Human Norovirus NTPase Antagonizes Interferon-β Production by Interacting With IkB Kinase ε.

Human norovirus (HuNoV) is the leading cause of epidemic acute gastroenteritis worldwide. Type I interferons (IFN)-α/β are highly potent cytokines that are initially identified for their essential roles in antiviral defense. It was reported that HuNoV infection did not induce IFN-β expression but was controlled in the presence of IFN-β in human intestinal enteroids and a gnotobiotic pig model, suggesting that HuNoV has likely developed evasion countermeasures. In this study, we found that a cDNA clone of GII.4 HuNoV, the predominantly circulating genotype worldwide, inhibits the production of IFN-β and identified the viral NTPase as a key component responsible for such inhibition. HuNoV NTPase not only inhibits the activity of IFN-β promoter but also the mRNA and protein production of IFN-β. Additional studies indicate that NTPase inhibits the phosphorylation and nuclear translocation of interferon-regulatory factor-3 (IRF-3), leading to the suppression of IFN-β promoter activation. Mechanistically, NTPase interacts with IkB kinase ε (IKKε), an important factor for IRF-3 phosphorylation, and such interaction blocks the association of IKKε with unanchored K48-linked polyubiquitin chains, resulting in the inhibition of IKKε phosphorylation. Further studies demonstrated that the 1-179 aa domain of NTPase which interacts with IKKε is critical for the suppression of IFN-β production. Our findings highlight the role of HuNoV NTPase in the inhibition of IFN-β production, providing insights into a novel mechanism underlying how HuNoV evades the host innate immunity

Regulation of Polysaccharide in Wu-Tou Decoction on Intestinal Microflora and Pharmacokinetics of Small Molecular Compounds in AIA Rats

Wu-tou decoction (WTD), a traditional Chinese medicine prescription, is used to treat rheumatoid arthritis (RA). It works by controlling intestinal flora and its metabolites, which in turn modulates the inflammatory response and intestinal barrier function. Small molecular compounds (SM) and polysaccharides (PS) were the primary constituents of WTD extract. In this work, a model of adjuvant-induced arthritis (AIA) in rats was established and treated with WTD, SM, and PS, respectively. 16S rRNA gene sequencing was used to examine the regulatory impact of the various groups on the disturbance of the gut flora induced by RA. Further, since PS cannot be absorbed into the blood, the influence of PS on the absorption and metabolism of SM was studied by examining their pharmacokinetic (PK) parameters of 23 active components in SM by UPLC-MS/MS. WTD was found to be more effective than PS and SM in alleviating arthritis in AIA rats, which may be related to changes in gut flora. The PK properties of 13 active compounds were altered after PS intervene. Based on the findings, PS may be able to manage the disruption of intestinal microbiota, enhance the intestinal environment of model animals, and hence influence SM absorption and metabolism

SparCL: Sparse Continual Learning on the Edge

Existing work in continual learning (CL) focuses on mitigating catastrophic forgetting, i.e., model performance deterioration on past tasks when learning a new task. However, the training efficiency of a CL system is under-investigated, which limits the real-world application of CL systems under resource-limited scenarios. In this work, we propose a novel framework called Sparse Continual Learning(SparCL), which is the first study that leverages sparsity to enable cost-effective continual learning on edge devices. SparCL achieves both training acceleration and accuracy preservation through the synergy of three aspects: weight sparsity, data efficiency, and gradient sparsity. Specifically, we propose task-aware dynamic masking (TDM) to learn a sparse network throughout the entire CL process, dynamic data removal (DDR) to remove less informative training data, and dynamic gradient masking (DGM) to sparsify the gradient updates. Each of them not only improves efficiency, but also further mitigates catastrophic forgetting. SparCL consistently improves the training efficiency of existing state-of-the-art (SOTA) CL methods by at most 23X less training FLOPs, and, surprisingly, further improves the SOTA accuracy by at most 1.7%. SparCL also outperforms competitive baselines obtained from adapting SOTA sparse training methods to the CL setting in both efficiency and accuracy. We also evaluate the effectiveness of SparCL on a real mobile phone, further indicating the practical potential of our method.Comment: Published at NeurIPS 2022 as a conference pape

Untargeted metabolomics analysis in drug-naïve patients with severe obsessive–compulsive disorder

IntroductionObsessive–compulsive disorder (OCD), characterized by the presence of obsessions and/or compulsions, is often difficult to diagnose and treat in routine clinical practice. The candidate circulating biomarkers and primary metabolic pathway alteration of plasma in OCD remain poorly understood.MethodsWe recruited 32 drug-naïve patients with severe OCD and 32 compared healthy controls and applied the untargeted metabolomics approach by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) to assess their circulating metabolic profiles. Both univariate and multivariate analyses were then utilized to filtrate differential metabolites between patients and healthy controls, and weighted Correlation Network Analysis (WGCNA) was utilized to screen out hub metabolites.ResultsA total of 929 metabolites were identified, including 34 differential metabolites and 51 hub metabolites, with an overlap of 13 metabolites. Notably, the following enrichment analyses underlined the importance of unsaturated fatty acids and tryptophan metabolism alterations in OCD. Metabolites of these pathways in plasma appeared to be promising biomarkers, such as Docosapentaenoic acid and 5-Hydroxytryptophan, which may be biomarkers for OCD identification and prediction of sertraline treatment outcome, respectively.ConclusionOur findings revealed alterations in the circulating metabolome and the potential utility of plasma metabolites as promising biomarkers in OCD

Transboundary health impacts of transported global air pollution and international trade

Millions of people die every year from diseases caused by exposure to outdoor air pollution1, 2, 3, 4, 5. Some studies have estimated premature mortality related to local sources of air pollution6, 7, but local air quality can also be affected by atmospheric transport of pollution from distant sources8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18. International trade is contributing to the globalization of emission and pollution as a result of the production of goods (and their associated emissions) in one region for consumption in another region14, 19, 20, 21, 22. The effects of international trade on air pollutant emissions23, air quality14 and health24 have been investigated regionally, but a combined, global assessment of the health impacts related to international trade and the transport of atmospheric air pollution is lacking. Here we combine four global models to estimate premature mortality caused by fine particulate matter (PM2.5) pollution as a result of atmospheric transport and the production and consumption of goods and services in different world regions. We find that, of the 3.45 million premature deaths related to PM2.5 pollution in 2007 worldwide, about 12 per cent (411,100 deaths) were related to air pollutants emitted in a region of the world other than that in which the death occurred, and about 22 per cent (762,400 deaths) were associated with goods and services produced in one region for consumption in another. For example, PM2.5 pollution produced in China in 2007 is linked to more than 64,800 premature deaths in regions other than China, including more than 3,100 premature deaths in western Europe and the USA; on the other hand, consumption in western Europe and the USA is linked to more than 108,600 premature deaths in China. Our results reveal that the transboundary health impacts of PM2.5 pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport

Deconvoluting and Quantifying the Real-time Fluxes and Ionic Currents of Various Species Using In Situ Electrochemical Quartz Crystal Microbalance Measurements

Electrochemical quartz crystal microbalance (EQCM) is a powerful technique to screen the gravimetric response of electrochemical electrodes. In this study, a straightforward mathematical method is proposed for extracting and deconvoluting the real-time fluxes and ionic currents of two species based on the EQCM measurement results. We creatively propose the concept of flux cyclic voltammograms (CVs) and ionic current CVs of various species and apply them to the real-time analyses of molecules/ions dynamics. For proof of concept, Ti3C2Tx MXene, a most studied two-dimensional metal carbide, is investigated as a supercapacitor electrode in a 1M H2SO4 electrolyte. The H2O and H+ flux CV plots are highly symmetrical, indicating reversible inserting/deserting species fluxes. The highest fluxes along with maximum hydration numbers are obtained at the peak current potential. This suggests the significant contribution of double-layer capacitance originates from the insertion of hydrated H+. The H+ CV with the ionic current induced by H+ flux overlaps the real CV, confirming that H+ is the only interactive ion for screening the electrode charge. Lastly, we also validate the proposed strategy using Ti3C2Tx MXene electrode in 1M KCl electrolyte and YP80 porous carbon electrode in 1 M LiCl electrolyte