Objective To analyze epidemiological characteristics and influencing factors of atrial fibrillation (AF) in Suqian in 2019-2023. Methods A total of 1 869 patients with AF admitted to medical institutions in Suqian from January 2019 to December 2023 were selected as the survey subjects. The diagnosis and treatment data of the AF patients were retrospectively analyzed to explore epidemiological characteristics. A total of 2 000 healthy controls during the same period were selected as the control group. The influencing factors of AF were analyzed by univariate and multivariate logistic regression models. Results The incidence of AF in Suqian increased with the increase of year, age and labor intensity. The incidence rate was higher (>50%) in patients with male gender, old age, education level of junior high school and below, city living, heavy physical labor, smoking history, drinking history and underlying diseases (coronary heart disease, stroke, heart failure, hyperuricemia, hyperthyroidism, hypertension, diabetes mellitus, and hyperlipidemia). Multivariate logistic regression analysis showed that hyperuricemia, hyperthyroidism, cognitive dysfunction and anxiety/depression were influencing factors of AF in Suqian (P<0.05). Conclusion From 2019 to 2023, AF risk is relatively high in patients in Suqian, which is closely related to hyperuricemia, hyperthyroidism, cognitive dysfunction and anxiety/depression.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveTo explore the role and potential mechanism of circulating glutamate in enhancing insulin sensitivity by aerobic exercise. This research may provide a novel strategy for preventing metabolic diseases through precise exercise interventions. MethodsTo investigate the effects of elevated circulating glutamate on insulin sensitivity and its potential mechanisms, 18 male C57BL/6 mice aged 6 to 8 weeks were randomly divided into 3 groups: a control group (C), a group receiving 500 mg/kg glutamate supplementation (M), and a group receiving 1 000 mg/kg glutamate supplementation (H). The intervention lasted for 12 weeks, with treatments administered 6 d per week. Following the intervention, an insulin tolerance test (ITT) and a glucose tolerance test (GTT) were conducted. Circulating glutamate levels were measured using a commercial kit, and the activity of the skeletal muscle InsR/IRS1/PI3K/AKT signaling pathway was analyzed via Western blot. To further investigate the role of circulating glutamate in enhancing insulin sensitivity through aerobic exercise, 30 male C57BL/6 mice were randomly assigned to 3 groups: a control group (CS), an exercise intervention group (ES), and an exercise combined with glutamate supplementation group (EG). The ES group underwent treadmill-based aerobic exercise, while the EG group received glutamate supplementation at a dosage of 1 000 mg/kg in addition to aerobic exercise. The intervention lasted for 10 weeks, with sessions occurring 6 d per week, and the same procedures were followed afterward. To further elucidate the mechanism by which glutamate modulates the InsR/IRS1/PI3K/AKT signaling pathway, C2C12 myotubes were initially subjected to graded glutamate treatment (0, 0.5, 1, 3, 5, 10 mmol/L) to determine the optimal concentration for cellular intervention. Subsequently, the cells were divided into 3 groups: a control group (C), a glutamate intervention group (G), and a glutamate combined with MK801 (an NMDA receptor antagonist) intervention group (GK). The G group was treated with 5 mmol/L glutamate, while the GK group received 50 μmol/L MK801 in addition to 5 mmol/L glutamate. After 24 h of intervention, the activity of the InsR/IRS1/PI3K/AKT signaling pathway was analyzed using Western blot. ResultsCompared to the mice in group C, the circulating glutamate levels, the area under curve (AUC) of ITT, and the AUC of GTT in the mice of group H were significantly increased. Additionally, the expression levels of p-InsRβ, IRS1, p-AKT, and p-mTOR proteins in skeletal muscle were significantly downregulated. Compared to the mice in group CS, the circulating glutamate levels, the AUC of ITT, and the AUC of GTT in the mice of group ES were significantly reduced. Additionally, the expression levels of p-InsRβ, IRS1, p-AKT, and p-mTOR proteins in skeletal muscle of group ES mice were significantly upregulated. There were no significant changes observed in the mice of group EG. Compared to the cells in group 0 mmol/L, the expression levels of p-InsRβ, p-IRS1, p-PI3K, and p-AKT proteins in cells of group 5 mmol/L were significantly downregulated. Compared to the cells in group C, the expression levels of p-InsRβ, p-IRS1, p-PI3K, and p-AKT proteins in the cells of group G were significantly downregulated. No significant changes were observed in the cells of group GK. ConclusionLong-term aerobic exercise can improve insulin sensitivity by lowering circulating levels of glutamate. This effect may be associated with the upregulation of the InsR/IRS1/AKT signaling pathway activity in skeletal muscle. Furthermore, glutamate can weaken the activity of the InsR/IRS1/PI3K/AKT signaling pathway in skeletal muscle, potentially by binding to NMDAR expressed in skeletal muscle.

Exercise, as a non-pharmacological intervention, holds a pivotal role in metabolic regulation, neuroplasticity, and immune homeostasis maintenance. However, human exercise studies are constrained by ethical limitations in tissue sampling, especially for key organs such as muscles and the brain. Meanwhile, rodent models like mice exhibit physiological differences in exercise patterns and metabolic rates from human. Despite these challenges, approximately 70% of human and mouse genes are conserved, providing a molecular basis for cross-species comparisons. This paper leverages the GEPREP database, which integrates human and mouse exercise transcriptomic data from multiple platforms, to conduct a comprehensive cross-species analysis of exercise-induced gene expression patterns. We employ a stringent data standardization process, including the conversion of orthologous genes and the filtering of low-expressing genes, to ensure the accuracy and reliability of the analysis. A mixed-effects model is utilized to assess differential gene expression across multiple cohorts, identifying genes that are significantly upregulated or downregulated in response to exercise. The analysis reveals a complex pattern of gene expression, with a significant number of genes showing conserved responses between humans and mice, particularly in acute aerobic exercise, where genes such as ATF3, PPARGC1A, and ANKRD1 are commonly upregulated. These genes are implicated in muscle stress response, metabolic regulation, and muscle adaptation, highlighting the shared molecular pathways activated by exercise across species. However, the study also uncovers substantial species-specific differences in gene expression, especially in chronic aerobic exercise, where the number of divergently regulated genes increases. These differences suggest that while some fundamental biological processes are conserved, the specific regulatory mechanisms and gene expression patterns can vary significantly between humans and mice. Functional enrichment analysis further reveals that conserved genes are involved in muscle development, inflammation regulation, and energy metabolism, while species-specific genes are associated with ion transport, extracellular matrix (ECM) organization, and muscle contraction, indicating the multifaceted impact of exercise on skeletal muscle function. The findings emphasize the importance of considering species-specific differences when interpreting results from animal models and translating them to human health applications. The study highlights the need for a more nuanced understanding of the molecular underpinnings of exercise-induced adaptations and underscores the value of cross-species comparative analyses in uncovering the evolutionary and functional basis of these responses. Future research should focus on integrating multi-omics data and expanding the analysis to include other tissues to provide a more comprehensive view of the systemic effects of exercise. Additionally, the development of species-specific gene editing models and the validation of key genes in exercise physiology will further enhance our understanding of the evolutionary logic behind exercise interventions. This study not only provides valuable insights into the molecular mechanisms of exercise-induced adaptations but also underscores the necessity of validating findings from animal models in human cohorts to ensure the reliability and applicability of translational research in exercise science. By addressing these aspects, the study aims to bridge the gap between basic research and clinical applications, ultimately contributing to the development of personalized exercise prescriptions and interventions that can effectively promote health and prevent diseases.

Esophageal cancer is one of the malignant tumors that poses a threat to human health, with both high incidence and malignancy. Currently, surgery following neoadjuvant chemoradiotherapy is the standard treatment for locally advanced esophageal cancer; however, the long-term prognosis remains unsatisfactory. In recent years, inhibitors of programmed death protein-1 (PD-1) and its ligand (programmed death ligand-1, PD-L1) have achieved breakthrough progress in other solid tumors, and research on esophageal cancer is gradually being conducted. With the demonstration of good efficacy of PD-1/PD-L1 inhibitors in the first-line and second-line treatment of advanced unresectable esophageal cancer, their incorporation into neoadjuvant treatment regimens has become a hot topic. Therefore, this article reviews the mechanism of action of PD-1/PD-L1 inhibitors and their application in the neoadjuvant treatment of esophageal cancer.

Sleep deprivation (SD) has emerged as a significant modifiable risk factor for Alzheimer’s disease (AD), with mounting evidence demonstrating its multifaceted role in accelerating AD pathogenesis through diverse molecular, cellular, and systemic mechanisms. SD is refined within the broader spectrum of sleep-wake and circadian disruption, emphasizing that both acute total sleep loss and chronic sleep restriction destabilize the homeostatic and circadian processes governing glymphatic clearance of neurotoxic proteins. During normal sleep, concentrations of interstitial Aβ and tau fall as cerebrospinal fluid oscillations flush extracellular waste; SD abolishes this rhythm, causing overnight rises in soluble Aβ and tau species in rodent hippocampus and human CSF. Orexinergic neurons sustain arousal, and become hyperactive under SD, further delaying sleep onset and amplifying Aβ production. At the molecular level, SD disrupts Aβ homeostasis through multiple converging pathways, including enhanced production via beta-site APP cleaving enzyme 1 (BACE1) upregulation, coupled with impaired clearance mechanisms involving the glymphatic system dysfunction and reduced Aβ-degrading enzymes (neprilysin and insulin-degrading enzyme). Cellular and histological analyses revealed that these proteinopathies are significantly exacerbated by SD-induced neuroinflammatory cascades characterized by microglial overactivation, astrocyte reactivity, and sustained elevation of pro-inflammatory cytokines (IL-1β, TNF-α, IL-6) through NF‑κB signaling and NLRP3 inflammasome activation, creating a self-perpetuating cycle of neurotoxicity. The synaptic and neuronal consequences of chronic SD are particularly profound and potentially irreversible, featuring reduced expression of critical synaptic markers (PSD95, synaptophysin), impaired long-term potentiation (LTP), dendritic spine loss, and diminished neurotrophic support, especially brain-derived neurotrophic factor (BDNF) depletion, which collectively contribute to progressive cognitive decline and memory deficits. Mechanistic investigations identify three core pathways through which SD exerts its neurodegenerative effects: circadian rhythm disruption via BMAL1 suppression, orexin system hyperactivity leading to sustained wakefulness and metabolic stress, and oxidative stress accumulation through mitochondrial dysfunction and reactive oxygen species overproduction. The review critically evaluates promising therapeutic interventions including pharmacological approaches (melatonin, dual orexin receptor antagonists), metabolic strategies (ketogenic diets, and Mediterranean diets rich in omega-3 fatty acids), lifestyle modifications (targeted exercise regimens, cognitive behavioral therapy for insomnia), and emerging technologies (non-invasive photobiomodulation, transcranial magnetic stimulation). Current research limitations include insufficient understanding of dose-response relationships between SD duration/intensity and AD pathology progression, lack of long-term longitudinal clinical data in genetically vulnerable populations (particularly APOE ε4 carriers and those with familial AD mutations), the absence of standardized SD protocols across experimental models that accurately mimic human chronic sleep restriction patterns, and limited investigation of sex differences in SD-induced AD risk. The accumulated evidence underscores the importance of addressing sleep disturbances as part of multimodal AD prevention strategies and highlights the urgent need for clinical trials evaluating sleep-focused interventions in at-risk populations. The review proposes future directions focused on translating mechanistic insights into precision medicine approaches, emphasizing the need for biomarkers to identify SD-vulnerable individuals, chronotherapeutic strategies aligned with circadian biology, and multi-omics integration across sleep, proteostasis and immune profiles may delineate precision-medicine strategies for at-risk populations. By systematically examining these critical connections, this analysis positions sleep quality optimization as a viable strategy for AD prevention and early intervention while providing a comprehensive roadmap for future mechanistic and interventional research in this rapidly evolving field.