[摘 要] 目的：评价DC-CIK细胞免疫治疗辅助西妥昔单抗联合CAPEOX（奥沙利铂 + 卡培他滨）化疗方案治疗全RAS基因野生型、BRAF基因野生型晚期结直肠癌（CRC）的临床疗效与安全性。方法：回顾性分析2020年12月至2023年10月期间东部战区总医院肿瘤科收治的52例晚期CRC的临床资料，其中对照组与观察组分别为26例。观察组在对照组化疗基础上给予DC-CIK细胞治疗，统计患者的临床疗效和不良反应，分析患者的近期疗效、生活质量评分、化疗不良反应发生情况，以及治疗前后肿瘤标志物和免疫指标的变化。结果：与对照组相比，观察组晚期CRC患者的疾病控制率（DCR）、生活质量均明显提高（均P < 0.05），化疗后腹泻或便秘的发生率、肿瘤标志物CA72-4均明显降低（均P < 0.05），NK细胞计数明显上升（P < 0.05）。结论：在晚期CRC患者行DC-CIK细胞免疫治疗辅助西妥昔单抗联合CAPEOX化疗方案治疗安全可行，能够显著提高DCR，为患者带来显著的临床获益。

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

OBJECTIVE: To evaluate the feasibility and short-term effectiveness of three-dimensional (3D)-printed customized porous acetabular components for reconstruction of extensive acetabular bone defects during primary total hip arthroplasty (THA). METHODS: The clinical data of 8 patients with extensive acetabular bone defects, who were treated with 3D-printed individualized porous acetabular components between July 2018 and January 2022, were retrospectively analyzed. The cohort comprised 4 males and 4 females with an average age of 48 years ranging from 34 to 56 years. Acetabular bone defects were classified as Paprosky type ⅢA in 3 cases and type ⅢB in 5 cases. The causes of acetabular destruction were hip tuberculosis (5 cases), pigmented villonodular synovitis (2 cases), and syphilitic arthritis (1 case). Visual analogue scale (VAS) score and Harris hip score (HHS) were used to evaluate the pain relief and hip function before and after operation. Reconstruction outcomes were further assessed by imaging results [X-ray film and Tomosynthesis Shimadzumetal artefact reduction technology (T-SMART)], and the mechanical properties were evaluated by finite element analysis. RESULTS: The operation time ranged from 174 to 195 minutes (mean, 187 minutes), and intraoperative blood loss ranged from 390 to 530 mL (mean, 465 mL). All 8 patients were follow-up 26-74 months (mean, 44 months). Among the 5 patients with tuberculosis, none experienced postoperative recurrence. At last follow-up, the VAS score was 0.3±0.5 and the HHS score was 87.9±3.7, both significantly improved compared to preoperative values ( t=25.170, P<0.001; t=-28.322, P<0.001). X-ray films at 2 years after operation demonstrated satisfactory matching between the 3D-printed customized acetabular component and the acetabulum. The postoperative center of rotation of the operated hip was shifted by (2.1±0.5) mm horizontally and (2.0±0.7) mm vertically relative to the contralateral side, with both offsets showing significant differences compared to preoperative values ( t=24.700, P<0.001; t=55.230, P<0.001). T-SMART imaging showed satisfactory osseointegration at the implant-host bone interface. No complications such as aseptic loosening or screw breakage was observed during follow-up. Finite element analysis showed that the acetabular component had good mechanical properties. CONCLUSION The application of 3D-printed individualized porous acetabular components in the reconstruction of extensive acetabular bone defects demonstrated precise anatomical reconstruction, stable mechanical support, and good functional performance in short-term follow-up, offering a potential alternative for acetabular defect reconstruction in primary THA.
Humans ; Middle Aged ; Male ; Female ; Printing, Three-Dimensional ; Arthroplasty, Replacement, Hip/instrumentation* ; Acetabulum/diagnostic imaging* ; Adult ; Follow-Up Studies ; Retrospective Studies ; Hip Prosthesis ; Prosthesis Design ; Porosity ; Treatment Outcome ; Plastic Surgery Procedures/methods*

Kirsten rat sarcoma viral oncogene homolog (KRAS) protein inhibitors are a promising class of therapeutics, but research on molecules that effectively penetrate the blood-brain barrier (BBB) remains limited, which is crucial for treating central nervous system (CNS) malignancies. Although molecular generation models have recently advanced drug discovery, they often overlook the complexity of biological and chemical factors, leaving room for improvement. In this study, we present a structure-constrained molecular generation workflow designed to optimize lead compounds for both drug efficacy and drug absorption properties. Our approach utilizes a variational autoencoder (VAE) generative model integrated with reinforcement learning for multi-objective optimization. This method specifically aims to enhance BBB permeability (BBBp) while maintaining high-affinity substructures of KRAS inhibitors. To support this, we incorporate a specialized KRAS BBB predictor based on active learning and an affinity predictor employing comparative learning models. Additionally, we introduce two novel metrics, the knowledge-integrated reproduction score (KIRS) and the composite diversity score (CDS), to assess structural performance and biological relevance. Retrospective validation with KRAS inhibitors, AMG510 and MRTX849, demonstrates the framework's effectiveness in optimizing BBBp and highlights its potential for real-world drug development applications. This study provides a robust framework for accelerating the structural enhancement of lead compounds, advancing the drug development process across diverse targets.

Objective To observe the expression of adhesion molecule CD226 on the small intestinal group 3 innate lymphoid cells (ILC3) in mice. Methods The bioinformatics was used to analyze the expression of CD226 on murine ILCs. Small intestinal mucosal lamina propria lymphocytes (LPL) were isolated from wild-type C57BL/6J mice, and the expression of CD226 on ILC1 and ILC3 was detected by flow cytometry. A mouse model of dextran sulfate sodium (DSS)-induced colitis was constructed to observe the changes in the expression of CD226 on ILC3. Results Both ILC1 and ILC3 in the mice small intestine expressed CD226 molecules; the proportion of ILC3 was reduced, while the expression level of CD226 on ILC3 was increased in the colitis model. Conclusion CD226 is expressed on the small intestines of mice, and although the proportion of ILC3 decreases in the DSS-induced colitis, the expression of CD226 on ILC3 increases.
Animals ; Mice ; Colitis/chemically induced* ; Immunity, Innate ; Intestine, Small ; Lymphocytes ; Mice, Inbred C57BL

Objective:To investigate the diagnostic value of an intelligent assisted grading algorithm for nuclear cataract using anterior segment optical coherence tomography (AS-OCT) images.Methods:A diagnostic test study was conducted.AS-OCT image data were collected from 939 cases of 1 608 eyes of nuclear cataract patients at the Shanghai Tenth People's Hospital of Tongji University from November 2020 to September 2021.The data were obtained from the electronic case system and met the requirements for clinical reading clarity.Among them, there were 398 cases of 664 male eyes and 541 cases of 944 female eyes.The ages of the patients ranged from 18 to 94 years, with a mean age of (65.7±18.6) years.The AS-OCT images were labelled manually from one to six levels according to the Lens Opacities Classification System Ⅲ (LOCS Ⅲ grading system) by three experienced clinicians.This study proposed a global-local cataract grading algorithm based on multi-level ranking, which contains five basic binary classification global local network (GL-Net).Each GL-Net aggregates multi-scale information, including the cataract nucleus region and original image, for nuclear cataract grading.Based on ablation test and model comparison test, the model's performance was evaluated using accuracy, precision, sensitivity, F1 and Kappa, and all results were cross-validated by five-fold.This study adhered to the Declaration of Helsinjki and was approrved by Shanghai Tenth People's Hospital of Tongji University (No.21K216).Results:The model achieved the results with an accuracy of 87.81%, precision of 88.88%, sensitivity of 88.33%, F1 of 88.51%, and Kappa of 85.22% on the cataract dataset.The ablation experiments demonstrated that ResNet18 combining local and global features for multi-level ranking classification improved the accuracy, recall, specificity, F1, and Kappa metrics.Compared with ResNet34, VGG16, Ranking-CNN, MRF-Net models, the performance index of this model were improved.Conclusions:The deep learning-based AS-OCT nuclear cataract image multi-level ranking classification algorithm demonstrates high accuracy in grading cataracts.This algorithm may help ophthalmologists in improving the diagnostic accuracy and efficiency of nuclear cataract.

Objective To construct a survival prediction model for the patients with extramedullary plasmacytoma (EMP),and to evaluate its application value.Methods The data of the patients diagnosed as EMP from 2000 to 2019 were collected from the National Cancer Institute's Surveillance,Epidemiology,and End Results (SEER) database.Random forest algorithm was used to screen variables,multivariate Cox pro-portional hazards regression model was used to determine the independent risk factors of EMP prognosis,and a nomogram model was constructed based on these factors.The total score of the patients was calculated ac-cording to the nomogram model,and the total samples were divided into the low,medium and high risk groups according to the optimal cutoff value by using X-tile software,and the Kaplan-Meier survival curves of the three groups were analyzed.The predictive performance of the model was evaluated using area under the curve (AUC) of time-dependent receiver operating characteristic (t-ROC) curve,AUC after X years N repeated K-fold cross-validation,calibration curve,and decision curve analysis (DCA).Results A total of 1458 patients with EMP were included,including 796 cases of deletions and 662 cases of death.In the deletion and deaths groups,the majority were aged 60-<75 years old (35.4％,41.2％),male (63.1％,66.3％),white race peo-ple (81.3％,80.4％),and married (68.2％,59.4％).Finally,age (45-<60 years old/60-<75 years old/≥ 75 years old),marital status (single/others),non-primary malignant tumor,and without surgery and radio-therapy were determined to be the independent risk factors for the survival of EPM patients (P<0.05).Based on the above independent risk factors,a survival prediction model was constructed,and a nomogram was drawn.According to the optimal cutoff value,the total sample was divided into the score of 0-96 group (low risk group),score of 98-135 group (medium risk group) and score of 139-191 group (high risk group).The Kaplan-Meier survival analysis revealed that there was statistically significant difference in the survival time a-mong the three groups (P<0.0001).AUC of t-ROC curves for 1,3,5 years and AUC after cross-validation all were>0.7,indicating that the model had a good degree of differentiation.The calibration curves suggested a good consistency between the prediction and practical over survival rate,and DCA indicated that the model could improve the clinical benefits.Conclusion The constructed survival prediction model for EMP patients based on the SEER database could help the clinicians to identify the prognostic risk factors and predict the o-verall survival rate of the patients.