BACKGROUND: To provide a comprehensive analysis of the landscape of artificial intelligence (AI) applications in cardiac arrest (CA). METHODS: Comprehensive searches were conducted in PubMed, the Cochrane Library, Web of Science, and EMBASE from database inception through 10 June 2025. Studies that applied AI in both in-hospital cardiac arrest (IHCA) and out-of-hospital cardiac arrest (OHCA) populations across the following domains were included: prediction of cardiac arrest occurrence, prognostication of CA outcomes, applications of large language models (LLMs), and evaluation of cardiopulmonary resuscitation (CPR) and other AI-driven interventions related to CA. RESULTS: The scoping review included 114 studies, encompassing data from 9,574,462 patients in total. AI was most commonly applied to the prediction of CA (overall, n=40; IHCA, n=30; OHCA, n=4; and both, n=6), CPR-related decision support during CA (n=16), and post-arrest prognosis and rehabilitation outcomes (overall, n=38; OHCA, n=21; IHCA, n=3; and both, n=14). Additional application areas included LLM-based applications (n=8), emergency call handling (n=4), wearable device-based detection (n=3), heart rhythm identification (n=2), education (n=2), and extracorporeal cardiopulmonary resuscitation (ECPR) candidate identification (n=1). Across all application scenarios, the highest area under the receiver operating characteristic curve (AUROC) value for pre-arrest CA prediction in IHCA patients was 0.998 using a multilayer perceptron (MLP) model, whereas the optimal AUROC for pre-arrest CA prediction in OHCA patients was 0.950 using extreme gradient boosting (XGBoost) or random forest (RF) models. For CPR-related decision support during CA, the highest AUROC achieved was 0.990 with a convolutional neural network (CNN) model. In prognostic prediction, the optimal AUROC for IHCA patients was 0.960 using XGBoost, while for OHCA patients it reached 0.976 using an MLP model. CONCLUSION: This review shows that AI is most commonly used for the prediction of CA and CPR-related support, as well as post-arrest and rehabilitation outcomes. Future research directions include drug discovery, post-resuscitation management, neurorehabilitation, and clinical trial innovation. Further studies should prioritize multicenter clinical trials to evaluate AI models in real-world settings and validate their effectiveness across diverse patient populations. Overall, AI has significant potential to improve clinical practice, and its role in CA application is increasingly important.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

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*

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

This study aimed to evaluate the efficacy and safety of combining albumin-bound paclitaxel (abpaclitaxel) and anlotinib for ovarian cancer. In this study, 44 patients diagnosed with platinum-resistant ovarian cancer were enrolled. Patients received ab-paclitaxel along with anlotinib until disease progression or intolerable toxicity. Efficacy was assessed according to RECIST 1.1 criteria or Rustin's criteria. The primary endpoint was the investigator-evaluated objective response rate (ORR). 44 patients were enrolled between January 2021 and March 2023 with a median age of 49 years. Twenty-nine had measurable lesions and 15 had non-measurable lesions. Overall, the investigator-evaluated ORR was 56.8% (25/44; 95% CI 0.411-0.713) in intention-to-treat population and 58.1% (25/43; 95% CI 0.422-0.726) in per-protocol population. The median progression-free survival was 9.8 months, and the median duration of response was 7.4 months. For safety, grade 3/4 adverse events (AEs) included leukopenia, gum pain, hypertension, and hand-foot syndrome. The response rates were 55.0% (11/20) in patients with previous use of antiangiogenic reagents and who had previous use of PARP inhibitors. The combination of ab-paclitaxel and anlotinib showed promising anti-tumor activity and a manageable safety profile in platinum-resistant ovarian cancer. Patients with previous use of antiangiogenic drugs or PARP inhibitors still benefited from this protocol.
Humans ; Female ; Middle Aged ; Indoles/therapeutic use* ; Quinolines/therapeutic use* ; Carcinoma, Ovarian Epithelial/drug therapy* ; Adult ; Ovarian Neoplasms/drug therapy* ; Prospective Studies ; Antineoplastic Combined Chemotherapy Protocols/administration & dosage* ; Aged ; Drug Resistance, Neoplasm ; Albumin-Bound Paclitaxel/therapeutic use* ; Neoplasm Recurrence, Local/drug therapy* ; Progression-Free Survival ; Paclitaxel/administration & dosage* ; Treatment Outcome

Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular structures, and creates limitations in the stability and diversity of the generated molecules. To address these challenges, we propose a deep molecular diffusion generative model, the three-dimensional (3D) equivariant diffusion-driven molecular generation (3D-EDiffMG) model. The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder (dual-SWLEE) is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions. Additionally, a gate multilayer perceptron (gMLP) block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies. The experimental results show that 3D-EDiffMG effectively generates unique, novel, stable, and diverse drug-like molecules, highlighting its potential for lead optimization and accelerating drug discovery.

The dysregulation of cyclin-dependent kinase 12 (CDK12), which may result from genomic alterations or modulation by upstream effectors, is implicated in cancer oncogenesis and progression. CDK12 overexpression or activation is sufficient to induce tumor initiation, recurrence, and therapeutic resistance. However, CDK12 may also exert tumor-suppressive functions in a context-dependent manner. Therefore, caution is warranted when targeting CDK12 in future clinical trials. A comprehensive elucidation of the dual roles and underlying mechanisms of CDK12 in carcinogenesis is urgently needed to advance precision oncology. This review provides an overview of the current understanding of the dysregulation and biological roles of CDK12 in cancer. Subsequently, we systematically summarize the functions and mechanisms of the oncogenic and tumor-suppressive roles of CDK12 in different contexts. Finally, we discuss the potential of CDK12 as a novel therapeutic target and its implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies.