Molar-incisor hypomineralization (MIH) is a developmental defect of enamel that is characterized primarily by abnormal enamel mineralization affecting the first permanent molars and permanent incisors. Due to insufficient mineralization, teeth affected by MIH are prone to post-eruptive breakdown and caries, potentially leading to sequelae such as tooth sensitivity and occlusal problems. The diagnosis of MIH is primarily based on relevant perinatal and infantile medical history, the characteristic distribution of affected teeth, and the morphological features of the enamel defects. Based on the extent and severity of the enamel defect, MIH is classified as mild or severe. Diagnosis and treatment strategies emphasize early screening, diagnosis, and intervention, prioritizing prevention, providing symptomatic care, and implementing regular recall assessments. Mild MIH predominantly manifests as demineralized enamel opacities or discoloration, typically without significant enamel breakdown. Treatment focuses on caries prevention and aesthetic restoration, employing techniques such as remineralization, micro-abrasion, resin infiltration, bleaching, fluoride application, and fissure sealants. Severe MIH typically presents with extensive enamel opacities accompanied by substantial enamel breakdown and may be complicated by caries and tooth sensitivity. Management primarily involves restoring the structural defects or, for teeth that cannot be preserved, extraction followed by orthodontic treatment. Comprehensive management often requires a multimodal approach integrating various therapeutic modalities to restore both the function and aesthetics of the affected teeth and overall dentition. This article provides a review of advancements in diagnosis and the treatment strategies for MIH, offering a reference for clinical practice.

This study aims to evaluate the efficacy of Chinese medicine injections in treating transient ischemic attack(TIA) based on network Meta-analysis. Randomized controlled trial(RCT) about Chinese medicine injections in treating TIA were retrieved from PubMed, Web of Science, Cochrane Library, EMbase, CNKI, VIP, Wanfang, and SinoMed with the time interval from inception to March 1, 2024. The methodological quality of the included articles was assessed by ROB 2.0, and the GRADE system was employed to evaluate the quality of evidence. The gemtc package of R 4.1.2 was used to perform the network Meta-analysis. Finally, 63 RCTs with a total sample size of 5 750 cases were included, involving 11 Chinese medicine injections(Shuxuetong Injection, Danhong Injection, Shuxuening Injection, Ginkgo Damo Injection, Shenxiong Glucose Injection, Ligustrazine Injection, Salviae Miltiorrhizae and Ligustrazine Hydrochloride Injection, Salvianolic Acids for Injection, Dengzhan Xixin Injection, Guhong Injection, and Xueshuantong Injection). All patients received conventional western medicine treatment, and the experimental group was additionally treated with Chinese medicine injection. Network Meta-analysis yielded the following results.(1) In terms of improving the clinical total response rate, 11 Chinese medicine injections combined with conventional western medicine outperformed conventional western medicine alone, and Dengzhan Xixin Injection + conventional western medicine had the best effect.(2) In terms of reducing plasma viscosity, 7 Chinese medicine injections combined with conventional western medicine outperformed conventional western medicine alone, and Shenxiong Glucose Injection + conventional western medicine had the best effect.(3) In terms of reducing whole blood high shear viscosity, 6 Chinese medicine injections combined with conventional western medicine outperformed conventional western medicine alone, and Guhong Injection + conventional western medicine had the best effect.(4) In terms of reducing whole blood low shear viscosity, 6 Chinese medicine injections combined with conventional western medicine outperformed conventional western medicine alone, and Shuxuening Injection + conventional western medicine had the best effect.(5) In terms of reducing fibrinogen, 9 Chinese medicine injections combined with conventional western medicine outperformed conventional western medicine alone, and Ginkgo Damo Injection + conventional western medicine had the best effect.(6) In terms of increasing the average blood flow velocity, 3 Chinese medicine injections combined with conventional western medicine outperformed conventional western medicine alone, and Shuxuening Injection + conventional western medicine had the best effect. In summary, compared with conventional western medicine alone, Chinese medicine injections combined with conventional western medicine were effective in improving the clinical total response rate and the average blood flow velocity, as well as reducing plasma viscosity, whole blood high shear viscosity, whole blood low shear viscosity, and fibrinogen. However, due to the limited quality and quantity of the included articles, the above conclusions need to be verified by more high-quality, multi-center, and large-sample RCT.
Humans ; Drugs, Chinese Herbal/administration & dosage* ; Injections ; Ischemic Attack, Transient/drug therapy* ; Randomized Controlled Trials as Topic ; Treatment Outcome

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

A novel fumigation moxibustion device has been designed to enable adjustable and controllable moxa smoke temperature, maintaining a relatively stable fumigation temperature while improving the utilization efficiency of moxa smoke. The device consists of five main components: a temperature control chamber, fumigation outlet, temperature measurement module, moxa smoke filtration chamber, and elastic band. It is compact, refined, and easy to operate. The device allows users to set the desired fumigation temperature according to therapeutic needs and simultaneously filters and eliminates residual moxa smoke after treatment. This design addresses the challenges of traditional fumigation moxibustion therapy, including unstable moxa smoke temperature, difficulty in regulation, low utilization efficiency, and high dependence on manual operation. It contributes to the promotion and application of fumigation moxibustion therapy and supports the establishment of a standardized moxibustion system.
Moxibustion/methods* ; Humans ; Equipment Design ; Fumigation ; Temperature

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*