Edaravone Improves the Post-traumatic Brain Injury Dysfunction in Learning and Memory by Modulating Nrf2/ARE Signal Pathway

OBJECTIVES: To investigate the molecular mechanism of edaravone (EDA) in improving the post-traumatic brain injury (TBI) dysfunction in learning and memory. METHODS: In vitro and in vivo TBI models were established using hydrogen peroxide (H2O2) treatment for hippocampal nerve stem cells (NSCs) and surgery for rats, followed by EDA treatment. WST 1 measurement, methylthiazol tetrazolium assay, and flow cytometry were performed to determine the activity, proliferation, and apoptosis of NSCs, and malondialdehyde (MDA), lactic dehydrogenase (LDH), and reactive oxygen species (ROS) detection kits were used to analyze the oxides in NSCs. RESULTS: Following EDA pretreatment, NSCs presented with promising resistance to H2O2-induced oxidative stress, whereas NSCs manifested significant increases in activity and proliferation and a decrease in apoptosis. Meanwhile, for NSCs, EDA pretreatment reduced the levels of MDA, LDH, and ROS, with a significant upregulation of Nrf2/antioxidant response element (ARE) signaling pathway, whereas for EDA-treated TBI rats, a significant reduction was observed in the trauma area and injury to the hippocampus, with improvement in memory and learning performance and upregulation of Nrf2/ARE signaling pathway. CONCLUSIONS: EDA, by regulating the activity of Nrf2/ARE signal pathway, can improve the TBI-induced injury to NSCs and learning and memory dysfunction in rats. &nbsp

Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes

Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (\eg tiny objects). The previous works usually utilize multiple instance learning (MIL), which highly depends on category information, to select and refine a low-quality box. Those methods suffer from object drift, group prediction and part domination problems without exploring spatial information. In this paper, we heuristically propose a \textbf{Spatial Self-Distillation based Object Detector (SSD-Det)} to mine spatial information to refine the inaccurate box in a self-distillation fashion. SSD-Det utilizes a Spatial Position Self-Distillation \textbf{(SPSD)} module to exploit spatial information and an interactive structure to combine spatial information and category information, thus constructing a high-quality proposal bag. To further improve the selection procedure, a Spatial Identity Self-Distillation \textbf{(SISD)} module is introduced in SSD-Det to obtain spatial confidence to help select the best proposals. Experiments on MS-COCO and VOC datasets with noisy box annotation verify our method's effectiveness and achieve state-of-the-art performance. The code is available at https://github.com/ucas-vg/PointTinyBenchmark/tree/SSD-Det.Comment: accepted by ICCV 202

Effect of Eucommia ulmoides extract on osteoblast proliferation

Purpose: To evaluate the effect of Eucommia ulmoides extract (EUE) on osteoblast proliferation as well as investigate its probable mechanisms of action.Methods: EUE was pharmacologically evaluated at three doses. Osteoblast cells were divided as follows: Group I: negative control; groups II–IV: received EUE (180, 360 and 540 μg/ml, respectively). We performed 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay to determine osteoblast viability following treatment. Alkaline phosphatase (ALP), osteocalcin, and collagen I levels in osteoblasts were quantified using commercially available kits. Thereafter, mRNA and protein expression of ALP, collagen I, osteocalcin, transforming growth factor-β1 (TGF-β1) were measured using real-time quantitative PCR (qPCR) and western blot, respectively.Results: EUE significantly (p < 0.01) promoted osteoblast proliferation at three treatment doses (180, 360, and 540 μg/mL). Furthermore, ALP, osteocalcin, collagen I and TGF-β1 expression at both mRNA and protein levels increased significantly (all p < 0.05) following EUE treatment.Conclusion: The results suggest that EUE may promote osteoblast cell proliferation and that ALP, osteocalcin, collagen I and TGF-β1 gene expression may be involved in the mechanism of action.Keywords: qPCR, collagen I, Bone, Liver, Eucommia ulmoides extrac

P2RBox: A Single Point is All You Need for Oriented Object Detection

Oriented object detection, a specialized subfield in computer vision, finds applications across diverse scenarios, excelling particularly when dealing with objects of arbitrary orientations. Conversely, point annotation, which treats objects as single points, offers a cost-effective alternative to rotated and horizontal bounding boxes but sacrifices performance due to the loss of size and orientation information. In this study, we introduce the P2RBox network, which leverages point annotations and a mask generator to create mask proposals, followed by filtration through our Inspector Module and Constrainer Module. This process selects high-quality masks, which are subsequently converted into rotated box annotations for training a fully supervised detector. Specifically, we've thoughtfully crafted an Inspector Module rooted in multi-instance learning principles to evaluate the semantic score of masks. We've also proposed a more robust mask quality assessment in conjunction with the Constrainer Module. Furthermore, we've introduced a Symmetry Axis Estimation (SAE) Module inspired by the spectral theorem for symmetric matrices to transform the top-performing mask proposal into rotated bounding boxes. P2RBox performs well with three fully supervised rotated object detectors: RetinaNet, Rotated FCOS, and Oriented R-CNN. By combining with Oriented R-CNN, P2RBox achieves 62.26% on DOTA-v1.0 test dataset. As far as we know, this is the first attempt at training an oriented object detector with point supervision

Group Sampling for Unsupervised Person Re-identification

Unsupervised person re-identification (re-ID) remains a challenging task, where the classifier and feature representation could be easily misled by the noisy pseudo labels towards deteriorated over-fitting. In this paper, we propose a simple yet effective approach, termed Group Sampling, to alleviate the negative impact of noisy pseudo labels within unsupervised person re-ID models. The idea behind Group Sampling is that it can gather a group of samples from the same class in the same mini-batch, such that the model is trained upon group normalized samples while alleviating the effect of a single sample. Group sampling updates the pipeline of pseudo label generation by guaranteeing the samples to be better divided into the correct classes. Group Sampling regularizes classifier training and representation learning, leading to the statistical stability of feature representation in a progressive fashion. Qualitative and quantitative experiments on Market-1501, DukeMTMC-reID, and MSMT17 show that Grouping Sampling improves the state-of-the-arts by up to 2.2%~6.1%. Code is available at https://github.com/wavinflaghxm/GroupSampling

SVCNet: Scribble-based Video Colorization Network with Temporal Aggregation

In this paper, we propose a scribble-based video colorization network with temporal aggregation called SVCNet. It can colorize monochrome videos based on different user-given color scribbles. It addresses three common issues in the scribble-based video colorization area: colorization vividness, temporal consistency, and color bleeding. To improve the colorization quality and strengthen the temporal consistency, we adopt two sequential sub-networks in SVCNet for precise colorization and temporal smoothing, respectively. The first stage includes a pyramid feature encoder to incorporate color scribbles with a grayscale frame, and a semantic feature encoder to extract semantics. The second stage finetunes the output from the first stage by aggregating the information of neighboring colorized frames (as short-range connections) and the first colorized frame (as a long-range connection). To alleviate the color bleeding artifacts, we learn video colorization and segmentation simultaneously. Furthermore, we set the majority of operations on a fixed small image resolution and use a Super-resolution Module at the tail of SVCNet to recover original sizes. It allows the SVCNet to fit different image resolutions at the inference. Finally, we evaluate the proposed SVCNet on DAVIS and Videvo benchmarks. The experimental results demonstrate that SVCNet produces both higher-quality and more temporally consistent videos than other well-known video colorization approaches. The codes and models can be found at https://github.com/zhaoyuzhi/SVCNet.Comment: accepted by IEEE Transactions on Image Processing (TIP

The effect of various pressure of pneumatic uterine bracket by using saccule sterine external stent on incidence of supine hypotensive syndrome

Objectives: The saccule uterine external stent with a pneumatic uterine bracket reportedly prevents the incidence of supine hypotension syndrome (SHS) during cesarean section under combined spinal — epidural anesthesia (CSEA). However, the preventive effect is affected by the pressure within pneumatic uterine bracket. This study aims to explore the optimal pressure.Material and methods: One hundred forty-eight pregnant women were selected and randomly divided into three groups: Group A (the control group, n = 49), Group B (n = 49), and Group C (n = 50). The pressure within pneumatic uterine bracket was set at 240 mmHg, 260mmHg, and 280mmHg, respectively, during cesarean section under CSEA for participants in groups A, B and C. The intraoperative comfort rate and incidence of SHS were recorded.Results: No significant difference in the anesthetic efficacy was observed among the three groups (p > 0.05). However, there was a significant difference in the occurrence of SHS, with a reduction of 30 mmHg in blood pressure. The incidence of SHS belong the three groups showed significant differences (36.73% in Group A, 18.37% in Group B and 18.00% in Group C, p < 0.05). In addition, significant differences (p < 0.05) in the intraoperative comfort rate were also found among the three groups, with the comfort rate of 69.39% in group A, 91.84% in group B and 90.00% in Group C.Conclusions: The optimal pressure within pneumatic uterine bracket for preventing SHS hypotension is about 260 mmHg. These findings might contribute to the prevention of SHS