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.

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.

The progress and clinical application of troponin detection technology have continuously improved the diagnosis rate of acute myocardial infarction(AMI),which effectively shortens the time of necrotic myocardial reperfusion.Earlier studies have found that high-sensitivity troponin(hs-cTn)is elevated to varying degrees in patients with chronic kidney disease(CKD).Therefore,when patients with CKD have AMI,the application of hs-cTn is limited to a certain extent,and with the lack of chest pain symptoms and the non-specificity of electrocardiogram performance in patients with CKD,it is particularly difficult to make a quick and accurate diagnosis of such patients.Based on this,this article will summarize the application of hs-cTn in AMI,the clinical characteristics of patients with CKD combined with AMI,how to improve the diagnostic accuracy of patients with CKD combined with AMI,and the value of hs-cTn in risk stratification and prognosis assessment of such patients to provide clinical medical staff with reference for early intervention or revascularization of patients.

BACKGROUND:Increased homocysteine level induces apoptosis of human umbilical vein endothelial cells,but the mechanism remains unclear. OBJECTIVE:To investigate the role of hsa-circ-0001360 in human umbilical vein endothelial cell apoptosis induced by homocysteine. METHODS:In vitro cultured human umbilical vein endothelial cells were divided into control group,homocysteine group,interference control group,interference control + homocysteine group,hsa-circ-0001360 interference group,hsa-circ-0001360 + homocysteine interference group,overexpression control group,overexpression control + homocysteine group,hsa-circ-0001360 overexpression group and hsa-circ-0001360 + homocysteine overexpression group.All groups were treated with 100 μmol/L homocysteine.After 72 hours of intervention,the expressions of apoptosis-related proteins Bax,Bcl-2,and Caspase-3 were detected by western blot assay.The apoptotic rate was detected by flow cytometry.Quantitative real-time PCR was used to detect the expression of hsa-circ-0001360. RESULTS AND CONCLUSION:(1)Compared with the control group,the expression of Caspase-3 and Bax was significantly increased(P<0.01),and the expression of Bcl-2 was significantly decreased(P<0.01),and the apoptotic rate was significantly increased(P<0.01)in the homocysteine group.(2)Compared with control group,the expression of hsa-circ-0001360 was significantly increased in the homocysteine group(P<0.01).(3)The expression of hsa-circ-0001360 was significantly higher in the cytoplasm than that in the nucleus(P<0.01).(4)Compared with the interference control C group and interference control + homocysteine group,the expressions of Caspase-3 and Bax were significantly decreased(P<0.01),while the expression of Bcl-2 was significantly increased(P<0.01);the apoptotic rate was significantly decreased(P<0.01)in sh-hsa-circ-0001360 interference group and sh-hsa-circ-0001360 + homocysteine interference group.(5)Compared with overexpression control group and overexpression control + homocysteine group,the expressions of Caspase-3 and Bax were significantly increased(P<0.01),while the expression of Bcl-2 was significantly decreased(P<0.01);the apoptotic rate was significantly increased(P<0.01)in the hsa-circ-0001360 overexpression group and the hsa-circ-0001360 + homocysteine overexpression group.(6)In conclusion,hsa-circ-0001360 can promote the apoptosis of human umbilical vein endothelial cells induced by homocysteine.

Objective To observe the efficacy of ruiyun procedure for hemorrhoids(RPH)combined with conformal suture in the treatment of severe prolapsed hemorrhoids.Methods Seventy-eight patients with severe prolapsed hemorrhoids admitted to the First People's Hospital of Xuzhou from June 2021 to August 2022 were selected and divided into observation group and control group according to random number table method,with 39 cases in each group.Patients in observation group were treated with RPH combined with conformal suture,and patients in control group were treated with external peeling and internal ligation.Operation duration,intraoperative blood loss,postoperative complications,wound healing time,anal function and overall satisfaction were compared between two groups.Results The intraoperative blood loss in observation group was significantly less than that in control group,hospital stay was significantly shorter than that in control group(P<0.05).Postoperative pain,bleeding,anal edema and the formation of anal skin pad in observation group were significantly better than those in control group(P<0.05).At 12 weeks after surgery,Wexner anal incontinence scores in both groups were significantly lower than before surgery(P<0.05),and the Wexner anal incontinence score in observation group was significantly lower than that in control group(P<0.05).The cure rate of observation group was significantly higher than that of control group(92.31%vs.74.36%,χ2=55.46,P=0.03),and the overall satisfaction with treatment was significantly higher than that of control group(χ2=58.57,P=0.02).Conclusion RPH combined with conformal suture is effective in treatment of severe prolapsed hemorrhoids,which can reduce the pain of patients,shorten the length of hospital stay,reduce complications,and improve the comfort and satisfaction of patients.

Improving the reproducibility of biomedical research results is a major challenge. Transparent and accurate reporting of the research process enables readers to evaluate the reliability of the research results and further explore the experiment by repeating it or building upon its findings. The ARRIVE 2.0 guidelines, released in 2019 by the UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), provide a checklist that is applicable to any in vivo animal research report. These guidelines aim to improve the standardization of experimental design, implementation, and reporting, as well as enhance the reliability, repeatability, and clinical translation of animal experimental results. The use of the ARRIVE 2.0 guidelines not only enriches the details of animal experimental research reports, ensuring that information on animal experimental results is fully evaluated and utilized, but also enables readers to understand the content expressed by the author accurately and clearly, promoting the transparency and completeness of the fundamental research review process. At present, the ARRIVE 2.0 guidelines have been widely adopted by international biomedical journals. This article is based on the best practices following the ARRIVE 2.0 guidelines in international journals, and it interprets, explains, and elaborates in Chinese the fifth part of the comprehensive version of the ARRIVE 2.0 guidelines published in PLoS Biology in 2020 (the original text can be found at https://arriveguidelines.org). This section includes the items 6-11 of Recommended 11 section, covering "Animal Care and Monitoring", "Interpretation/Scientific Implications", "Generalisability/Translation", "Protocol Registration", "Data Access" and "Declaration of Interests". Its aim is to promote a comprehensive understanding and use of the ARRIVE 2.0 guidelines among domestic researchers, to enhance the standardization of experimental animal research and reporting, and to promote high-quality development of experimental animal sciences and comparative medicine research in China.