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.

Cholangiocarcinoma (CCA) is a fatal malignancy with steadily increasing incidence and poor prognosis. Since most CCA cases are diagnosed at an advanced stage, systemic therapies, including chemotherapy, radiotherapy, targeted therapy, and immunotherapy, play a crucial role in the management of unresectable CCA. The recent advances in targeted therapies and immunotherapies brought more options in the clinical management of unresectable CCA. This review depicts the advances of targeted therapies and immunotherapies for unresectable CCA, summarizes crucial clinical trials, and describes the efficacy and safety of different drugs, which may help further develop precision and individualization in the clinical treatment of unresectable CCA.
Humans ; Cholangiocarcinoma/drug therapy* ; Immunotherapy/methods* ; Bile Duct Neoplasms/drug therapy* ; Molecular Targeted Therapy/methods*

OBJECTIVES: To explore the application of the colloidal gold method and chemiluminescence method in detecting gonadotropin (Gn) in morning urine for assessing pubertal development status in children. METHODS: A total of 132 children diagnosed with central precocious puberty (CPP), early and fast puberty (EFP), and premature thelarche (PT) at Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from November 2021 to December 2022 were included, along with 685 healthy children who underwent routine health examinations at the hospital's pediatric health care department during the same period. All 132 patients underwent a gonadotropin-releasing hormone (GnRH) stimulation test. Both patients and healthy children had their urinary Gn levels measured using the colloidal gold method and chemiluminescence method, including levels of luteinizing hormone (LH) and follicle-stimulating hormone (FSH). The correlation between serum Gn and urinary Gn detected by the two methods, as well as the correlation between Tanner stages of healthy children and urinary Gn, was analyzed. RESULTS: Urine Gn levels detected by both the colloidal gold method and chemiluminescence method showed a positive correlation with serum LH baseline values, LH peak values, baseline LH/FSH ratios, and peak LH/FSH ratios (P<0.05). In healthy children, urinary LH levels detected by the chemiluminescence method gradually increased from Tanner stage Ⅰ to Ⅳ (P<0.05), while urinary FSH levels were lower in Tanner stage I than in stages Ⅱ, Ⅲ, and IV (P<0.05). Urinary LH levels detected by the colloidal gold method were lower in Tanner stage I compared to stages Ⅱ, Ⅲ, and IV, with the highest levels observed in Tanner stage Ⅳ (P<0.05). Additionally, urinary FSH levels in Tanner stage Ⅲ were higher than in stages Ⅰ and Ⅱ (P<0.05). The area under the receiver operating characteristic curve for evaluating Tanner stages I and II in healthy children using urinary LH and FSH levels by the chemiluminescence method and urinary LH levels by the colloidal gold method were 0.730, 0.699, and 0.783, respectively. CONCLUSIONS The colloidal gold method and chemiluminescence method for detecting Gn in morning urine show good correlation with serum Gn levels. As a non-invasive and convenient detection method, the colloidal gold method can serve as a useful tool for screening the onset of pubertal development in children.
Humans ; Child ; Male ; Female ; Gold Colloid ; Luminescent Measurements/methods* ; Gonadotropins/urine* ; Puberty ; Luteinizing Hormone/urine* ; Child, Preschool ; Adolescent ; Follicle Stimulating Hormone/urine*

The incidence of thyroid cancer keeps rising globally,with the majority being papillary thyroid carcinoma (PTC),which has a favorable prognosis.However,some aggressive PTCs exhibit different clinical behaviors and higher mortality risks,with the growth rate surpassing that of well-differentiated PTC and undifferentiated cancers.Therefore,achieving precise diagnosis and treatment of thyroid carcinoma presents a significant challenge.Photoacoustic imaging is a molecular imaging technology that integrates optical imaging and ultrasound,providing imaging information on structure,function,and molecules.Moreover,it can utilize exogenous contrast agents to realize tumor treatment,such as photothermal therapy,serving as a promising technology for precise diagnosis and treatment of thyroid carcinoma.Researchers both domestically and internationally have explored the application of photoacoustic imaging in the precise diagnosis and treatment of thyroid tumors.This article reviews the research progress,elucidates the advantages and limitations of photoacoustic imaging in the diagnosis and treatment of thyroid carcinoma,and prospects on the precise diagnosis and treatment of this disease.
Humans ; Thyroid Neoplasms/diagnostic imaging* ; Photoacoustic Techniques/methods* ; Precision Medicine

Objective:To investigate the relationship between serum osteopontin (OPN), bone morphogenetic protein 2 (BMP2), retinol binding protein 4 (RBP4) and renal function and bone mineral density in patients with diabetes nephropathy (DN).Methods:A total of 120 patients with DN diagnosed in the Affiliated Hospital of Jining Medical University from January 2020 to December 2021 were selected as the DN group, 60 patients with simple diabetes as the type 2 diabetes mellitus (T2DM) group, and 60 subjects with normal glucose tolerance test as the control group. The serum OPN, BMP2, RBP4, low bone mineral density (LBMD), femoral neck bone density (FNBMD) and renal function indicators of the three groups were compared. According to the urinary albumin excretion rate (UAER) of DN patients, the patients were divided into microalbuminuria DN group (71 cases) and massive albuminuria DN group (49 cases), and stratified comparison was made. The simple linear correlation analysis was used to analyze the OPN of DN patients. BMP2, RBP4, renal function and bone mineral density.Results:The fasting blood glucose (FPG), glycated hemoglobin (HbA 1c), serum creatinine (Scr), UAER, and cystatin (CysC) levels of DN group patients were significantly higher than those of T2DM group and control group, and the differences were statistically significant (all P<0.05); The FPG and HbA 1c in the T2DM group were higher than those in the control group, and the differences were statistically significant (all P<0.05); The OPN and BMP2 of DN group patients were higher than those of T2DM group and control group, while the RBP4, LBMD, FNBMD of DN group were lower than those of T2DM group and control group, and the differences were statistically significant (all P<0.05); The OPN and BMP2 of the T2DM group were higher than those of the control group, while RBP4 was lower than that of the control group, and the differences were statistically significant (all P<0.05); The levels of FPG, HbA 1c, Scr, UAER, and CysC in patients with macroalbuminuria DN were significantly higher than those in patients with microalbuminuria DN, and the differences were statistically significant (all P<0.05); The OPN and BMP2 of patients in the large albuminuria DN group were higher than those in the microalbuminuria DN group, while the RBP4, LBMD, and FNBMD of patients in the large albuminuria DN group were lower than those in the microalbuminuria DN group, and the differences were statistically significant (all P<0.05). The OPN of DN group patients was positively correlated with Scr, UAER, and CysC (all P<0.05), while BMP2 was positively correlated with UAER and CysC (all P<0.05); The OPN and BMP2 of DN group patients were negatively correlated with LBMD and FNBMD (all P<0.05), while RBP4 was positively correlated with LBMD and FNBMD (all P<0.05). Conclusions:OPN, BMP2, RBP4 are closely related to the degree of renal function impairment and bone loss in DN patients, and can to some extent reflect the degree of bone metabolism and osteoporosis in T2DM patients.