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This paper establishes a coherent framework for delineating the nexus between the digital economy and the subjective efficacy of labor resource allocation. It elucidates the theoretical underpinnings of the digital economy’s impact and its channel effects on the efficiency of labor allocation. Within the digital economy landscape, the phenomena of survivorship bias, digital divide, and algorithmic hegemony wield substantial sway over the efficiency of labor market allocation. Empirical analysis, conducted through a cross-sectional data model, validates the theoretical framework. The findings demonstrate that the digital economy markedly diminishes the subjective efficiency of labor allocation. Notably, this inhibitory effect is more pronounced among female workers, households with multiple residences, the non-unmarried demographic, and individuals over the age of 40, with the most pronounced effect observed among those aged over 60. In the examination of the causative mechanisms, it is discerned that the digital economy attenuates the subjective efficiency of labor allocation by workers through three conduits: alterations in social and economic status, shifts in living standards, and modifications in workplace comfort.

With the development of Industry 5.0, the logistics industry, serving as a bridge between production and consumption, is undergoing profound changes. However, this transformation faces challenges such as data fragmentation, difficult system integration, and insufficient real-time monitoring capabilities. Consequently, the modern logistics system demands higher standards for the prediction and management of transportation behavior. To address these challenges, this paper introduces Digital Twin (DT) technology and proposes a research methodology for DT-driven management strategies. DT technology constructs virtual models of physical objects to enable real-time monitoring and data analysis of unmanned vehicle states, effectively resolving the identified issues. Specifically, the proposed method leverages DT to integrate multi-source heterogeneous data and establishes a digital model of unmanned vehicles. Furthermore, it combines the LSTM neural network algorithm to design a predictive model for time-series forecasting of transportation behaviors. The digital model is dynamically adjusted based on prediction results, further optimizing the management strategy. Finally, the effectiveness of the proposed method is validated through a case study on unmanned vehicle transportation behavior. Experimental results demonstrate that the DT-based management strategy significantly improves the accuracy of predicting unmanned vehicle transportation behaviors and exhibits superior performance in decision aid and fault tolerance. Additionally, simulation tests confirm the reliability and efficiency of the improved algorithm in practical applications, providing an important reference for the intelligent development of modern logistics systems.

Background Emerging evidence suggests that microRNAs (miRs) are associated with the progression of osteoarthritis (OA). In this study, the role of exosomal miR-136-5p derived from mesenchymal stem cells (MSCs) in OA progression is investigated and the potential therapeutic mechanism explored. Methods Bone marrow mesenchymal stem cells (BMMSCs) and their exosomes were isolated from patients and identified. The endocytosis of chondrocytes and the effects of exosome miR-136-5p on cartilage degradation were observed and examined by immunofluorescence and cartilage staining. Then, the targeting relationship between miR-136-5p and E74-like factor 3 (ELF3) was analyzed by dual-luciferase report assay. Based on gain- or loss-of-function experiments, the effects of exosomes and exosomal miR-136-5p on chondrocyte migration were examined by EdU and Transwell assay. Finally, a mouse model of post-traumatic OA was developed to evaluate effects of miR-136-5p on chondrocyte degeneration in vivo. Results In the clinical samples of traumatic OA cartilage tissues, we detected increased ELF3 expression, and reduced miR-136-5p expression was determined. The BMMSC-derived exosomes showed an enriched level of miR-136-5p, which could be internalized by chondrocytes. The migration of chondrocyte was promoted by miR-136-5p, while collagen II, aggrecan, and SOX9 expression was increased and MMP-13 expression was reduced. miR-136-5p was verified to target ELF3 and could downregulate its expression. Moreover, the expression of ELF3 was reduced in chondrocytes after internalization of exosomes. In the mouse model of post-traumatic OA, exosomal miR-136-5p was found to reduce the degeneration of cartilage extracellular matrix. Conclusion These data provide evidence that BMMSC-derived exosomal miR-136-5p could promote chondrocyte migration in vitro and inhibit cartilage degeneration in vivo, thereby inhibiting OA pathology, which highlighted the transfer of exosomal miR-136-5p as a promising therapeutic strategy for patients with OA.

Breast cancer (BC) diagnosis and treatment rely heavily on molecular markers such as HER2, Ki67, PR, and ER. Currently, these markers are identified by invasive methods. This meta-analysis investigates the diagnostic accuracy of ultrasound-based radiomics as a novel approach to predicting these markers. A comprehensive search of PubMed, EMBASE, and Web of Science databases was conducted to identify studies evaluating ultrasound-based radiomics in BC. Inclusion criteria encompassed research on HER2, Ki67, PR, and ER as key molecular markers. Quality assessment using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Radiomics Quality Score (RQS) was performed. The data extraction step was performed systematically. Our meta-analysis quantifies the diagnostic accuracy of ultrasound-based radiomics with a sensitivity and specificity of 0.76 and 0.78 for predicting HER2, 0.80, and 0.76 for Ki67 biomarkers. Studies did not provide sufficient data for quantitative PR and ER prediction analysis. The overall quality of studies based on the RQS tool was moderate. The QUADAS-2 evaluation showed that the studies had an unclear risk of bias regarding the flow and timing domain. Our analysis indicated that AI models have a promising accuracy for predicting key molecular biomarkers' status in BC patients. We performed the quantitative analysis for HER2 and Ki67 biomarkers which yielded a moderate to high accuracy. However, studies did not provide adequate data for meta-analysis of ER and PR prediction accuracy of developed models. The overall quality of the studies was acceptable. In future research, studies need to report the results thoroughly. Also, we suggest more prospective studies from different centers.

To evaluate the clinical performance of expanded non-invasive prenatal testing (NIPT-plus) and compare its effectiveness in screening for chromosomal aneuploidies with that of NIPT. Screening results, confirmatory invasive testing results, and follow-up data from pregnant women who underwent either NIPT (6792 cases) or NIPT-Plus (5237 cases) testing at Luohe Central Hospital, China, from January 2019 to June 2023 were collected. The positive predictive value (PPV), sensitivity, specificity, and other indicators for different types of chromosomal abnormalities in NIPT/NIPT-plus screening were calculated. The willingness of pregnant women with various types of abnormalities to undergo confirmatory invasive testing and the proportion of pregnancy terminations were investigated. The average number of unique reads in NIPT-plus samples was 5.26 times greater than that in NIPT samples. There was no significant difference in the PPV or positive rate between NIPT-plus and NIPT for screening chromosomal aneuploidies. Compared with the low-risk group, the high-risk group had a greater PPV; however, in the NIPT-plus group, there was no significant disparity in the PPV between the low-risk and high-risk groups. Compared with rare autosomal aneuploidies (RAAs), pregnant women had a higher rate of confirmatory invasive testing for common trisomies, sex chromosomal abnormalities (SCAs), and copy number variations (CNVs). However, the rate of pregnancy termination for common trisomies, RAAs, and CNVs was higher than that for SCAs. By enhancing sequencing data, NIPT-plus can effectively screen for CNVs as well as chromosomal aneuploidies. However, NIPT-plus does not have an advantage over standard NIPT in screening for chromosomal aneuploidies.

Considering the characteristics of complex texture backgrounds, uneven brightness, varying defect sizes, and multiple defect types of the bearing surface images, a surface defect detection method for bearing rings is proposed based on improved YOLOv5. First, replacing the C3 module in the backbone network with a C2f module can effectively reduce the number of network parameters and computational complexity, thereby improving the speed and accuracy of the backbone network. Second, adding the SPD module into the backbone and neck networks enhances their ability to process low-resolution and small-object images. Next, replacing the nearest-neighbor upsampling with the lightweight and universal CARAFE operator fully utilizes feature semantic information, enriches contextual information, and reduces information loss during transmission, thereby effectively improving the model’s diversity and robustness. Finally, we constructed a dataset of bearing ring surface images collected from industrial sites and conducted numerous experiments based on this dataset. Experimental results show that the mean average precision (mAP) of the network is 97.3%, especially for dents and black spot defects, improved by 2.2% and 3.9%, respectively, and that the detection speed can reach 100 frames per second (FPS). Compared with mainstream surface defect detection algorithms, the proposed method shows significant improvements in both accuracy and detection time and can meet the requirements of industrial defect detection.

IntroductionRecent studies have indicated the potential of stem cell therapy in combination with cytokines to restore the bone repair via migration and homing of stem cells to the defected area. The present study aimed to investigate the mobilization and recruitment of mesenchymal stem cells (MSCs) in response to SDF-1.Materials and MethodsHerein, the knockout rat model of the bone defect (BD) was treated with the induced membrane technique. Then, wild type Wistar rats and SDF-1-knockout rats were selected for the establishment of BD-induced membrane (BD-IM) models and bone-graft (BG) models. The number of MSCs was evaluated by flow cytometry, along with the expression pattern of the SDF-1/CXCR4 axis as well as osteogenic factors was identified by RT-qPCR and Western blot analyses. Finally, the MSC migration ability was assessed by the Transwell assay.ResultsOur data illustrated that in the induced membrane tissues, the number of MSCs among the BD-IM modeled rats was increased, whereas, a lower number was documented among BG modeled rats. Besides, we found that lentivirus-mediated over-expression of SDF-1 in BG modeled rats could activate the SDF-1/CXCR4 axis, mobilize MSCs into the defect area, and up-regulate the osteogenic proteins.ConclusionsCollectively, our study speculated that up-regulation of SDF-1 promotes the mobilization and migration of MSCs through the activation of the SDF-1/CXCR4 signal pathway.

Cyclin-dependent kinase 2 (CDK2) complex is significantly over-activated in many cancers. While it makes CDK2 an attractive target for cancer therapy, most inhibitors against CDK2 are ATP competitors that are either nonspecific or highly toxic, and typically fail clinical trials. One alternative approach is to develop non-ATP competitive inhibitors; they disrupt interactions between CDK2 and either its partners or substrates, resulting in specific inhibition of CDK2 activities. In this report, we identify two potential druggable pockets located in the protein-protein interaction interface (PPI) between CDK2 and Cyclin A. To target the potential druggable pockets, we perform a LIVS in silico screening of a library containing 1925 FDA approved drugs. Using this approach, homoharringtonine (HHT) shows high affinity to the PPI and strongly disrupts the interaction between CDK2 and cyclins. Further, we demonstrate that HHT induces autophagic degradation of the CDK2 protein via tripartite motif 21 (Trim21) in cancer cells, which is confirmed in a leukemia mouse model and in human primary leukemia cells. These results thus identify an autophagic degradation mechanism of CDK2 protein and provide a potential avenue towards treating CDK2-dependent cancers. CDK2 can drive the proliferation of cancer cells. Here, the authors screened for a non-ATP competitive inhibitor of the CDK2/cylinA complex and find that Homoharringtonine can disrupt the complex and promote the degradation of CDK2.

The preparation process parameters and composition of polyurethane/phosphogypsum-modified asphalt were studied to achieve comprehensive utilization of phosphogypsum and reduce asphalt pavement costs while ensuring performance compliance. Additionally, the aging resistances of the modified asphalt and its mixtures were investigated. The results showed that the order of the influence of the different preparation process parameters on the performance of modified asphalt is preparation temperature, storage time, reaction time, and shear rate. The optimal preparation process parameters, namely 130°C preparation temperature, 2000 rpm shear rate, 1.5 h reaction time, and 1.0 h storage time, of polyurethane/phosphogypsum composite-modified asphalt are recommended based on the experimental results. Polyurethane/phosphogypsum-modified asphalt with 3% component A, 1% component B, 5% phosphogypsum, and 0.5% coupling agent exhibited superior performance. The average change rates of the modified asphalt properties after short- and long-term aging were 23.9% and 42.2% lower than those of the base asphalt, respectively. Finally, the modified asphalt mixture exhibited average change rates of 8.7% and 18.2% in high-temperature performance after short- and long-term aging, respectively, which were significantly lower than the change rates of 15.3% and 23.5% observed in the base asphalt mixture.

This study investigates the binding interactions between bovine serum albumin (BSA) and camptothecin (CPT) drugs (camptothecin, 10-hydroxycamptothecin, topotecan, and irinotecan) using UV–Vis spectroscopy, fluorescence spectroscopy, three-dimensional fluorescence spectroscopy, and molecular docking techniques. The fluorescence quenching of BSA by CPT drugs follows a static mechanism, with binding constants (K b ) ranging from 4.23 × 10 3 M − 1 (CPT) to 101.30 × 10 3 M − 1 (irinotecan), demonstrating significant drug binding selectivity. Thermodynamic analysis reveals distinct interaction mechanisms: topotecan binding is driven by hydrogen bonding (ΔH = − 10.96 kJ·mol − 1 ) and hydrophobic interactions (ΔS = 0.066 kJ·mol − 1 ·K − 1 ), while irinotecan exhibits stronger binding dominated by electrostatic forces (ΔH = − 86.77 kJ·mol − 1 ) with significant entropy loss (ΔS = − 0.161 kJ·mol − 1 ·K − 1 ). Molecular docking confirms preferential binding at Sudlow site I of BSA, with hydrophobic interactions and hydrogen bonding as the primary driving forces. These findings provide a comprehensive understanding of CPT-BSA interactions, offering valuable insights for the design of albumin-based drug delivery systems with optimized pharmacokinetic profiles.