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 investigate the effect and mechanism of Shuangshi Tonglin Capsules (SSTL) in the treatment of prostate fibrosis (PF). METHODS: Human prostate stromal cells (WPMY-1) were used for in vitro experiments to establish PF cell models induced with estradiol (E₂). The cell proliferation, migration and clonogenic capacity were determined by cell counting kit-8, scratch assay, and crystal violet staining, respectively. Sprague-Dawley rats were used for in vivo experiments. The changes in histomorphology and organ index of rat prostate by SSTL were determined. Pathologic changes and collagen deposition changes in rat prostate were observed by haematoxylin and eosin (HE) and Masson staining. Enzyme-linked immunosorbent assay kits were used to determine changes in rat PF markers fibroblast growth factor-23 (FGF-23), E₂ and prostate specific antigen (PSA). Mechanistically, changes in oxidative stress indicators by SSTL were determined in WPMY-1 cells and PF rats. Then the expressions of nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) and transforming growth factor-β1 (TGF-β1)/Smad pathway-related proteins as well as Nrf2 and TGF-β1 mRNA were further detected by Western blot or quantitative real-time polymerase chain reaction both in vivo and in vitro. RESULTS: In the efficacy study, SSTL significantly reduced the proliferation, migration, and clonogenic ability of cells, improved the morphology of the glandular tissue, significantly reduced the prostate index, reduced glandular fibrous tissue and collagen deposition, and resulted in a significant decrease in the levels of FGF-23, E₂ and PSA (P<0.01 or P<0.05). In the mechanistic study, SSTL ameliorated oxidative stress by significantly increasing superoxide dismutase and glutathione peroxidase levels and decreasing malondialdehyde level in WPMY-1 cells and rats (P<0.01 or P<0.05). SSTL significantly elevated the expressions of Nrf2, HO-1, NAD(P)H quinone oxidoreductase 1 (NQO-1), and Smad7 proteins in both cells and rats, and significantly decreased the expressions of TGF-β1, collagen I, α-smooth muscle actin and Smad4 proteins (P<0.01 or P<0.05). SSTL also elevated the content of Nrf2 mRNA and decreased the content of TGF-β1 mRNA in cells and rats (P<0.01 or P<0.05). The Nrf2 inhibitor ML385 was added in in vitro experiments to further validate the pathway relevance. CONCLUSION SSTL was effective in improving PF in vivo and in vitro, and its mechanism of action may function through the Nrf2/TGF-β1 signaling pathway.
Male ; NF-E2-Related Factor 2/metabolism* ; Animals ; Drugs, Chinese Herbal/therapeutic use* ; Signal Transduction/drug effects* ; Transforming Growth Factor beta1/metabolism* ; Rats, Sprague-Dawley ; Humans ; Fibrosis ; Prostate/drug effects* ; Cell Proliferation/drug effects* ; Capsules ; Cell Movement/drug effects* ; Oxidative Stress/drug effects* ; Rats

Seasonal influenza leads to a significant disease burden, and older people infected with influenza are susceptible to various complications. Influenza immunization can prevent infection effectively and significantly reduce the risk of complications and severe cases. Creating a supportive environment for vaccination is crucial in advancing the influenza vaccination rate among the elderly population. In China, the present environment for supporting influenza vaccinations among the elderly is primarily comprised of policies for free vaccination and expense reimbursement, which exhibit noteworthy regional variations across cities and regions. This study systematically analyses the supportive environment and regional disparities associated with influenza vaccination among the elderly in China. It aims to comprehend the opportunities for influenza prevention and control resulting from the current background of influenza vaccination and to identify potential health inequality challenges caused by regional differences. The findings should inform the introduction of relevant national policies and programs to protect the health and well-being of the elderly population.
Humans ; Aged ; Health Status Disparities ; Influenza, Human/prevention & control* ; China ; Cities ; Vaccination

Seasonal influenza leads to a significant disease burden, and older people infected with influenza are susceptible to various complications. Influenza immunization can prevent infection effectively and significantly reduce the risk of complications and severe cases. Creating a supportive environment for vaccination is crucial in advancing the influenza vaccination rate among the elderly population. In China, the present environment for supporting influenza vaccinations among the elderly is primarily comprised of policies for free vaccination and expense reimbursement, which exhibit noteworthy regional variations across cities and regions. This study systematically analyses the supportive environment and regional disparities associated with influenza vaccination among the elderly in China. It aims to comprehend the opportunities for influenza prevention and control resulting from the current background of influenza vaccination and to identify potential health inequality challenges caused by regional differences. The findings should inform the introduction of relevant national policies and programs to protect the health and well-being of the elderly population.
Humans ; Aged ; Health Status Disparities ; Influenza, Human/prevention & control* ; China ; Cities ; Vaccination

Objective: To investigate the association between muscle mass and quality of life in adults in Shaanxi adults. Methods: The data in this analysis were part of the baseline survey of the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019 in Shaanxi Province. The participants' quality of life, including physical component summary (PCS) and mental component summary (MCS), was assessed by the 12-Item Short Form Survey, and the Body Fat Determination System measured muscle mass. A logistic regression model with adjustment for confounding factors was established to analyze the association between muscle mass and quality of life in different genders. Further, sensitivity and subgroup analyses were conducted to explore its stability. Finally, a restricted cubic spline was employed to investigate the dose-response relationship between muscle mass and quality of life in different genders. Results: A total of 20 595 participants were included, with an average age of 55.0, and 33.4% were male. After controlling for potential confounders, compared with the Q₁ group, the risk of low PCS was reduced by 20.6% (OR=0.794, 95%CI: 0.681-0.925) and the risk of low MCS was lower reduced by 20.1% (OR=0.799, 95%CI: 0.689-0.926) in female Q₅ groups. Compared with the Q₁ group, the risk of low PCS was reduced by 24.4% (OR=0.756, 95%CI: 0.644-0.888) in the male Q₂ group. However, no significant association between muscle mass and MCS in males has been found. In females, restricted cubic spline analysis showed a significant linear dose-response relationship between muscle mass and PCS and MCS. Conclusions: There is a positive association between muscle mass and quality of life in Shaanxi adults, especially females. With the increase in muscle mass, the physical and mental functions of the population continue to improve.
Humans ; Female ; Adult ; Male ; Quality of Life ; Cohort Studies ; Adipose Tissue ; China ; Muscles

Objective: To provide a new solution for the digital design of nasal prostheses, this study explores the three-dimensional (3D) facial morphology completion method for external nasal defects based on the non-rigid registration process of 3D face template. Methods: A total of 20 male patients with tooth defect and dentition defect who visited the Department of Prosthodontics, Peking University School and Hospital of Stomatology from June to December 2022 were selected, age 18-45 years old. The original 3D facial data of patients were collected, and the 3D facial data of the external nose defect was constructed in Geomagic Wrap 2021 software. Using the structured 3D face template data constructed in the previous research of the research group, the 3D face template was deformed and registered to the 3D facial data of external nose defect (based on the morphology of non-defective area) by non-rigid registration algorithm (MeshMonk program), and the personalized deformed data of the 3D face template was obtained, as the complemented facial 3D data. Based on the defect boundary of the 3D facial data of the external nose defect, the complemented external nose 3D data can be cut out from the complemented facial 3D data. Then the nasofacial angle and nasolabial angle of the complemented facial 3D data and the original 3D facial data was compared and analyzed, the ratio between the nose length and mid-face height, nose width and medial canthal distance of the complemented facial 3D data was measured, the edge fit between the edge curve of the complemented external nose 3D data and the defect edge curve of the 3D facial data of external nose defect was evaluated, and the morphological difference of the nose between the complemented external nose 3D data and the original 3D facial data was analyzed. Results: There was no significant statistically difference (t=-0.23, P=0.823; Z=-1.72, P=0.086) in the nasofacial angle (28.2°±2.9°, 28.4°±3.5° respectively) and nasolabial angle [95.4°(19.2°), 99.9°(9.5°) respectively] between the 20 original 3D facial data and the complemented facial 3D data. The value of the ratio of nose length to mid-face height in the complemented facial 3D data was 0.63±0.03, and the value of the ratio of nose width to medial canthal distance was 1.07±0.08. The curve deviation (root mean square value) between the edge curve of the complemented external nose 3D data and the defect edge curve of the 3D facial data of external nose defect was (0.37±0.09) mm, the maximum deviation was (1.14±0.32) mm, and the proportion of the curve deviation value within±1 mm was (97±3)%. The distance of corresponding nose landmarks between the complemented facial 3D data and the original 3D facial data were respectively, Nasion: [1.52(1.92)] mm; Pronasale: (3.27±1.21) mm; Subnasale: (1.99±1.09) mm; Right Alare: (2.64±1.34) mm; Left Alare: (2.42± 1.38) mm. Conclusions: The method of 3D facial morphology completion of external nose defect proposed in this study has good feasibility. The constructed complemented external nose 3D data has good facial coordination and edge fit, and the morphology is close to the nose morphology of the original 3D facial data.