146 research outputs found
ESG risk exposure: a tale of two tails
No full textThis paper studies the ESG impact to the downside risk of companies in the US market by introducing a novel measure, the ESG risk contribution (Delta CoESGRisk). Delta CoESGRisk is a measurement based on the co-movement between the ESG risk factor and the downside risk. When there is a sudden increase in the ESG risk factor, the downside risk of high-ESG companies is reduced. However, under extreme conditions, the downside risk of high-ESG companies could also be increased, due to the increased company volatility. The ESG impact is positively correlated with the ESG performance and size, and it varies among sectors
Brain Dynamic Information Flow Estimation Based on EEG and Diffusion MRI: A Proof-of-principle Study and Application in Stroke
No full textIn the hemiparetic stroke, functional recovery of paretic limb may occur with the reorganization of neural networks in the brain. Electroencephalography (EEG), with an excellent temporal resolution, can be used to reveal functional changes in the brain following a stroke. This study assessed a novel multimodal brain imaging technique namely Variational Bayesian Multimodal Encephalography (VBMEG), which combines EEG, anatomical MRI and diffusion weighted imaging (DWI), to estimation brain dynamic information flow and its changes following a stroke. EEG data were acquired from individuals suffering from a stroke as well as able-bodied participants while electrical stimuli were delivered sequentially at their index finger in the left and right hand, respectively. The locations of active sources related to this stimulus were precisely identified, resulting in high Variance Accounted For (VAF above 80%). An accurate estimation of dynamic information flow between sources was achieved in this study, showing a high VAF (above 88%) in the cross-validation test. The estimated dynamic information flow was compared between chronic hemiparetic stroke and able-bodied individuals, using matrices lateralization index and activation complexity. The results demonstrate the feasibility of VBMEG method in revealing the changes of information flow in the brain after stroke. This study verified the VBMEG method as an advanced computational approach to track the dynamic information flow in the brain following a stroke. This may lead to the development of a quantitative tool for monitoring functional changes of the cortical neural networks after a unilateral brain injury and therefore facilitate the research into, and the practice of stroke rehabilitation.Mechanical Engineerin
Multiband orthogonal frequency division multiplexing modulation and demodulation for wireless universal serial bus
No full textWireless Universal Serial Bus (W-USB) has been proposed to offer a mechanism in short range and high speed Wireless Personal Area Networks (WPAN). Wireless USB has now been standardized by utilizing the common WiMedia Ultra Wideband (UWB) radio platform to use the services of Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) as the transport mechanism. With regards to the high data rate mode using DCM modulation scheme, different DCM demapping methods resulting in different system performance are presented, which include soft bit demapping, Maximum Likelihood (ML) soft bit demapping and I Log Likelihood Ratio (LLR) demapping. The proposed Channel State Information (CSl) aided scheme coupled with the band hopping information is used as the further technique to improve the DCM demapping performance.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Lianhuaqingwen Exerts Anti-Viral and Anti-Inflammatory Activity Against Novel Coronavirus (SARS-CoV-2)
No full textAuteurs : Li Runfeng, Hou Yunlong, Huang Jicheng, Pan Weiqi , Ma Qinhai, Shi Yongxia , Li Chufang, Zhao Jin, Jia Zhenhua, Jiang Haiming, Zheng Kui, Huang Shuxiang, Dai Jun, Li Xiaobo, Hou Xiaotao, Wang Lin, Zhong Nanshan, Yang Zifeng. Production : Pharmacological Research, Volume 156, June 2020, 104761 Diffusion : ScienceDirect, site web géré par l'éditeur Elsevier. Date : Reçu le 29 février 2020, révisé le 14 mars 2020, accepté le 17 mars 2020, disponible en ligne le 20 mars 2020. ..
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Fixed point dual carrier modulation performance for wireless USB
No full textDual Carrier Modulation (DCM) is currently used
as the higher data rate modulation scheme for Multiband
Orthogonal Frequency Division Multiplexing (MB-OFDM) in the
ECMA-368 defined Ultra-Wideband (UWB) radio platform.
ECMA-368 has been chosen as the physical radio platform for
many systems including Wireless USB (W-USB), Bluetooth 3.0
and Wireless HDMI; hence ECMA-368 is an important issue to
consumer electronics and the user’s experience of these products.
In this paper, Log Likelihood Ratio (LLR) demapping method
is used for the DCM demaper implemented in fixed point model.
Channel State Information (CSI) aided scheme coupled with the
band hopping information is used as the further technique to
improve the DCM demapping performance. The receiver
performance for the fixed point DCM is simulated in realistic
multi-path environments
Redox proteomics combined with lipidomics and metabolomics to elucidate the mechanism of ferroptosis in colorectal cancer using human colorectal carcinoma HCT-116 cells
No full textAbstract Background: Colorectal cancer (CRC) ranks as the third leading cause of cancer-related death worldwide, and the second leading cause of cancer-related deaths in New Zealand. It is frequently driven by mutations in key oncogenes and tumor suppressor genes. Current treatment modalities for CRC, offer only limited efficacy, as many chemotherapeutic agents fail to elicit consistent responses across patient populations. This clinical challenge underscores the urgent need for novel therapeutic strategies. Ferroptosis, first described in 2012, is an iron-dependent form of regulated cell death characterized by the accumulation of lipid peroxides and reactive oxygen species (ROS). Increasing evidence has demonstrated that ferroptosis selectively targets vulnerabilities in cancer cells, particularly in iron metabolism and oxidative stress pathways, making it a promising therapeutic avenue for CRC. Furthermore, modulation of ferroptosis pathways has been shown to enhance the anti-tumor efficacy of conventional chemotherapeutics. A better understanding of the initiation, propagation, and resistance mechanisms of ferroptosis in CRC is therefore critical for the development of ferroptosis-based therapeutic interventions. During ferroptosis, cysteine thiol groups serve as direct targets of ROS and act as reversible “redox switches” through oxidative modifications such as disulfide bond formation or thiol oxidation. These modifications regulate key physiological processes, including metabolic reprogramming, oxidative stress responses, and cell survival. The goal of the research is to identify novel redox-regulated proteins, lipid species, and metabolites associated with ferroptosis, generate new insights into the molecular mechanisms of ferroptosis in CRC, and ultimately contribute to the identification of potential biomarkers and therapeutic targets for CRC treatment. Methods: In this study, the human colorectal carcinoma cell line HCT-116 was used as the experimental model. Ferroptosis was induced by treatment with ferric ammonium citrate (FAC), and phenotypic changes were characterized through a combination of morphological observation under a microscope, cell counting using hemocytometer, CCK-8 metabolic activity assay, and ROS assay.To investigate the oxidative modification of cysteine thiol groups of proteins extracted from the studied cells, we employed a quantitative proteomics approach. We employed an isobaric labeling strategy using the iodoTMT6plex reagent to selectively label reversibly oxidized thiols on cysteine residues. An anti-TMT resin-based enrichment step was then applied to enrich iodoTMT-labeled peptides and reduce interference from non-target peptides during liquid chromatography tanden mass spectrometry (LC-MS/MS) analysis. Protein and peptide identification and quantification were performed using LC-MS/MS and Proteome Discoverer software, enabling comprehensive analysis of redox modifications at the peptide and protein levels.Differential expression analysis was conducted using the MSstatsTMT package to identify proteins exhibiting significant redox changes. These proteins were further subjected to pathway and network analysis using STRING (for protein–protein interaction (PPI) and Gene Ontology (GO) enrichment) and WebGestalt (for KEGG and GSEA pathway enrichment).Lipidomic and metabolomic analyses were also performed to explore ferroptosis-related metabolic alterations. LipidSearch was used for lipid identification and quantification, followed by statistical analysis in MetaboAnalyst. For metabolites, Compound Discoverer was used for identification and differential analysis of metabolites, with manual curation to improve accuracy. Pathway enrichment was then performed using WebGestalt. Results: Redox proteomics identified 45 redox-modified proteins associated with 79 oxidized cysteine sites, of which 5 oxidation sites were newly discovered in this study. Furthermore, two newly discovered redox-regulated proteins, PPP1R9B and S100A16, were identified. Among these 45 proteins, MDH2 and PRDX3, have been both previously reported to be associated with ferroptosis. Pathway enrichment analysis revealed a high involvement of endoplasmic reticulum (ER)-related processes, such as protein folding and ER lumen organization. PPI network analysis further identified 15 highly interconnected hub proteins, including CALR, HSPA9, PDIA3, HSP90B1, and HSPD1. Most of these ER-associated may serve as key mediators of redox regulation during ferroptosis. Lipidomic profiling identified 67 significantly altered lipid species, among which CerP(d15:0/2:0), PE(16:0e/8:0), PIP3(37:3/13:1), PE(8:0p/10:0), PIP2(16:1/21:6), PIP2(37:0/19:0), and PIP3(37:1/13:1) showed potential as ferroptosis-related biomarkers. Metabolomic analysis identified 27 dysregulated metabolites, including L-arginine, spermine, spermidine, and N1-acetylspermidine, which were significantly changed under ion-induced oxidative stress.Integrated pathway analysis of lipidomic and metabolomic datasets showed strong convergence on L-arginine and polyamine metabolism pathways. Additionally, HIF-1 signaling was implicated as a potential regulatory axis in ferroptosis within CRC cells. In summary, this study provides a comprehensive multi-omics landscape of iron-induced ferroptosis in HCT-116 cells, integrating redox proteomic, lipidomic, and metabolomic underlying ferroptosis initiation and execution, and to uncover novel ferroptosis-related molecular candidates such as CALR, CerP(d15:0/2:0), and ether phospholipids.</p
A Data-driven System-level Health State Prognostics Method for Large-scale Spacecraft Systems
No full textA novel approach for modeling neural responses to joint perturbations using the NARMAX method and a hierarchical neural network
No full textThe human nervous system is an ensemble of connected neuronal networks. Modeling and system identification of the human nervous system helps us understand how the brain processes sensory input and controls responses at the systems level. This study aims to propose an advanced approach based on a hierarchical neural network and non-linear system identification method to model neural activity in the nervous system in response to an external somatosensory input. The proposed approach incorporates basic concepts of Non-linear AutoRegressive Moving Average Model with eXogenous input (NARMAX) and neural network to acknowledge non-linear closed-loop neural interactions. Different from the commonly used polynomial NARMAX method, the proposed approach replaced the polynomial non-linear terms with a hierarchical neural network. The hierarchical neural network is built based on known neuroanatomical connections and corresponding transmission delays in neural pathways. The proposed method is applied to an experimental dataset, where cortical activities from ten young able-bodied individuals are extracted from electroencephalographic signals while applying mechanical perturbations to their wrist joint. The results yielded by the proposed method were compared with those obtained by the polynomial NARMAX and Volterra methods, evaluated by the variance accounted for (VAF). Both the proposed and polynomial NARMAX methods yielded much better modeling results than the Volterra model. Furthermore, the proposed method modeled cortical responded with a mean VAF of 69.35% for a three-step ahead prediction, which is significantly better than the VAF from a polynomial NARMAX model (mean VAF 47.09%). This study provides a novel approach for precise modeling of cortical responses to sensory input. The results indicate that the incorporation of knowledge of neuroanatomical connections in building a realistic model greatly improves the performance of system identification of the human nervous system.Biomechatronics & Human-Machine Contro
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