SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator

In this paper, we propose a novel network, SVDFormer, to tackle two specific challenges in point cloud completion: understanding faithful global shapes from incomplete point clouds and generating high-accuracy local structures. Current methods either perceive shape patterns using only 3D coordinates or import extra images with well-calibrated intrinsic parameters to guide the geometry estimation of the missing parts. However, these approaches do not always fully leverage the cross-modal self-structures available for accurate and high-quality point cloud completion. To this end, we first design a Self-view Fusion Network that leverages multiple-view depth image information to observe incomplete self-shape and generate a compact global shape. To reveal highly detailed structures, we then introduce a refinement module, called Self-structure Dual-generator, in which we incorporate learned shape priors and geometric self-similarities for producing new points. By perceiving the incompleteness of each point, the dual-path design disentangles refinement strategies conditioned on the structural type of each point. SVDFormer absorbs the wisdom of self-structures, avoiding any additional paired information such as color images with precisely calibrated camera intrinsic parameters. Comprehensive experiments indicate that our method achieves state-of-the-art performance on widely-used benchmarks. Code will be available at https://github.com/czvvd/SVDFormer.Comment: Accepted by ICCV 202

JZTX-V Targets the Voltage Sensor in Kv4.2 to Inhibit Ito Potassium Channels in Cardiomyocytes

Kv4 potassium channels are responsible for transient outward K+ currents in the cardiac action potential (AP). Previous experiments by our group demonstrated that Jingzhaotoxin-V (JZTX-V) selectively inhibits A-type potassium channels. However, the specific effects of JZTX-V on the transient outward (Ito) current of cardiomyocytes and underlying mechanism of action remain unclear. In the current study, 100 nM JZTX-V effectively inhibited the Ito current and extended the action potential duration (APD) of neonatal rat ventricular myocytes (NRVM). We further analyzed the effects of JZTX-V on Kv4.2, a cloned channel believed to underlie the Ito current in rat cardiomyocytes. JZTX-V inhibited the Kv4.2 current with a half-maximal inhibitory concentration (IC50) of 13 ± 1.7 nM. To establish the molecular mechanism underlying the inhibitory action of JZTX-V on Kv4.2, we performed alanine scanning mutagenesis of Kv4.2 and JZTX-V and assessed the effects of the mutations on binding activities of the proteins. Interestingly, the Kv4.2 mutations V285A, F289A, and V290A reduced the affinity for JZTX-V while I275A and L277A increased the affinity for JZTX-V. Moreover, mutation of positively charged residues (R20 and K22) of JZTX-V and the hydrophobic patch (formed by W5, M6, and W7) led to a significant reduction in toxin sensitivity, indicating that the hydrophobic patch and electrostatic interactions played key roles in the binding of JZTX-V with Kv4.2. Data from our study have shed light on the specific roles and molecular mechanisms of JZTX-V in the regulation of Ito potassium channels and supported its utility as a potential novel antiarrhythmic drug

Exploration of the protective mechanisms of Icariin against cisplatin-induced renal cell damage in canines

This study delves into the protective mechanisms of Icariin (ICA) against cisplatin-induced damage in Madin-Darby canine kidney (MDCK) cells. Comprising two distinct phases, the investigation initially employed a single-factor randomized design to ascertain the minimal cisplatin concentration eliciting MDCK cell damage, spanning concentrations from 0 to 16 mmol/L. Concurrently, various concentrations of ICA (ranging from 5 to 50 mmol/L) were combined with 1 mmol/L cisplatin to determine the most efficacious treatment concentration. Subsequent investigations utilized four treatment groups: control, 1 mmol/L cisplatin, 1 mmol/L cisplatin + 20 mmol/L ICA, and 1 mmol/L cisplatin + 25 mmol/L ICA, aimed at elucidating ICA's protective mechanisms. Findings from the initial phase underscored a significant reduction in MDCK cell viability with 1 mmol/L cisplatin in comparison to the control (P < 0.01). Notably, the inclusion of 20 and 25 mmol/L ICA substantively ameliorated MDCK cell viability under 1 mmol/L cisplatin (P < 0.01). Moreover, cisplatin administration induced an elevation in inflammatory factors, malondialdehyde (MDA), reactive oxygen species (ROS), and Bax protein levels, while concurrently suppressing superoxide dismutase (SOD), catalase (CAT), and Bcl-2 expression (P < 0.01). Conversely, supplementation of 20 and 25 mmol/L ICA demonstrated a marked increase in mitochondrial membrane potential and levels of SOD, CAT, and Bcl-2 (P < 0.01). These interventions effectively attenuated inflammatory responses and suppressed Bax protein expression (P < 0.05), consequently mitigating cisplatin-induced apoptosis in MDCK cells (P < 0.01). In summary, these findings elucidate the role of ICA in impeding apoptosis in cisplatin-induced MDCK cells by regulating inflammatory responses, oxidative stress, and autophagic protein expression

Peroxynitrite-Induced Apoptosis in FaDu Cells is Correlated with the Up-Regulation of PDCD4 Gene

Peroxynitrite (ONOO-) is a highly reactive species that attacks a range of biological targets. The present study was designed to investigate the effect of ONOOon FaDu cells, a human hypopharyngeal cancer cell line, with special attention given to the PDCD4 gene expression in response to this oxidative stress. The in vitro cultured FaDu cells were subjected to various concentrations of ONOO-, then, the cell viability and morphological changes were examined by MTT assay and acridine orange staining, respectively. The protein expressions of Caspase-9, Caspase-3, and PDCD4 were determined by western blot and the mRNA expression of PDCD4 was analyzed by RT-PCR. This work demonstrated that ONOOcould inhibit the proliferation and induce apoptosis of FaDu cells. The protein expressions of Caspase-9, Caspase-3, and PDCD4 were up-regulated and, meanwhile, the mRNA expression of PDCD4 was increased, in response to ONOO-. These data suggest that ONOOcan effectively suppress proliferation of FaDu cells via triggering the apoptotic pathway. PDCD4 gene may play an important role in ONOO--induced apoptosis in FaDu cells, which may offer a new target for the treatment of hypopharyngeal carcinoma.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Superionic iron oxide-hydroxide in Earth’s deep mantle

H2O ice becomes a superionic phase under the high pressure and temperature conditions of deep planetary interiors of ice planets such as Neptune and Uranus, which affects interior structures and generates magnetic fields. The solid Earth, however, contains only hydrous minerals with negligible amount of ice. Here we combine high pressure and temperature electrical conductivity experiments, Raman spectroscopy, and first-principles simulations, to investigate the state of hydrogen in the pyrite type FeO2Hx (x ≤ 1) which is a potential H-bearing phase near the core-mantle boundary. We find that when the pressure increases beyond 73 GPa at room temperature, symmetric hydroxyl bonds are softened and the H+ (or proton) become diffusive within the vicinity of its crystallographic site. Increasing temperature under pressure, the diffusivity of hydrogen is extended beyond individual unit cell to cover the entire solid, and the electrical conductivity soars, indicating a transition to the superionic state which is characterized by freely-moving proton and solid FeO2 lattice. The highly diffusive hydrogen provides fresh transport mechanisms for charge and mass, which dictate the geophysical behaviors of electrical conductivity and magnetism, as well as geochemical processes of redox, hydrogen circulation, and hydrogen isotopic mixing in Earth’s deep mantle

Focused ultrasound-mediated brain genome editing.

Gene editing in the brain has been challenging because of the restricted transport imposed by the blood-brain barrier (BBB). Current approaches mainly rely on local injection to bypass the BBB. However, such administration is highly invasive and not amenable to treating certain delicate regions of the brain. We demonstrate a safe and effective gene editing technique by using focused ultrasound (FUS) to transiently open the BBB for the transport of intravenously delivered CRISPR/Cas9 machinery to the brain

Government is expected to lead the payment of heat-resilient infrastructure

Summary: Urban heat is severe in numerous cities, but the urgency of heat action and support for the development of heat-resilient infrastructure is unclear. To address these research gaps, this study investigated the perceived urgency of developing heat-resilient infrastructure and associated payment issues in eight megacities, in China using a questionnaire survey of 3758 respondents in August 2020. Overall, the respondents thought it was moderately urgent to take actions to address heat-related challenges. The development of mitigation and adaptation infrastructure is urgent. About 86.4% of the 3758 respondents expected the government to be involved in paying for heat-resilient infrastructure, but 41.2% supported cost-sharing among the government, developers, and owners. There were 1299 respondents willing to pay, resulting in an average annual payment of 44.06 RMB in a conservative scenario. This study is important for decision-makers to formulate plans on heat-resilient infrastructure and to release financial strategies for collecting investments and funds

Adaptive Unsupervised-Shadow-Detection Approach for Remote-Sensing Image Based on Multichannel Features

Shadow detection is an essential research topic in the remote-sensing domain, as the presence of shadow causes the loss of ground-object information in real areas. It is hard to define specific threshold values for the identification of shadow areas with the existing unsupervised approaches due to the complexity of remote-sensing scenes. In this study, an adaptive unsupervised-shadow-detection method based on multichannel features is proposed, which can adaptively distinguish shadow in different scenes. First, new multichannel features were designed in the hue, saturation, and intensity color space, and the shadow properties of high hue, high saturation, and low intensity were considered to solve the insufficient feature-extraction problem of shadows. Then, a dynamic local adaptive particle swarm optimization was proposed to calculate the segmentation thresholds for shadows in an adaptive manner. Finally, experiments performed on the Aerial Imagery dataset for Shadow Detection (AISD) demonstrated the superior performance of the proposed approach in comparison with traditional unsupervised shadow-detection and state-of-the-art deep-learning methods. The experimental results show that the proposed approach can detect the shadow areas in remote-sensing images more accurately and efficiently, with the F index being 82.70% on the testing images. Thus, the proposed approach has better application potential in scenarios without a large number of labeled samples

Adaptive Unsupervised-Shadow-Detection Approach for Remote-Sensing Image Based on Multichannel Features

Shadow detection is an essential research topic in the remote-sensing domain, as the presence of shadow causes the loss of ground-object information in real areas. It is hard to define specific threshold values for the identification of shadow areas with the existing unsupervised approaches due to the complexity of remote-sensing scenes. In this study, an adaptive unsupervised-shadow-detection method based on multichannel features is proposed, which can adaptively distinguish shadow in different scenes. First, new multichannel features were designed in the hue, saturation, and intensity color space, and the shadow properties of high hue, high saturation, and low intensity were considered to solve the insufficient feature-extraction problem of shadows. Then, a dynamic local adaptive particle swarm optimization was proposed to calculate the segmentation thresholds for shadows in an adaptive manner. Finally, experiments performed on the Aerial Imagery dataset for Shadow Detection (AISD) demonstrated the superior performance of the proposed approach in comparison with traditional unsupervised shadow-detection and state-of-the-art deep-learning methods. The experimental results show that the proposed approach can detect the shadow areas in remote-sensing images more accurately and efficiently, with the F index being 82.70% on the testing images. Thus, the proposed approach has better application potential in scenarios without a large number of labeled samples