Objective: To summarize the circumstances of rescue events in hospitalized patients after radiotherapy for head and neck cancer in order to provide a reference for clinical decision-making. Methods: This study was approved by the hospital's medical ethics committee. A retrospective analysis was conducted on the clinical data of 86 hospitalized patients admitted between 2015 and 2023 for oral and maxillofacial diseases following radiotherapy for head and neck cancer. Based on the occurrence of rescue events, patients were divided into a rescue group (n=20) and a non-rescue group (n=66). In addition, 20 healthy subjects matched for age and gender with the rescue group were included as a control group. First, baseline characteristics were compared between the rescue and non-rescue groups. Second, a descriptive analysis of the clinical characteristics and rescue events of the rescue group patients was performed. Third, differences in laboratory inflammatory and nutritional indicators, as well as tracheostomy status, were compared between the rescue and non-rescue groups. Fourth, Dolphin Imaging software was used to measure cone beam computed tomography images of the rescue group, non-rescue group, and control group. Upper airway parameters were measured, including the sagittal and coronal diameters of the nasopharyngeal, palatopharyngeal, glossopharyngeal, and laryngopharyngeal segments Results: ① A comparison of baseline characteristics between the rescue and non-rescue groups showed no statistically significant differences in age, gender, or body mass index, but the proportion of patients with comorbid pulmonary diseases was higher in the rescue group (P<0.05). ② In the rescue group, the primary reasons for radiotherapy were nasopharyngeal carcinoma (65%) and tongue cancer (25%). The mean age was (54.75 ± 11.59) years, with a male-to-female ratio of 3:1. The main reasons for this admission included radio-osteomyelitis in the mandible (55%) and recurrence of oral and maxillofacial tumors or new primary tumors in the oral and maxillofacial region (40%). The primary reason for rescue during hospitalization was dyspnea (55%), followed by acute massive hemorrhage (15%) and cardiac arrest (15%). Rescue events occurred mostly postoperatively (65%), with a median time of occurrence at 5 days post-operatively; 30% occurred preoperatively, and 5% occurred intraoperatively. ③ Laboratory indicators and tracheostomy status: preoperative and postoperative neutrophil counts, as well as the proportion of patients undergoing tracheostomy, were higher in the rescue group compared to the non-rescue group, while postoperative albumin levels were lower (P<0.05). ④ Upper airway measurements: the coronal and sagittal diameters of the nasopharyngeal segment and the coronal diameter of the glossopharyngeal segment were smaller in both the rescue and non-rescue groups compared to the control group (P<0.001). Conclusion The data from this study indicate that hospitalized patients experiencing rescue events after radiotherapy for head and neck cancer often have comorbid pulmonary diseases or tumor recurrence/new primary tumors, and frequently present with dyspnea. They exhibit a higher inflammatory state, poorer nutritional status, a greater need for emergency airway intervention, and share a common anatomical basis for dyspnea--upper airway narrowing. Clinical attention should be fully given to high-risk patients with these characteristics.

BackgroundCurrently， the incidence of depression among teenagers is on the rise， and the related academic problems are becoming increasingly serious. Short video addiction has a negative impact on teenagers' emotional issues and academic achievements. However， few studies have explored the relationship between this addiction and the learning burnout of teenagers with depression， and even fewer have focused on the role paths of impulsivity and coping disposition in this process. ObjectiveTo explore the relationship between short video addiction and learning burnout in adolescent patients with depression， as well as the pathway of impulsivity and coping disposition， so as to provide references for the intervention of learning burnout in adolescent patients with depression. MethodsA total of 191 adolescent patients who were hospitalized at The Affiliated Brain Hospital of Guangzhou Medical University from December 2024 to April 2025 and met the diagnostic criteria for depression according to the International Classification of Diseases， tenth edition （ICD-10） were selected consecutively. The Short Video Addiction Measurement Scale （SVAMS）， the Brief Barratt Impulsiveness Scale （BBIS）， the Simplified Coping Style Questionnaire （SCSQ）， and the Adolescent Student Burnout Inventory （ASBI） were used for assessment. Pearson correlation analysis was employed to examine the correlations of the scores of each scale. Model 6 of the SPSS macro Process 4.2 was employed to analyze the chained mediation pathway of impulsivity and coping disposition between short video addiction and learning burnout. ResultsA total of 173 cases （90.58%） of adolescent patients with depression completed the valid questionnaire survey. Correlation analysis showed that SCSQ coping disposition score was negatively correlated with the SVAMS score， the BBIS score， and the ASBI score （r=-0.282， -0.341， -0.431， P<0.01）， the SVAMS score was positively correlated with the BBIS score and the ASBI score （r=0.339， 0.262， P<0.01）， and the BBIS score was positively correlated with the ASBI score （r=0.486， P<0.01）. The pathway analysis showed that the direct effect of short video addiction on learning burnout was not statistically significant， but the total effect and the indirect effect were statistically significant. The effect values were 0.275 （95% CI： 0.207–0.343） and 0.193 （95% CI： 0.143–0.246）， respectively， with the indirect effect accounting for 70.18%. Impulsivity and coping disposition both played independent mediating roles between short video addiction and learning burnout， with effect values of 0.122 （95% CI： 0.090–0.156） and 0.054 （95% CI： 0.032–0.079）， accounting for 44.36% and 19.64% of the total effect， respectively. The chained mediation effect of impulsivity and coping disposition was significant， with an effect value of 0.017 （95% CI： 0.011–0.026）， accounting for 6.18% of the total effect. ConclusionAlthough short video addiction does not directly affect learning burnout in adolescent patients with depression， it may indirectly influence learning burnout through independent and chain paths of impulsivity and coping disposition. ［Funded by Guangzhou Key Clinical Specialty （Clinical Medical Research Institute）］

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.

Iron is an essential trace element in the human body, crucial in maintaining normal physiological functions. Recent studies have identified iron ions as a significant factor in initiating the ferroptosis process, a novel mode of programmed cell death characterized by iron overload and lipid peroxide accumulation. The iron metabolism pathway is one of the primary mechanisms regulating ferroptosis, as it maintains iron homeostasis within the cell. Numerous studies have demonstrated that abnormalities in iron metabolism can trigger the Fenton reaction, exacerbating oxidative stress, and leading to cell membrane rupture, cellular dysfunction, and damage to tissue structures. Therefore, regulation of iron metabolism represents a key strategy for ameliorating ferroptosis and offers new insights for treating diseases associated with iron metabolism imbalances. This review first summarizes the mechanisms that regulate iron metabolic pathways in ferroptosis and discusses the connections between the pathogenesis of various diseases and iron metabolism. Next, we introduce natural and synthetic small molecule compounds, hormones, proteins, and new nanomaterials that can affect iron metabolism. Finally, we provide an overview of the challenges faced by iron regulators in clinical translation and a summary and outlook on iron metabolism in ferroptosis, aiming to pave the way for future exploration and optimization of iron metabolism regulation strategies.

OBJECTIVES: This study aimed to compare the osteogenic performance differences of titanium surface coatings modified by dopamine or silanized graphene oxide, and to provide a more suitable modification scheme for titanium surface graphene oxide coatings. METHODS: Titanium was subjected to alkali-heat treatment and then modified with dopamine and silanization, respectively, followed by coating with graphene oxide. Control and experimental groups were designed as follows: pure titanium (Ti) group; titanium after alkali-heat treatment (Ti-NaOH) group; titanium after alkali-heat treatment and silanization modification (Ti-APTES) group; titanium after alkali-heat treatment and dopamine modification (Ti-DOPA) group; titanium with silanization-modified surface decorated with graphene oxide (Ti-APTES/GO) group; titanium with dopamine-modified surface decorated with graphene oxide (Ti-DOPA/GO) group. The physical and chemical properties of the material surfaces were analyzed using scanning electron microscopy (SEM), contact angle goniometer, X-ray photoelectron spectroscopy (XPS), and Raman spectrometer. The proliferation and adhesion morphology of mouse embryonic osteoblast precursor cells MC3T3-E1 on the material surfaces were observed by cell viability detection and immunofluorescence staining followed by laser confocal microscopy. The effects on the osteogenic differentiation of MC3T3-E1 cells were studied by alkaline phosphatase (ALP) staining, alizarin red staining and quantification, and real-time quantitative polymerase chain reaction. RESULTS: After modification with graphene oxide coating, a thin-film-like structure was observed on the surface under SEM. The hydrophilicity of all experimental groups was improved, among which the Ti-DOPA/GO group had the best hydrophilicity. XPS and Raman spectroscopy analysis showed that the modified materials exhibited typical D and G peaks, and XPS revealed the presence of a large number of oxygen-containing functional groups on the surface. CCK8 assay showed that all groups of materials had no cytotoxicity, and the proliferation level of the Ti-APTES/GO group was higher than that of the Ti-DOPA/GO group. Under the laser confocal microscope, the cells in the Ti-DOPA/GO and Ti-APTES/GO groups spread more fully. The Ti-DOPA/GO and Ti-APTES/GO groups had the deepest ALP staining, and the Ti-APTES/GO group had the most alizarin red-stained mineralized nodules and the highest quantitative result of alizarin red staining. In the Ti-DOPA/GO and Ti-APTES/GO groups, the expression of the early osteogenic-related gene RUNX2 reached a relatively high level, while in the expression of the late osteogenic-related genes OPN and OCN, the Ti-APTES/GO group performed better than the Ti-DOPA/GO group. CONCLUSIONS Ti-APTES/GO significantly outperformed Ti-DOPA/GO in promoting the adhesion, proliferation, and in vitro osteogenic differentiation of MC3T3-E1 cells.
Titanium/chemistry* ; Graphite/chemistry* ; Dopamine/chemistry* ; Animals ; Mice ; Osteogenesis ; Osteoblasts/cytology* ; Surface Properties ; Cell Proliferation ; Silanes/chemistry* ; Cell Adhesion ; Coated Materials, Biocompatible/chemistry* ; Cell Differentiation ; Alkaline Phosphatase/metabolism* ; Microscopy, Electron, Scanning