Temporomandibular disorders （TMD） encompass a prevalent group of conditions affecting the masticatory muscles， temporomandibular joint， and associated structures. Currently， it is widely recognized by scholars both domestically and internationally that TMD has a complex etiology and pathogenesis. Most patients present clinically with pain， yet effective treatment options remain limited. In recent years， the role of ion channels in the pathological mechanisms and therapeutic approaches for TMD has garnered increasing attention. This review systematically summarizes the function of ion channels in the management of temporomandibular joint diseases. First， the multifaceted roles of ion channels in treating TMD are examined， including their regulatory effects on TMJ muscle dysfunction， joint structural abnormalities， and TMJ-related pain. Finally， the potential value of ion channel research in TMD therapy is discussed. With advancing research in this field， ion channel-targeted therapies for temporomandibular disorders are expected to achieve new breakthroughs， thereby providing an important theoretical foundation and practical guidance for developing novel clinical treatment strategies.

Objective To explore the independent risk factors for complicated coronary heart disease (CHD) in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) and to construct a risk prediction model. Methods A retrospective study was performed to analyze the clinical data of 308 OSAHS patients who visited Jiangsu Provincial People's Hospital from January 2021 to June 2025. The patients were divided into the CHD group (n=80) and non-CHD group (n=228) according to the presence or absence of complicated CHD. Independent risk factors were identified using univariate analysis and multivariate logistic regression, and a nomogram prediction model was constructed. The model was evaluated using the calibration curve, Hosmer-Lemeshow test, Decision Curve Analysis (DCA) curve, and Receiver Operating Characteristic (ROC) curve. Results The incidence of CHD in OSAHS patients was 25.97%. Age, history of hypertension, oxygen desaturation index (ODI), severe polysomnography (PSG) grade, decreased high-density lipoprotein cholesterol, elevated homocysteine, and elevated troponin I were independent risk factors for OSAHS complicated with CHD (P<0.05). The nomogram model demonstrated good calibration (Hosmer-Lemeshow test, P=0.995), and the DCA curve showed high clinical net benefit. The area under the ROC curve was 0.940 (95% CI: 0.908~0.972), with a sensitivity of 0.842 and a specificity of 0.900. Conclusion Age, history of hypertension, ODI, PSG grade, high-density lipoprotein cholesterol, homocysteine, and troponin I are independent risk factors for CHD in OSAHS patients. The prediction model constructed based on these factors can provide a reliable tool for clinical nurses to early identify high-risk individuals and formulate targeted intervention strategies.

Alzheimer's disease (AD) is characterized by cognitive and functional deterioration, with pathological features such as amyloid-beta (Aβ) aggregates in the extracellular spaces of parenchymal neurons and intracellular neurofibrillary tangles formed by the hyperphosphorylation of tau protein. Despite a thorough investigation, current treatments targeting the reduction of Aβ production, promotion of its clearance, and inhibition of tau protein phosphorylation and aggregation have not met clinical expectations, posing a substantial obstacle in the development of drugs for AD. Recently, artificial intelligence (AI), computational biology (CB), and systems biology (SB) have emerged as promising methodologies in AD research. Their capacity to analyze extensive and varied datasets facilitates the identification of intricate patterns, thereby enriching our comprehension of AD pathology. This paper provides a comprehensive examination of the utilization of AI, CB, and SB in the diagnosis of AD, including the use of imaging omics for early detection, drug discovery methods such as lecanemab, and complementary therapies like phototherapy. This review offers novel perspectives and potential avenues for further research in the realm of translational AD studies.

Vascular damage plays a significant role in the onset and progression of Alzheimer's disease (AD). However, the precise molecular mechanisms underlying the induction of neuronal injury by vascular damage remain unclear. The present study aimed to examine the impact of fibrinogen (Fg) on tau pathology. The results showed that Fg deposits in the brains of tau P301S transgenic mice interact with tau, enhancing the cytotoxicity of pathological tau aggregates and promoting tau phosphorylation and aggregation. Notably, Fg-modified tau fibrils caused enhanced neuronal apoptosis and synaptic damage compared to unmodified fibrils. Furthermore, intrahippocampal injection of Fg-modified tau fibrils worsened the tau pathology, neuroinflammation, synaptic damage, neuronal apoptosis, and cognitive dysfunction in tau P301S mice compared to controls. The present study provides compelling evidence linking Fg and tau, thereby connecting cerebrovascular damage to tau pathology in AD. Consequently, inhibiting Fg-mediated tau pathology could potentially impede the progression of AD.
Animals ; tau Proteins/metabolism* ; Alzheimer Disease/metabolism* ; Fibrinogen/metabolism* ; Mice, Transgenic ; Mice ; Disease Models, Animal ; Memory Disorders/metabolism* ; Male ; Mice, Inbred C57BL ; Brain/metabolism* ; Hippocampus/metabolism* ; Protein Aggregation, Pathological/metabolism* ; Apoptosis ; Phosphorylation

Neuropathic pain is a chronic condition caused by damage or dysfunction in the nervous system. While the spleen may influence neuropathic pain, its role has been poorly understood. This study demonstrates that the spleen plays a crucial role in regulating neuropathic pain through the bed nucleus of the stria terminalis (BNST) - paraventricular nucleus of the hypothalamus (PVN) neural circuit in a chronic constriction injury (CCI) mouse model. Splenectomy, splenic denervation, or splenic sympathectomy significantly increased the mechanical withdrawal threshold (MWT) and reduced macrophage infiltration in the dorsal root ganglia (DRG) of CCI mice. Pseudorabies virus injections into the spleen revealed connections to the BNST and PVN in the brain. Chemogenetic inhibition of the BNST-PVN circuit increased macrophage infiltration in the DRG and decreased the MWT; these effects were reversed by splenectomy, splenic denervation, or sympathectomy. These findings underscore the critical role of the spleen, regulated by the BNST-PVN circuit, in neuropathic pain.
Animals ; Neuralgia/pathology* ; Septal Nuclei/physiopathology* ; Male ; Spleen/physiopathology* ; Paraventricular Hypothalamic Nucleus/physiopathology* ; Mice, Inbred C57BL ; Splenectomy ; Mice ; Neural Pathways/physiopathology* ; Disease Models, Animal ; Ganglia, Spinal/physiopathology* ; Sympathectomy ; Macrophages

The mechanism of action of traditional Chinese medicine (TCM) remains unclear. Historically, research on TCM has mainly focused on exploring the mechanisms of active components acting on single targets. However, it is insufficient to explain the complex mechanisms by which these active components in TCM treat diseases. In recent years, the emergence of molecular glues (MGs) theory has provided new strategies to address this issue. MGs are small molecules that can promote interactions between proteins at their interface. The characteristic of MGs is to establish connections between diverse protein structures, thereby enabling a chemically-mediated proximity effect that triggers a wide spectrum of biological functions. Natural products are the result of billions of years of evolutionary processes in the natural environment. Thus, the extensive structural diversity of natural products renders them a rich source of MGs, including polyketides, terpenoids, steroids, lignans, organic acids, alkaloids and other classes. Currently, several well-known natural MGs, including the immunosuppressants cyclosporin A (CsA) and tacrolimus (FK506), as well as the anticancer agent taxol, have been incorporated into clinical practice. Meanwhile, the advancement of new technologies is propelling the discovery of novel MGs from natural products. Thus, we primarily summarize a growing variety of MGs from natural origins reported in recent years and categorize them based on the chemical structural types. Moreover, the main sources of TCM are natural products. The discovery of natural MGs promises to provide a new perspective for the elucidation of the molecular mechanism behind the efficiency of TCM. In summary, this review aims to provide insights from the perspective of natural products that could potentially influence TCM and modern drug development.

Small cell lung cancer (SCLC) is the thoracic malignant tumor and accounts for about 15% of lung malignancies and transfer often occurs by the time of diagnosis. Extensive stage-small cell lung cancer (ES-SCLC) accounts for about 2/3 of all SCLC. For many years, radiotherapy has occupied an important position in the treatment of SCLC, especially in the treatment of ES-SCLC, because SCLC is more sensitive to radiotherapy. However, in recent years, immune checkpoint inhibitor has shown more excellent antitumor activity in the treatment of ES-SCLC and become the mainstream argument for the treatment of ES-SCLC. However, will radiotherapy be buried by the times among the therapeutic approaches for ES-SCLC? In this article, we will review the clinical progress of radiotherapy, immunotherapy and combination therapy for ES-SCLC.
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Humans ; Small Cell Lung Carcinoma/therapy* ; Lung Neoplasms/therapy* ; Immunotherapy ; Neoplasm Staging ; Radiotherapy/methods* ; Combined Modality Therapy

Inflammatory bowel disease (IBD) is a chronic and recurrent intestinal inflammatory disease, which not only affects the digestive tract, but also involves extraintestinal organs and tissues such as joints and eyes, and ultimately endangers human health and affects the quality of life of patients. With the development of information technology, there is an increasing application of digital therapeutics in the management of IBD. This article aims to comprehensively analyze the characteristics, use, and challenges of digital therapeutics in the management of IBD, and explore its potential to improve treatment adherence, disease surveillance, and improve patients' quality of life.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To establish criteria for diagnosing lymph node metastasis (LNM) in newly diagnosed papillary thyroid cancer (PTC) patients based on 18F-FDG PET/MR and evaluate its diagnostic efficiency. Methods:The data of 14 patients with PTC (all females, age (38.8±13.5) years) who underwent 18F-FDG PET/MR and ultrasound sequentially 2 weeks before surgery at the First Affiliated Hospital of the Air Force Medical University from May 2021 to August 2023 were retrospectively analyzed. Visual and semi-quantitative assessments were performed on all patients step by step (Ⅱ-Ⅵ area) and neck by neck (left, right, and central area). The dimensions of all suspected lymph nodes were measured on T 2 weighted imaging (WI)-MRI and SUV max was measured on PET. Taking postoperative pathology as the reference standard, the independent risk factors for predicting LNM were determined by multivariate logistic regression analysis, and the diagnostic efficiency of each model was evaluated by ROC curve analysis. Results:A total of 21 macroscopic regions of lymph nodes(15 were malignant, 6 were benign) and 178 lymph nodes (120 were malignant, 58 were benign) were cleared by surgery. Multivariate logistic regression analysis showed that SUV max (odds ratio ( OR)=1.865, 95% CI: 1.323-2.630, P<0.001) and short diameter on MRI (SD-MRI) ( OR=1.752, 95% CI: 1.189-2.580, P=0.005) were independent predictors of LNM. The cut-off value of SD-MRI in predicting LNM was 5.7mm (AUC=0.812, Youden index (YI)=0.463). For the SD-MRI cut-off values ≥5.7 or <5.7mm, the corresponding SUV max cut-off values were 1.6 and 1.8, respectively. When " dual threshold" quantitative criteria (SD-MRI≥5.7mm + SUV max≥1.6 or SD-MRI<5.7mm + SUV max≥1.8) was used as the diagnostic criteria of 18F-FDG PET/MR, the AUC and YI could be improved to 0.909 and 0.818. Based on the regional level analysis, sensitivity, specificity, and accuracy of LNM diagnosis by ultrasound, MRI, and 18F-FDG PET/MR " dual threshold" criteria were 11/15 vs 12/15 vs 13/15, 5/6 vs 3/6 vs 5/6, 76.2%(16/21) vs 71.4%(15/21) vs 85.7%(18/21), respectively. Conclusion:Compared with the ultrasound and MRI, the 18F-FDG PET/MR " dual threshold" criteria exhibits higher sensitivity and accuracy in determining the scope of LNM clearance for PTC patients.