Search

This study proposes to investigate the therapeutic efficacy and mechanism of combining tibial transverse transport (TTT) with platelet-rich plasma (PRP) for diabetic foot ulcer (DFU). The diabetic rabbit model was constructed with Streptozotocin, which was intervened with TTT and PRP. PRP injection combined with TTT significantly promoted vascularisation and enhanced CD31, VEGFA, and VEGFR2 expressions compared to traditional TTT. However, the VEGFR2 inhibitor suppressed these phenomena. In the in vitro injury model, PRP reversed the diminished human umbilical vein endothelial cells (HUVECs) function and vascularisation caused by high-glucose damage. Additionally, PRP reduced inflammation and oxidative stress (approximately 47% ROS level) and enhanced VEGFA and VEGFR2 expression in HUVECs. However, the knockdown of VEGFR2 reversed the effect of PRP. In conclusion, TTT combined with intraosseous flap injection of PRP sustained-release microspheres activated the VEGFA/VEGFR2 pathway to promote microcirculatory reconstruction in DFU. These findings may provide new potential therapeutic strategies for DFU. [ABSTRACT FROM AUTHOR]

The presence of defects in substation equipment is a major factor affecting the safety of power transmission. Therefore, timely and accurate detection of these defects is crucial. As intelligent inspection robots advance, using mainstream object detection models to diagnose surface defects in substation equipment has become a focal point of current research. However, the lack of defect image data is one of the main factors affecting the accuracy of supervised deep learning-based defect detection models. To address the issue of insufficient training data for defect images with complex backgrounds, such as rust and surface oil leakage in substation equipment, which leads to the poor performance of detection models, this paper proposes a novel adversarial deep learning model for substation defect image generation: the Abnormal Defect Detection Generative Adversarial Network (ADD-GAN). Unlike existing generative adversarial networks, this model generates defect images based on effectively segmented local areas of substation equipment images, avoiding image distortion caused by global style changes. Additionally, the model uses a joint discriminator for both overall images and defect images to address the issue of low attention to local defect areas, thereby reducing the loss of image features. This approach enhances the overall quality of generated images as well as locally generated defect images, ultimately improving image realism. Experimental results demonstrate that the YOLOV7 object detection model trained on the dataset generated using the ADD-GAN method achieves a mean average precision (mAP) of 81.5% on the test dataset, and outperforms other image data augmentation and generation methods. This confirms that the ADD-GAN method can generate a high-fidelity image dataset of substation equipment defects. [ABSTRACT FROM AUTHOR]

In this paper, using a self-developed silicon carbide epitaxial reactor, we obtained high-quality 6-inch epitaxial wafers with doping concentration uniformity less than 2%, thickness uniformity less than 1% and roughness less than 0.2 nm on domestic substrates, which meets the application requirements of high-quality Schottky Barrier Diode (SBD) and Metal–Oxide–Semiconductor Field-Effect Transistor (MOSFET) devices. We found that increasing the carrier gas flow rate can minimize source gas depletion and optimize the doping uniformity of the 6-inch epitaxial wafer from over 5% to less than 2%. Moreover, reducing the C/Si ratio significantly can suppress the "two-dimensional nucleation growth mode" and improve the wafer surface roughness Ra from 1.82 nm to 0.16 nm. [ABSTRACT FROM AUTHOR]

Aiming at the problem of low detection accuracy caused by insufficient target feature extraction in substation 3D scene, a voxelization-based 3D object detection model AugSecond for substation scene is proposed, which is designed based on the Second network structure. It introduces a triple attention mechanism in the voxel feature encoding stage, which focuses on multi-dimensional attention to enhance the key information of the target and reduce the interference of irrelevant feature information. It designes asymmetric sparse convolutional networks, uses asymmetric convolution to improve convolutional kernel representation capabilities and fuses multi-scale features to enrich target geometry information. Meanwhile, the position regression loss is optimized, and CIoU Loss is used to further consider the geometric correlation between bounding boxes to speed up the network convergence. Experiments on self-built power scene data sets and public data sets show that compared with the benchmark model, AugSecond model significantly improves recognition accuracy and has real-time reasoning speed, which proves the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Background This prospective study investigated the association between tooth loss and upper gastrointestinal (UGI) cancer mortality in the Linxian Dysplasia Nutrition Intervention Trial Cohort. Methods Subjects were categorized into three groups according to age at baseline. No missing teeth and less or greater than median tooth loss in each group was defined as none, moderate, and severe, respectively. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using the Cox proportional hazard model. Results Through 30 September 2015, 541 esophageal squamous cell carcinoma (ESCC), 284 gastric cardia carcinoma (GCC), and 77 gastric non‐cardia carcinoma (GNCC) deaths occurred. In the six‐year follow‐up, severe tooth loss was associated with an increased risk of GCC mortality (HR 1.55, 95% CI 1.06–2.18). In the 15‐year follow‐up, moderate tooth loss increased the ESCC mortality risk by 58% (HR 1.58, 95% CI 1.06–2.35), while severe loss increased the GCC mortality risk by 30% (HR 1.30, 95% CI 1.03–1.64). In the 30‐year follow‐up, moderate tooth loss increased the risk of ESCC mortality (HR 1.34, 95% CI 1.01–1.76). In subjects aged < 55 at baseline and men, moderate tooth loss had 53% and 52% higher risks of ESCC mortality (HR

ObjectiveThe objective of this study was to investigate family history (FH) of upper gastrointestinal (UGI) cancer and risk of esophageal squamous cell carcinoma (ESCC), gastric cardia carcinoma (GCC), and gastric non-cardia carcinoma (GNCC) in the Linxian General Population Nutrition Intervention Trial (NIT) cohort. Methods: This prospective analysis was conducted using the Linxian NIT cohort data. Subjects with FH of UGI cancer was treated as an exposed group while the remainders were considered as a comparison group. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between FH of UGI cancer and risk of UGI cancer incidence and mortality were estimated using Cox proportional hazards models.ResultsThere were 5,680 newly diagnosed UGI cancer cases during the follow-up period, with a total of 4,573 UGI cancer deaths occurred, including 2,603 ESCC, 1,410 GCC, and 560 GNCC deaths. A positive FH of UGI cancer was associated with a significantly increased risk of ESCC and GCC (Incidence: HRESCC = 1.45, 95%CI: 1.35–1.56; HRGCC = 1.27, 95%CI: 1.15–1.40; Mortality: HRESCC = 1.40, 95%CI: 1.30–1.52; HRGCC = 1.27, 95%CI: 1.14–1.42) after adjusting for age at baseline, gender, smoking status, alcohol drinking, education level, and frequency of fresh fruit and vegetable consumption. Subjects with FH in both parents had the highest risk of ESCC and GCC incidence (HRESCC = 1.65, 95%CI: 1.40–1.95; HRGCC = 1.42, 95%CI: 1.12–1.81) and deaths (HRESCC = 1.65, 95%CI: 1.38–1.97; HRGCC = 1.42, 95%CI: 1.09–1.85). Spouse diagnosed with UGI cancer did not increase the risk of any UGI cancers of the subjects. In subgroup analysis, FH of UGI cancer was shown to significantly increase the risk of GCC in non-drinkers (Incidence: HR = 1.31, 95%CI: 1.17–1.47; Mortality: HR = 1.33, 95%CI: 1.17–1.50). No associations were observed for risk of GNCC. Sensitivity analysis by excluding subjects who were followed up less than three years did not materially alter our results.ConclusionOur data point to the role of the FH of UGI cancer to the risk of ESCC and GCC incidence and mortality. The influence of family history on the risk of UGI cancer varies from different types of family members.