Knee osteoarthritis(KOA)is a prevalent chronic degenerative disorder among older adults,with biomechanical factors playing a crucial role in its pathogenesis and progression.This article aims to direct clinical studies on Tai Ji Quan(Shadow Boxing)therapeutic intervention for KOA by analyzing biomechanical factors in the pathogenesis of KOA and generalizing the biomechanical characteristics of Tai Ji Quan exercise and its impact on the gait pattern,overall mechanical balance,muscle function,plantar pressure,and proprioception of KOA patients,as well as summarizing the limitations in current clinical research.

Objective To investigate the effect of programmed death-1(PD-1)on cell infiltration in muscle tissue and immune response types in mice infected with Trichinella spiralis.Methods C57BL/6J wild-type(WT)and PD-1 deficient(PD-1-/-)mice were infected with T.spiralis(400 muscle larvae per mouse),and samples were collected on day 35 after infection.The proportions of infiltrating inflammatory cells and fibroblasts around encapsulated larvae were assessed by immunohistochemistry.The expression levels of interferon-γ(IFN-γ),interleukin(IL)-4,IL-5,IL-13,and eotaxin in muscle tissue were measured using enzyme-linked immunosorbent assay.Peripheral blood and spleen were collected at different time points after infection.The percentages of CD4+IFN-γ+Th1 and CD4+IL-4+Th2 within CD4+T cells population in peripheral blood and spleen of mice were analyzed using flow cytometry.Results The proportions of eosinophils and fibroblasts among total infiltrating cells around the encapsulated larvae in the muscle of PD-1-/-mice were significantly lower than those in WT mice after T.spiralis infection(P＜0.01).The infected PD-1-/-mice exhibited higher proportions of macrophages,T cells and B cells in total infiltrating cells than the infected WT mice(P＜0.01).The levels of IL-4,IL-5,IL-13,and eotaxin in the muscle tissue of infected PD-1-/-mice were significantly lower than those in infected WT mice(P＜0.05).However,IFN-γ levels were not significantly different between the infected WT and PD-1-/-mice.The proportions of Th2 cells in CD4+T cells from peripheral blood and spleen of infected PD-1-/-mice were significantly lower than those in infected WT mice,whereas the proportion of Th1 cells showed no difference among the infected groups.Conclusions PD-1 deletion results in decreased expression of key chemokines of eosinophils and key cytokines of fibroblast formation,and a corresponding decrease in inflammatory cells in muscle in T.spiralis-infected mice.This effect may be associated with a diminished Th2 immune response caused by PD-1 deletion.

Objective To investigate the effects of ischemia time and storage periods on RNA quality in fresh-frozen breast cancer(BC)and esophageal cancer(EC)tissue samples in order to establish evidence-based protocols for biobank sample management.Methods The tumor(T)and paired normal(N)tissue samples from 6 cases of BC and 6 cases of EC were collected and cryopreserved in Biobank,Shantou Central Hospital.Mirror paraffin-embedded tissues were simultaneously prepared into sections for morphological analysis.The samples were divided into two groups of<15 min and 15-30 min according to ischemia time,and RNA quality was analyzed at 4 storage periods of 8-10 months(T1),14-16 months(T2),26-28 months(T3)and 38-40 months(T4).Results In 96 analyzed samples,93.8%(90/96)exhibited high quality(RIN≥6),with 89.6%(43/48)in BC and 97.9%(47/48)in EC.Significant differences in RIN were observed between BC group and EC group(8.050 vs.8.600,P=0.009).In EC group,RIN value was significantly negatively correlated with RNA yield(P<0.001).Moreover,RIN values of tumor-normal pairs exhibited markedly significant differences(7.550 vs.9.000,P<0.001).In contrast,no significant difference was detected in BC group(8.200 vs.7.700,P=0.348).Statistical analysis showed that RIN value was positively correlated with 28S/18S(P<0.001),but had no correlation with tumor content(P=0.676)and necrotic content(P=0.055).Neither ischemia time(<15 min vs.15-30 min:8.200 vs.8.300,P=0.932)nor storage periods(T1-T4:8.400,7.700,8.450,8.600,P=0.163)compromised RNA quality.Conclusion Organ origin and tissue type could influence RNA quality of fresh-frozen tissue samples.However,limited ischemia time(≤30 min)and long-term storage period(38-40 months)do not adversely affect RNA quality in fresh-frozen breast cancer and esophageal cancer tissue samples.

Objective:To investigate the mechanism of mitochondrial DNA (mtDNA)-reactive oxygen species (ROS)-dynamin-related protein 1 (Drp1) axis in regulating phenotypic transformation of vascular smooth muscle cells (VSMCs).Methods:(1) VSMCs were divided into a control group, a synthetic VSMCs group, and a Drp1 siRNA+synthetic VSMCs group; cells in the Drp1 siRNA+synthetic VSMCs group were transfected with 50 nmol/L Drp1 siRNA for 48 h; cells in the latter two groups were treated with 20 ng/mL platelet-derived growth factor (PDGF)-BB, while cells in the control group were treated with an equal volume of solvent. After another 24 h of culture, Drp1 expression in VSMCs, and mitochondrial Drp1 and mitofusin 2 (Mfn2) expressions were detected by Western blotting, and changes in mitochondrial morphology were detected by mitochondrial fluorescent staining. (2) VSMCs were divided into a control group, a synthetic VSMCs group, and a mitochondrial fission inhibitor 1 (Mdivi-1)+synthetic VSMCs group; cells in the Mdivi-1+synthetic VSMCs group were pretreated with 50 μmol/L Mdivi-1 for 2 h; and cells in the latter two groups were treated with 20 ng/mL PDGF-BB, while cells in the control group were treated with an equal volume of solvent. After 24 hours of continued culture, expressions of α-smooth muscle actin (α-SMA), smooth muscle protein 22-α (SM22-α), proliferating cell nuclear antigen (PCNA), and Cyclin D1 were detected by Western blotting; invasion and migration abilities of VSMCs were detected by Transwell assay and scratch wound healing assay, respectively. (3) VSMCs were divided into a control group, a synthetic VSMCs group, and a N-acetylcysteine (NAC)+synthetic VSMCs group; cells in the NAC+synthetic VSMCs group were pretreated with 5 mmol/L NAC for 1 h; cells in the latter two groups were treated with 20 ng/mL PDGF-BB, while cells in the control group were treated with an equal volume of solvent. After 24 h of continued culture, expressions of Drp1, phosphorylated (p)-Drp1, α-SMA, SM22-α, PCNA, and Cyclin D1 were detected by Western blotting; changes in mitochondrial morphology were detected by mitochondrial fluorescent staining; intracellular ROS level was detected by 2', 7' -dichlorodihydrofluorescein diacetate (DCFH-DA) fluorescent probe; cell invasion and migration abilities were detected by Transwell assay and scratch wound healing assay, respectively. (4) VSMCs were divided into a control group, a synthetic VSMCs group, and a 5-Aza-2'-deoxycytidine (5-Aza-dC)+synthetic VSMCs group; cells in the 5-Aza-dC+synthetic VSMCs group were pretreated with 2 μmol/L 5-Aza-dC for 1 h; and then, cells in the latter two groups were treated with 20 ng/mL PDGF-BB, while cells in the control group were treated with an equal volume of solvent. After 24 h of continued culture, agarose gel electrophoresis was used to analyze the methylation degree in the mitochondrial D-loop region; intracellular ROS level was detected using DCFH-DA fluorescent probe; expressions of mitochondrial DNMT1, α-SMA, SM22-α, PCNA, and Cyclin D1 were detected by Western blotting; invasion and migration abilities were detected by Transwell assay and scratch wound healing assay, respectively.Results:(1) Compared with the control group and synthetic VSMCs group, the Drp1 siRNA+synthetic VSMCs group had significantly decreased Drp1 protein expression ( P<0.05). Compared with the control group, the synthetic VSMCs group had significantly increased Drp1 protein expression and decreased Mfn2 protein expression in the mitochondria ( P<0.05); compared with the synthetic VSMCs group, the Drp1 siRNA+synthetic VSMCs group had statistically decreased Drp1 protein expression and increased Mfn2 protein expression in the mitochondria ( P<0.05). Results of mitochondrial fluorescent staining showed that mitochondria in the control group were with filamentous structure, while mitochondrial fission in the synthetic VSMCs group was enhanced, and morphology of mitochondria in the Drp1 siRNA+synthetic VSMCs group tended to be continuous and complete. (2) Compared with the control group, the synthetic VSMCs group had statistically decreased α-SMA and SM22-α protein expressions and increased PCNA and Cyclin D1 protein expressions ( P<0.05). Compared with the synthetic VSMCs group, the Mdivi-1+synthetic VSMCs group had significantly increased α-SMA and SM22-α protein expressions and decreased PCNA and Cyclin D1 protein expressions ( P<0.05). Results of Transwell and scratch wound healing assays showed that compared with the control group, the synthetic VSMCs group had larger number of migrating cells and faster cell scratch healing; compared with the synthetic VSMCs group, the Mdivi-1+synthetic VSMCs group had smaller number of migrating cells and slower cell scratch healing. (3) Compared with the control group (1.10±0.02), the synthetic VSMCs group (1.53±0.02) had significantly increased p-Drp1 protein expression ( P<0.05). Compared with the synthetic VSMCs group, the NAC+synthetic VSMCs group (0.90±0.02) had statistically decreased p-Drp1 protein expression ( P<0.05). Results of mitochondrial fluorescent staining showed that mitochondria in cells of the control group were in a filamentous structure, while mitochondrial fission in cells of the synthetic VSMCs group was enhanced, and morphology of mitochondria in the NAC+synthetic VSMCs group tended to be continuous and complete. Results of DCFH-DA fluorescent probe showed that ROS level in the synthetic VSMCs group was higher than that in the control group, and ROS level in the NAC+synthetic VSMCs group was lower than that in the synthetic VSMCs group. Compared with the control group, the synthetic VSMCs group had significantly decreased α-SMA and SM22-α protein expressions and increased PCNA and Cyclin D1 protein expressions ( P<0.05). Compared with the synthetic VSMCs group, the NAC+synthetic VSMCs group had significantly increased α-SMA and SM22-α protein expressions and decreased PCNA and Cyclin D1 protein expressions ( P<0.05). Results of Transwell and scratch wound healing assays showed that compared with the control group, the synthetic VSMCs group had larger number of migrating cells and faster cell scratch healing; compared with the synthetic VSMCs group, the NAC+synthetic VSMCs group had smaller number of migrating cells and slower cell scratch healing. (4) Results of agarose gel electrophoresis showed that compared with the control group, the synthetic VSMCs group had significantly increased methylation rate in the mitochondrial D-loop region ( P<0.05); compared with the synthetic VSMCs group, the 5-Aza-dC+synthetic VSMCs group had statistically decreased methylation rate in the mitochondrial D-loop region ( P<0.05). Compared with the control group, the synthetic VSMCs group had statistically increased mitochondrial DNMT1 protein expression (1.03±0.03 vs. 0.55±0.03, P<0.05); and compared with the synthetic VSMCs group, the the 5-Aza-dC+synthetic VSMCs group (0.62±0.03) had significantly decreased mitochondrial DNMT1 protein expression ( P<0.05). Results of DCFH-DA fluorescent probe showed that ROS level in the synthetic VSMCs group was higher than that in the control group; ROS level in the 5-Aza-dC+synthetic VSMCs group was lower than that in the synthetic VSMCs group. Compared with the control group, the synthetic VSMCs group had significantly decreased α-SMA and SM22-α protein expressions and increased PCNA and Cyclin D1 protein expressions ( P<0.05). Compared with the synthetic VSMCs group, the 5-Aza-dC+synthetic VSMCs group had significantly increased α-SMA and SM22-α protein expressions and decreased PCNA and Cyclin D1 protein expressions ( P<0.05). Results of Transwell and scratch wound healing assays showed that compared with the control group, the synthetic VSMCs group had larger number of migrating cells and faster scratch healing. Compared with the synthetic VSMCs group, the 5-Aza-dC+synthetic VSMCs group had smaller number of migrating cells and slower scratch healing. Conclusion:The mtDNA-ROS-Drp1 axis may regulate the phenotypic transformation of VSMCs by modulating mitochondrial epigenetic modifications.

Objective:To investigate whether paclitaxel (PTX) can induce immunogenic cell death (ICD) in vascular smooth muscle cells (VSMCs), and explore the new molecular mechanism of PTX-coated balloon angioplasty in intracranial atherosclerotic stenosis.Methods:(1) Cell culture and identification: VSMCs were induced into synthetic vascular smooth muscle cells (sVSMCs); the mRNA and protein expressions of smooth muscle protein 22-α (SM22-α) and α-smooth muscle actin (α-SMA) in VSMCsS and sVSMCs were detected by real-time fluorescent quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) and Western blotting, respectively. Human acute monocytic leukemia cell line THP-1 was induced into dendritic cells (DCs); the CD86 and CD83 expressions in THP-1 and DCs were detected by flow cytometry. (2) Cell viability detection: cell counting kit-8 (CCK-8) assay was used to detect the cell viability of sVSMCs after 0, 0.01, 0.05, 0.5, 5, 10, 50, and 100 μmol/L PTX or under 0, 50, 100, 200, 400, and 600 mmHg (1 mmHg=0.133 kPa) pressures. (3) ICD marker detection: sVSMCs were collected and divided into blank-control group, dimethyl sulfoxide (DMSO) group and PTX group (cultured with 3.2 μmol/L PTX) at normal state and pressure procedure (188 mmHg), respectively; calreticulin (CRT) expression was detected by immunofluorescent staining; adenosine triphosphate (ATP) expression was detected by luciferase assay, and high mobility group protein B1 (HMGB1) expression was detected by enzyme-linked immunosorbent assay (ELISA). (4) ICD-related immune activation assay detection: sVSMCs and DCs were collected and divided into DCs group, PTX+DCs group (cultured with 3.2 μmol/L PTX), DCs+sVSMCs group, and PTX+DCs+sVSMCs group (cultured with 3.2 μmol/L PTX); CD86 and CD83 expressions were detected by flow cytometry; interleukin (IL)-2, IL-10 and interferon-γ (IFN-γ) levels were detected by ELISA. The sVSMCs, DCs and CD8 +T cells were collected and divided into sVSMCs group, sVSMCs+DCs group, sVSMCs+CD8 +T cell group, sVSMCs+DCs+CD8 +T cell group, PTX+sVSMCs group (cultured with 3.2 μmol/L PTX), and PTX+sVSMCs+DCs+CD8 +T cell group (cultured with 3.2 μmol/L PTX); proliferation of these cells was detected by cell clone formation assay. Results:(1) The SM22-α and α-SMA mRNA and protein expressions in the sVSMCs group were significantly lower than those in the VSMCs group ( P<0.05); rate of double-positive CD83 and CD86 in the DCs group was significantly higher than that in the THP-1 group ( P<0.05). (2) The sVSMCs viability decreased in a concentration-dependent manner after PTX treatment at concentrations of 0, 0.01, 0.05, 0.5, 5, 10, 50, and 100 μmol/L, respectively, with significant differences ( P<0.05); half maximal inhibitory concentration (IC 50) of PTX on sVSMCs was 3.2 μmol/L; no significant difference in sVSMCs viability after 3.2 μmol/L PTX treatment was noted under 0, 50, 100, 200, 400, and 600 mmHg pressures ( P>0.05). (3) Under normal state and pressure procedure, CRT fluorescent intensity of sVSMCs in the PTX group (42.00±3.50, 24.19±2.41) was significantly higher than that in the blank-control group (8.60±1.8, 8.42±1.7) and DMSO group (10.23±1.47, 9.71±1.01), ATP luminescence intensity (17 399.33±2 035.58, 17 445.67±2 449.34) was significantly higher than that in the blank-control group (9 021.33±726.84, 10 271.33±2 194.22) and DMSO group (11 977.33±960.91, 11 683.33±419.50), and HMGB1 concentration ([3 258.31±502.08] pg/mL, [3 265.27±246.06] pg/mL) was significantly higher than that in the blank-control group ([1 156.48±184.96] pg/mL, [1 205.20±196.36] pg/mL) and DMSO group ([1 309.59±75.03] pg/mL, [1 265.51±14.52] pg/mL, P<0.05). (4) The PTX+DCs+sVSMCs group had significantly higher CD83, CD86, IFN-γ and IL-2 expressions and lower IL-10 expression than the DCs group, PTX+DCs group, and DCs+sVSMCs group ( P<0.05); the PTX+sVSMCs group and PTX+sVSMCs+DCs+CD8 +T cell group had significantly lower clone formation rate compared with the sVSMCs group, sVSMCs+DCs group, sVSMCs+CD8 +T cell group, and sVSMCs+DCs+CD8 +T cell group ( P<0.05). Conclusion:PTX can promote ICD in VSMCs by promoting DCs activation and enhancing CD8 +T cell toxicity.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

The circadian clock plays a critical role in regulating various physiological processes, including gene expression, metabolic regulation, immune response, and the sleep-wake cycle in living organisms. Post-translational modifications (PTMs) are crucial regulatory mechanisms to maintain the precise oscillation of the circadian clock. By modulating the stability, activity, cell localization and protein-protein interactions of core clock proteins, PTMs enable these proteins to respond dynamically to environmental and intracellular changes, thereby sustaining the periodic oscillations of the circadian clock. Different types of PTMs exert their effects through distincting molecular mechanisms, collectively ensuring the proper function of the circadian system. This review systematically summarized several major types of PTMs, including phosphorylation, acetylation, ubiquitination, SUMOylation and oxidative modification, and overviewed their roles in regulating the core clock proteins and the associated pathways, with the goals of providing a theoretical foundation for the deeper understanding of clock mechanisms and the treatment of diseases associated with circadian disruption.
Protein Processing, Post-Translational/physiology* ; Circadian Rhythm/physiology* ; Humans ; Animals ; CLOCK Proteins/physiology* ; Circadian Clocks/physiology* ; Phosphorylation ; Acetylation ; Ubiquitination ; Sumoylation

This study aims to comprehensively analyze the material basis of toad visceral oil(hereafter referred to as toad oil), and explore the pharmacological effect of toad oil on atopic dermatitis(AD). Ultra-high performance liquid chromatography-linear ion trap/orbitrap high-resolution mass spectrometry(UHPLC-LTQ-Orbitrap-MS) and gas chromatography-mass spectrometry(GC-MS) were employed to comprehensively identify the chemical components in toad oil. The animal model of AD was prepared by the hapten stimulation method. The modeled animals were respectively administrated with positive drug(0.1% hydrocortisone butyrate cream) and low-and high-doses(1%, 10%) of toad oil by gavage. The effect of toad oil on AD was evaluated with the AD score, ear swelling rate, spleen index, and pathological section results as indicators. A total of 99 components were identified by UHPLC-LTQ-Orbitrap-MS, including 14 bufadienolides, 7 fatty acids, 6 alkaloids, 10 ketones, 18 amides, and other compounds. After methylation of toad oil samples, a total of 20 compounds were identified by GC-MS. Compared with the model group, the low-and high-dose toad oil groups showed declined AD score, ear swelling rate, and spleen index, alleviated skin lesions, and reduced infiltrating mast cells. This study comprehensively analyzes the chemical composition and clarifies the material basis of toad oil. Meanwhile, this study proves that toad oil has a good therapeutic effect on AD and is a reserve resource of traditional Chinese medicine for external use in the treatment of AD.
Animals ; Dermatitis, Atopic/immunology* ; Disease Models, Animal ; Mice ; Male ; Gas Chromatography-Mass Spectrometry ; Humans ; Bufonidae ; Oils/administration & dosage* ; Chromatography, High Pressure Liquid ; Female ; Mice, Inbred BALB C