Dual Stream Long Short-Term Memory Feature Fusion Classifier for Surface Electromyography Gesture Recognition.

Gesture recognition using electromyography (EMG) signals has prevailed recently in the field of human-computer interactions for controlling intelligent prosthetics. Currently, machine learning and deep learning are the two most commonly employed methods for classifying hand gestures. Despite traditional machine learning methods already achieving impressive performance, it is still a huge amount of work to carry out feature extraction manually. The existing deep learning methods utilize complex neural network architectures to achieve higher accuracy, which will suffer from overfitting, insufficient adaptability, and low recognition accuracy. To improve the existing phenomenon, a novel lightweight model named dual stream LSTM feature fusion classifier is proposed based on the concatenation of five time-domain features of EMG signals and raw data, which are both processed with one-dimensional convolutional neural networks and LSTM layers to carry out the classification. The proposed method can effectively capture global features of EMG signals using a simple architecture, which means less computational cost. An experiment is conducted on a public DB1 dataset with 52 gestures, and each of the 27 subjects repeats every gesture 10 times. The accuracy rate achieved by the model is 89.66%, which is comparable to that achieved by more complex deep learning neural networks, and the inference time for each gesture is 87.6 ms, which can also be implied in a real-time control system. The proposed model is validated using a subject-wise experiment on 10 out of the 40 subjects in the DB2 dataset, achieving a mean accuracy of 91.74%. This is illustrated by its ability to fuse time-domain features and raw data to extract more effective information from the sEMG signal and select an appropriate, efficient, lightweight network to enhance the recognition results.

Efficient and Robust Point Cloud Registration via Heuristics-guided Parameter Search.

Estimating the rigid transformation with 6 degrees of freedom based on a putative 3D correspondence set is a crucial procedure in point cloud registration. Existing correspondence identification methods usually lead to large outlier ratios (> 95% is common), underscoring the significance of robust registration methods. Many researchers turn to parameter search-based strategies (e.g., Branch-and-Bround) for robust registration. Although related methods show high robustness, their efficiency is limited to the high-dimensional search space. This paper proposes a heuristics-guided parameter search strategy to accelerate the search while maintaining high robustness. We first sample some correspondences (i.e., heuristics) and then just need to sequentially search the feasible regions that make each sample an inlier. Our strategy largely reduces the search space and can guarantee accuracy with only a few inlier samples, therefore enjoying an excellent trade-off between efficiency and robustness. Since directly parameterizing the 6-dimensional nonlinear feasible region for efficient search is intractable, we construct a three-stage decomposition pipeline to reparameterize the feasible region, resulting in three lower-dimensional sub-problems that are easily solvable via our strategy. Besides reducing the searching dimension, our decomposition enables the leverage of 1-dimensional interval stabbing at all three stages for searching acceleration. Moreover, we propose a valid sampling strategy to guarantee our sampling effectiveness, and a compatibility verification setup to further accelerate our search. Extensive experiments on both simulated and real-world datasets demonstrate that our approach exhibits comparable robustness with state-of-the-art methods while achieving a significant efficiency boost.

Low-frequency magnetic field therapy for glioblastoma: Current advances, mechanisms, challenges and future perspectives.

BACKGROUND: Glioblastoma (GBM) is the most common malignant tumour of the central nervous system. Despite recent advances in multimodal GBM therapy incorporating surgery, radiotherapy, systemic therapy (chemotherapy, targeted therapy), and supportive care, the overall survival (OS) remains poor, and long-term survival is rare. Currently, the primary obstacles hindering the effectiveness of GBM treatment are still the blood-brain barrier and tumor heterogeneity. In light of its substantial advantages over conventional therapies, such as strong penetrative ability and minimal side effects, low-frequency magnetic fields (LF-MFs) therapy has gradually caught the attention of scientists. AIM OF REVIEW: In this review, we shed the light on the current status of applying LF-MFs in the treatment of GBM. We specifically emphasize our current understanding of the mechanisms by which LF-MFs mediate anticancer effects and the challenges faced by LF-MFs in treating GBM cells. Furthermore, we discuss the prospective applications of magnetic field therapy in the future treatment of GBM. Key scientific concepts of review: The review explores the current progress on the use of LF-MFs in the treatment of GBM with a special focus on the potential underlying mechanisms of LF-MFs in anticancer effects. Additionally, we also discussed the complex magnetic field features and biological characteristics related to magnetic bioeffects. Finally, we proposed a promising magnetic field treatment strategy for future applications in GBM therapy.

HRegNet: A Hierarchical Network for Efficient and Accurate Outdoor LiDAR Point Cloud Registration.

Point cloud registration is a fundamental problem in 3D computer vision. Outdoor LiDAR point clouds are typically large-scale and complexly distributed, which makes the registration challenging. In this paper, we propose an efficient hierarchical network named HRegNet for large-scale outdoor LiDAR point cloud registration. Instead of using all points in the point clouds, HRegNet performs registration on hierarchically extracted keypoints and descriptors. The overall framework combines the reliable features in deeper layer and the precise position information in shallower layers to achieve robust and precise registration. We present a correspondence network to generate correct and accurate keypoints correspondences. Moreover, bilateral consensus and neighborhood consensus are introduced for keypoints matching, and novel similarity features are designed to incorporate them into the correspondence network, which significantly improves the registration performance. In addition, we design a consistency propagation strategy to effectively incorporate spatial consistency into the registration pipeline. The whole network is also highly efficient since only a small number of keypoints are used for registration. Extensive experiments are conducted on three large-scale outdoor LiDAR point cloud datasets to demonstrate the high accuracy and efficiency of the proposed HRegNet. The source code of the proposed HRegNet is available at https://github.com/ispc-lab/HRegNet2.

First report of Aloe root and stem rot caused by Phytophthora palmivora in Yunnan Province, China.

Aloe genus plants are perennial evergreen herb belonging to Liliaceae family which is widely used in food, medicine, beauty, and health care (Kumar et al. 2019). In August 2021, symptoms of root and stem rot was observed in approximately 20% of Aloe vera plantings in Yuanjiang County, Yunnan Province, China (23° 64' 53" N, 101° 99' 84" E). The most typical symptoms were stem and root rot, browning and necrosis of vascular tissues, gradual greening, and reddish-browning of leaves from bottom to top, abscission, and eventual plant death (Fig. S1). Therefore, to isolate and identify the pathogen, the plants showing the above symptoms were collected. The plant tissues were cut from the edges of root and stem lesions, followed by disinfection with 75% ethanol for 1 min, rinsed three times with sterilized distilled water, and cut into 3 × 3 mm small squares after excision of marginal tissues. The tissues were transferred to the oomycetes selective medium (Liu et al. 2022) and incubated at 28 °C in the dark for 3~5 days, and suspected colonies were purified. The colonies were then inoculated onto potato dextrose agar (PDA), V8-juice agar (V8), and oatmeal agar (OA) medium plates for morphological characteristics. Finally, 18 isolates with the same colonial and morphological characteristics were obtained from 30 lesioned tissue and one of them was named as ARP1. On PDA, V8 and OA medium plates, the ARP1 colonies were white. On PDA plate, the mycelia were dense and the colonies were petal-like; on V8 plate, the mycelia were cashmere and the colonies were radial or star-like. Whereas, on OA plate, the mycelia were cotton-like and the colonies were fluffy and radial (Fig. S2 A~C). Mycelium did not have septum with high branching and swelling. Sporangia were abundant, semi-papillate, varying in shape from ovoid-ellipsoid to long-ellipsoid, 18-26 × 45-63 µm (average: 22 × 54 µm, n = 30), sporangia released numerous zoospores from the papillate after maturation. The chlamydospores were spherical, 20-35 µm in diameter (average: 27.5 µm, n = 30) (Fig. S2 D~F). These morphological features were like those of the pathogenic species of the oomycetes (Chen et al. 2022). For the molecular characterization, the genomic DNA of the isolate was extracted using the cetyl trimethyl ammonium bromide method, and the translation elongation factor 1α (tef-1α) (Stielow et al. 2015), ß-tubulin (ß-tub) (Kroon et al. 2004) and internal transcribed spacer (ITS) (White et al. 1990) of isolated strain ARP1 were amplified using primer pairs EF1-1018F/EF1-1620R, TUBUF2/TUBUR1 and ITS1/ITS4, respectively. The tef-1α, ß-tub genes and ITS region of ARP1 were directly sequenced and their sequence information was deposited in GenBank under accession numbers OQ506129, OQ506127 and OQ449628. ARP1 was clustered on the same evolutionary branch with Phytophthora palmivora (Fig. S3). To confirm the pathogenicity of ARP1, the main root of A. vera was wounded to 1 cm long and 2 mm deep with a scalpel blade followed by inoculation with 50 ml suspension of ARP1 zoospores at a concentration of 1 × 106 spores / ml per potted plant, and an equal volume of water as control. All inoculated plants were placed in the greenhouse at 28°C, 12 h / 12 h light / dark. After 15 dpi, the inoculated plants showed typical symptoms of wilted and drooping leaves and stem and root rot, same as observed in the field condition (Fig. S4). After inoculation with ARP1, a strain with the same morphological and molecular characteristics as the original isolate was re-isolated, confirming Koch's postulates. To our knowledge, this is the first report of P. palmivora causing root and stem rot of A. vera in the study region. This disease could be a potential risk for aloe production and therefore appropriate management measures should be taken.

Sparse-to-Dense Matching Network for Large-Scale LiDAR Point Cloud Registration.

Point cloud registration is a fundamental problem in 3D computer vision. Previous learning-based methods for LiDAR point cloud registration can be categorized into two schemes: dense-to-dense matching methods and sparse-to-sparse matching methods. However, for large-scale outdoor LiDAR point clouds, solving dense point correspondences is time-consuming, whereas sparse keypoint matching easily suffers from keypoint detection error. In this paper, we propose SDMNet, a novel Sparse-to-Dense Matching Network for large-scale outdoor LiDAR point cloud registration. Specifically, SDMNet performs registration in two sequential stages: sparse matching stage and local-dense matching stage. In the sparse matching stage, we sample a set of sparse points from the source point cloud and then match them to the dense target point cloud using a spatial consistency enhanced soft matching network and a robust outlier rejection module. Furthermore, a novel neighborhood matching module is developed to incorporate local neighborhood consensus, significantly improving performance. The local-dense matching stage is followed for fine-grained performance, where dense correspondences are efficiently obtained by performing point matching in local spatial neighborhoods of high-confidence sparse correspondences. Extensive experiments on three large-scale outdoor LiDAR point cloud datasets demonstrate that the proposed SDMNet achieves state-of-the-art performance with high efficiency.

Ecological Risks of Antibiotics in Urban Wetlands on the Qinghai-Tibet Plateau, China.

Although the ecological risks of antibiotics have been extensively researched globally, fewer studies have been conducted in sensitive and fragile plateau wetland ecosystems. To evaluate the ecological risk of antibiotics in plateau urban wetlands, 18 water samples, 10 plant samples, and 8 sediment samples were collected in March 2022 in the Xining urban wetlands on the Qinghai-Tibet Plateau. The liquid chromatography-electrospray ionization tandem mass spectrometry method was utilized to measure the concentrations of 15 antibiotics in three categories in three types of environmental media. Risk quotients were adopted to assess the ecological risk of antibiotics, and the principal component analysis-multiple linear regression model was used to analyze the source of antibiotics. The results showed that (1) the maximum concentrations of antibiotics in water samples, plants, and sediments reached 1220.86 ng/L, 78.30 ng/g, and 5.64 ng/g, respectively; (2) Tylosin (TYL), norfloxacin (NFX), ofloxacin (OFX), and ciprofloxacin (CFX) in water were at medium and high-risk levels, and OFX had the highest risk value, of 108.04; and (3) the results of source apportionment indicate that 58.94% of the antibiotics came from the Huangshui river and wastewater treatment plant (WWTP) near the wetlands. The current study may provide a reference for the risks and management of antibiotics in plateau urban wetlands.

Globally-Optimal Inlier Maximization for Relative Pose Estimation Under Planar Motion.

Planar motion constraint occurs in visual odometry (VO) and SLAM for Automated Guided Vehicles (AGVs) or mobile robots in general. Conventionally, two-point solvers can be nested to RANdom SAmple Consensus to reject outliers in real data, but the performance descends when the ratio of outliers goes high. This study proposes a globally-optimal Branch-and-Bound (BnB) solver for relative pose estimation under general planar motion, which aims to figure out the globally-optimal solution even under a quite noisy environment. Through reasonable modification of the motion equation, we decouple the relative pose into relative rotation and translation so that a simplified bounding strategy can be applied. It enhances the efficiency of the BnB technique. Experimental results support the global optimality and demonstrate that the proposed method performs more robustly than existing approaches. In addition, the proposed algorithm outperforms state-of-art methods in global optimality under the varying level of outliers.

Globally Optimal Vertical Direction Estimation in Atlanta World.

In man-made environments, most of the objects and structures are organized in the form of orthogonal and parallel planes. These planes can be approximated by an Atlanta world assumption, in which the normals of planes can be represented by Atlanta frames. The Atlanta world assumption has one vertical frame and multiple horizontal frames. Conventionally, given a set of inputs such as surface normals, the Atlanta frame estimation problem can be solved by a branch-and-bound (BnB) algorithm. However, the runtime of the BnB algorithm will increase greatly when the dimensionality (i.e., the number of horizontal frames) increases. In this paper, we estimate only the vertical direction, instead of all Atlanta frames at once. Accordingly, we propose a vertical direction estimation method by considering the relationship between the vertical frame and horizontal frames. Concretely, our approach employs a BnB algorithm to search the vertical direction, thereby guaranteeing global optimality without requiring prior knowledge of the number of Atlanta frames. In order to guarantee convergence, four novel bounds are investigated, by mapping a 3D hemisphere to a 2D region. We verify the feasibility of the proposed method using various challenging synthetic and real-world data.

Efficient and Outlier-Robust Simultaneous Pose and Correspondence Determination by Branch-and-Bound and Transformation Decomposition.

Estimating the pose of a calibrated camera relative to a 3D point set from one image is an important task in computer vision. Perspective-n-Point algorithms are often used if perfect 2D-3D correspondences are known. However, it is difficult to determine 2D-3D correspondences perfectly, and then the simultaneous pose and correspondence determination problem is needed to be solved. Early methods aimed to solve this problem by local optimization. Recently, several new methods are proposed to globally solve this problem by using branch-and-bound (BnB) method, but they tend to be slow because the time complexity of the BnB-based methods is exponential to the dimensionality of the parameter space, and they directly search the 6D parameter space. In this paper, we propose to decompose the joint searching into two separate searching processes by introducing a rotation invariant feature (RIF). Specifically, we construct RIFs from the original 3D and 2D point sets and search for the globally optimal translation to match these two RIFs first. Then, the original 3D point set is translated and matched with the 2D point set to find a globally optimal rotation. Experiments on challenging data show that the proposed method outperforms state-of-the-art methods in terms of both speed and accuracy.

Prokineticin-2 prevents neuronal cell deaths in a model of traumatic brain injury.

Prokineticin-2 (Prok2) is an important secreted protein likely involved in the pathogenesis of several acute and chronic neurological diseases through currently unidentified regulatory mechanisms. The initial mechanical injury of neurons by traumatic brain injury triggers multiple secondary responses including various cell death programs. One of these is ferroptosis, which is associated with dysregulation of iron and thiols and culminates in fatal lipid peroxidation. Here, we explore the regulatory role of Prok2 in neuronal ferroptosis in vitro and in vivo. We show that Prok2 prevents neuronal cell death by suppressing the biosynthesis of lipid peroxidation substrates, arachidonic acid-phospholipids, via accelerated F-box only protein 10 (Fbxo10)-driven ubiquitination, degradation of long-chain-fatty-acid-CoA ligase 4 (Acsl4), and inhibition of lipid peroxidation. Mice injected with adeno-associated virus-Prok2 before controlled cortical impact injury show reduced neuronal degeneration and improved motor and cognitive functions, which could be inhibited by Fbxo10 knockdown. Our study shows that Prok2 mediates neuronal cell deaths in traumatic brain injury via ferroptosis.

miR-720 is a key regulator of glioma migration and invasion by controlling TARSL2 expression.

Glioblastoma (GBM) is the most lethal type of primary brain tumor and is characterized by diffuse infiltrative growth. However, the mechanisms that control this phenotype remain largely unknown. Emerging evidence has demonstrated that the abnormal expression of microRNAs and their target genes are involved in the migration and invasion of glioma cells. In this study, we demonstrated that microRNA-720 (miR-720) was significantly upregulated in glioma tissues and cells. Functional experiments showed that overexpression of miR-720 promotes glioma migration and invasion, while downregulation of miR-720 inhibits glioma migration and invasion. Meanwhile, we found that threonyl-tRNA synthetase like-2 (TARSL2) was a direct and functional target of miR-720 in glioma. Reintroduction of TARSL2 into glioma cells repressed the invasion promoting function of miR-720, whereas downregulation of TARSL2 reversed the anti-invasion function of anti-miR-720. Furthermore, quantitative real-time polymerase chain reaction results showed that miR-720 was inversely correlated with TARSL2 expression in 40 GBM tissues. Finally, in vivo experiments showed that miR-720 promotes glioma growth and upregulates invasion-related genes in nude mice. Overall, our findings suggest increasing miR-720 enhances glioma migration and invasion through downregulation of TARSL2, which may provide novel insight into the treatment of glioma.

Silencing of A20 Aggravates Neuronal Death and Inflammation After Traumatic Brain Injury: A Potential Trigger of Necroptosis.

Programmed cell death is an important biological process that plays an indispensable role in traumatic brain injury (TBI). Inhibition of necroptosis, a type of programmed cell death, is pivotal in neuroprotection and in preventing associated inflammatory responses. Our results showed that necroptosis occurred in human brain tissues after TBI. Necroptosis was also induced by controlled cortical impact (CCI) injury in a rat model of TBI and was accompanied by high translocation of high-mobility group box-1 (HMGB1) to the cytoplasm. HMGB1 was then passed through the impaired cell membrane to upregulate the receptor for advanced glycation end-products (RAGE), nuclear factor (NF)-κB, and inflammatory factors such as interleukin-6 (IL-6), interleukin-1 (IL-1ß), as well as NACHT, LRR and PYD domains-containing protein 3 (NLRP3). Necroptosis was alleviated by necrostatin-1 and melatonin but not Z-VAD (a caspase inhibitor), which is consistent with the characteristic of caspase-independent signaling. This study also demonstrated that tumor necrosis factor, alpha-induced protein 3 (TNFAIP3, also known as A20) was indispensable for regulating and controlling necroptosis and inflammation after CCI. We found that a lack of A20 in a CCI model led to aggressive necroptosis and attenuated the anti-necroptotic effects of necrostatin-1 and melatonin.

Nogo-A/Pir-B/TrkB Signaling Pathway Activation Inhibits Neuronal Survival and Axonal Regeneration After Experimental Intracerebral Hemorrhage in Rats.

Intracerebral hemorrhage (ICH) leads to widespread pathological lesions in the brain, especially impacting neuronal survival and axonal regeneration. This study aimed to elucidate whether the Nogo-A (a myelin-related protein)/paired immunoglobulin-like receptor B (Pir-B)/tropomyosin receptor kinase B (TrkB) pathway could exert a regulatory effect in ICH. An ICH model was first established in Sprague Dawley rats, followed by different administrations of vehicle, k252a, or NSC 87877. The Morris water maze test was performed to observe ICH-induced cognitive dysfunction in rats. Rats in the ICH + NSC 87877 group showed better cognitive performance compared with those injected with vehicle or k252a. Neurobehavioral scores were identical. By harvesting brain tissues at different time points after ICH, we detected the expression levels of Nogo-A and PirB with western blot and immunofluorescence and found that they were markedly upregulated at 48 h after ICH. TUNEL and Fluoro-Jade B staining showed that NSC 87877 treatment attenuated ICH-induced apoptosis and neuronal death, whereas k252a treatment aggravated these pathological changes. The expression levels of growth-associated protein 43 (GAP43) and neurofilament 200 (NF200) were higher in the ICH + NSC 87877 group compared with the ICH + vehicle group, but were lower in the ICH + k252a group. Finally, we confirmed the protective role of p-TrkB/TrkB in ICH by western blot. To sum up, our study identified the inhibitory role of the Nogo-A/PirB/TrkB pathway in ICH; however, p-TrkB/TrkB may serve as a potential target for secondary brain injury post-ICH.

Cardiolipin-Dependent Mitophagy Guides Outcome after Traumatic Brain Injury.

Mitochondrial energy production is essential for normal brain function. Traumatic brain injury (TBI) increases brain energy demands, results in the activation of mitochondrial respiration, associated with enhanced generation of reactive oxygen species. This chain of events triggers neuronal apoptosis via oxidation of a mitochondria-specific phospholipid, cardiolipin (CL). One pathway through which cells can avoid apoptosis is via elimination of damaged mitochondria by mitophagy. Previously, we showed that externalization of CL to the mitochondrial surface acts as an elimination signal in cells. Whether CL-mediated mitophagy occurs in vivo or its significance in the disease processes are not known. In this study, we showed that TBI leads to increased mitophagy in the human brain, which was also detected using TBI models in male rats. Knockdown of CL synthase, responsible for de novo synthesis of CL, or phospholipid scramblase-3, responsible for CL translocation to the outer mitochondrial membrane, significantly decreased TBI-induced mitophagy. Inhibition of mitochondrial clearance by 3-methyladenine, mdivi-1, or phospholipid scramblase-3 knockdown after TBI led to a worse outcome, suggesting that mitophagy is beneficial. Together, our findings indicate that TBI-induced mitophagy is an endogenous neuroprotective process that is directed by CL, which marks damaged mitochondria for elimination, thereby limiting neuronal death and behavioral deficits.SIGNIFICANCE STATEMENT Traumatic brain injury (TBI) increases energy demands leading to activation of mitochondrial respiration associated with enhanced generation of reactive oxygen species and resultant damage to mitochondria. We demonstrate that the complete elimination of irreparably damaged organelles via mitophagy is activated as an early response to TBI. This response includes translocation of mitochondria phospholipid cardiolipin from the inner membrane to the outer membrane where externalized cardiolipin mediates targeted protein light chain 3-mediated autophagy of damaged mitochondria. Our data on targeting phospholipid scramblase and cardiolipin synthase in genetically manipulated cells and animals strongly support the essential role of cardiolipin externalization mechanisms in the endogenous reparative plasticity of injured brain cells. Furthermore, successful execution and completion of mitophagy is beneficial in the context of preservation of cognitive functions after TBI.

2D-3D Point Set Registration Based on Global Rotation Search.

Simultaneously determining the relative pose and correspondence between a set of 3D points and its 2D projection is a fundamental problem in computer vision, and the problem becomes more difficult when the point sets are contaminated by noise and outliers. Traditionally, this problem is solved by local optimization methods, which usually start from an initial guess of the pose and alternately optimize the pose and the correspondence. In this paper, we formulate the problem as optimizing the pose of the 3D points in the SE(3) space to make its 2D projection best align with the 2D point set, which is measured by the cardinality of the inlier set on the 2D projection plane. We propose four geometric bounds for the position of the projection of a 3D point on the 2D projection plane and solve the 2D-3D point set registration problem by combining a global optimal rotation search and a grid search of translation. Compared with existing global optimization approaches, the proposed method utilizes a different problem formulation and more efficiently searches the translation space, which improves the registration speed. Experiments with synthetic and real data showed that the proposed approach significantly outperformed state-of-the-art local and global methods.

Clinical Study on Complications of Intracranial Ruptured Aneurysm Embolization by Stent-Assisted Coil.

BACKGROUND The aim of this study was to retrospectively analyze the incidence of complications of intracranial complex aneurysms embolization by stent-assisted coils, and to investigate the causes of complications and corresponding treatment methods. MATERIAL AND METHODS A total of 71 patients with subarachnoid hemorrhage (SAH) underwent stent-assisted coil embolization from 2015 to 2018 were enrolled in this study. Among them, 59 cases were single aneurysm, 12 cases were multiple aneurysms (11 cases with 2 aneurysms and 1 case with 3 aneurysms), for a total of 84 aneurysms. All enrolled patients received stent angioplasty except for 1 case. RESULTS There were 62 aneurysms (73.81%) treated with complete tamponade, 21 aneurysms (25.00%) treated with near-total tamponade and 1 aneurysm (1.19%) treated with partial tamponade. All aneurysms were evaluated based on GOS (Glascow outcome scale): 55 cases had GOS of 5 scores, 12 cases had GOS of 4 scores, 3 cases had GOS of 3 scores, and 1 case had GOS of 1 score. There were 67 SAH patients with good prognosis (GOS of 4-5 scores). In our study, the incidence of complications was 12.7%. Three cases experienced acute thrombosis, 2 cases experienced aneurysm rupture during embolization, and 1 case experienced postoperative focal ischemic changes with mild neurological deficits. CONCLUSIONS Stent-assisted coil embolization is safe, effective, and feasible for the treatment of intracranial ruptured aneurysms. Patients had a favorable outcome of as high as 94.4%. However, clinical skills should be improved to reduce the occurrence of complications. Prompt and timely treatment for complications of intracranial ruptured aneurysm is also of great significance.

PBX3/MEK/ERK1/2/LIN28/let-7b positive feedback loop enhances mesenchymal phenotype to promote glioblastoma migration and invasion.

BACKGROUND: Brain invasion by glioblastoma (GBM) determines recurrence and prognosis in patients, which is, in part, attributed to increased mesenchymal transition. Here, we report evidence favoring such a role for the Pre-B-cell leukemia homebox (PBX) family member PBX3. METHODS: Western blot, immunohistochemistry, qRT-PCR and datasets mining were used to determined proteins or genes expression levels. Wound-healing and transwell assays were used to examine the invasive abilities of GBM cells. Dual-luciferase reporter assays were used to determine how let-7b regulates PBX3. Chromatin-immunoprecipitation (ChIP) and rescue experiments were performed to investigate the involved molecular mechanisms. Orthotopic mouse models were used to assess the role of PBX3 in vivo. RESULTS: We found that PBX3 expression levels positively correlated with glioma mesenchymal markers. Ectopic expression of PBX3 promoted invasive phenotypes and triggered the expression of mesenchymal markers, whereas depletion of PBX3 reduced GBM cell invasive abilities and decreased the expression of mesenchymal markers. In addition, inhibition of PBX3 attenuated transforming growth factor-ß (TGFß)-induced GBM mesenchymal transition. Mechanistic studies revealed that PBX3 mediated GBM mesenchymal transition through activation of MEK/ERK1/2, leading to increased expression of LIN28 by c-myc. Increased LIN28 inhibited let-7b biogenesis, which then promoted the pro-invasive genes, such as HMGA2 and IL-6. Furthermore, let-7b suppressed PBX3 by directly targeting 3'-UTR of PBX3. Thus, repressed let-7b by PBX3 amplifies PBX3 signaling and forms a positive feedback loop to promote GBM mesenchymal transition. CONCLUSIONS: These data highlight the importance of PBX3 as a key driver of mesenchymal transition and potential therapeutic target.

Activation of bradykinin B2 receptor induced the inflammatory responses of cytosolic phospholipase A2 after the early traumatic brain injury.

Phospholipase A2 is a known aggravator of inflammation and deteriorates neurological outcomes after traumatic brain injury (TBI), however the exact inflammatory mechanisms remain unknown. This study investigated the role of bradykinin and its receptor, which are known initial mediators within inflammation activation, as well as the mechanisms of the cytosolic phospholipase A2 (cPLA2)-related inflammatory responses after TBI. We found that cPLA2 and bradykinin B2 receptor were upregulated after a TBI. Rats treated with the bradykinin B2 receptor inhibitor LF 16-0687 exhibited significantly less cPLA2 expression and related inflammatory responses in the brain cortex after sustaining a controlled cortical impact (CCI) injury. Both the cPLA2 inhibitor and the LF16-0687 improved CCI rat outcomes by decreasing neuron death and reducing brain edema. The following TBI model utilized both primary astrocytes and primary neurons in order to gain further understanding of the inflammation mechanisms of the B2 bradykinin receptor and the cPLA2 in the central nervous system. There was a stronger reaction from the astrocytes as well as a protective effect of LF16-0687 after the stretch injury and bradykinin treatment. The protein kinase C pathway was thought to be involved in the B2 bradykinin receptor as well as the cPLA2-related inflammatory responses. Rottlerin, a Protein Kinase C (PKC) δ inhibitor, decreased the activity of the cPLA2 activity post-injury, and LF16-0687 suppressed both the PKC pathway and the cPLA2 activity within the astrocytes. These results indicated that the bradykinin B2 receptor-mediated pathway is involved in the cPLA2-related inflammatory response from the PKC pathway.