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.

Objectives: This study aimed to achieve expert consensus on menopause management in the Asia-Pacific region, taking into account patient diversity, the latest evidence, and current treatment options. Methods: A focused literature search was performed to identify clinical practice statements on menopause management. Menopause experts were nominated by members of the Asia-Pacific Menopause Federation (APMF) society. A modified Delphi methodology, involving iterative rounds of anonymous surveys, was employed until consensus was reached for each statement. Consensus was defined as ≥ 70% of experts voting ‘agree’ or ‘strongly agree’ for a given clinical practice statement. Results: A total of 39 participants from 14 different APMF member societies were involved. Eighty-five clinical practice statements reached a consensus. Based on the clinical practice statements, an algorithm was created as a tool to guide clinicians on menopause management. APMF experts agreed that, in addition to vasomotor symptoms, Asian women experiencing somatic or psychological symptoms may also benefit from treatment with menopausal hormone therapy (MHT). MHT should also be considered for the prevention of osteoporosis in asymptomatic peri- and postmenopausal women. Conclusions This APMF consensus statement supersedes the previous one published in 2008. It provides guidance to gynecologists, endocrinologists, family physicians, and other healthcare professionals in delivering optimal care to menopausal women in the ethnically and culturally diverse Asia-Pacific region.

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.

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*

Objectives: This study aimed to achieve expert consensus on menopause management in the Asia-Pacific region, taking into account patient diversity, the latest evidence, and current treatment options. Methods: A focused literature search was performed to identify clinical practice statements on menopause management. Menopause experts were nominated by members of the Asia-Pacific Menopause Federation (APMF) society. A modified Delphi methodology, involving iterative rounds of anonymous surveys, was employed until consensus was reached for each statement. Consensus was defined as ≥ 70% of experts voting ‘agree’ or ‘strongly agree’ for a given clinical practice statement. Results: A total of 39 participants from 14 different APMF member societies were involved. Eighty-five clinical practice statements reached a consensus. Based on the clinical practice statements, an algorithm was created as a tool to guide clinicians on menopause management. APMF experts agreed that, in addition to vasomotor symptoms, Asian women experiencing somatic or psychological symptoms may also benefit from treatment with menopausal hormone therapy (MHT). MHT should also be considered for the prevention of osteoporosis in asymptomatic peri- and postmenopausal women. Conclusions This APMF consensus statement supersedes the previous one published in 2008. It provides guidance to gynecologists, endocrinologists, family physicians, and other healthcare professionals in delivering optimal care to menopausal women in the ethnically and culturally diverse Asia-Pacific region.

Objectives: This study aimed to achieve expert consensus on menopause management in the Asia-Pacific region, taking into account patient diversity, the latest evidence, and current treatment options. Methods: A focused literature search was performed to identify clinical practice statements on menopause management. Menopause experts were nominated by members of the Asia-Pacific Menopause Federation (APMF) society. A modified Delphi methodology, involving iterative rounds of anonymous surveys, was employed until consensus was reached for each statement. Consensus was defined as ≥ 70% of experts voting ‘agree’ or ‘strongly agree’ for a given clinical practice statement. Results: A total of 39 participants from 14 different APMF member societies were involved. Eighty-five clinical practice statements reached a consensus. Based on the clinical practice statements, an algorithm was created as a tool to guide clinicians on menopause management. APMF experts agreed that, in addition to vasomotor symptoms, Asian women experiencing somatic or psychological symptoms may also benefit from treatment with menopausal hormone therapy (MHT). MHT should also be considered for the prevention of osteoporosis in asymptomatic peri- and postmenopausal women. Conclusions This APMF consensus statement supersedes the previous one published in 2008. It provides guidance to gynecologists, endocrinologists, family physicians, and other healthcare professionals in delivering optimal care to menopausal women in the ethnically and culturally diverse Asia-Pacific region.

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.