Sumei Xu

Latent autoimmune diabetes in adults (LADA) is clinically between type 2 and type 1 diabetes with progressive autoimmune loss of β-cells and variable insulin dependence. Lactate was once thought to be a glucan byproduct and is now recognized as a signaling enzyme regulating gene expression via lysine lactylation. One of these marks is histone H3 lysine 18 lactylation (H3K18la), which is enriched at active enhancers and links immune genes. We examined literature and systematically distinguished direct LADA evidence from inferences from studies of type 1 diabetes, β-cell biology, autoimmune disease, and cancer. Present data posits elevated lactate and H3K9la in cell dedifferentiation, and H3K18la has stronger mechanistic support in immune regulation and enhancer activity. Cell-type-specific validation in longitudinal LADA cohorts and disease-specific experiments is lacking. We consider H3K18la a biologically plausible mechanism of LADA pathogenesis rather than an established driver. We emphasize that biomarker development or therapeutic translation will require strict LADA-specific evidence.

Background: Autophagy is a cellular process in which damaged organelles or unnecessary proteins are encapsulated into double-membrane structures and transported to lysosomes for degradation. Autophagy plays a crucial role in various liver diseases, including nonalcoholic fatty liver disease. This study aims to elucidate the role of autophagy in nonalcoholic fatty liver disease through bibliometric analysis. Methods: Literature was retrieved from Web of Science CoreCollection database, and the search time was from January 01, 2004 to December 31, 2023. Data retrieval was performed using the Bibliometrix package in R software. VOSviewer and CiteSpace were utilized to visualize the research hotspots and trends related to the effect of autophagy on nonalcoholic fatty liver disease. Results: A total of 966 papers were obtained, published in 343 journals from 1385 institutions across 57 countries. The journals with the most publications were the “International Journal of Molecular Sciences” and “Scientific Reports.” China had the highest number of published papers. The most productive authors were Yen Paul M and Jung Tae Woo, while Singh R was the most frequently co-cited author. Emerging research hotspots were associated with keywords such as insulin resistance, ferroptosis, endoplasmic reticulum stress, and mitochondrial function. Conclusion: Research on autophagy in nonalcoholic fatty liver disease is still in its early stages, with a growing body of literature. This study is the first to provide a comprehensive bibliometric analysis, synthesizing research trends and advancements. It identifies current development trends, global cooperation models, foundational knowledge, research hotspots, and emerging frontiers in the field.

Shenqi pill (SQP), a famous traditional Chinese medicine (TCM) herbal formula derived from Jinguiyaolue (Synopsis of Prescriptions of the Golden Chamber), has long been used to treat kidney yang deficiency syndrome. According to the TCM treatment principle that the liver and kidney are homologies, the clinical use of SQP in the treatment of nonalcoholic steatohepatitis (NASH) has achieved a good effect. However, the active targeted genes and underlying mechanism remain unclear. In this study, we aimed to explore the treatment mechanism of SQP in NASH rats, which may further contribute to the in-depth exploration of SQP in clinical applications. Network pharmacology analysis was used to screen the target genes of SQP for NASH treatment based on public databases. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and proteinprotein interaction (PPI) analysis were used to search for crucial target genes and mechanisms. UPLCMS/MS was used to verify the active compounds of the SQP screened. The hepatic pathology and biochemical indicators of rats were used to judge the modeling results and the curative effect of SQP. Western blotting and qRTPCR were used to verify the expression of crucial target genes at the protein and RNA levels, respectively. Network pharmacology analysis and bioinformatics analysis showed that PTGS2, JUN, MYC, and CDKN1A might be crucial target genes in the primary mechanism of SQP in treating NASH and improving the inflammatory response. The UPLCMS/MS results confirmed that the hub active compound, quercetin, screened out through the TCMSP database, is indeed present in SQP. Hepatic injury and lipid metabolism indicators of NASH rats were significantly improved after SQP treatment. The results of WB and qRTPCR showed that the expression of PTGS2, JUN, MYC, and CDKN1A was higher in NASH rats than in normal rats and decreased after SQP treatment. The expression of inflammatory cytokines (IL-1β, IL-6, TNF-α) was reduced after SQP treatment, which confirmed that SQP could improve hepatic inflammation in rats. These results suggested that SQP could ameliorate NASH in rats, and that quercetin may be the critical active compound that exerts the therapeutic effect.

Background: The prevalence of NAFLD is increasing annually. The early diagnosis and control are crucial for the disease. Currently, metabolic indicators are always used clinically as an auxiliary diagnosis of NAFLD. However, the prevalence of NAFLD is not only increased in obese/metabolic-disordered populations. NAFLD patients with thin body are also increasing. Only using metabolic indicators to assist in the diagnosis of NAFLD may have some deficiencies. Continue to develop more clinical auxiliary diagnostic indicators is pressing. Methods: Machine learning methods are applied to capture risk factors for NAFLD in 365 adults from Zhejiang Province. Predictive models are constructed for NAFLD using fibrinolytic indicators and metabolic indicators as predictors respectively. Then the predictive effects are compared; ELISA kits were used to detect the blood indicators of non-NAFLD and NAFLD patients and compare the differences. Results: The prediction accuracy for NAFLD based on fibrinolytic indicators [Tissue Plasminogen Activator (TPA), Plasminogen Activator Inhibitor-1 (PAI-1)] is higher than that based on metabolic indicators. TPA and PAI-1 are more suitable than metabolic indicators to be selected to predict NAFLD. Conclusions: The fibrinolytic indicators have a stronger association with NAFLD than metabolic indicators. We should attach more importance to TPA and PAI-1, in addition to TC, HDL-C, LDL-C, and ALT/AST, when conducting blood tests to assess NAFLD.

Background: In China, the prevalence and mortality of colorectal cancer (CRC) have always been high, and more than 95% of CRC cases have evolved from colorectal polyps (CPs), especially adenoma. Early detection and treatment of CPs through colonoscopy is essential to reduce the incidence of CRC. Helicobacter pylori (Hp) is regarded as a risk factor for gastritis and gastric cancer and may also be a risk factor for CPs and CRC. However, few studies based on vast clinical cases exist in China to clarify whether Hp is a risk factor for CPs and CRC, and whether Hp-positive patients need to undergo colonoscopy checks earlier. This article attempts to make up for that deficiency.Method: This cross-sectional study was conducted based on 13,037 patients without a treatment history of Hp who underwent their first gastroscopy and colonoscopy simultaneously at The First Affiliated Hospital of Zhejiang Chinese Medical University from January 2018 to December 2019. Pearson χ² test and logistic regression were used to determine whether Hp is a risk factor for CPs and CRC. Multifactor analysis of variance was used to define the impact of Hp on CPs prevalence with different ages, sexes.Results: For Chinese individuals, Hp is a risk factor for CPs and CRC. The odds ratio (OR) value are 1.228 (95% CI, 1.130 to 1.336) and 1.862 (95% CI 1.240-2.796), respectively. Hp-positive patients have a higher probability of multiple or large intestinal polyps. However, Hp infection does not increase the incidence of adenomas, nor does it affect the pathological type of adenomas. The OR of Hp on the risk of CPs was 1.432 (95%CI 1.275-1.608) for males but increased to 1.937 (95%CI 1.334-2.815) for those aged 35 to 40. For females, the results were similar.Conclusions: For the Chinese, Hp is a risk factor for CPs and CRC (OR>1); the infection of Hp increased CPs risk in Chinese of all ages, especially aged 35-40, suggesting that Hp-positive patients should undergo colonoscopy frequently.

Background: Colon cancer is a worldwide leading cause of cancer-related mortality, and the prognosis of colon cancer is still needed to be improved. This study aimed to construct a prognostic model for predicting the prognosis of colon cancer.Methods: The gene expression profile data of colon cancer were obtained from the TCGA, GSE44861, and GSE44076 datasets. The WGCNA module genes and common differentially expressed genes (DEGs) were used to screen out the prognosis-associated DEGs, which were used to construct a prognostic model. The performance of the prognostic model was assessed and validated in the TCGA training and microarray validation sets (GSE38832 and GSE17538). At last, the model and prognosis-associated clinical factors were used for the construction of the nomogram.Results: Five colon cancer-related WGCNA modules (including 1160 genes) and 1153 DEGs between tumor and normal tissues were identified, inclusive of 556 overlapping DEGs. Stepwise Cox regression analyses identified there were 14 prognosis-associated DEGs, of which 12 DEGs were included in the optimized prognostic gene signature. This prognostic model presented a high forecast ability for the prognosis of colon cancer both in the TCGA training dataset and the validation datasets (GSE38832 and GSE17538; AUC > 0.8). In addition, patients’ age, T classification, recurrence status, and prognostic risk score were associated with the prognosis of TCGA patients with colon cancer. The nomogram was constructed using the above factors, and the predictive 3- and 5-year survival probabilities had high compliance with the actual survival proportions.Conclusions: The 12-gene signature prognostic model had a high predictive ability for the prognosis of colon cancer.

Background This study aimed to construct prognostic model by screening prognostic gene signature of colon cancer. Methods The gene expression profile data of colon cancer were obtained from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) and differently expressed genes (DEGs) between tumor and control samples were identified. Prognosis-associated genes were then identified and used for the construction of prognostic model. The independent factors that associated with the prognosis of colon in the TCGA cohort was identified. Results Totally, 1153 consistent DEGs were screened out between tumor and normal tissues in the TCGA cohort, GSE44861 and GSE44076 datasets. Among these genes, 12 DEGs were related to the prognosis of colon cancer and were used for constructing the prognostic model. This model presented a high predictive power for the prognosis of colon cancer both in the training dataset and in the validation datasets (AUC > 0.8). Statistical analysis showed that age, pathological T, tumor recurrence, and model status were the independent factors for prognosis of patients with colon cancer in TCGA. Conclusions The 12-gene signature prognostic model had a high predictive power for colon cancer prognosis.