bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antisense therapy in a new rat model of Alexander disease reverses GFAP pathology, white matter deficits, and motor impairment
Authors: Hagemann Tracy L. , Powers Berit , Lin Ni-Hsuan , Mohamed Ahmed F. , Dague Katerina L. , Hannah Seth C. , Mazur Curt , Rigo Frank , Feany Mel B. , Perng Ming-Der , Berman Robert F. , Messing Albee 
Published: February 2021

AbstractAlexander disease (AxD) is a devastating leukodystrophy caused by gain of function mutations inGFAP, and the only available treatments are supportive. Recent advances in antisense oligonucleotide (ASO) therapy have demonstrated that transcript targeting can be a successful strategy for human neurodegenerative diseases amenable to this approach. We have previously used mouse models of AxD to show thatGfap-targeted ASO suppresses protein accumulation and reverses pathology; however, the mice have a mild phenotype with no apparent leukodystrophy or overt clinical features and are therefore limited for assessing functional outcomes. In this report we introduce a new rat model of AxD that exhibits hallmark pathology with GFAP aggregation in the form of Rosenthal fibers, widespread astrogliosis, and white matter deficits. These animals develop normally during the first postnatal weeks but fail to thrive after weaning and develop severe motor deficits as they mature, with approximately 15 % dying of unknown cause between 6 to 12 weeks of age. In this model, a single treatment withGfap-targeted ASO provides long lasting suppression, reverses GFAP pathology, and depending on age of treatment, prevents or mitigates white matter deficits and motor impairment. This is the first report of an animal model of AxD with myelin pathology and motor impairment, recapitulating prominent features of the human disease. We use this model to show that ASO therapy has the potential to not only prevent but also reverse many aspects of disease.
Rest-fMRI Based Comparison Study between Autism Spectrum Disorder and Typically Control Using Graph Frequency Bands
Authors: Jafadideh Alireza Talesh , Mohammadzadeh Asl Babak 
Published: February 2021

AbstractGraph signal processing is a subset of signal processing enabling the analysis of functional magnetic resonance imaging (fMRI) data in brain topological domain. One of the most important and highly interested tool of GSP is graph Fourier transform (GFT) by which brain signals can be analyzed in different graph frequency bands. In this paper, the resting-state fMRI (rfMRI) data is analyzed using GFT tool in order to discover new knowledge about the autism spectrum disorder (ASD) and find features discriminating between ASD and typically control (TC) subjects. For ASD group, the signal concentration in both low and high frequency bands is decreased by increasing the age in most of the brain well-known networks. The ASD in comparison to TC shows less intention for changing the signal concentration level when the level is very low or very high. In graph low frequency band, increasing the age is along with increasing the segregation and integration of brain ROIs respectively for ASD and TC. Also, in this band, the brain ROIs integration of ASD is more than TC. By increasing the age, the auditory network of ASD subjects shows increasing segregation and integration in graph low and high frequency bands, respectively. The reduced segregation of default mode network in ASD is happened in graph middle and higher frequency bands. The functional connectivity analysis between low and high frequency signals shows that some of the high frequency ROIs have connections with all low frequency ROIs so that the most of these connections are dramatically and significantly different between ASD and TC. By analyzing the local vertex frequency spectrum (LVFS) of ASD and TC at different states, it is seen these groups show contradictory behaviors with respect to each other in brain default mode network in two states. The results of different scenarios at different graph frequency bands demonstrate that using functional and structural data together can provide powerful tool for recognizing the ASD or even other brain disorders.
EXPERT: Transfer Learning-enabled context-aware microbial source tracking
Authors: Chong Hui , Yu Qingyang , Zha Yuguo , Xiong Guangzhou , Wang Nan , Huang Xinhe , Huang Shijuan , Sun Chuqing , Wu Sicheng , Chen Wei-Hua , Coelho Luis Pedro , Ning Kang 
Published: February 2021

AbstractMicrobial source tracking quantifies the potential origin of microbial communities, facilitates better understanding of how the taxonomic structure and community functions were formed and maintained. However, previous methods involve a tradeoff between speed and accuracy, and have encountered difficulty in source tracking under many context-dependent settings. Here, we present EXPERT for context-aware microbial source tracking, in which we adopted a Transfer Learning approach to profoundly elevate and expand the applicability of source tracking, enabling biologically informed novel microbial knowledge discovery. We demonstrate that EXPERT can predict microbial sources with performance superior to other methods in efficiency and accuracy. More importantly, we demonstrate EXPERT’s context-aware ability on several applications, including tracking the progression of infant gut microbiome development and monitoring the changes of gut microbiome for colorectal cancer patients. Broadly, transfer learning enables accurate and context-aware microbial source tracking and has the potential for novel microbial knowledge discovery.
linc2function: A deep learning model to identify and assign function to long noncoding RNA (lncRNA)
Authors: Ramakrishnaiah Yashpal , Kuhlmann Levin , Tyagi Sonika 
Published: February 2021

AbstractMotivationLncRNAs are much more versatile and are involved in many regulatory roles inside the cell than previously believed. Existing databases lack consistencies in lncRNA annotations, and the functionality of over 95% of the known lncRNAs are yet to be established. LncRNA transcript identification involves discriminating them from their coding counterparts, which can be done with traditional experimental approaches, or viain silicomethods. The later approach employs various computational algorithms, including machine learning classifiers to predict the lncRNA forming potential of a given transcript. Such approaches provide an economical and faster alternative to the experimental methods. Currentin silicomethods mainly use primary-sequence based features to build predictive models limiting their accuracy and robustness. Moreover, many of these tools make use of reference genome based features, in consequence making them unsuitable for non-model species. Hence, there is a need to comprehensively evaluate the efficacy of different predictive features to build computational models. Additionally, effective models will have to provide maximum prediction performance using the least number of features in a species-agnostic manner.It is popularly known in the protein world that “structure is function”. This also applies to lncRNAs as their functional mechanisms are similar to those of proteins. Generally, lncRNA function by structurally binding to its target proteins or nucleic acid forming complexes. The secondary structures of the lncRNAs are modular providing interaction sites for their interactome made of DNA, RNA, and proteins. Through these interactions, they epigenetically regulate cellular biology, thereby forming a layer of genomic programming on top of the coding genes. We demonstrate that in addition to using transcript sequence, we can provide comprehensive functional annotation by collating their interactome and secondary structure information.ResultsHere, we evaluated an exhaustive list of sequence-based, secondary-structure, interactome, and physicochemical features for their ability to predict the lncRNA potential of a transcript. Based on our analysis, we built different machine learning models using optimum feature-set. We found our model to be on par or exceeding the execution of the state-of-the-art methods with AUC values of over 0.9 for a diverse collection of species tested. Finally, we built a pipeline calledlinc2functionthat provides the information necessary to functionally annotate a lncRNA conveniently in a single window.AvailabilityThe source code is accessible use under MIT license in standalone mode, and as a webserver (https://bioinformaticslab.erc.monash.edu/linc2function).
Defensive freezing and its relation to approach-avoidance decision-making under threat
Authors: Klaassen Felix H. , Held Leslie , Figner Bernd , O’Reilly Jill X. , Klumpers Floris , de Voogd Lycia D. , Roelofs Karin 
Published: February 2021

AbstractSuccessful responding to acutely threatening situations requires adequate approach-avoidance decisions. However, it is unclear how threat-induced states-like freezing-related bradycardia-impact the weighing of the potential outcomes of such value-based decisions. Insight into the underlying computations is essential, not only to improve our models of decision-making but also to improve interventions for maladaptive decisions, for instance in anxiety patients and first-responders who frequently have to make decisions under acute threat. Forty-two participants made passive and active approach-avoidance decisions under threat-of-shock when confronted with mixed outcome-prospects (i.e., varying money and shock amounts). Choice behavior was best predicted by a model including individual action-tendencies and bradycardia, beyond the subjective value of the outcome. Moreover, threat-related bradycardia interacted with subjective value, depending on the action-context (i.e., passive vs. active). Specifically, in action-contexts incongruent with participants’ intrinsic action-tendencies, strong freezers showed diminished effects of subjective value on choice. These findings illustrate the relevance of testing approach-avoidance decisions in relatively ecologically valid conditions of acute and primarily reinforced threat. These mechanistic insights into approach-avoidance conflict-resolution may inspire biofeedback-related techniques to optimize decision-making under threat. Critically, the findings demonstrate the relevance of incorporatinginternalpsychophysiological states andexternalaction-contexts into models of approach-avoidance decision-making.
Chemical defense and tonic immobility in early life stages of the Harlequin cabbage bug,Murgantia histrionica(Heteroptera: Pentatomidae)
Authors: Guerra-Grenier Eric , Liu Rui , Arnason John T. , Sherratt Thomas N. 
Published: February 2021

AbstractAntipredation strategies are important for the survival and fitness of animals, especially in more vulnerable life stages. In insects, eggs and early juvenile stages are often either immobile or unable to rapidly flee and hide when facing predators. Understanding what alternative antipredation strategies they use, but also how those change over development time, is required to fully appreciate how species have adapted to biotic threats.Murgantia histrionicais a stink bug, conspicuously colored from egg to adult, known to sequester defensive glucosinolates from its cruciferous hosts as adults. We sought to assess whether this chemical defense is also present in its eggs and early nymphal instars and quantified how it fluctuates among life stages. In parallel, we looked at an alternative antipredation strategy, described for the first time in this species: tonic immobility. Our results show that the eggs are significantly more chemically defended than the first two mobile life stages, but not than the third instar. Tonic immobility is also favored by hatchlings, but less so by subsequent instars. We argue the case that over development time, tonic immobility is a useful defensive strategy until adequate chemical protection is achieved over an extended feeding period.
Gypenosides modulate NCX calcium flux, insulin secretion and cytoprotection in BRIN-BD11 pancreatic β-cells
Authors: Patibandla Chinmai , Shu Xinhua , Shaw Angus M , Dolan Sharron , Patterson Steven 
Published: February 2021

AbstractGypenosides are saponins extracted from the plantGynostemma pentaphyllum, suggested to have antidiabetic and anti-obesity potential. However, its mechanism of action is not fully understood. The present study aimed to investigate the cytoprotective and insulin stimulatory effects of gypenosides using the rat BRIN-BD11 β-cell line. Gypenosides provided a significant cytoprotective effect against palmitate-, peroxide- and cytokine-induced cytotoxicity, with upregulation of antioxidant genesNrf2,Cat,Sod1,andGpx1. Acutely, gypenosides enhanced intracellular calcium ([Ca2+]i) and insulin secretion in a dose-dependent manner. The presence of the sodium/calcium exchanger (NCX) reverse mode inhibitor SN-6 blocked the gypenosides mediated increase in [Ca2+]Ibut not the insulin secretion. These findings indicate that gypenosides may enhance [Ca2+]iby activating the reverse mode of NCX channels and a possible calcium-independent mechanism involved in their insulin secretion. Gypenosides also upregulate the antioxidant gene expression and protect against oxidative stress and lipotoxicity, providing the rationale for their observed antidiabetic actions.
Natural IgA andTNFRSF13Bpolymorphism: a double edged sword fueling balancing selection
Authors: Platt Jeffrey L. , de Mattos Barbosa Mayara Garcia , Huynh Daniel , Lefferts Adam R. , Katta Juhi , Kharas Cyra , Freddolino Peter , Bassis Christine M. , Wobus Christiane , Geha Raif , Bram Richard , Nunez Gabriel , Kamada Nobuhiko , Cascalho Marilia 
Published: February 2021

AbstractTNFRSF13Bencodes the “transmembrane-activator and CAML-interactor” (TACI) receptor, which drives plasma cell differentiation. AlthoughTNFRSF13Bsupports host defense, dominant-negativeTNFRSF13Balleles are common in humans and other species and only rarely associate with disease. We reasoned the high frequency of disruptiveTNFRSF13Balleles reflects balancing selection, the loss of function conferring advantage in some settings. Testing that concept, we asked whether and how a common human dominant negative variant, TNFRSF13B A181E, imparts resistance to enteric pathogens. Mice engineered to express mono-allelic or bi-allelic A144E variants oftnrsf13B, corresponding to A181E exhibited striking resistance to pathogenicity and transmission ofC. rodentium, a murine pathogen that models enterohemorrhagicE. coli, and resistance was principally owed to deficiency of natural IgA in the intestine. In wild type mice with gut IgA and in mutant mice fed IgA, binding of Ig induces expression ofLEEencoded virulence genes, which confer pathogenicity and transmission. C. rodentiumand probably some other enteric organisms thus appropriated binding of otherwise protective antibodies to signal induction of the virulence program and the high prevalence ofTNFRSF13Bdominant negative variants thus reflects balancing selection.
Quantitative analysis and genome-scale modeling of human CD4+T-cell differentiation reveals subset-specific regulation of glycosphingolipid pathways
Authors: Sen Partho , Andrabi Syed Bilal Ahmad , Buchacher Tanja , Khan Mohd Moin , Ullah Ubaid , Lindeman Tuomas , Amaral Marina Alves , Hinkkanen Victoria , Kemppainen Esko , Dickens Alex M , Rasool Omid , Hyötyläinen Tuulia , Lahesmaa Riitta , Orešič Matej 
Published: February 2021

ABSTRACTT-cells are sentinels of adaptive cell-mediated immune responses. T-cell activation, proliferation and differentiation involves metabolic reprogramming involving the interplay of genes, proteins and metabolites. Here, we aim to understand the metabolic pathways involved in the activation and functional differentiation of human CD4+T-cell subsets (Th1, Th2, Th17 and iTregs). We combined genome-scale metabolic modeling, gene expression data, targeted and non-targeted lipidomics experiments, together within vitrogene knockdown experiments and showed that human CD4+T-cells undergo specific metabolic changes during activation and functional differentiation. In addition, we identified and confirmed the importance of ceramide and glycosphingolipid synthesis pathways in Th17 differentiation and effector functions. Finally, throughin vitrogene knockdown experiments, we substantiated the requirement of serine palmitoyl transferase (SPT), ade novosphingolipid pathway in the expression of proinflammatory cytokine (IL17A and IL17F) by Th17 cells. Our findings may provide a comprehensive resource for identifying CD4+T-cell-specific targets for their selective manipulation under disease conditions, particularly, diseases characterized by an imbalance of Treg / Th17 cells. Our data also suggest a role for elevated levels of ceramides in conditions comorbid with these diseases,e.g., obesity and insulin resistance.
Moving outside the lab: The viability of conducting sensorimotor learning studies online
Authors: Tsay Jonathan S. , Lee Alan S. , Ivry Richard B. , Avraham Guy 
Published: February 2021

AbstractCollecting data online via crowdsourcing platforms has proven to be a very efficient way to recruit a large and diverse sample. Studies of motor learning, however, have been largely confined to the lab due to the need for special equipment to record movement kinematics and, as such, are typically only accessible to specific participants (e.g., college students). As a first foray to make motor learning studies accessible to a larger and more diverse audience, we developed an online, web-based platform (OnPoint) to collect kinematic data, serving as a template for researchers to create their own online sensorimotor control and learning experiments. As a proof-of-concept, we asked if fundamental motor learning phenomena discovered in the lab could be replicated online. In a series of three experiments, we observed a close correspondence between the results obtained online with those previously reported from research conducted in the laboratory. This web-based platform paired with online crowdsourcing can serve as a powerful new method for the study of motor control and learning.
In silicoassessment of missense point mutations on human cathelicidin LL-37
Authors: Porto William F. , Alencar Sergio A. 
Published: February 2021

AbstractCathelicidin antimicrobial peptides are a diverse family of cationic amphipathic peptides with multiple activities. In humans, cathelicidin LL-37 is one of the main host defense peptides with a remarkable medical and biotechnological potential. Deregulation of LL-37 expression has been associated with inflammatory diseases. However the effects of point mutations driven by single nucleotide polymorphisms (SNPs) on LL-37 are unknown. Here we applied an array of computational tools to investigate the effects of such mutations on LL-37 structure and activity. Due to the fact that, on cathelicidins, the prodomain is more conserved than the mature peptide, the SNP effect predictions were biased and, overall, resulted in neutral effects; and due to the slight changes in physicochemical properties, the antimicrobial predictions indicated the maintenance of such activity. Nonetheless, R07P, R07W, R29Q, R29W mutations reduced the peptide net charge, which in turn could result in less active LL-37 variants. Molecular dynamics data indicated that R07Q and N30Y mutations altered the LL-37 structure, leading to potential deleterious effects. In addition, the helix dipole is altered in G03A, R07P, R07W and L31P mutations, which could also alter the antimicrobial activity. Our results indicated that despite the mutations did not alter the residues from LL-37 active core, they could influence the antimicrobial activity and consequently, could be involved in inflammatory diseases.
An artificial self-assembling nanocompartment for organising metabolic pathways in yeast
Authors: Cheah Li Chen , Stark Terra , Adamson Lachlan S. R. , Abidin Rufika S. , Lau Yu Heng , Sainsbury Frank , Vickers Claudia E. 
Published: February 2021

ABSTRACTMetabolic pathways are commonly organised by sequestration into discrete cellular compartments. Compartments prevent unfavourable interactions with other pathways and provide local environments conducive to the activity of encapsulated enzymes. Such compartments are also useful synthetic biology tools for examining enzyme/pathway behaviour and for metabolic engineering. Here, we expand the intracellular compartmentalisation toolbox for budding yeast (Saccharomyces cerevisiae) with engineered Murine polyomavirus virus-like particles (MPyV VLPs). The MPyV system has two components: VP1 which self-assembles into the compartment shell; and a short anchor, VP2C, which mediates cargo protein encapsulation via binding to the inner surface of the VP1 shell. Destabilised GFP fused to VP2C was specifically sorted into VLPs and thereby protected from host-mediated degradation. In order to access metabolites of native and engineered yeast metabolism, VLP-based nanocompartments were directed to assemble in the cytosol by removal of the VP1 nuclear localisation signal. To demonstrate their ability to function as a metabolic compartment, MPyV VLPs were used to encapsulate myo-inositol oxygenase (MIOX), an unstable and rate-limiting enzyme in D-glucaric acid biosynthesis. Strains with encapsulated MIOX produced ~20% more D-glucaric acid compared to controls expressing ‘free’ MIOX - despite accumulating dramatically less expressed protein - and also grew to higher cell densities. These effects were linked to enzyme stabilisation and mitigation of cellular toxicity by the engineered compartment. This is the first demonstration in yeast of an artificial biocatalytic compartment that can participate in a metabolic pathway and establishes the MPyV platform as a promising synthetic biology tool for yeast engineering.