ObjectiveTo establish a tumor prognostic risk assessment model related to target genes of the miR-34 family. MethodsTarget genes of the miR-34 family were screened， and the scores of miR-34 target genes were assessed in 16 tumor types. Univariate Cox regression analysis was used to identify the tumor type with the strongest correlation between miR-34 target gene scores and overall survival （OS）. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed to elucidate the functional roles and signaling pathways of miR-34 target genes. A prognostic risk model based on the miR-34 target genes was constructed using univariate Cox and LASSO regression analyses. Quantitative real-time PCR （qPCR） and dual-luciferase reporter assays were conducted to validate whether the target genes bind to miR-34 and measure their RNA expression levels in the relevant tumors. Additionally， the risk score was integrated with other clinical indicators to develop a nomogram prediction model for patient survival. ResultsA total of 65 target genes of the miR-34 family were screened. The cancer type exhibiting stronger correlation between the target gene scores and OS was lung adenocarcinoma （P = 0.003， HR= 5.150）. Furthermore， miR-34 target genes were predominantly enriched in oxidative stress pathways and various tumor-related processes. Three genes， LDHA， GALNT7， and SATB2， were identified as core components of the prognostic analysis model for lung adenocarcinoma. Additionally， the constructed nomogram model demonstrated robust predictive performance. ConclusionThe risk model and prognosis model of lung adenocarcinoma constructed based on the key target genes of miR-34 have good predictive performance.

Purpose: Endoscopic submucosal dissection (ESD) has become a standard minimally invasive treatment for selected patients with early gastric cancer (EGC). This study presents the first nationwide survey of patients with EGC treated with ESD in 2023, conducted by the Korean College of Helicobacter and Upper Gastrointestinal Research. Materials and Methods: Data were retrospectively collected from participating referral centers across Korea using a standardized case report form covering patient characteristics, tumor features, procedural details, histopathological findings, and clinical outcomes.Descriptive and comparative analyses were conducted to summarize nationwide ESD practice patterns and outcomes. Results: Data from 5,460 ESD cases from 5,250 patients across 27 institutions were analyzed. The mean age was 67.4 years, with 74.1% males. Multiple synchronous lesions were identified in 3.7%. Most lesions were located in the lower third of the stomach (64.0%), and differentiated-type adenocarcinomas accounted for 87.8%. The en bloc and complete resection rates were 99.2% and 91.4%, respectively. Curative resection was achieved in 80.5%, whereas local non-curative resection (L-NCR) and surgical non-curative resection (S-NCR) were identified in 2.8% and 16.7%, respectively. Additional surgery was performed more frequently in patients with S-NCR than in those with L-NCR (59.3% vs. 24.7%). The bleeding and perforation rates were 3.6% and 0.9%, respectively, and were mostly managed conservatively or endoscopically. The median length of hospitalization was 4.0 days. Conclusions This first nationwide survey provides a comprehensive overview of the current practice of EGC treatment using ESD in Korea, demonstrating high technical success and safety, and establishing a baseline dataset for future longitudinal research.

Objectives: Endoscopic submucosal dissection (ESD) has become a standard minimally invasive treatment for selected patients with early gastric cancer (EGC). This study presents the first nationwide survey of patients with EGC treated with ESD in 2023, conducted by the Korean College of Helicobacter and Upper Gastrointestinal Research. Methods: Data were retrospectively collected from participating referral centers across Korea using a standardized case report form covering patient characteristics, tumor features, procedural details, histopathological findings, and clinical outcomes. Descriptive and comparative analyses were conducted to summarize nationwide ESD practice patterns and outcomes. Results: Data from 5460 ESD cases from 5250 patients across 27 institutions were analyzed. The mean age was 67.4 years, with 74.1% males. Multiple synchronous lesions were identified in 3.7%. Most lesions were located in the lower third of the stomach (64.0%), and differentiated-type adenocarcinomas accounted for 87.8%. The en bloc and complete resection rates were 99.2% and 91.4%, respectively. Curative resection was achieved in 80.5%, whereas local non-curative resection (L-NCR) and surgical non-curative resection (S-NCR) were identified in 2.8% and 16.7%, respectively. Additional surgery was performed more frequently in patients with S-NCR than in those with L-NCR (59.3% vs. 24.7%). The bleeding and perforation rates were 3.6% and 0.9%, respectively, and were mostly managed conservatively or endoscopically. The median length of hospitalization was 4.0 days. Conclusions This first nationwide survey provides a comprehensive overview of the current practice of EGC treatment using ESD in Korea, demonstrating high technical success and safety, and establishing a baseline dataset for future longitudinal research.

Epigallocatechin-3-gallate (EGCG), a bioactive polyphenol abundant in green tea, has garnered significant attention for its diverse therapeutic applications, ranging from antioxidant and anti-inflammatory effects to potential anticancer properties. Despite its immense promise, the practical utilization of EGCG in therapeutic settings as a medication has been hampered by inherent limitations of this drug, including poor bioavailability, instability, and rapid degradation. This review comprehensively explores the current challenges associated with the application of EGCG and evaluates the potential of nanoparticle-based formulations in addressing these limitations. Nanoparticles, with their unique physicochemical properties, offer a platform for the enhanced stability, bioavailability, and targeted delivery of EGCG. Various nanoparticle strategies, including polymeric nanoparticle, micelle, lipid-based nanocarrier, metal nanoparticle, and silica nanoparticle, are currently employed to enhance EGCG stability and pharmacological activity. This review concludes that the particle sizes of most of these formulated nanocarriers fall within 300 nm and their encapsulation efficiency ranges from 51% to 97%. Notably, the pharmacological activities of EGCG-loaded nanoparticles, such as antioxidative, anti-inflammatory, anticancer, and antimicrobial effects, are significantly enhanced compared to those of free EGCG. By critically analyzing the existing literature and highlighting recent advancements, this article provides valuable insights into the promising prospects of nanoparticle-mediated EGCG formulations, paving the way for the development of more effective and clinically viable therapeutic strategies.
Animals ; Humans ; Anti-Inflammatory Agents/administration & dosage* ; Antineoplastic Agents/administration & dosage* ; Antioxidants/administration & dosage* ; Biological Availability ; Catechin/analogs & derivatives* ; Micelles ; Particle Size ; Nanoparticle Drug Delivery System/chemistry*

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

Acute respiratory distress syndrome (ARDS) is a common respiratory emergency, but current clinical treatment remains at the level of symptomatic support and there is a lack of effective targeted treatment measures. Our previous study confirmed that inhalation of hydrogen gas can reduce the acute lung injury of ARDS, but the application of hydrogen has flammable and explosive safety concerns. Drinking hydrogen-rich liquid or inhaling hydrogen gas has been shown to play an important role in scavenging reactive oxygen species and maintaining mitochondrial quality control balance, thus improving ARDS in patients and animal models. Coral calcium hydrogenation (CCH) is a new solid molecular hydrogen carrier prepared from coral calcium (CC). Whether and how CCH affects acute lung injury in ARDS remains unstudied. In this study, we observed the therapeutic effect of CCH on lipopolysaccharide (LPS) induced acute lung injury in ARDS mice. The survival rate of mice treated with CCH and hydrogen inhalation was found to be comparable, demonstrating a significant improvement compared to the untreated ARDS model group. CCH treatment significantly reduced pulmonary hemorrhage and edema, and improved pulmonary function and local microcirculation in ARDS mice. CCH promoted mitochondrial peripheral division in the early course of ARDS by activating mitochondrial thioredoxin 2 (Trx2), improved lung mitochondrial dysfunction induced by LPS, and reduced oxidative stress damage. The results indicate that CCH is a highly efficient hydrogen-rich agent that can attenuate acute lung injury of ARDS by improving the mitochondrial function through Trx2 activation.

Epigallocatechin-3-gallate (EGCG), a prominent plant-based catechin predominantly derived from Camellia sinensis and widely available on the market as a health supplement, has garnered significant attention for its potential therapeutic benefits, particularly in the context of type 2 diabetes mellitus (T2DM). This review explores the multifaceted role of EGCG in addressing the "ominous octet"-the 8 core pathophysiological defects associated with T2DM. The literature search was carried out using key terms "EGCG" OR "epigallocatechin-3-gallate" OR "epigallocatechin gallate" AND "diabetes" OR "insulin resistance" OR "hyperglycemia" in the PubMed and Scopus databases. The search was constrained to articles published between January 2018 and April 2024, focusing on the document type. Full-text articles published in English and relevant to EGCG that featured a single active ingredient, included clearly explained diabetes relief mechanism, and included ominous octet aspects were included in the final review. The outcomes of the included studies were reviewed and categorized based on 8 core pathophysiological defects, collectively referred to as the ominous octet in T2DM. This review concludes that EGCG is a potent hypoglycemic agent that has beneficial effects against the ominous octet in addition to its pharmacological activities in modulating gut microbiota dysbiosis, carbohydrate digestion and metabolism, glucose transporter-mediated intestinal glucose-uptake, endothelial dysfunction, and renal damage that are significantly associated with pathogenesis of T2DM. This extensive scientific evidence suggests that EGCG may offer a novel approach to traditional antidiabetic therapies, potentially improving glycemic control and mitigating complications associated with T2DM. The inhibitory effects of EGCG on sodium-glucose transport proteins and their role in reducing renal glucose reabsorption remain unexplored, highlighting a significant research gap. Future research should also aim to broaden the scope by investigating the "egregious eleven," which comprise a more comprehensive range of diabetic pathophysiological features. This review underscores the therapeutic promise of EGCG for managing T2DM and encourages ongoing research to fully elucidate its clinical applications. Please cite this article as: Wong CN, Lim YM, Liew KB, Chew YL, Chua AL, Lee SK. A review on mechanistic actions of epigallocatechin-3-gallate in targeting the ominous octet of type 2 diabetes mellitus. J Integr Med. 2025; 23(4): 344-356.
Diabetes Mellitus, Type 2/physiopathology* ; Humans ; Catechin/therapeutic use* ; Hypoglycemic Agents/therapeutic use* ; Animals ; Insulin Resistance

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.