were male, and 58.7% were female. This current study suggested that social support was proven to be a relevant factor affecting anxiety symptoms and depression symptoms. Particularly, the results also indicated that emotional exhaustion partially mediated the impact of social support on anxiety symptoms and depression symptoms among Chinese residents in the standardized residency training program. Conclusions: Our study signifies that enhancements in social support and reduction of emotional exhaustion can directly or indirectly affect anxiety symptoms and depression symptoms among Chinese residents in the standardized residency training program. These findings will offer insight for health-sector managers to develop programs aimed at social support and adopt individual-level interventions and organization-level interventions to reduce emotional exhaustion. [ABSTRACT FROM AUTHOR]