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.

This study aimed to compare the ameliorative effects of Lycii Fructus and Chrysanthemi Flos at different ratios on retinal damage in mice and to elucidate the underlying mechanisms. A retinal injury model was established by intraperitoneal injection of sodium iodate(NaIO_3) solution. The mice were divided into the following groups: blank group, model group, positive drug(AREDS 2) group, low-and high-dose groups of Lycii Fructus and Chrysanthemi Flos at 1∶1, low-and high-dose groups at 3∶1, and low-and high-dose groups at 1∶3. Administration was carried out 15 days after modeling. The visual acuity of the mice was assessed using the black-and-white box test. The fundus was observed using an optical coherence tomography device, and retinal thickness was measured. HE staining was used to observe the morphology and pathological changes of the retina. The levels of oxidative factors in serum and ocular tissues were measured using assay kits. The levels of inflammatory factors in serum and ocular tissues were detected by enzyme-linked immunosorbent assay(ELISA), and the expression of Nrf2, HO-1, and NF-κB proteins in ocular tissues was analyzed by Western blot. The results showed that after administration of Lycii Fructus and Chrysanthemi Flos at different ratios, the model group showed improved retinal thinning and disordered arrangement of retinal layers, elevated content of SOD and GSH in the serum and ocular tissues, and reduced levels of MDA, TNF-α, IL-1β, and IL-6. Lycii Fructus and Chrysanthemi Flos at 1∶1 and 1∶3 showed better improvement effects. The combination significantly upregulated the expression levels of Nrf2 and HO-1 and downregulated the expression of NF-κB p65. These results indicate that Lycii Fructus and Chrysanthemi Flos at different ratios can improve retinal damage, reduce oxidative stress, and alleviate inflammation in both the body and ocular tissues of mice. The mechanism may be related to the regulation of the Nrf2/HO-1 and NF-κB signaling pathways in ocular tissues. These findings provide a theoretical basis for the clinical application of Lycii Fructus and Chrysanthemi Flos in the treatment of dry age-related macular degeneration.
Animals ; Mice ; Retina/injuries* ; Male ; Lycium/chemistry* ; Drugs, Chinese Herbal/administration & dosage* ; Chrysanthemum/chemistry* ; NF-kappa B/genetics* ; Humans ; Retinal Diseases/metabolism* ; NF-E2-Related Factor 2/metabolism* ; Oxidative Stress/drug effects* ; Flowers/chemistry* ; Heme Oxygenase-1/genetics*

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To evaluate the effect of sodium hyaluronate combined with recombinant human epidermal growth factor(rhEGF)in the treatment of dry eye after cataract surgery.Methods Patients with dry eye after cataract surgery were divided into treatment group and control group.The control group was treated with sodium hyaluronate eye drops via dropping into the conjunctival sac,a drop per dose,tid,for 4 weeks.On this basis,the treatment group was treated with rhEGF eye drops via dropping into the conjunctival sac,1-2 drops per dose,tid,for 4 weeks.The two groups were compared on overall clinical efficacy,dry eye symptoms before treatment and after 4 weeks of treatment.Tear-film breakup time(BUT),basic tear secretion test(schirmer Ⅰ test,SⅠT),corneal fluorescein staining(CFS)score,meibomian gland yield secretion score(MGYSS),and the levels of tear inflammatory factors were compared between two groups before treatment and after 4 weeks of treatment.The safety was evaluated.Results Finally,41 cases and 39 cases were included in the treatment group and the control group,respectively.After treatment,the total effective rates in the treatment group and the control group were 95.12％and 79.49％,with statistically significant difference(P＜0.05).After 4 weeks of treatment,dry eye symptom scores of the treatment group and control group were 1.42±0.18 and 2.31±0.26;BUT were(11.89±1.26)and(10.46±1.27)s;SⅠT were(10.12±1.35)and(8.45±0.87)mm;CFS scores were 0.83±0.11 and 1.94±0.25;MGYSS scores were 10.85±1.17 and 12.43±1.56;interleukin-1β levels in tears were(35.26±3.53)and(74.12±7.55)ng·L-1;interleukin-6 levels were(8.35±0.86)and(12.41±12.56)pg·mL-1.Compared with the control group,the above indexes in the treatment group were statistically significant(all P＜0.05).The incidence rates of adverse drug reactions in the treatment group and the control group were 12.20％and 10.26％,without statistically significant difference between the groups(P＞0.05).Conclusion Sodium hyaluronate combined with rhEGF can significantly improve dry eye symptoms after cataract surgery,enhance the stability of tear film,reduce tear inflammatory factors,and protect the integrity of meibomian gland.

Purpose: This study aims to evaluate the efficacy and safety of a new combination treatment of vinorelbine and pyrotinib in human epidermal growth factor receptor 2 (HER2)–positive metastatic breast cancer (MBC) and provide higher level evidence for clinical practice. Materials and Methods: This was a prospective, single-arm, phase 2 trial conducted at three institutions in China. Patients with HER2-positive MBC, who had previously been treated with trastuzumab plus a taxane or trastuzumab plus pertuzumab combined with a chemotherapeutic agent, were enrolled between March 2020 and December 2021. All patients received pyrotinib 400 mg orally once daily plus vinorelbine 25 mg/m2 intravenously or 60-80 mg/m2 orally on day 1 and day 8 of 21-day cycle. The primary endpoint was progression-free survival (PFS), and the secondary endpoints included the objective response rate (ORR), disease control rate (DCR), overall survival, and safety. Results: A total of 39 patients were enrolled. All patients had been pretreated with trastuzumab and 23.1% (n=9) of them had accepted trastuzumab plus pertuzumab. The median follow-up time was 16.3 months (95% confidence interval [CI], 5.3 to 27.2), and the median PFS was 6.4 months (95% CI, 4.0 to 8.8). The ORR was 43.6% (95% CI, 27.8% to 60.4%) and the DCR was 84.6% (95% CI, 69.5% to 94.1%). The median PFS of patients with versus without prior pertuzumab treatment was 4.6 and 8.3 months (p=0.017). The most common grade 3/4 adverse events were diarrhea (28.2%), neutrophil count decreased (15.4%), white blood cell count decreased (7.7%), vomiting (5.1%), and anemia (2.6%). Conclusion Pyrotinib plus vinorelbine showed promising efficacy and tolerable toxicity as second-line treatment in patients with HER2-positive MBC.

ObjectiveThis study aimed to analyze the difference in setup error before and after correction of systematic error. To determine the most appropriate image-guided strategy during HT treatment， we use different scanning ranges and image-guidance frequencies in patients with nasopharyngeal carcinoma （NPC） treated with helical tomotherapy （HT）. MethodsFifteen patients with NPC who received HT treatment in Sun Yat-sen University Cancer Center from October 2019 to February 2020 were selected. Megavoltage computed tomography （MVCT） scanning was performed before each treatment. After five times of radiotherapy， system-error correction was performed to adjust the setup center. The setup errors before and after the correction of systematic errors， as well as the setup errors of different scanning ranges and different scanning frequencies， were collected for analysis and comparison. ResultsWhen comparing the setup errors before and after the correction of systematic error， the differences in setup errors in the left–right （LR）， superior–inferior （SI）， and anterior–posterior （AP） directions were statistically significant （P<0.05）.The different scanning ranges of "nasopharynx + neck" and "nasopharynx" were compared， and a statistically significant difference was found in yaw rotational errors （P<0.05）. In the comparison of daily and weekly scan frequency after system-error correction， a significant difference was found in AP direction （P<0.05）. ConclusionDuring radiotherapy for NPC， the systematic error can be corrected according to the first five setup errors， and then small-scale scanning was selected for image-guided radiotherapy every day.