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.

Objective: To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. Methods: A multidisciplinary collaborative model was adopted to develop a preoperative anemia management system that integrates intelligent early warning, standardized treatment pathways, and quality control. The system utilizes natural language processing technology to automatically capture laboratory data and establish evidence-based medical decision support functions. A pre-post study design was employed to compare changes in preoperative anemia screening rates, preoperative anemia intervention rates, reasonable use of iron supplements, and perioperative red blood cell transfusion rates before and after system implementation. Results: After system implementation, the standardization of anemia diagnosis and treatment significantly improved: 1) Screening effectiveness: The anemia screening rate increased to 50.00% (an increase of 27.24%); 2) Intervention effectiveness: The anemia treatment rate rose to 56.30% (an increase of 14.02%); 3) Treatment standardization: The reasonable use rate of iron supplements increased to 55.33% (an increase of 21.02%); the red blood cell transfusion rate decreased to 18.29% (a decrease of 4.07%), and the amount of red blood cell transfusions was reduced by 291 units. Conclusion: This system achieves full-process management of preoperative anemia through information technology, significantly enhancing the standardization of diagnosis and treatment as well as intervention effectiveness, providing an effective solution for perioperative anemia management.

Objective: To explore the independent and interactive effects of school green space exposure and outdoor activity duration on screening myopia among primary and secondary school students, so as to provide theoretical support for the prevention and control of screening myopia in children and adolescents. Methods: From September to November 2023, 117 487 primary and secondary school students from 497 schools were selected using a cluster random sampling method, covering 98 counties (cities, districts) in Jiangsu Province. Data on the students screening myopia status and associated health influencing factors were collected and analyzed. School green space exposure was quantified using the normalized difference vegetation index (NDVI), which was extracted with ArcGIS Pro software; meanwhile, information on students outdoor activity duration was gathered through self reported questionnaires. Multivariate Logistic regression was applied to assess the independent and interactive effects of green space exposure and outdoor activity duration on screening myopia among primary and secondary school students. Results: Univariate analysis showed that there were statistically significant differences in screening myopia detection rates among primary and secondary school students of different genders, NDVI groups, every outdoor activity duration, monitoring points, school stages, parents educational level, and whether they lived on campus or had parents with screening myopia ( χ 2=88.91-1 950.08, all P <0.05); as the school age and sedentary time increased, the detection rate of screening myopia in primary and secondary school students also increased ( χ 2 trend =8 410.15, 2 028.91, both P <0.05). Independent effects showed that compared to the low NDVI group, the medium and high NDVI groups had lower risks of screening myopia ( OR =0.93, 0.95, both P <0.05). Compared to those with outdoor activity duration<2 h/d, students with outdoor activity duration≥2 h/d had a lower risk of screening myopia ( OR =0.96, P <0.05). When stratified by school level, compared to the low NDVI group, the medium NDVI group had lower risks of screening myopia in primary and junior high schools (primary school: OR =0.91; junior high school: OR =0.88, both P <0.05). Compared to those with outdoor activity duration<2 h/d, junior high school students with outdoor activity duration≥2 h/d had a lower risk of screening myopia ( OR = 0.90, P <0.05). When stratified by monitoring site, urban primary and secondary school students in the medium and high NDVI groups and those with outdoor activity duration≥2 h/d had lower risks of screening myopia ( OR =0.92, 0.92, 0.93, all P <0.05). Interactive effects showed that when medium or high NDVI was combined with outdoor activity duration≥2 h/d, the risks of screening myopia among primary and secondary school students were lower (medium NDVI×≥2 h/d: OR =0.89; high NDVI×≥ 2 h/d : OR =0.89, both P <0.05), and the combined effect was superior to that of a single factor. Conclusion Green space exposure and outdoor activity duration have negative correlations with screening myopia among primary and secondary students, and the combined effect is better than that of a single factor.

Objective: To investigate the association between outdoor light at night (LAN) exposure and sleep quality among primary and secondary school students, and to examine the pathways of negative affects including depressive, stress and anxiety symptoms, so as to provide a theoretical basis for optimizing the school environment and enhancing the physical and mental well being of students. Methods: In December 2024, a total of 36 885 students from 154 primary and secondary schools in Suzhou, Nantong, and Changzhou were included via a stratified cluster sampling method. Sleep quality and negative affect were assessed by using the Pittsburgh Sleep Quality Index (PSQI), Center for Epidemiologic Studies Depression Scale (CES-D), Generalized Anxiety Disorder-7 (GAD-7), and Depression, Anxiety and Stress Scale-21 (DASS-21), respectively. Outdoor LAN exposure data were obtained from the national polar orbiting partnership visible infrared imaging radiometer suite nighttime light(NPP-VIIRS NTL) dataset provided by the National Earth System Science Data Center. Multivariate Logistic regression model was employed to analyze the association between LAN exposure and sleep quality across different regions, with stratification by monitoring site. Spearman correlation analysis was used to examine the relationships between LAN, negative affect, and sleep quality. The mediating role of negative affect was tested by using Model 4 of the PROCESS macro. Results: The detection rates among students were 13.95%( n =5 147) for depressive symptom, 16.72%( n =6 166) for stress symptom, and 17.49%( n =6 451) for anxiety symptom. The median outdoor LAN exposure was 28.85(19.10, 41.44)nW/(cm 2 · ( sr). After adjusting for confounders, multivariate Logistic regression analysis showed that high LAN exposure ( Q 4) was positively associated with sleep problems (urban areas: OR =1.28, 95% CI = 1.17- 1.41; rural areas: OR =1.21, 95% CI =1.07-1.36; both P <0.05). Spearman correlation analysis revealed significant positive correlations between LAN exposure, depressive symptoms, stress symptoms, anxiety symptoms, and sleep quality ( r =0.03-0.75, all P < 0.01). The mediation analysis indicated that all dimensions of negative affect significantly mediated the relationship between high LAN exposure and poor sleep quality (all P <0.01). Specifically, the indirect effects were 0.03 (95% CI =0.02-0.05) for depressive symptom, 0.05(95% CI =0.03-0.08) for stress symptom, and 0.07(95% CI =0.05-0.09) for anxiety symptom. Overall, 31.9% of the total effect was mediated by negative affect, with anxiety (14.89%) being the strongest mediator, followed by stress (10.64%) and depression(6.38%). Conclusion Reducing high levels of outdoor LAN exposure and implementing interventions targeting negative affect may contribute to improved sleep quality among primary and secondary school students.

Aim To investigate whether salvianolic acid B ( Sal B) has inhibitory effect on hepatoma HuH- 7 cells and explore whether it works via Hippo/YAP signaling pathway. Methods HuH-7 cells were induced by TGF-β1 (9 pmol · L

Three 2,3-diketoquinoxaline alkaloids were isolated from Heterosmilax yunnanensis Gagnep. Their structures were determined through 1D and 2D NMR, HR-ESI-MS, UV, and IR as 1-[5′-(3″-hydroxy-3″-methyl) glutaryl] ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (1), 1-[2′-(3″-hydroxy-3″-methyl) glutaryl]ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (2), and 1-ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (3). Compounds 1 and 2 are novel compounds, and 3 was isolated from H. yunnanensis for the first time. The hepatoprotective activity of these three compounds was evaluated, with compound 3 showing promising hepatoprotective activity.