Objective To explore the clinical factors influencing complete response in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT). Methods Clinical data of LARC patients treated in the Department of Radiation Oncology at Beijing Shijitan Hospital between January 2013 and December 2024 were retrospectively collected. All patients received nCRT, after which surgery or a watch-and-wait approach was adopted based on treatment response. Univariable and multivariable logistic regression analyses were performed to identify prognostic factors influencing complete response. A clinical prediction model was constructed based on the multivariable analysis results, and its predictive performance was evaluated using the receiver operating characteristic curve. Results A total of 113 eligible patients were included. After nCRT, 19 patients (16.8%) achieved complete response, including 3 with clinical complete response and 16 with pathological complete response. Univariable analysis indicated that pretreatment clinical N stage, extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen were associated with complete response after nCRT (P<0.05). Multivariable logistic regression analysis identified pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen as independent influencing factors for complete response (P<0.05). A prediction model incorporating these independent factors yielded an area under the receiver operating characteristic curve of 0.813 (95% confidence interval: 0.713-0.913), with a sensitivity of 89.5% and a specificity of 60.6%, demonstrating good predictive performance. Conclusion Pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen are independent factors influencing complete response after nCRT in LARC patients. The prediction model combining these factors may assist in evaluating treatment efficacy following nCRT in LARC patients.

Objective To compare the dosimetric and radiobiological differences of helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) in craniospinal irradiation. Methods The CT images of 15 patients who received craniospinal irradiation in our hospital were selected. The target volumes and organs at risk (OARs) were contoured, and HT and VMAT plans were designed. The dosimetric parameters of the two plans were compared. A Matlab program based on equivalent uniform dose was developed to calculate the normal tissue complication probability (NTCP). The NTCP values of the two plans were compared. Results The homogeneity index of the target volume in the HT group was better than that in the VMAT group, with values of 0.06 ± 0.01 and 0.08 ± 0.24, respectively, and the difference was statistically significant (P=0.03). However, there was no significant difference in the conformity index of the target volume (P>0.05). There were significant differences in key indicators (D_mean, V₅, D_max) of the lungs, liver, lens, and eyeballs between the two groups (P<0.05). Regarding OARs, the NTCP values of the lens, optic chiasm, lungs, and liver in the HT and VMAT groups were as follows: 0.04 ± 0.03 vs. 0.1 ± 0.06 in the left lens, 0.04 ± 0.06 vs. 0.1 ± 0.07 in the right lens, 0.16 (0.14-0.17) vs. 0.21 (0.18-0.24) in the optic chiasm, 3.89 × 10⁻⁴ (2.45 × 10⁻⁴-7.3 × 10⁻⁴) vs. 8.95 × 10⁻⁴ (5.19 × 10⁻⁴-1.75 × 10⁻³) in the lungs, and 3.45 × 10⁻⁸ (6.0 × 10⁻⁹-1.036 × 10⁻⁷) vs. 9.54 × 10⁻⁸ (1.70 × 10⁻⁸-2.056 × 10⁻⁷) in the liver; the HT group was superior to the VMAT group, and all differences were statistically significant (P<0.05). The NTCP values of the heart in the two groups were 1.35 × 10⁻⁸ (6.34 × 10⁻⁹-2.06 × 10⁻⁹) vs. 5.06 × 10⁻⁹ (2.29 × 10⁻⁹-7.9 × 10⁻⁹), significantly lower in the VMAT group than in the HT group (P<0.05). Conclusion HT has high homogeneity and consistency. The two plans have their own advantages in OAR protection. For OARs with no significant differences in physical dosimetry, NTCP results can be used as a reference. Therefore, comparing the dosimetric parameters and OAR NTCP of HT and VMAT plans can help select the optimal clinical treatment strategy.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

ObjectiveStroke remains the leading cause of acquired disability in adults worldwide, imposing a substantial socioeconomic burden on patients, families, and healthcare systems. Among the various neurological deficits caused by stroke, motor dysfunction——particularly contralateral hemiplegia——is the most common and debilitating consequence, and it predominantly results from damage to the cortical motor conduction pathways. When motor cortex neurons or their projecting fibers are damaged, the distal axons and their associated myelin sheaths undergo a series of progressive, programmed degeneration, fragmentation, and eventual phagocytic clearance. This pathological process is termed Wallerian degeneration (WD). However, the temporal progression of WD following ischemic stroke and the associated alterations in the local glial microenvironment remain incompletely understood. The present study was designed to systematically elucidate the time course of corticospinal tract (CST) axonal WD after ischemic stroke in mice, and to simultaneously characterize the dynamic pathological changes of astrocytes, microglia, oligodendrocyte lineage cells, and myelinating oligodendrocytes during the WD process. MethodsEight-week-old male C57BL/6J mice were randomly assigned to control and ischemic stroke groups. A focal cortical ischemic stroke model was established in the right sensorimotor cortex using the photothrombotic method. This method induces localized intravascular thrombosis in the target cortical region through precisely controlled interaction between the photosensitizer and laser light of specific wavelength. At day 1 post‑surgery, 2,3,5-triphenyltetrazolium chloride (TTC) staining was performed to evaluate infarct volume, hematoxylin and eosin (HE) staining for histopathological examination, and Nissl staining for assessment of neuronal injury. For axonal degeneration time-course analysis, rAAV-CAG-mCherry anterograde viral tracing was employed to specifically label CST neurons. Cervical spinal cord sections at the CST region were collected at day 3, 5, 7, 14, and 60 post-injury. Morphological changes of mCherry-positive CST fibers were observed under fluorescence microscopy, and the fluorescence signal area fraction within the defined region was quantitatively analyzed to evaluate the dynamic process of axonal degeneration. For glial response assessment, immunofluorescence staining against Iba1 (microglia), GFAP (astrocytes), Olig2 (oligodendrocyte lineage cells), and APC (myelinating oligodendrocytes) was performed at day 7, 14, and 60 post‑surgery. The numbers of positive cells were counted to quantitatively analyze the dynamic changes in each glial population at different time points after ischemia, thereby revealing the evolution of the glial microenvironment during WD. ResultsThe photothrombotic method stably and reliably established an ischemic brain injury model confined to the sensorimotor cortex. Viral tracing revealed that the proportion of mCherry‑positive CST fibers was significantly reduced at day 7 after ischemic injury to the neuronal soma. Immunofluorescence staining demonstrated that during WD, the numbers of microglia and astrocytes in the CST region were significantly increased, whereas the numbers of oligodendrocyte lineage cells and myelinating oligodendrocytes showed no significant changes. ConclusionWD of CST axons is observed at day 7 post-ischemic stroke in a delayed manner. This degenerative process selectively activates microglia and astrocytes, while leaving the number of oligodendrocyte lineage cells largely unaffected.

AIM To investigate the effects of Wuzi Yanzong Pills on subacute aging-induced testicular trauma and AMPK/mTOR pathway in rats.METHODS Rat models of subacute aging were induced by 8-week subcutaneous injection of D-gal(200 mg/kg)into the rat neck,followed by their random assignment into the model group,the metformin group(0.3 g/kg)and the low-dose and high-dose Wuzi Yanzong Pills groups(0.54,2.16 g/kg),with 9 rats in each group,in contrast to the 8 intact rats of the normal group.And the corresponding drug was given by gavage for 4 weeks after modeling,after which the rats had their levels of serum T,FSH,SOD,LH,8-OHdG and MDA detected by ELISA;their pathological changes of testes observed by HE and β-galactosidase staining;and their expressions of aging-related proteins(p16,p21,p53),testicle secretory function-related proteins(CYP11A1,HSD17B3,STAR),autophagy-related proteins(p62,ATG5,Beclin-1,LC3B)and AMPK/mTOR pathway-related protein detected by Western blot and immunohistochemistry.RESULTS Compared with the normal group,the model group displayed morphologically smaller testes and body surface;dry hair;overall atrophic testicular tissue structure;increased testicular protein expressions of γ-H2AX,p16,p21 andβ-galactosidase(P＜0.05,P＜0.01);and decreased p53 protein expression(P＜0.05);suggesting the modeling success.Compared with the model group,the high-dose Wuzi Yanzong Pills group shared decreased levels of serum 8-OHdG,MDA,FSH and LH(P＜0.01);increased levels of SOD and T(P＜0.01);improved sperm damage and almost morphologically normal testicular tissue;decreased testicular protein expressions of p16,p21,p53,p62 and p-mTOR(P＜0.01);and increased protein expressions of CYP11A1,HSD17B3,STAR,ATG5,Beclin-1,LC3B and p-AMPK(P＜0.01).CONCLUSION Wuzi Yanzong Pills can improve the subacute aging-induced testicular injury and testicular function in rats by reducing their oxidative stress through improving their autophagy level and testicle antioxidant capacity.

Objective To explore the effect of evening primrose oil(EPO)on aortic endothelial damage in rats with polycystic ovary syndrome(PCOS),using network pharmacology and in vivo experiments.Methods The potential targets of EPO for improving aortic endothelial injury in PCOS rats were predicted by network pharmacology,and the selected core targets and renin-angiotensin signaling(RAS)pathway were verified by experiments.Fifty-eight female SD rats were divided randomly into a blank group(n=10)and a modeling group(n=48).Rats in the blank group were fed a normal diet and rats in the modeling group received a high-fat diet for 8 weeks.The PCOS model was prepared at week 6 by administration of letrozole(1 mg/(kg·d))for 21 days.Blood was taken from the tail vein after modeling and serum was collected to detect hormone levels.The model rats were then divided randomly into four groups and treated with the corresponding drugs for 6 weeks.Blood,blood vessels,and ovaries were then collected.Tissue morphology was examined by hematoxylin and eosin staining and serum levels of luteinizing hormone(LH),testosterone(T),follicle-stimulating hormone(FSH),endothelin(ET-1),and tumor necrosis factor(TNF-α)were detected by enzyme-linked immunosorbent assay(ELISA).Serum levels of nitric oxide(NO)were determined by spectrophotometry.Protein expression levels of core targets and RAS pathway-related factors were assessed by western blotting and immunohistochemistry.Results Twenty-five intersection targets of EPO and PCOS were identified by network pharmacological analysis.Kyoto encyclopedia of genes and genomes analysis showed that EPO improved vascular injury in PCOS rats via multiple pathways,including RAS.Serum levels of ET-1,FSH,LH,and T measured by ELISA were significantly decreased after EPO treatment,compared with the model group(P＜0.01).EPO significantly decreased the expression levels of Ang Ⅰ,VEGF-B,AT2R,ET-1,and TNF-α proteins in the aorta(P＜0.01)and significantly increased expression levels of Ang Ⅱ,CD31,and endothelial NO synthase proteins(P＜0.01).Conclusions EPO may ameliorate vascular endothelial injury in PCOS model rats by inhibiting the RAS signaling pathway and by overactivation of the ACE/Ang Ⅱ/AT1 axis.

Objective To explore the effect of evening primrose oil(EPO)on aortic endothelial damage in rats with polycystic ovary syndrome(PCOS),using network pharmacology and in vivo experiments.Methods The potential targets of EPO for improving aortic endothelial injury in PCOS rats were predicted by network pharmacology,and the selected core targets and renin-angiotensin signaling(RAS)pathway were verified by experiments.Fifty-eight female SD rats were divided randomly into a blank group(n=10)and a modeling group(n=48).Rats in the blank group were fed a normal diet and rats in the modeling group received a high-fat diet for 8 weeks.The PCOS model was prepared at week 6 by administration of letrozole(1 mg/(kg·d))for 21 days.Blood was taken from the tail vein after modeling and serum was collected to detect hormone levels.The model rats were then divided randomly into four groups and treated with the corresponding drugs for 6 weeks.Blood,blood vessels,and ovaries were then collected.Tissue morphology was examined by hematoxylin and eosin staining and serum levels of luteinizing hormone(LH),testosterone(T),follicle-stimulating hormone(FSH),endothelin(ET-1),and tumor necrosis factor(TNF-α)were detected by enzyme-linked immunosorbent assay(ELISA).Serum levels of nitric oxide(NO)were determined by spectrophotometry.Protein expression levels of core targets and RAS pathway-related factors were assessed by western blotting and immunohistochemistry.Results Twenty-five intersection targets of EPO and PCOS were identified by network pharmacological analysis.Kyoto encyclopedia of genes and genomes analysis showed that EPO improved vascular injury in PCOS rats via multiple pathways,including RAS.Serum levels of ET-1,FSH,LH,and T measured by ELISA were significantly decreased after EPO treatment,compared with the model group(P＜0.01).EPO significantly decreased the expression levels of Ang Ⅰ,VEGF-B,AT2R,ET-1,and TNF-α proteins in the aorta(P＜0.01)and significantly increased expression levels of Ang Ⅱ,CD31,and endothelial NO synthase proteins(P＜0.01).Conclusions EPO may ameliorate vascular endothelial injury in PCOS model rats by inhibiting the RAS signaling pathway and by overactivation of the ACE/Ang Ⅱ/AT1 axis.

Protein-protein interactions play an extremely important role in the biochemical functions of cells,and in-depth analysis of protein interactions is the key to understanding cellular life activities.In this study,we systematically mined the interacting proteins of Golgi protein 73(GP73)using classical immunoprecipitation combined with mass spectrometry,and sought to further analyze the molecular func-tion of GP73.Hepatocellular carcinoma cell line HepG2 was selected,and a stable cell line overexpress-ing GP73-3Flag was constructed using lentiviral infection technology.A total of 78 high-confidence GP73 interacting proteins were identified by immunoprecipitation coupled with mass spectrometry.Bioinformat-ics analyses suggested that GP73 interacted with nearly 40 cytosolic proteins and participated in the bio-logical processes of RNA transport,splicing,and translation.Further immunofluorescence and cytosolic protein isolation experiments confirmed the cytosolic localization of GP73 in a variety of tumor cells.Based on the 78 interacting proteins,we further screened protein interaction networks related to mRNA splicing and verified the existence of interactions between GP73 and seven proteins,including HNRN-PH3,SMN1,RBM14,andNCBP1,by co-immunoprecipitation experiments.In addition,minigene spli-cing assay results indicated that GP73 inhibited the splicing efficiency of pre-mRNA by cells.This study contributes to the expansion of knowledge regarding the function of GP73 and aids in elucidating its criti-cal role in cell biology and its potential association with diseases.