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*

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.
Humans ; Female ; Pelvic Organ Prolapse/epidemiology* ; Middle Aged ; Risk Assessment/methods* ; China/epidemiology* ; Multifactorial Inheritance ; Aged ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Case-Control Studies ; Adult ; Polymorphism, Single Nucleotide ; Genetic Risk Score ; East Asian People

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ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To explore the relationship between osteoporosis and carotid atherosclerosis in patients with coronary heart disease aged≥60 years and analyze prevention suggestions. Methods The clinical data of 380 patients with coronary heart disease aged≥60 years who underwent various examinations in the hospital between April 2024 and April 2025 were retrospectively analyzed. According to the bone mineral density (BMD) classification criteria, the patients were divided into osteoporosis group and non-osteoporosis group. The differences in general data and carotid atherosclerosis-related indicators were compared between osteoporosis group and non-osteoporosis group. Pearson method was used to analyze the correlation between carotid atherosclerosis indicators and clinical indicators in patients with coronary heart disease aged≥60 years. According to the IMT detection thickness in patients with coronary heart disease and osteoporosis aged≥60 years were divided into IMT thickening group and IMT non-thickening group and between plaque group and non-plaque group, and the differences in BMD and bone metabolism indicators were compared. Binary logistics analysis was adopted to analyze the risk factors of IMT thickening and carotid plaque formation in patients with coronary heart disease≥60 years old. Results Age and duration of osteoporosis group TC、LDL-C、CTX、 Carotid artery IMT and carotid atherosclerosis degree were higher than those in the non osteoporosis group, the difference was statistically significant (P<0.05). BMI, OPG, OCN, 25 (OH) D, BMD, carotid artery elasticity coefficient were lower than those in the non osteoporosis group, the difference was statistically significant (P<0.05). Carotid IMT, carotid atherosclerosis degree, and carotid elasticity coefficient were significantly correlated with age, course of disease, TC, LDL-C, CTX, BMI, OPG, OCN, BMD, and 25 (OH) D of coronary heart disease patients ≥60 years old (P<0.05). OPG, OCN, BMD and 25(OH)D in IMT thickening group and plaque group were lower compared to IMT non-thickening group and non-plaque group (P<0.05) while CTX was significantly higher than that in IMT non-thickening group and non-plaque group (P<0.05). Binary logistics regression analysis showed that OPG, OCN, BMD, 25(OH)D and CTX were associated with IMT thickening in patients with coronary heart disease and osteoporosis aged≥60 years (P<0.05). OPG, OCN and BMD were associated with carotid plaque formation in patients with coronary heart disease complicated with osteoporosis aged≥60 years (P<0.05). Conclusion There is a significant correlation between osteoporosis and arteriosclerosis in patients with coronary heart disease aged≥60 years. As the bone mass decreases, the manifestations of arteriosclerosis become become more and more obvious, which needs attention and prevention.

This study employed the "disease-medicine-dose" pattern to mine the medication rules of traditional Chinese medicine(TCM) prescriptions containing Astragali Radix in ancient Chinese medical books, aiming to provide a scientific basis for the clinical application of Astragali Radix and the development of new medicines. The TCM prescriptions containing Astragali Radix were retrieved from databases such as Chinese Medical Dictionary and imported into Excel 2020 to construct the prescription library. Statical analysis were performed for the prescriptions regarding the indications, syndromes, medicine use frequency, herb effects, nature and taste, meridian tropism, dosage forms, and dose. SPSS statistics 26.0 and IBM SPSS Modeler 18.0 were used for association rules analysis and cluster analysis. A total of 2 297 prescriptions containing Astragali Radix were collected, involving 233 indications, among which sore and ulcer, consumptive disease, sweating disorder, and apoplexy had high frequency(>25), and their syndromes were mainly Qi and blood deficiency, Qi and blood deficiency, Yin and Yang deficiency, and Qi deficiency and collateral obstruction, respectively. In the prescriptions, 98 medicines were used with the frequency >25 and they mainly included Qi-tonifying medicines and blood-tonifying medicines. Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, and Citri Reticulatae Pericarpium were frequently used. The medicines with high frequency mainly have warm or cold nature, and sweet, pungent, or bitter taste, with tropism to spleen, lung, heart, liver, and kidney meridians. In the treatment of sore and ulcer, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to promote granulation and heal up sores. In the treatment of consumptive disease, Astragali Radix was mainly used with the dose of 37.30 g and combined with Ginseng Radix et Rhizoma to tonify deficiency and replenish Qi. In the treatment of sweating disorder, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to consolidate exterior and stop sweating. In the treatment of apoplexy, Astragali Radix was mainly used with the dose of 7.46 g and combined with Glycyrrhizae Radix et Rhizoma to dispell wind and stop convulsions. Astragali Radix can be used in the treatment of multiple system diseases, with the effects of tonifying Qi and ascending Yang, consolidating exterior and stopping sweating, and expressing toxin and promoting granulation. According to the manifestations of different diseases, when combined with other medicines, Astragali Radix was endowed with the effects of promoting granulation and healing up sores, tonifying deficiency and Qi, consolidating exterior and stopping sweating, and dispelling wind and replenishing Qi. The findings provide a theoretical reference and a scientific basis for the clinical application of Astragali Radix and the development of new medicines.
Drugs, Chinese Herbal/history* ; Humans ; Medicine, Chinese Traditional/history* ; History, Ancient ; Astragalus Plant/chemistry* ; China ; Astragalus propinquus

Osteoarthritis (OA) is the most common degenerative joint disease. Its pathological process is related to inflammatory response, chondrocyte apoptosis, and cartilage degeneration. Hippo-yes-associate protein(YAP) signaling pathway plays an important role in mediating organ size and tissue homeostasis. In recent years, the key effector protein YAP in the Hippo-YAP pathway has become a research hotspot in osteoarthritis. This article introduces the activation process of Hippo-YAP signaling pathway and the biological role of YAP. It reviews the progress of YAP in regulating osteoarthritis by influencing the proliferation and differentiation of mesenchymal stem cells and the proliferation, differentiation, and apoptosis of articular chondrocytes. It analyzed the problems encountered in YAP research in OA, introduces the research potential of YAP in other orthopedic diseases, and provides new ideas for subsequent research in Osteoarthritis.
Osteoarthritis/metabolism* ; Humans ; Signal Transduction ; Protein Serine-Threonine Kinases/physiology* ; Hippo Signaling Pathway ; YAP-Signaling Proteins ; Adaptor Proteins, Signal Transducing/physiology* ; Animals ; Transcription Factors ; Chondrocytes/cytology* ; Cell Cycle Proteins

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex disease that is often accompanied by mental health disorders. However, the potential mechanisms underlying the heterogeneous clinical presentation of CP/CPPS remain uncertain. This study analyzed widely targeted metabolomic data of expressed prostatic secretions (EPS) and plasma to reveal the underlying pathological mechanisms of CP/CPPS. A total of 24 CP/CPPS patients from The Second Nanning People's Hospital (Nanning, China), and 35 asymptomatic control individuals from First Affiliated Hospital of Guangxi Medical University (Nanning, China) were enrolled. The indicators related to CP/CPPS and psychiatric symptoms were recorded. Differential analysis, coexpression network analysis, and correlation analysis were performed to identify metabolites that were specifically altered in patients and associated with various phenotypes of CP/CPPS. The crucial links between EPS and plasma were further investigated. The metabolomic data of EPS from CP/CPPS patients were significantly different from those from control individuals. Pathway analysis revealed dysregulation of amino acid metabolism, lipid metabolism, and the citrate cycle in EPS. The tryptophan metabolic pathway was found to be the most significantly altered pathway associated with distinct CP/CPPS phenotypes. Moreover, the dysregulation of tryptophan and tyrosine metabolism and elevation of oxidative stress-related metabolites in plasma were found to effectively elucidate the development of depression in CP/CPPS. Overall, metabolomic alterations in the EPS and plasma of patients were primarily associated with oxidative damage, energy metabolism abnormalities, neurological impairment, and immune dysregulation. These alterations may be associated with chronic pain, voiding symptoms, reduced fertility, and depression in CP/CPPS. This study provides a local-global perspective for understanding the pathological mechanisms of CP/CPPS and offers potential diagnostic and therapeutic targets.
Humans ; Male ; Prostatitis/blood* ; Adult ; Pelvic Pain/blood* ; Metabolomics ; Prostate/metabolism* ; Middle Aged ; Chronic Pain/blood* ; Metabolome ; Case-Control Studies ; Tryptophan/blood* ; Depression/blood* ; Oxidative Stress/physiology* ; Chronic Disease ; Lipid Metabolism/physiology*

OBJECTIVES: To investigate the effects of methylenetetrahydrofolate reductase (MTHFR) rs1801133 and γ-glutamyl hydrolase (GGH) rs11545078 gene polymorphisms on plasma concentrations and toxicity following high-dose methotrexate (MTX) therapy in children with acute lymphoblastic leukemia (ALL). METHODS: Children with ALL treated at the Xuzhou Children's Hospital of Xuzhou Medical University from January 2021 to April 2024 were selected for this study. Genotypes of MTHFR rs1801133 and GGH rs11545078 were determined using multiplex polymerase chain reaction. MTX plasma concentrations were measured by enzyme-multiplied immunoassay technique, and toxicity was graded according to the Common Terminology Criteria for Adverse Events version 5.0. The relationships between MTHFR rs1801133 and GGH rs11545078 genotypes and both MTX plasma concentrations and associated toxicities were analyzed. RESULTS: In the low-risk ALL group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 72 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05), and the GGH rs11545078 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with the occurrence of reduced hemoglobin (P<0.05), and the GGH rs11545078 genotype was associated with the occurrence of thrombocytopenia (P<0.05). CONCLUSIONS Detection of MTHFR rs1801133 and GGH rs11545078 genotypes can be used to predict increased MTX plasma concentrations and the occurrence of toxic reactions in high-dose MTX treatment of ALL, enabling timely interventions to enhance safety.
Humans ; Methotrexate/toxicity* ; Methylenetetrahydrofolate Reductase (NADPH2)/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/blood* ; Male ; Female ; Child ; Child, Preschool ; gamma-Glutamyl Hydrolase/genetics* ; Antimetabolites, Antineoplastic/adverse effects* ; Infant ; Polymorphism, Genetic ; Adolescent ; Genotype ; Polymorphism, Single Nucleotide