Kidney transplantation is the most effective treatment for end-stage renal failure, and antibody-mediated rejection remains the leading cause of late allograft loss. Macrophages, as central effectors of innate immunity, play a crucial role in the initiation, progression and tissue damage of antibody-mediated rejection. This article reviews the spatiotemporal dynamic evolution of macrophage polarization status in different stages of antibody-mediated rejection, the fine regulation of key signaling pathways for macrophage polarization, macrophage related molecules and the application prospects of targeted macrophage therapy. In depth analysis of the research progress of macrophages in antibody-mediated rejection, aiming to provide important theoretical basis for the development of precision diagnostic tools based on macrophages and novel immune intervention targets for antibody mediated rejection, ultimately promoting the improvement of long-term prognosis in kidney transplantation.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo investigate the correlation between iron metabolism parameters and various syndrome types of unstable angina pectoris （UAP）. MethodsA cross-sectional study was conducted from October 2021 to October 2023， encompassing 213 patients diagnosed with UAP at Xiyuan Hospital of Chinese Academy of Chinese Medical Sciences. Additionally， 30 healthy individuals were selected as control cases. Single-factor analysis was used to investigate the differences in clinical data among different Traditional Chinese Medicine （TCM） syndrome types of UAP and their correlation with iron metabolism indices. The study conducted a comparative analysis of the aforementioned clinical data among patients with and without heat-toxic and blood-stasis syndrome. Logistic regression was used to analyze the correlation between TCM syndrome types and related factors. The receiver operator characteristic （ROC） curve was employed to assess the predictive value of iron metabolism indices， along with their sensitivity and specificity. ResultsCompared to those in the control group， serum iron （SI） and serum ferritin （SF） levels were significantly increased in the UAP group （P<0.01）， while transferrin （TRF） and total iron binding capacity （TIBC） levels were decreased （P<0.01）. However， there was no significant difference in unsaturated iron binding capacity （UIBC）. Multivariate binary Logistic regression analysis identified apolipoprotein A1 （ApoA1）， homocysteine （HCY）， high-sensitivity C-reactive protein （hs-CRP）， and SF as independent influencing factors for the UAP patients （P<0.05， P<0.01）. Additionally， statistically significant differences were observed in SI， SF， TRF， and TIBC among 213 patients with different TCM types （P<0.01）. Patients with heat-toxic and blood-stasis syndrome had higher SI and SF values than those without the syndrome （P<0.01）， while their TIBC and TRF values were lower （P<0.01）. Multivariate binary logistic regression analysis showed that SI and LDL-C levels were closely associated with the differentiation of heat-toxic and blood-stasis syndrome. ConclusionUAP patients often experience iron metabolism disorders， and the heat-toxic and blood-stasis syndrome are significantly correlated with iron metabolism parameters. The SI and LDL-C levels have high specificity and sensitivity in diagnosing heat-toxic and blood-stasis syndrome.

Taxifolin (TAX) is a natural compound known for its liver protection effect, but the mechanism remains unknown. Phosphorylated proteomics analyses discovered that the phosphorylation level of NDRG1 at T328 was a key event of TAX-improved liver fibrosis. We established models with NDRG1 knockout (KO) in vivo and in vitro, demonstrating that NDRG1 KO attenuated the development of hepatocyte injury, and combining NDRG1 KO and TAX administration did not result in a reduction in protection against liver injury. Cellular thermal shift assay and surface plasma resonance analysis showed that TAX directly binds to NDRG1 rather than its upstream kinase, subsequently demonstrating that TAX regulated phosphorylation of NDRG1 at T328 through binding to its C289 site. NDRG1 T328A (phosphorylated mutation) and T328E (mimic phosphorylation) in vivo and in vitro confirmed that pNDRG1_T328 exacerbates hepatocyte injury along with DNA damage, inflammatory response, and apoptosis, thereby contributing to hepatic stellate cells (HSCs) activation. In contrast, TAX can inhibit the above pathological abnormalities and block hepatocyte injury-triggered HSCs activation and fibrosis. Overall, TAX is a potent liver protection drug primarily targeting NDRG1 and inhibiting pNDRG1_T328 in hepatocytes.

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.
Plant Leaves/growth & development* ; Saccharum/growth & development* ; Algorithms ; Unmanned Aerial Devices ; Remote Sensing Technology/methods* ; Crops, Agricultural/growth & development*

Accurately obtaining the crop quantity and density is not only crucial for the demand-based input of water and fertilizer in the field but also vital for ensuring the yield and quality of crops. Aerial photography by unmanned aerial vehicles (UAVs) can quickly acquire the distribution image information of crops over a large area. However, the accurate recognition of a single type of dense targets is a huge challenge for most recognition algorithms. Taking banana seedlings as an example in this study, we captured the images of banana plantations by UAVs from high altitudes to explore an efficient recognition method for dense targets. We proposed a strategy of "cut-recognition-stitch" and constructed a counting method based on the improved Faster R-CNN algorithm. First, the images containing highly dense targets were cropped into a large number of image tiles according to different sizes (simulating different flight altitudes), and the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm was adopted to improve the image quality. A banana seedling dataset containing 36 000 image tiles was constructed. Then, the Faster R-CNN network with optimized parameters was used to train the banana seedling recognition model. Finally, the recognition results were reversely stitched together, and a boundary deduplication algorithm was designed to correct the final counting results to reduce the repeated recognition caused by image cropping. The results show that the recognition accuracy of the Faster R-CNN with optimized parameters for banana image datasets of different sizes can reach up to 0.99 at most. The deduplication algorithm can reduce the average counting error for the original aerial images from 1.60% to 0.60%, and the average counting accuracy of banana seedlings reaches 99.4%. The proposed method effectively addresses the challenge of recognizing dense small objects in high-resolution aerial images, providing an efficient and reliable technical solution for intelligent crop density monitoring in precision agriculture.
Musa/growth & development* ; Crops, Agricultural/growth & development* ; Algorithms ; Neural Networks, Computer ; Unmanned Aerial Devices ; Seedlings/growth & development* ; Image Processing, Computer-Assisted/methods* ; Photography ; Agriculture/methods*

Objective: To construct and to validate a nomogram prediction model based on Lipoprotein-associated phospholipase A2(Lp-PLA2) and Lipoprotein(a) [LP(a) ]for predicting the risk of major adverse cardiovascular events(MACE) in patients with coronary heart disease(CHD). Methods: A retrospective analysis was conducted on the clinical data of 442 patients with coronary heart disease(CHD). Among them,411 patients who completed follow-up were randomly divided into a training set(288 cases) and a validation set(123 cases) at a 7 ∶ 3 ratio.Independent risk factors for major adverse cardiovascular events(MACE) in CHD patients were screened through Lasso regression analysis and Cox regression analysis,and a nomogram prediction model was constructed. The predictive performance of the model was evaluated using time-dependent receiver operating characteristic curves(ROC),calibration curves,and decision curve analysis. Results: Variables were screened through Lasso regression and Cox regression analysis. The final model included nine independent predictors,namely age,smoking history,clinical phenotype of CHD,the number of coronary artery lesions,Gensini score,BNP,Lp-PLA2,LP(a), and the history of statin use. The area under the ROC curve in the training set was 0. 897,0. 885,and 0. 909 at 1,2,and 3 years,respectively; The area under the ROC curve in the validation set was 0. 885,0. 881,and 0. 923 at 1,2,and 3 years,respectively. These results demonstrated that the model had excellent discriminatory power. The calibration curves and decision curves demonstrated that the model had high clinical practicality in predicting the occurrence of MACE in CHD patients. Conclusion The nomogram prediction model based on LP-PLA2,LP(a)and other risk factors provides an effective tool for the prognosis assessment of CHD patients,facilitating the early identification of high-risk patients and enabling individualized intervention.

Objective To investigate the mechanism of morin-induced autophagy in non-small cell lung cancer A549 cells based on mTOR/STAT3 signaling axis.Methods A549 cells were divided into blank group and 30,60,90,120 and 150 μg·mL-1 of morin groups.After 24,48 and 72 hours of culture,the cell proliferation activity was detected by CCK-8 method,and the cell inhibition rate was calculated.A549 cells were divided into blank group and 30,90,150 μg·mL-1 morin groups.After 14 days of culture,the cell proliferation was detected by colony formation assay.After 24 hours of culture,the cell proliferation ability was detected by BeyoClickTM EdU-488.Apoptosis was detected by flow cytometry;acridine orange staining was used to detect cell autophagy;the formation of autophagosomes was observed by transmission electron microscopy.Western Blot was used to detect the expression levels of apoptosis,autophagy and mTOR/STAT3 signaling axis-related proteins in cells.A549 cells were divided into blank group,blank group + chloroquine(10 μg·mL-1)group,morin(30,150 μg·mL-1)group,morin(30,150 μg·mL-1)+ chloroquine(10 μg·mL-1)group.After 48 hours of intervention,the cell activity was detected by CCK-8 method,and the cell survival rate was calculated.Results Compared with the blank group,the inhibition rate of A549 cells in 60,90,120,150 μ g·mL-1 of morin group was significantly increased after 24 hours of intervention(P＜0.05,P＜0.001).The inhibition rates of A549 cells in 30,60,90,120 and 150 μg·mL-1 of morin groups were significantly increased after 48 and 72 hours of intervention(P＜0.001).The number of A549 cell colonies and the number of green fluorescent proliferation positive cells in the 30,90,150 μg·mL-1 of morin groups were significantly decreased(P＜0.01,P＜0.001),the apoptosis rate was significantly increased(P＜0.01,P＜0.001),and the protein expression level of cleaved-PARP was significantly increased(P＜0.001).The protein expression levels of p-P38/P38 MAPK in A549 cells of 90 and 150 μg·mL-1 of morin groups were significantly increased(P＜0.01,P＜0.001).Different degrees of orange fluorescence appeared in A549 cells of 30,90 and 150 μg·mL-1 of morin groups,and the orange fluorescence of 90 and 150 μg·mL-1 of morin groups was significant.Autophagosomes and autolysosomes appeared in the cytoplasm of A549 cells in 150 μg·mL-1 of morin group,respectively.The protein expression of LC3-Ⅱ in A549 cells of 150 μg·mL-1 of morin group was significantly up-regulated(P＜0.05).The protein expression of Atg16L1-Ⅱ in A549 cells of 90,150 μg·mL-1 of morin group was significantly up-regulated(P＜0.001),and the protein expressions of p-mTOR/mTOR and p-STAT3/STAT3 were significantly down-regulated(P＜0.001).Compared with the morin(150 μg·mL-1)group,the survival rate of A549 cells in the morin(150 μg·mL-1)+chloroquine(10 μg·mL-1)group was significantly increased(P＜0.05).Conclusion Morin can promote the apoptosis of A549 cells and induce autophagy in A549 cells,and the mechanism may be related to mTOR/STAT3 axis.