PURPOSE: The secondary damage of spinal cord injury (SCI) starts from the collapse of the blood spinal cord barrier (BSCB) to chronic and devastating neurological deficits. Thereby, the retention of the integrity and permeability of BSCB is well-recognized as one of the major therapies to promote functional recovery after SCI. Previous studies have demonstrated that activation of hypoxia inducible factor-1α (HIF-1α) provides anti-apoptosis and neuroprotection in SCI. Endogenous HIF-1α, rapidly degraded by prolylhydroxylase, is insufficient for promoting functional recovery. Dimethyloxalylglycine (DMOG), a highly selective inhibitor of prolylhydroxylase, has been reported to have a positive effect on axon regeneration. However, the roles and underlying mechanisms of DMOG in BSCB restoration remain unclear. Herein, we aim to investigate pathological changes of BSCB restoration in rats with SCI treated by DOMG and evaluate the therapeutic effects of DMOG. METHODS: The work was performed from 2022 to 2023. In this study, Allen's impact model and human umbilical vein endothelial cells were employed to explore the mechanism of DMOG. In the phenotypic validation experiment, the rats were randomly divided into 3 groups: sham group, SCI group, and SCI + DMOG group (10 rats for each). Histological analysis via Nissl staining, Basso-Beattie-Bresnahan scale, and footprint analysis was used to evaluate the functional recovery after SCI. Western blotting, TUNEL assay, and immunofluorescence staining were employed to exhibit levels of tight junction and adhesion junction of BSCB, HIF-1α, cell apoptosis, and endoplasmic reticulum (ER) stress. The one-way ANOVA test was used for statistical analysis. The difference was considered statistically significant at p < 0.05. RESULTS: In this study, we observed the expression of HIF-1α reduced in the SCI model. DMOG treatment remarkably augmented HIF-1α level, alleviated endothelial cells apoptosis and disruption of BSCB, and enhanced functional recovery post-SCI. Besides, the administration of DMOG offset the activation of ER stress induced by SCI, but this phenomenon was blocked by tunicamycin (an ER stress activator). Finally, we disclosed that DMOG maintained the integrity and permeability of BSCB by inhibiting ER stress, and inhibition of HIF-1α erased the protection from DMOG. CONCLUSIONS Our findings illustrate that the administration of DMOG alleviates the devastation of BSCB and HIF-1α-induced inhibition of ER stress.
Spinal Cord Injuries/pathology* ; Animals ; Apoptosis/drug effects* ; Amino Acids, Dicarboxylic/therapeutic use* ; Recovery of Function/drug effects* ; Rats ; Rats, Sprague-Dawley ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Male ; Spinal Cord/blood supply*

Recent studies have shown that the physiological homeostasis of oral mucosal cells is regulated by the circadian clock.Dis-ruption or dysfunction of the circadian clock is closely associated with the development of oral squamous cell carcinoma(OSCC).Research based on the circadian clock offers a novel perspective on the pathogenesis and therapeutic strategies for OSCC.However,there is current-ly limited research on this topic,and people generally have insufficient understanding and recognition of the circadian clock.Given the complexity and challenges of circadian clock which is the fourth dimension of medical research,we organize relevant experts based on summarizing the current research results of circadian clock in the pathogenesis and precision diagnosis and treatment of OSCC,combining the scientific principles of the circadian clock's role and their long-term research experience,then summarizes and recommends the con-sensus opinions for the research of circadian clock in the pathogenesis mechanism and precision diagnosis and treatment of human OSCC,with the hope of providing guidance for the basic research and clinical application of circadian clock or circadian rhythm in the pathogene-sis mechanism and precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma.

Oropharyngeal squamous cell carcinoma(OPSCC)is a malignant tumor originating from the squamous epithelium of the oro-pharyngeal mucosa,accounting for more than 90％of oropharyngeal malignancies.In recent years,human papillomavirus(HPV)infec-tion has become one of the primary etiological factors of oropharyngeal squamous carcinoma.The incidence of HPV-associated oropharyn-geal squamous carcinoma has been rising annually,with a noticeable trend toward younger populations,posing a significant threat to hu-man health.Due to the distinct biological behavior and clinical characteristics of HPV-associated oropharyngeal squamous carcinoma com-pared to its non-HPV-related counterpart,the diagnostic and treatment strategies for oropharyngeal squamous carcinoma have undergone substantial changes.Prevention and screening for oropharyngeal squamous carcinoma are of critical importance.The diagnostic and treat-ment process involves multi-disciplinary collaboration,including oral and maxillofacial surgery,otolaryngology,head and neck surgery,oncology,radiology and pathology.Based on evidence from clinical practice,a comprehensive,integrated diagnostic and therapeutic ap-proach has been established,centered around the concept of"prevention,screening,diagnosis,treatment,and rehabilitation",covering the entire patient lifecycle and providing a valuable reference for clinical practice.

Colorectal cancer(CRC)is a common malignancy of the digestive system,with increasing morbidity and mortality worldwide.The standard treatment for CRC has,in the past,been surgery,chemotherapy,and radiotherapy.However,these treatments have significant side effects and are particularly challenging for patients with advanced metastatic CRC(mCRC).Therefore,it is crucial to explore alternative and more effective treatments.In recent years,with the development of molecular technology,numerous biomarkers have been identified,and targeted therapy and immunotherapy have achieved surprisingly positive results in the treatment of mCRC.Patients receiving targeted ther-apy and immunotherapy have an improved prognosis and quality of life.On this basis,this article reviews the latest research progress in tar-geted therapy and immunotherapy for mCRC,providing a reference for precision treatment of mCRC.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

BACKGROUND:During the treatment of posterolateral tibial plateau fractures through the fibular head approach,the gap between the fibular head and the lateral plateau cannot accommodate the posterior placement of a plate for all patients.OBJECTIVE:To analyze,via finite element analysis,the differences in fixation strength resulting from varying the angles and quantities of horizontal arm variable angle screws in the plate during the treatment of posterolateral tibial plateau fractures through the fibular head approach.METHODS:A finite element model was established based on CT images of the knee to ankle joints of a 30-year-old healthy adult male volunteer.The models were divided into two categories:posteriorly placed group and non-posteriorly placed group based on whether the lateral locking compression plate was posteriorly placed.The posteriorly placed group was further subdivided into groups A-D based on the offset angle of the two variable angle screws(0°,5°,10°,and 15°).The non-posteriorly placed group was subdivided into groups E and F based on offset angles(0° and 15°).Finite element analysis was used to evaluate the von Mises stress distribution,maximum von Mises stress,and compressive displacement under loads of 250,500,and 750 N,exploring the mechanical differences between the groups.RESULTS AND CONCLUSION:(1)Finite element analysis results showed that under a 750 N load,the maximum compressive displacement trend of the internal fixation device was D＜B=C=F＜A＜E.The trend for maximum von Mises stress was B＜C＜A＜D＜F＜E.The trend for maximum compressive displacement on the bone was C=D＜B＜A＜F＜E,and for maximum von Mises stress,it was B＜C＜A＜F＜D＜E.The displacement and stress trends for the six models were similar under loads ranging from 250 N to 750 N.(2)These results suggest that for posterolateral tibial plateau fractures fixed through the fibular head approach,posterior placement of the plate should aim to accommodate two screws.If only one screw can be fixed during surgery,variable angle screws should be offset in the range of 0-15° to increase the probability of securing two screws.

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.

Dopamine, as a catecholamine neurotransmitter widely distributed in the central nervous system, is involved in physiological functions such as motivation, arousal, reinforcement, and movement through various dopamine signaling pathways. The hippocampus receives dopaminergic neuron projections from regions such as the ventral tegmental area, locus coeruleus, and substantia nigra. Through D1-like and D2-like receptors, dopamine exerts significant regulatory effects such as spatial navigation, episodic memory, fear, anxiety, and reward. This review mainly summarizes the research progress on the functions of dopamine in the hippocampus from aspects including the sources of dopamine, receptor distribution and function, and the association of hippocampal dopamine system dysregulation with neurodegenerative diseases. The aim is to provide insights into the involvement of the dopamine system in hippocampal functions and the diagnosis and treatment of related diseases.
Hippocampus/physiology* ; Dopamine/physiology* ; Humans ; Animals ; Receptors, Dopamine D2/physiology* ; Memory/physiology* ; Signal Transduction/physiology* ; Neurodegenerative Diseases/physiopathology*

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult