Optimal Schedules in Multitask Motor Learning

Although scheduling multiple tasks in motor learning to maximize long-term retention of performance is of great practical importance in sports training and motor rehabilitation after brain injury, it is unclear how to do so. We propose here a novel theoretical approach that uses optimal control theory and computational models of motor adaptation to determine schedules that maximize long-term retention predictively. Using Pontryagin’s maximum principle, we derived a control law that determines the trial-by-trial task choice that maximizes overall delayed retention for all tasks, as predicted by the state-space model. Simulations of a single session of adaptation with two tasks show that when task interference is high, there exists a threshold in relative task difficulty below which the alternating schedule is optimal. Only for large differences in task difficulties do optimal schedules assign more trials to the harder task. However, over the parameter range tested, alternating schedules yield long-term retention performance that is only slightly inferior to performance given by the true optimal schedules. Our results thus predict that in a large number of learning situations wherein tasks interfere, intermixing tasks with an equal number of trials is an effective strategy in enhancing long-term retention

Exchange Bias Effect in Au-Fe3O4 Nanocomposites

We report exchange bias (EB) effect in the Au-Fe3O4 composite nanoparticle system, where one or more Fe3O4 nanoparticles are attached to an Au seed particle forming dimer and cluster morphologies, with the clusters showing much stronger EB in comparison with the dimers. The EB effect develops due to the presence of stress in the Au-Fe3O4 interface which leads to the generation of highly disordered, anisotropic surface spins in the Fe3O4 particle. The EB effect is lost with the removal of the interfacial stress. Our atomistic Monte-Carlo studies are in excellent agreement with the experimental results. These results show a new path towards tuning EB in nanostructures, namely controllably creating interfacial stress, and open up the possibility of tuning the anisotropic properties of biocompatible nanoparticles via a controllable exchange coupling mechanism.Comment: 28 pages, 6 figures, submitted to Nanotechnolog

Complete Genome Sequences of Three Historically Important, Spatiotemporally Distinct, and Genetically Divergent Strains of Zika Virus: MR-766, P6-740, and PRVABC-59

Here, we report the 10,807-nucleotide-long consensus RNA genome sequences of three spatiotemporally distinct and genetically divergent Zika virus strains, with the functionality of their genomic sequences substantiated by reverse genetics: MR-766 (African lineage, Uganda, 1947), P6-740 (Asian lineage, Malaysia, 1966), and PRVABC-59 (Asian lineage-derived American strain, Puerto Rico, 2015)

Hepatic Autophagy Deficiency Compromises FXR Functionality and Causes Cholestatic Injury

Autophagy is important for hepatic homeostasis, nutrient regeneration and organelle quality control. We investigated the mechanisms by which liver injury occurred in the absence of autophagy function. We found that mice deficient in autophagy due to the lack of Atg7 or Atg5, key autophagy‐related genes, manifested intracellular cholestasis with increased levels of serum bile acids, a higher ratio of TMCA/TCA in the bile, increased hepatic bile acid load, abnormal bile canaliculi and altered expression of hepatic transporters. In determining the underlying mechanism, we found that autophagy sustained and promoted the basal and upregulated expression of Fxr in the fed and starved conditions, respectively. Consequently, expression of Fxr and its downstream genes, particularly Bsep, and the binding of FXR to the promoter regions of these genes, were suppressed in autophagy‐deficient livers. In addition, co‐deletion of Nrf2 in autophagy deficiency status reversed the FXR suppression. Furthermore, the cholestatic injury of autophagy‐deficient livers was reversed by enhancement of FXR activity or expression, or by Nrf2 deletion

Predictive value of baseline serum carbohydrate antigen 19-9 level on treatment effect of neoadjuvant chemoradiotherapy in patients with resectable and borderline resectable pancreatic cancer in two randomized trials

BACKGROUND: Guidelines suggest that the serum carbohydrate antigen (CA19-9) level should be used when deciding on neoadjuvant treatment in patients with resectable and borderline resectable pancreatic ductal adenocarcinoma (hereafter referred to as pancreatic cancer). In patients with resectable pancreatic cancer, neoadjuvant therapy is advised when the CA19-9 level is 'markedly elevated'. This study investigated the impact of baseline CA19-9 concentration on the treatment effect of neoadjuvant chemoradiotherapy (CRT) in patients with resectable and borderline resectable pancreatic cancers.METHODS: In this post hoc analysis, data were obtained from two RCTs that compared neoadjuvant CRT with upfront surgery in patients with resectable and borderline resectable pancreatic cancers. The effect of neoadjuvant treatment on overall survival was compared between patients with a serum CA19-9 level above or below 500 units/ml using the interaction test.RESULTS: Of 296 patients, 179 were eligible for analysis, 90 in the neoadjuvant CRT group and 89 in the upfront surgery group. Neoadjuvant CRT was associated with superior overall survival (HR 0.67, 95 per cent c.i. 0.48 to 0.94; P = 0.019). Among 127 patients (70, 9 per cent) with a low CA19-9 level, median overall survival was 23.5 months with neoadjuvant CRT and 16.3 months with upfront surgery (HR 0.63, 0.42 to 0.93). For 52 patients (29 per cent) with a high CA19-9 level, median overall survival was 15.5 months with neoadjuvant CRT and 12.9 months with upfront surgery (HR 0.82, 0.45 to 1.49). The interaction test for CA19-9 level exceeding 500 units/ml on the treatment effect of neoadjuvant CRT was not significant (P = 0.501).CONCLUSION: Baseline serum CA19-9 level defined as either high or low has prognostic value, but was not associated with the treatment effect of neoadjuvant CRT in patients with resectable and borderline resectable pancreatic cancers, in contrast with current guideline advice.</p

Transcriptome-based repurposing of apigenin as a potential anti-fibrotic agent targeting hepatic stellate cells

We have used a computational approach to identify anti-fibrotic therapies by querying a transcriptome. A transcriptome signature of activated hepatic stellate cells (HSCs), the primary collagen-secreting cell in liver, and queried against a transcriptomic database that quantifies changes in gene expression in response to 1,309 FDA-approved drugs and bioactives (CMap). The flavonoid apigenin was among 9 top-ranked compounds predicted to have anti-fibrotic activity; indeed, apigenin dose-dependently reduced collagen I in the human HSC line, TWNT-4. To identify proteins mediating apigenin’s effect, we next overlapped a 122-gene signature unique to HSCs with a list of 160 genes encoding proteins that are known to interact with apigenin, which identified C1QTNF2, encoding for Complement C1q tumor necrosis factor-related protein 2, a secreted adipocytokine with metabolic effects in liver. To validate its disease relevance, C1QTNF2 expression is reduced during hepatic stellate cell activation in culture and in a mouse model of alcoholic liver injury in vivo, and its expression correlates with better clinical outcomes in patients with hepatitis C cirrhosis (n = 216), suggesting it may have a protective role in cirrhosis progression.These findings reinforce the value of computational approaches to drug discovery for hepatic fibrosis, and identify C1QTNF2 as a potential mediator of apigenin’s anti-fibrotic activity

Molecular characterization of hepatocellular carcinoma in patients with nonalcoholic steatohepatitis

Background and aims: Non-alcoholic steatohepatitis (NASH)-related hepatocellular carcinoma (HCC) is increasing globally, but its molecular features are not well defined. We aimed to identify unique molecular traits characterising NASH-HCC compared to other HCC aetiologies. Methods: We collected 80 NASH-HCC and 125 NASH samples from 5 institutions. Expression array (n = 53 NASH-HCC; n = 74 NASH) and whole exome sequencing (n = 52 NASH-HCC) data were compared to HCCs of other aetiologies (n = 184). Three NASH-HCC mouse models were analysed by RNA-seq/expression-array (n = 20). Activin A receptor type 2A (ACVR2A) was silenced in HCC cells and proliferation assessed by colorimetric and colony formation assays. Results: Mutational profiling of NASH-HCC tumours revealed TERT promoter (56%), CTNNB1 (28%), TP53 (18%) and ACVR2A (10%) as the most frequently mutated genes. ACVR2A mutation rates were higher in NASH-HCC than in other HCC aetiologies (10% vs. 3%, p <0.05). In vitro, ACVR2A silencing prompted a significant increase in cell proliferation in HCC cells. We identified a novel mutational signature (MutSig-NASH-HCC) significantly associated with NASH-HCC (16% vs. 2% in viral/alcohol-HCC, p = 0.03). Tumour mutational burden was higher in non-cirrhotic than in cirrhotic NASH-HCCs (1.45 vs. 0.94 mutations/megabase; p <0.0017). Compared to other aetiologies of HCC, NASH-HCCs were enriched in bile and fatty acid signalling, oxidative stress and inflammation, and presented a higher fraction of Wnt/TGF-β proliferation subclass tumours (42% vs. 26%, p = 0.01) and a lower prevalence of the CTNNB1 subclass. Compared to other aetiologies, NASH-HCC showed a significantly higher prevalence of an immunosuppressive cancer field. In 3 murine models of NASH-HCC, key features of human NASH-HCC were preserved. Conclusions: NASH-HCCs display unique molecular features including higher rates of ACVR2A mutations and the presence of a newly identified mutational signature. Lay summary: The prevalence of hepatocellular carcinoma (HCC) associated with non-alcoholic steatohepatitis (NASH) is increasing globally, but its molecular traits are not well characterised. In this study, we uncovered higher rates of ACVR2A mutations (10%) - a potential tumour suppressor - and the presence of a novel mutational signature that characterises NASH-related HCC

Phosphorescent Sensor for Robust Quantification of Copper(II) Ion

A phosphorescent sensor based on a multichromophoric iridium(III) complex was synthesized and characterized. The construct exhibits concomitant changes in its phosphorescence intensity ratio and phosphorescence lifetime in response to copper(II) ion. The sensor, which is reversible and selective, is able to quantify copper(II) ions in aqueous media, and it detects intracellular copper ratiometrically.National Institute of General Medical Sciences (U.S.) ((Grant GM065519)Ewha Woman's University (Korea) (RP-Grant 2009

The future sea-level contribution of the Greenland ice sheet: A multi-model ensemble study of ISMIP6

The Greenland ice sheet is one of the largest contributors to global mean sea-level rise today and is expected to continue to lose mass as the Arctic continues to warm. The two predominant mass loss mechanisms are increased surface meltwater run-off and mass loss associated with the retreat of marine-terminating outlet glaciers. In this paper we use a large ensemble of Greenland ice sheet models forced by output from a representative subset of the Coupled Model Intercomparison Project (CMIP5) global climate models to project ice sheet changes and sea-level rise contributions over the 21st century. The simulations are part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6).We estimate the sea-level contribution together with uncertainties due to future climate forcing, ice sheet model formulations and ocean forcing for the two greenhouse gas concentration scenarios RCP8.5 and RCP2.6. The results indicate that the Greenland ice sheet will continue to lose mass in both scenarios until 2100, with contributions of 90-50 and 32-17mm to sea-level rise for RCP8.5 and RCP2.6, respectively. The largest mass loss is expected from the south-west of Greenland, which is governed by surface mass balance changes, continuing what is already observed today. Because the contributions are calculated against an unforced control experiment, these numbers do not include any committed mass loss, i.e. mass loss that would occur over the coming century if the climate forcing remained constant. Under RCP8.5 forcing, ice sheet model uncertainty explains an ensemble spread of 40 mm, while climate model uncertainty and ocean forcing uncertainty account for a spread of 36 and 19 mm, respectively. Apart from those formally derived uncertainty ranges, the largest gap in our knowledge is about the physical understanding and implementation of the calving process, i.e. the interaction of the ice sheet with the ocean. © Author(s) 2020

The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6

The Greenland ice sheet is one of the largest contributors to global mean sea-level rise today and is expected to continue to lose mass as the Arctic continues to warm. The two predominant mass loss mechanisms are increased surface meltwater run-off and mass loss associated with the retreat of marine-terminating outlet glaciers. In this paper we use a large ensemble of Greenland ice sheet models forced by output from a representative subset of the Coupled Model Intercomparison Project (CMIP5) global climate models to project ice sheet changes and sea-level rise contributions over the 21st century. The simulations are part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We estimate the sea-level contribution together with uncertainties due to future climate forcing, ice sheet model formulations and ocean forcing for the two greenhouse gas concentration scenarios RCP8.5 and RCP2.6. The results indicate that the Greenland ice sheet will continue to lose mass in both scenarios until 2100, with contributions of 90±50 and 32±17 mm to sea-level rise for RCP8.5 and RCP2.6, respectively. The largest mass loss is expected from the south-west of Greenland, which is governed by surface mass balance changes, continuing what is already observed today. Because the contributions are calculated against an unforced control experiment, these numbers do not include any committed mass loss, i.e. mass loss that would occur over the coming century if the climate forcing remained constant. Under RCP8.5 forcing, ice sheet model uncertainty explains an ensemble spread of 40 mm, while climate model uncertainty and ocean forcing uncertainty account for a spread of 36 and 19 mm, respectively. Apart from those formally derived uncertainty ranges, the largest gap in our knowledge is about the physical understanding and implementation of the calving process, i.e. the interaction of the ice sheet with the ocean