A Critical Review on Recent Progress of Solution-Processed Monolayer Assembly of Nanomaterials and Applications.

The rapid development in nanotechnology has necessitated accurate and efficient assembly strategies for nanomaterials. Monolayer assembly of nanomaterials (MAN) represents a challenging and important architecture to manufacture and is critical in understanding interactions among nanomaterials, solvents, and substrates. MAN enables highly tunable performance in electronic and photonic devices. This review summarizes the recent progress on the methods to achieve MAN and discusses important control factors. Moreover, the importance of MAN is elaborated by a broad range of applications in electronics and photonics. In the end, the opportunities as well as challenges in manufacturing and new applications are outlooked.

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as vaccines and receptor decoys. However, the continuous mutating coronavirus, especially the variants of Delta and Omicron, are tended to invalidate the therapeutic biological product. Thus, it is necessary to develop molecular entities as broad-spectrum antiviral drugs. Coronavirus replication is controlled by the viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme, which is required for the virus's life cycle. In the cases of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV), 3CLpro has been shown to be a promising therapeutic development target. Here we proposed an attention-based deep learning framework for molecular graphs and sequences, training from the BindingDB 3CLpro dataset (114,555 compounds). After construction of such model, we conducted large-scale screening the in vivo/vitro dataset (276,003 compounds) from Zinc Database and visualize the candidate compounds with attention score. geometric-based affinity prediction was employed for validation. Finally, we established a 3CLpro-specific deep learning framework, namely GraphDPI-3CL (AUROC: 0.958) achieved superior performance beyond the existing state of the art model and discovered 10 molecules with a high binding affinity of 3CLpro and superior binding mode.

A review on fermented vegetables: Microbial community and potential upgrading strategy via inoculated fermentation.

Fermentation is a traditional method utilized for vegetable preservation, with microorganisms playing a crucial role in the process. Nowadays, traditional spontaneous fermentation methods are widely employed, which excessively depend on the microorganisms attached to the surface of raw materials, resulting in great difficulties in ideal control over the fermentation process. To achieve standardized production and improve product quality, it is essential to promote inoculated fermentation. In this way, starter cultures can dominate the fermentation processes successfully. Unfortunately, inoculated fermentation has not been thoroughly studied and applied. Therefore, this paper provides a systematic review of the potential upgrading strategy of vegetable fermentation technology. First, we disclose the microbial community structures and succession rules in some typical spontaneously fermented vegetables to comprehend the microbial fermentation processes well. Then, internal and external factors affecting microorganisms are explored to provide references for the selection of fermented materials and conditions. Besides, we widely summarize the potential starter candidates with various characteristics isolated from spontaneously fermented products. Subsequently, we exhibited the inoculated fermentation strategies with those isolations. To optimize the product quality, not only lactic acid bacteria that lead the fermentation, but also yeasts that contribute to aroma formation should be combined for inoculation. The inoculation order of the starter cultures also affects the microbial fermentation. It is equally important to choose a proper processing method to guarantee the activity and convenience of starter cultures. Only in this way can we achieve the transition from traditional spontaneous fermentation to modern inoculated fermentation.

Heterologous expression of P9 from Akkermansia muciniphila increases the GLP-1 secretion of intestinal L cells.

Glucagon-like peptide-1(GLP-1) is an incretin hormone secreted primarily from the intestinal L-cells in response to meals. GLP-1 is a key regulator of energy metabolism and food intake. It has been proven that P9 protein from A. muciniphila could increase GLP-1 release and improve glucose homeostasis in HFD-induced mice. To obtain an engineered Lactococcus lactis which produced P9 protein, mature polypeptide chain of P9 was codon-optimized, fused with N-terminal signal peptide Usp45, and expressed in L. lactis NZ9000. Heterologous secretion of P9 by recombinant L. lactis NZP9 were successfully detected by SDS-PAGE and western blotting. Notably, the supernatant of L. lactis NZP9 stimulated GLP-1 production of NCI-H716 cells. The relative expression level of GLP-1 biosynthesis gene GCG and PCSK1 were upregulated by 1.63 and 1.53 folds, respectively. To our knowledge, this is the first report on the secretory expression of carboxyl-terminal processing protease P9 from A. muciniphila in L. lactis. Our results suggest that genetically engineered L. lactis which expressed P9 may have therapeutic potential for the treatment of diabetes, obesity and other metabolic disorders.

[Retracted] MicroRNA­329­3p targets MAPK1 to suppress cell proliferation, migration and invasion in cervical cancer.

Following the publication of the above article, a concerned reader drew to the Editor's attention that certain of the Transwell cell migration and invasion assay data featured in Figs. 5C and 6C were strikingly similar to data appearing in different form in other articles written by different authors at different research institutes that had already been published elsewhere prior to the submission of this paper to Oncology Reports, or were submitted for consideration for publication at around the same time. In view of the fact that certain of these data had already apparently been published prior to the submission of this article for publication, the Editor of Oncology Reports has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 37: 2743­2750, 2017; DOI: 10.3892/or.2017.5555].

Molecular Design Based on Integer Programming and Splitting Data Sets by Hyperplanes.

A novel framework for designing the molecular structure of chemical compounds with a desired chemical property has recently been proposed. The framework infers a desired chemical graph by solving a mixed integer linear program (MILP) that simulates the computation process of two functions: a feature function defined by a two-layered model on chemical graphs and a prediction function constructed by a machine learning method. To improve the learning performance of prediction functions in the framework, we design a method that splits a given data set C into two subsets C(i),i=1,2 by a hyperplane in a chemical space so that most compounds in the first (resp., second) subset have observed values lower (resp., higher) than a threshold θ. We construct a prediction function ψ to the data set C by combining prediction functions ψi,i=1,2 each of which is constructed on C(i) independently. The results of our computational experiments suggest that the proposed method improved the learning performance for several chemical properties to which a good prediction function has been difficult to construct.

Impact of sequential (first- to third-generation) EGFR-TKI treatment on corrected QT interval in NSCLC patients.

Objective: To evaluate the impact of sequential (first- to third-generation) epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) treatment on top-corrected QT interval (top-QTc) in non-small cell lung cancer (NSCLC) patients. Methods: We retrospectively reviewed the medical records of NSCLC patients undergoing sequential EGFR-TKI treatment at Shanghai Chest Hospital between October 2016 and August 2021. The heart rate (HR), top-QT interval, and top-QTc of their ECGs were extracted from the institutional database and analyzed. Logistic regression was performed to identify predictors for top-QTc prolongation. Results: Overall, 228 patients were enrolled. Compared with baseline (median, 368 ms, same below), both first-generation (376 ms vs. 368 ms, p < 0.001) and sequential third-generation EGFR-TKIs (376 ms vs. 368 ms, p = 0.002) prolonged top-QT interval to a similar extent (p = 0.635). Top-QTc (438 ms vs. 423 ms, p < 0.001) and HR (81 bpm vs.79 bpm, p = 0.008) increased after first-generation EGFR-TKI treatment. Further top-QTc prolongation (453 ms vs. 438 ms, p < 0.001) and HR increase (88 bpm vs. 81 bpm, p < 0.001) occurred after treatment advanced. Notably, as HR elevated during treatment, top-QT interval paradoxically increased rather than decreased, and the top-QTc increased rather than slightly fluctuated. Moreover, such phenomena were more significant after treatment advanced. After adjusting for confounding factors, pericardial effusion and lower serum potassium levels were independent predictors of additional QTc prolongation during sequential third-generation EGFR-TKI treatment. Conclusion: First-generation EGFR-TKI could prolong top-QTc, and sequential third-generation EGFR-TKI induced further prolongation. Top-QT interval paradoxically increased and top-QTc significantly increased as HR elevated, which was more significant after sequential EGFR-TKI treatment. Pericardial effusion and lower serum potassium levels were independent predictors of additional QTc prolongation after sequential EGFR-TKI treatment.

Correlations of FCGR2A 131R/H and FCGR3A 158V/F Polymorphisms with the Susceptibility of Peri-implantitis in Chinese Han Population.

The purpose of the study is to investigate the relationship of peri-implantitis (PI) with FCGR2A and FCGR3A gene polymorphisms. One hundred and forty-four patients with PI and 136 patients without PI infection were selected. Gingival crevicular fluid samples were collected from the two groups. The FCGR2A and FCGR3A polymorphism in the two groups were measured. All volunteers were evaluated for periodontal status. The effect of polymorphisms on PI susceptibility was investigated by chi-square analysis and logistic regression. The frequency of FCGR2A rs1801274 GG genotype of PI group was higher than that of the control group, while the GA and AA genotype carriers were less in PI group. After adjusting for other clinical indicators, rs1801274 GA genotype, AA genotype, and the A allele were still negatively correlated with the onset of PI. FCGR3A rs396991 polymorphism was not associated with PI. FCGR2A rs1801274 polymorphism was significantly associated with PI in the Chinese Han population, and GG genotype might be a genetic risk factor for PI.

Predicting the association of different levels of physical activity on postoperative pulmonary complications using the international physical activity questionnaire in patients undergoing thoracoscopic lung surgery under general anaesthesia: protocol for a prospective cohort study.

INTRODUCTION: Postoperative pulmonary complications (PPCs) occur frequently in patients undergoing lung surgery under general anaesthesia and are strongly associated with longer postoperative hospital stays and increased mortality. The existing literature has shown that a higher level of preoperative physical activity (PA) plays a positive role in the low incidence of postoperative complications and the quality of life in patients undergoing lung surgery. However, the association between preoperative PA levels and the incidence of PPCs has rarely been studied, particularly in thoracoscopic lung surgery. This study aims to evaluate PA levels in patients undergoing thoracoscopic lung surgery using the International Physical Activity Questionnaire and to investigate the association between PA levels and the incidence of PPCs. METHODS AND ANALYSIS: A total of 204 participants aged 18-80 years undergoing thoracoscopic lung surgery (thoracoscopic wedge resection, thoracoscopic segmentectomy and thoracoscopic lobectomy) will be included in the study. The primary outcome is the incidence of PPCs within the first 5 postoperative days. The secondary outcomes include the number of PPCs, the incidence of PPCs 1 month postoperatively, the arterial blood levels of inflammatory markers, the incidence of postoperative adverse events within the first 5 postoperative days, extubation time, unplanned admission to the intensive care unit, postoperative length of stay and mortality 1 month postoperatively. ETHICS AND DISSEMINATION: The study was reviewed and approved by the Research Ethics Committee of the First Affiliated Hospital of Shandong First Medical University on 31 March 2022 (YXLL-KY-2022(014)) and is registered at ClinicalTrials.gov. We plan to disseminate the data and findings of this study in international and peer-reviewed journals. TRIAL REGISTRATION NUMBER: The trial has been prospectively registered at the clinicaltrials.gov registry (NCT05401253).

Severe flood modulates the sources and age of dissolved organic carbon in the Yangtze River Estuary.

Floods in global large rivers modulate the transport of dissolved organic carbon (DOC) and estuarine hydrological characteristics significantly. This study investigated the impact of a severe flood on the sources and age of DOC in the Yangtze River Estuary (YRE) in 2020. Comparing the flood period in 2020 to the non-flood period in 2017, we found that the flood enhanced the transport of young DOC to the East China Sea (ECS), resulting in significantly enriched Δ14C-DOC values. During the flood period, the proportion of modern terrestrial organic carbon (OC) was significantly higher compared to the non-flood period. Conversely, the proportion of pre-aged sediment OC was significantly lower during the flood period. The high turbidity associated with the flood facilitated rapid transformation and mineralization of sedimentary and fresh terrestrial OC, modifying the sources of DOC. The flux of modern terrestrial OC transported to the ECS during the flood period was 1.58 times higher than that of the non-flood period. These findings suggest that floods can modulate the sources and decrease the age of DOC, potentially leading to increased greenhouse gas emissions. Further research is needed to understand the long-term impacts of floods on DOC dynamics in global estuaries.

Metabolic reprogramming of tumor-associated macrophages using glutamine antagonist JHU083 drives tumor immunity in myeloid-rich prostate and bladder cancer tumors.

Glutamine metabolism in tumor microenvironments critically regulates anti-tumor immunity. Using glutamine-antagonist prodrug JHU083, we report potent tumor growth inhibition in urologic tumors by JHU083-reprogrammed tumor-associated macrophages (TAMs) and tumor-infiltrating monocytes (TIMs). We show JHU083-mediated glutamine antagonism in tumor microenvironments induces TNF, pro-inflammatory, and mTORC1 signaling in intratumoral TAM clusters. JHU083-reprogrammed TAMs also exhibit increased tumor cell phagocytosis and diminished pro-angiogenic capacities. In vivo inhibition of TAM glutamine consumption resulted in increased glycolysis, a broken TCA cycle, and purine metabolism disruption. Although the anti-tumor effect of glutamine antagonism on tumor-infiltrating T cells was moderate, JHU083 promoted a stem cell-like phenotype in CD8+ T cells and decreased Treg abundance. Finally, JHU083 caused a ubiquitous shutdown in glutamine utilizing metabolic pathways in tumor cells, leading to reduced HIF-1alpha, c-MYC phosphorylation, and induction of tumor cell apoptosis, all key anti-tumor features.

Multi-omics reveal the gut microbiota-mediated severe foraging environment adaption of small wild ruminants in the Three-River-Source National Park, China.

The Tibetan antelope (Pantholops hodgsonii), blue sheep (Pseudois nayaur), and Tibetan sheep (Ovis aries) are the dominant small ruminants in the Three-River-Source National Park (TRSNP). However, knowledge about the association between gut microbiota and host adaptability remains poorly understood. Herein, multi-omics sequencing approaches were employed to investigate the gut microbiota-mediated forage adaption in these ruminants. The results revealed that although wild ruminants (WR) of P. hodgsoni and P. nayaur were faced with severe foraging environments with significantly low vegetation coverage and nutrition, the apparent forage digestibility of dry matter, crude protein, and acid detergent fiber was significantly higher than that of O. aries. The 16s rRNA sequencing showed that the gut microbiota in WR underwent convergent evolution, and alpha diversity in these two groups was significantly higher than that in O. aries. Moreover, indicator species, including Bacteroidetes and Firmicutes, exhibited positive relationships with apparent forage digestibility, and their relative abundances were enriched in the gut of WR. Enterotype analysis further revealed that enterotype 1 belonged to WR, and the abundance of fatty acid synthesis metabolic pathway-related enzyme genes was significantly higher than enterotype 2, represented by O. aries. Besides, the metagenomic analysis identified 14 pathogenic bacterial species, among which 10 potentially pathogenic bacteria were significantly enriched in the gut microbiota of O. aries. Furthermore, the cellulolytic strains and genes encoding cellulase and hemicellulase were significantly enriched in WR. In conclusion, our results provide new evidence of gut microbiota to facilitate wildlife adaption in severe foraging environments of the TRSNP, China.

Vacancy-Driven High-Performance Metabolic Assay for Diagnosis and Therapeutic Evaluation of Depression.

Depression is one of the most common mental illnesses and is a well-known risk factor for suicide, characterized by low overall efficacy (<50%) and high relapse rate (40%). A rapid and objective approach for screening and prognosis of depression is highly desirable but still awaits further development. Herein, a high-performance metabolite-based assay to aid the diagnosis and therapeutic evaluation of depression by developing a vacancy-engineered cobalt oxide (Vo-Co3O4) assisted laser desorption/ionization mass spectrometer platform is presented. The easy-prepared nanoparticles with optimal vacancy achieve a considerable signal enhancement, characterized by favorable charge transfer and increased photothermal conversion. The optimized Vo-Co3O4 allows for a direct and robust record of plasma metabolic fingerprints (PMFs). Through machine learning of PMFs, high-performance depression diagnosis is achieved, with the areas under the curve (AUC) of 0.941-0.980 and an accuracy of over 92%. Furthermore, a simplified diagnostic panel for depression is established, with a desirable AUC value of 0.933. Finally, proline levels are quantified in a follow-up cohort of depressive patients, highlighting the potential of metabolite quantification in the therapeutic evaluation of depression. This work promotes the progression of advanced matrixes and brings insights into the management of depression.

The Efficacy of Diabetic Foot Treatment in a "TOSF" Pattern: A Five-Year Retrospective Study.

Aim: To evaluate the advantages and problems in the diagnosis and treatment of diabetic foot (DF) patients by analyzing the results of a 5-year follow-up of the organ system based (TOSF) treatment model. Methods: A retrospective study was conducted in 229 patients with diabetic foot. Chi-square test and rank-sum test were used to analyze the effects of patients' general condition, behavioral and nutritional status, degree of infection (inflammatory markers), comorbidity, diabetic foot grade/classification, and revascularization on readmission rate, amputation rate, all-cause mortality, incidence of other complications, and wound healing time. Logistic regression was used to analyze the risk factors affecting the prognosis of diabetic foot. Kaplan-Meier survival curve was used to analyze the differences in amputation rate and mortality rate at each time point. Results: This study showed that nutritional status, degree of infection, and revascularization influenced readmission rates. General condition, behavior and nutritional status, degree of infection, Wagner grade and revascularization affect the amputation rate. General conditions, behavioral and nutritional status, degree of infection, comorbidities, classification and revascularization affect the mortality of patients. Age and white blood cell(WBC) count affected the incidence of other complications. Influence of infection degree and Wagner grade and revascularization in patients with wound healing time. Revascularization was an independent protective factor for readmission, amputation, and mortality.Elevated serum inflammatory markers are an independent risk factor for amputation. Hypoproteinemia is an independent risk factor for mortality. Conclusion: In the "TOSF" diagnosis and treatment pattern, diabetic foot patients have a good prognosis. Special attention should be paid to the screening and revascularization of lower extremity vascular disease in patients with diabetic foot.

Fibroblast Activation Protein Inhibitor Tracers and Their Preclinical, Translational, and Clinical Status in China.

Quinoline-based fibroblast activation protein (FAP) inhibitors (FAPIs) have recently emerged as a focal point in global nuclear medicine, underscored by their promising applications in cancer theranostics and the diagnosis of various nononcological conditions. This review offers an in-depth summary of the existing literature on the evolution and use of FAPI tracers in China, tracing their journey from preclinical to clinical research. Moreover, this review also assesses the diagnostic accuracy of FAPI PET for the most common cancers in China, analyzes its impact on oncologic management paradigms, and investigates the potential of FAP-targeted radionuclide therapy in patients with advanced or metastatic cancer. This review also summarizes studies using FAPI PET for nononcologic disorders in China. Thus, this qualitative overview presents a snapshot of China's engagement with FAPI tracers, aiming to guide future research endeavors.

Carboxypeptidase M modulates BMSCs osteogenesis-adipogenesis via the MAPK/ERK pathway: An integrated single-cell and bulk transcriptomic study.

The pathogenesis of osteoporosis (OP) is closely associated with the disrupted balance between osteogenesis and adipogenesis in bone marrow-derived mesenchymal stem cells (BMSCs). We analyzed published single-cell RNA sequencing (scRNA-seq) data to dissect the transcriptomic profiles of bone marrow-derived cells in OP, reviewing 56 377 cells across eight scRNA-seq datasets from femoral heads (osteoporosis or osteopenia n = 5, osteoarthritis n = 3). Seventeen genes, including carboxypeptidase M (CPM), were identified as key osteogenesis-adipogenesis regulators through comprehensive gene set enrichment, differential expression, regulon activity, and pseudotime analyses. In vitro, CPM knockdown reduced osteogenesis and promoted adipogenesis in BMSCs, while adenovirus-mediated CPM overexpression had the reverse effects. In vivo, intraosseous injection of CPM-overexpressing BMSCs mitigated bone loss in ovariectomized mice. Integrated scRNA-seq and bulk RNA sequencing analyses provided insight into the MAPK/ERK pathway's role in the CPM-mediated regulation of BMSC osteogenesis and adipogenesis; specifically, CPM overexpression enhanced MAPK/ERK signaling and osteogenesis. In contrast, the ERK1/2 inhibitor binimetinib negated the effects of CPM overexpression. Overall, our findings identify CPM as a pivotal regulator of BMSC differentiation, which provides new clues for the mechanistic study of OP.

Drug resistance mechanisms and treatment strategies mediated by Ubiquitin-Specific Proteases (USPs) in cancers: new directions and therapeutic options.

Drug resistance represents a significant obstacle in cancer treatment, underscoring the need for the discovery of novel therapeutic targets. Ubiquitin-specific proteases (USPs), a subclass of deubiquitinating enzymes, play a pivotal role in protein deubiquitination. As scientific research advances, USPs have been recognized as key regulators of drug resistance across a spectrum of treatment modalities, including chemotherapy, targeted therapy, immunotherapy, and radiotherapy. This comprehensive review examines the complex relationship between USPs and drug resistance mechanisms, focusing on specific treatment strategies and highlighting the influence of USPs on DNA damage repair, apoptosis, characteristics of cancer stem cells, immune evasion, and other crucial biological functions. Additionally, the review highlights the potential clinical significance of USP inhibitors as a means to counter drug resistance in cancer treatment. By inhibiting particular USP, cancer cells can become more susceptible to a variety of anti-cancer drugs. The integration of USP inhibitors with current anti-cancer therapies offers a promising strategy to circumvent drug resistance. Therefore, this review emphasizes the importance of USPs as viable therapeutic targets and offers insight into fruitful directions for future research and drug development. Targeting USPs presents an effective method to combat drug resistance across various cancer types, leading to enhanced treatment strategies and better patient outcomes.

Socioeconomic characteristics, cancer mortality, and universal health coverage: A global analysis.

BACKGROUND: Achieving universal health coverage (UHC) involves all individuals attaining accessible health interventions at an affordable cost. We examined current patterns and temporal trends of cancer mortality and UHC across sociodemographic index (SDI) settings, and quantified these association. METHODS: We used data from the Global Burden of Disease Study 2019 and Our World in Data. The UHC effective coverage index was obtained to assess the potential population health gains delivered by health systems. The estimated annual percentage change (EAPC) with a 95% confidence interval (CI) was calculated to quantify the trend of cancer age-standardized mortality rate (ASMR). A generalized linear model was applied to estimate the association between ASMR and UHC. FINDINGS: The high (EAPC = -0.9% [95% CI, -1.0%, -0.9%]) and high-middle (-0.9% [-1.0%, -0.8%]) SDI regions had the fastest decline in ASMR (per 100,000) for total cancers from 1990 to 2019. The overall UHC effective coverage index increased by 27.9% in the high-SDI quintile to 62.2% in the low-SDI quintile. A negative association was observed between ASMR for all-cancer (adjusted odds ratio [OR] = 0.87 [0.76, 0.99]), stomach (0.73 [0.56, 0.95]), breast (0.64 [0.52, 0.79]), cervical (0.42 [0.30, 0.60]), lip and oral cavity (0.55 [0.40, 0.75]), and nasopharynx (0.42 [0.26, 0.68]) cancers and high UHC level (the lowest as the reference). CONCLUSIONS: Our findings strengthen the evidence base for achieving UHC to improve cancer outcomes. FUNDING: This work is funded by the China National Natural Science Foundation and Chinese Academy of Medical Sciences Innovation Fund for Medical Science.

Subtype-WGME enables whole-genome-wide multi-omics cancer subtyping.

We present an innovative strategy for integrating whole-genome-wide multi-omics data, which facilitates adaptive amalgamation by leveraging hidden layer features derived from high-dimensional omics data through a multi-task encoder. Empirical evaluations on eight benchmark cancer datasets substantiated that our proposed framework outstripped the comparative algorithms in cancer subtyping, delivering superior subtyping outcomes. Building upon these subtyping results, we establish a robust pipeline for identifying whole-genome-wide biomarkers, unearthing 195 significant biomarkers. Furthermore, we conduct an exhaustive analysis to assess the importance of each omic and non-coding region features at the whole-genome-wide level during cancer subtyping. Our investigation shows that both omics and non-coding region features substantially impact cancer development and survival prognosis. This study emphasizes the potential and practical implications of integrating genome-wide data in cancer research, demonstrating the potency of comprehensive genomic characterization. Additionally, our findings offer insightful perspectives for multi-omics analysis employing deep learning methodologies.

Transcriptomic analysis of epicardial adipose tissue reveals the potential crosstalk genes and immune relationship between type 2 diabetes mellitus and atrial fibrillation.

BACKGROUND: The complex relationship between atrial fibrillation (AF) and type 2 diabetes mellitus (T2DM) suggests a potential role for epicardial adipose tissue (EAT) that requires further investigation. This study employs bioinformatics and experimental approaches to clarify EAT's role in linking T2DM and AF, aiming to unravel the biological mechanisms involved. METHOD: Bioinformatics analysis initially identified common differentially expressed genes (DEGs) in EAT from T2DM and AF datasets. Pathway enrichment and network analyses were then performed to determine the biological significance and network connections of these DEGs. Hub genes were identified through six CytoHubba algorithms and subsequently validated biologically, with further in-depth analyses confirming their roles and interactions. Experimentally, db/db mice were utilized to establish a T2DM model. AF induction was executed via programmed transesophageal electrical stimulation and burst pacing, focusing on comparing the incidence and duration of AF. Frozen sections and Hematoxylin and Eosin (H&E) staining illuminated the structures of the heart and EAT. Moreover, quantitative PCR (qPCR) measured the expression of hub genes. RESULTS: The study identified 106 DEGs in EAT from T2DM and AF datasets, underscoring significant pathways in energy metabolism and immune regulation. Three hub genes, CEBPZ, PAK1IP1, and BCCIP, emerged as pivotal in this context. In db/db mice, a marked predisposition towards AF induction and extended duration was observed, with HE staining verifying the presence of EAT. Additionally, qPCR validated significant changes in hub genes expression in db/db mice EAT. In-depth analysis identified 299 miRNAs and 33 TFs as potential regulators, notably GRHL1 and MYC. GeneMANIA analysis highlighted the hub genes' critical roles in stress responses and leukocyte differentiation, while immune profile correlations highlighted their impact on mast cells and neutrophils, emphasizing the genes' significant influence on immune regulation within the context of T2DM and AF. CONCLUSION: This investigation reveals the molecular links between T2DM and AF with a focus on EAT. Targeting these pathways, especially EAT-related ones, may enable personalized treatments and improved outcomes.