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.

Objective To investigate the role and potential mechanism of secreted phosphoprotein 1 (SPP1)⁺ macrophages in the formation of chronic renal allograft fibrosis. Methods The expression features of SPP1⁺ macrophages in renal allografts of chronic allograft dysfunction (CAD) patients were analyzed based on single-cell transcriptome data of renal tissues from patients with CAD. Transcription factor VIPER analysis and DoRothEA transcription factor activity analysis were performed on the single-cell transcriptome data. Renal tissue samples were collected from kidney transplant recipients, including the CAD group (n=5) and the non-renal allograft fibrosis group (CTL group, n=5). A mouse model of chronic allograft rejection was established and divided into the allogeneic kidney transplantation group (CAD group, n=3) and the syngeneic kidney transplantation group (SYN group, n=3). Hematoxylin-eosin staining was used to detect renal tissue injury in mice, and Masson staining was used to detect renal tissue fibrosis. Immunofluorescence staining was performed to detect SPP1 expression in renal tissues of transplant recipients and mouse renal allografts. Bone marrow-derived macrophages (BMDMs) were extracted from mice and subjected to hypoxia stimulation. The expression of hypoxia-inducible factor (HIF)-1α and SPP1 was detected by Western blot, and SPP1 expression was detected by flow cytometry. BMDMs were transfected with HIF-1α overexpression plasmid and HIF-1α small interfering RNA (siRNA) followed by hypoxia intervention, and the expression of HIF-1α and SPP1 was detected by Western blot. Mouse aortic endothelial cells (MAECs) were co-cultured with the supernatant of BMDMs, and the expression of endothelial-mesenchymal transition (EndMT)-related markers was detected by Western blot and immunofluorescence. Results Single-cell transcriptome analysis showed that the proportion of SPP1⁺ macrophages in renal allograft tissues was significantly higher in the CAD group than in the CTL group (P<0.05). The renal injury score and the percentage of interstitial fibrotic area in the CAD group were significantly higher than those in the SYN group (both P<0.05). Immunofluorescence staining showed that the proportion of SPP1⁺ macrophages was increased in the CAD group compared with the CTL group, and also increased in the CAD group compared with the SYN group (both P<0.05). VIPER analysis and DoRothEA transcription factor activity analysis revealed activation of the hypoxia pathway and upregulated expression of transcription factors such as HIF-1α in SPP1⁺ macrophages. SPP1 expression was elevated in BMDMs under hypoxic conditions. Knockdown of HIF-1α inhibited hypoxia-induced SPP1 protein expression, whereas overexpression of HIF-1α upregulated SPP1 protein levels. After co-culture of hypoxia-induced BMDMs with MAECs, the expression levels of EndMT-related markers were increased. Conclusions SPP1⁺ macrophages differentiated under hypoxia are significantly infiltrated in the formation of chronic renal allograft fibrosis, and may promote renal allograft fibrosis by inducing EndMT in renal vascular endothelial cells.

The morphological characteristics and pathological progression of vulnerable plaques in atherosclerosis （AS） exhibit a high degree of similarity to the concept of "abscesses and ulcers" in traditional Chinese medicine （TCM）. Therefore， vulnerable atherosclerotic plaques can be analogized as "abscesses and ulcers within the vessels"， for which deficiency， stasis and toxin constitute the core pathogenesis. The pathological evolution progresses through three sequential stages， deficiency leading to pathological substances， with phlegm and stasis accumulating into a mass； the mass transforming into putridity， with internal decay and external thinning； putridity brewing toxin， and toxin accumulation threatening rupture， ultimately resulting in plaque instability. Accordingly， a stage-specific treatment strategy is established. In the early stage， it is suggested to supplement deficiency， resolve the mass， dissipate stasis， and prevent putridity， using Liujunzi Decoction （六君子汤） combined with Danshen Decoction （丹参饮） with modifications. In the middle stage， the treatment should focus on transforming putridity to generate new tissue， and rectifying healthy qi to consolidate the body， with modified Tuoli Xiaodu Powder （托里消毒散）. In the late stage， the treatment principle is clearing and resolving putridity toxin， cooling the blood， and preventing ulcerative rupture， using modified Simiao Yong'an Decoction （四妙勇安汤） combined with Xijiao Dihuang Decoction （犀角地黄汤）.

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.

AIM:To investigate the effects of nebulized sodium tanshinone ⅡA sulfonate(STS)in a mouse model of pulmonary hypertension associated with chronic obstructive pulmonary disease(COPD-PH).METHODS:A to-tal of 32 healthy SPF-grade male C57BL/6 mice were randomly divided into 4 groups:control(CTL,n=8)group,COPD-PH(CS+LPS,n=8)group,STS-treated COPD-PH(CS+LPS+STS,n=8)group,and STS(n=8)group.The COPD-PH model was established through whole-body exposure to cigarette smoke(CS)combined with lipopolysaccharide(LPS)in-halation.Mice were subjected to cigarette smoke exposure in a chamber(9 cigarettes/h,2 h/session,2 sessions/d,6 d/week)for 60 d,except on days of LPS inhalation.On days 1 and 14,COPD-PH model mice received LPS(7.5 μg/mouse in 50 μL saline)via intranasal inhalation,while the CTL and STS groups received an equivalent volume of saline.STS was administered via nebulized inhalation(5 mg/kg,30 min per session,twice daily)immediately before CS exposure.At the end of the modeling period,lung function and right heart pressure were assessed.Bronchoalveolar lavage fluid(BALF)was collected for inflammatory cell counting.Levels of interleukin-6(IL-6)in BALF supernatants and plasma were measured using ELISA.Pathological changes in the airway and lung tissues were evaluated.RESULTS:(1)Com-pared to CTL mice,those exposed to CS and LPS exhibited lesions characteristic of COPD-PH,including emphysema,lung inflammation,decreased lung function,and increased right ventricular systolic pressure(RVSP)and right ventricu-lar hypertrophy index(RVHI)(P<0.05);(2)COPD-PH mice showed significantly elevated IL-6 levels in both BALF and plasma(P<0.05);(3)STS treatment alleviated emphysema and lung inflammation,improved lung function,prevent-ed increases in RVSP and the RV/(LV+S)ratio,and reduced IL-6 levels in both BALF and plasma(P<0.05).CON-CLUSION:The results indicate that nebulized inhalation of STS significantly slows the progression of COPD-PH,likely due to its ability to inhibit lung inflammation and reduce IL-6 expression in the lungs.

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*