bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced analgesic cholinergic tone after neuropathy
Authors: Dhanasobhon Dhanasak , Medrano Maria-Carmen , Moreno-Lopez Yunuen , Kavraal Sehrazat , Bichara Charlotte , Schlichter Rémy , Inquimbert Perrine , Yalcin Ipek , Cordero-Erausquin Matilde 
Published: June 2020

AbstractAt the spinal cord level, a tone of endogenous acetylcholine (ACh) modulates nociceptive sensory processing. Increasing the level of spinal ACh induces analgesia in naïve animals or in situation of acute pain in the clinics, but whether this is still the case in situations or models of chronic pain is controversial. Here, we demonstrate the persistence, and even increased impact of the analgesic cholinergic tone acting through nicotinic receptors in neuropathic mice. The neuropathy does not affect the number and properties of dorsal horn cholinergic neurons, proposed to be the source of spinal ACh. Subthreshold doses of acetylcholinesterase (AChE) inhibitors in sham animals become anti-allodynic in cuff mice suggesting that the alterations occur in the cholino-receptive neurons. Thus endogenous cholinergic signaling can be manipulated with low doses of drugs to relieve mechanical allodynia in animal neuropathy models. This opens new avenues with potentially fewer side effects for neuropathic pain treatment.
Confronting pitfalls of AI-augmented molecular dynamics using statistical physics
Authors: Pant Shashank , Smith Zachary , Wang Yihang , Tajkhorshid Emad , Tiwary Pratyush 
Published: June 2020

AbstractArtificial intelligence (AI)-based approaches have had indubitable impact across the sciences through the ability to extract relevant information from raw data. Recently AI has also seen use for enhancing the efficiency of molecular simulations, wherein AI derived slow modes are used to accelerate the simulation in targeted ways. However, while typical fields where AI is used are characterized by a plethora of data, molecular simulations per-construction suffer from limited sampling and thus limited data. As such the use of AI in molecular simulations can suffer from a dangerous situation where the AI-optimization could get stuck in spurious regimes, leading to incorrect characterization of the reaction coordinate (RC) for the problem at hand. When such an incorrect RC is then used to perform additional simulations, one could start to deviate progressively from the ground truth. To deal with this problem of spurious AI-solutions, here we report a novel and automated algorithm using ideas from statistical mechanics. It is based on the notion that a more reliable AI-solution will be one that maximizes the time-scale separation between slow and fast processes. To learn this time-scale separation even from limited data, we use a maximum caliber-based framework. We show the applicability of this automatic protocol for 3 classic benchmark problems, namely the conformational dynamics of a model peptide, ligand-unbinding from a protein, and folding/unfolding energy landscape of the C-terminal domain of protein G. We believe our work will lead to increased and robust use of trustworthy AI in molecular simulations of complex systems.
Synthetic observations from deep generative models and binary omics data with limited sample size
Authors: Nußberger Jens , Boesel Frederic , Lenz Stefan , Binder Harald , Hess Moritz 
Published: June 2020

AbstractDeep generative models can be trained to represent the joint distribution of data, such as measurements of single nucleotide polymorphisms (SNPs) from several individuals. Subsequently, synthetic observations are obtained by drawing from this distribution. This has been shown to be useful for several tasks, such as removal of noise, imputation, for better understanding underlying patterns, or even exchanging data under privacy constraints. Yet, it is still unclear how well these approaches work with limited sample size. We investigate such settings specifically for binary data, e.g., as relevant when considering SNP measurements, and evaluate three frequently employed generative modeling approaches, variational autoencoders (VAEs), deep Boltzmann machines (DBMs) and generative adversarial networks (GANs). This includes conditional approaches, such as when considering gene expression conditional on SNPs. Recovery of pair-wise odds ratios is considered as a primary performance criterion. For simulated as well as real SNP data, we observe that DBMs generally can recover structure for up to 100 variables with as little as 500 observations, with a tendency of over-estimating odds ratios when not carefully tuned. VAEs generally get the direction and relative strength of pairwise relations right, yet with considerable under-estimation of odds ratios. GANs provide stable results only with larger sample sizes and strong pair-wise relations in the data. Taken together, DBMs and VAEs (in contrast to GANs) appear to be well suited for binary omics data, even at rather small sample sizes. This opens the way for many potential applications where synthetic observations from omics data might be useful.
A hybrid Embden–Meyerhof–Parnas pathway provides a synthetic link between sugar and phosphate metabolism
Authors: Lee Yoojin , Cho Hye Jeong , Woo Han Min 
Published: June 2020

AbstractThe fundamental Embden–Meyerhoff–Paranas (EMP) pathway for sugar catabolism, anabolism, and energy metabolism has been reconstituted with non-oxidative glycolysis (NOG). Although carbon conservation was achieved via NOG, the energy metabolism was significantly limited. Herein, we showed the construction of a hybrid EMP that replaced the first phase of the EMP inCorynebacterium glutamicumwith NOG and revealed a metabolic link of carbon and phosphorus metabolism. In accordance with synthetic glucose kinase activity and phosphoketolase on the hybrid EMP, cell growth was completely recovered in theC. glutamicum pfkAmutant strain where the first phase of EMP was eliminated. Notably, we have revealed a phosphate-replenishing pathway that involved trehalose biosynthesis for the generation of inorganic phosphate (Pi) sources in the hybrid EMP when external Pisupply was limited. Thus, the re-designed hybrid EMP pathway with balanced carbon and phosphorus states provides an efficient microbial platform for biochemical production.
Unilateral and Bilateral Subthalamic stimulation differently promote apathy: a translational approach
Authors: Vachez Yvan , Bahout Marie , Magnard Robin , David Pierre-Maxime , Carcenac Carole , Robert Gabriel , Savasta Marc , Carnicella Sebastien , Vérin Marc , Boulet Sabrina 
Published: June 2020

ABSTRACTApathy, depression, and anxiety represent the main neuropsychiatric symptoms of Parkinson’s disease (PD). How subthalamic nucleus deep brain stimulation (STN-DBS) influences these symptoms, especially apathy, is a controversial topic. The present translational study investigates and compares the effect of bilateral or unilateral STN-DBS on this neuropsychiatric triad, combining a pre-clinical approach in rodents and a clinical follow-up of patients with PD. While depression and anxiety related behaviors remain unchanged, bilateral but not unilateral STN-DBS consistently induces apathy in patients and a reward seeking deficit in rodents. Together, these data substantiate the claim that STN-DBS may induce apathy by itself and suggest that bilateral but not the unilateral stimulation might be a critical factor.
Localized cell-surface sampling of a secreted factor using cell-targeting beads
Authors: van Neel Tammi L. , Berry Samuel B. , Berthier Erwin , Theberge Ashleigh B. 
Published: June 2020

AbstractIntercellular communication through the secretion of soluble factors plays a vital role in a wide range of biological processes (e.g., homeostasis, immune response), yet identification and quantification of many of these factors can be challenging due to their degradation or sequestration in cell culture media prior to analysis. Here, we present a customizable bead-based system capable of simultaneously binding to live cells (through antibody-mediated cell-tethering) and capturing cell-secreted molecules. Our functionalized beads capture secreted molecules (e.g., hepatocyte growth factor secreted by fibroblasts) that are diminished when sampledviatraditional supernatant analysis techniques (p < 0.05), effectively rescuing reduced signal in the presence of neutralizing components in the cell culture media. Our system enables capture and analysis of molecules integral to chemical communication that would otherwise be markedly decreased prior to analysis.For Table of Contents Only
Defining the impact of deep brain stimulation contact size and shape on neural selectivity
Authors: Anderson Daria Nesterovich , Dorval Alan D. , Rolston John D. , Pulst Stefan M. , Anderson Collin J 
Published: June 2020

AbstractBackgroundUnderstanding neural selectivity is essential for optimizing medical applications of deep brain stimulation (DBS). We previously showed that modulation of the DBS waveform can induce changes in orientation-based selectivity, and that lengthening of DBS pulses or directional segmentation can reduce preferential selectivity for large axons. In this work, we sought to answer a simple, but important question: how do the size and shape of the contact influence neural selectivity?MethodsWe created multicompartment neuron models for several axon diameters and used finite element modeling with standard-sized cylindrical leads to determine the effects on changing contact size and shape on axon activation profiles and volumes of tissue activated. Contacts ranged in size from 0.04 to 16 mm2, compared with a standard size of 6 mm2.ResultsWe found that changes in contact size induce substantial changes in orientation-based selectivity in the context of a cylindrical lead, and rectangular shaping of the contact can alter this selectivity. Smaller contact sizes were more effective in constraining neural activation to small, nearby axons representative of grey matter. However, micro-scale contacts enable only limited spread of neural activation before exceeding standard charge density limitations; further, energetic efficiency is optimized by somewhat larger contacts.InterpretationsSmall-scale contacts are optimal for constraining stimulation in nearby grey matter and avoiding orientation-selective activation. However, given charge density limitations and energy inefficiency of micro-scale contacts, our results suggest that contacts about half the size of those on segmented clinical leads may optimize efficiency and charge density limitation avoidance.
Co-Occurrence of Enzyme Domains Guides the Discovery of an Oxazolone Synthetase
Authors: de Rond Tristan , Asay Julia E. , Moore Bradley S. 
Published: June 2020

AbstractMultidomain enzymes are cellular machines that orchestrate two or more catalytic activities to carry out metabolic transformations with increased control and speed. Our understanding of these enzymes’ capabilities drives progress in fundamental metabolic research, biocatalysis, and human health. Here, we report the development of a new genome mining approach for the targeted discovery of novel biochemical transformations through the analysis of co-occurring enzyme domains (CO-ED) in a single protein. CO-ED was designed to identify unannotated multifunctional enzymes for functional characterization and discovery based on the premise that linked enzyme domains have evolved to function collaboratively. Guided by CO-ED, we targeted an unannotated predicted ThiF-nitroreductase di-domain enzyme found in more than 50 proteobacteria. Through heterologous expression and biochemical reconstitution, we discovered a series of new natural products containing the rare oxazolone (azlactone) heterocycle and characterized the di-domain enzyme as the first reported oxazolone synthetase in biology. This enzyme has the potential to become a valuable biocatalyst for the production of versatile oxazolone synthetic intermediates. This proof-of-principle experiment validates CO-ED-guided genome mining as a new method with potential broad utility for both the discovery of novel enzymatic transformations and the functional gene annotation of multidomain enzymes.TOC graphic
Direct RNA sequencing reveals structural differences between transcript isoforms
Authors: Ashley Aw Jong Ghut , Lim Shaun W. , Wang Jia Xu , Shen Yang , Kaewsapsak Pornchai , Louis Kok Eng Piew , Li Chenhao , Ng Boon Hsi , Vardy Leah A. , Tan Meng How , Nagarajan Niranjan , Wan Yue 
Published: June 2020

AbstractThe ability to correctly assign structure information to an individual transcript in a continuous and phased manner is critical to understanding RNA function. RNA structure play important roles in every step of an RNA’s lifecycle, however current short-read high throughput RNA structure mapping strategies are long, complex and cannot assign unique structures to individual gene-linked isoforms in shared sequences. To address these limitations, we present an approach that combines structure probing with SHAPE-like compound NAI-N3, nanopore direct RNA sequencing, and one-class support vector machines to detect secondary structures on near full-length RNAs (PORE-cupine).PORE-cupineprovides rapid, direct, accurate and robust structure information along known RNAs and recapitulates global structural features in human embryonic stem cells. The majority of gene-linked isoforms showed structural differences in shared sequences both local and distal to the alternative splice site, highlighting the importance of long-read sequencing for phasing of structures. Structural differences between gene-linked isoforms are associated with differential translation efficiencies globally, highlighting the role of structure as a pervasive mechanism for regulating isoform-specific gene expression inside cells.
scGRNom: a computational pipeline of integrative multi-omics analyses for predicting cell-type disease genes and regulatory networks
Authors: Jin Ting , Rehani Peter , Ying Mufang , Huang Jiawei , Liu Shuang , Roussos Panagiotis , Wang Daifeng 
Published: June 2020

AbstractUnderstanding cell-type-specific gene regulatory mechanisms from genetic variants to diseases remains challenging. To address this, we developed an open-source computational pipeline, scGRNom, to predict the cell-type disease genes and regulatory networks from multi-omics data, including cell-type chromatin interactions, epigenomics, and single-cell transcriptomics. With applications to Schizophrenia and Alzheimer’s Disease, our predicted cell-type regulatory networks link transcription factors and enhancers to disease genes for excitatory and inhibitory neurons, microglia, and oligodendrocytes. The enrichments of cell-type disease genes reveal cross-disease and disease-specific functions and pathways. Finally, machine learning analysis found that cell-type disease genes shared by diseases have improved clinical phenotype predictions.
Whole blood immunophenotyping uncovers immature neutrophil-to-VD2 T-cell ratio as an early prognostic marker for severe COVID-19
Authors: Carissimo Guillaume , Xu Weili , Kwok Immanuel , Abdad Mohammad Yazid , Chan Yi-Hao , Fong Siew-Wai , Puan Kia Joo , Lee Cheryl Yi-Pin , Yeo Nicholas Kim-Wah , Amrun Siti Naqiah , Chee Rhonda Sin-Ling , How Wilson , Chan Stephrene , Fan Eugene Bingwen , Andiappan Anand Kumar , Lee Bernett , Rötzschke Olaf , Young Barnaby Edward , Leo Yee-Sin , Lye David C. , Renia Laurent , Ng Lai Guan , Larbi Anis , Ng Lisa F.P. 
Published: June 2020

AbstractSARS-CoV-2 is the novel coronavirus responsible for the current COVID-19 pandemic. Severe complications are observed only in a small proportion of infected patients but the cellular mechanisms underlying this progression are still unknown. Comprehensive flow cytometry of whole blood samples from 54 COVID-19 patients revealed a dramatic increase in the number of immature neutrophils. This increase strongly correlated with disease severity and was associated with elevated IL-6 and IP-10 levels, two key players in the cytokine storm. The most pronounced decrease in cell counts was observed for CD8 T-cells and VD2 γδ T-cells, which both exhibited increased differentiation and activation. ROC analysis revealed that the count ratio of immature neutrophils to CD8 or VD2 T-cells predicts pneumonia onset (0.9071) as well as hypoxia onset (0.8908) with high sensitivity and specificity. It would thus be a useful prognostic marker for preventive patient management and improved healthcare resource management.
Model-based learning deficits in compulsivity are linked to faulty representations of task structure
Authors: Seow Tricia X.F. , O’Connell Redmond , Gillan Claire M. 
Published: June 2020

AbstractIndividuals with higher levels of compulsivity exhibit poorer performance on tasks that require model-based planning but the underlying causes have yet to be established. Here, we sought to determine whether these deficits stem from impoverished action-outcome relational knowledge (i.e. issues building an accurate model of the world) and/or an inability to translate models into action. 192 participants performed a two-step reinforcement learning task with concurrent EEG recordings. We found that representations of task-relevant action-outcome associations reflected in reaction time and parietal-occipital alpha-band power were stronger in individuals whose decisions were more model-based, and critically, were weaker in those high in compulsivity. At the time of choice, mid-frontal theta power, a general marker of cognitive control, was also negatively associated with compulsivity, but not model-based planning. These data suggest that model-based planning deficits in compulsive individuals may arise from failures in building an accurate model of the world.
DNA glycosylase NEIL2 preventsFusobacterium-mediated inflammation and DNA damage in colonic epithelial cells
Authors: Sayed Ibrahim M , Chakraborty Anirban , Ali Amer , Sharma Aditi , Sahan Ayse Z. , Sahoo Debashis , Ghosh Pradipta , Hazra Tapas K , Das Soumita 
Published: June 2020

AbstractColorectal cancer (CRC) is the third most prevalent and deadly cancer. Approximately, 15-20 % of CRCs display microsatellite instability (MSI); however, the majority (80–85%) of cases are sporadic and known as microsatellite stable (MSS). Several recent studies indicated that infection and uncontrolled inflammation initiate DNA damage and lead to cancer progression. One of the major microbes,Fusobacterium nucleatum(Fn) is highly associated with CRC, but the role of DNA repair in microbe-associated CRC has been largely unknown. Here we show that NEIL2, an oxidized base-specific DNA glycosylase, is significantly downregulated among all the key DNA repair proteins involved in various DNA repair pathways, after infection ofFnwith stem-cell-based enteroid-derived monolayers (EDMs) of murine and human healthy subjects. Furthermore, followingFninfection, NEIL2-null mouse-derived EDMs showed significantly higher level of DNA damage, including double strand breaks, and inflammatory cytokines.. Murine CRC model also showed downregulation of the NEIL2 transcript and accumulation of DNA damage. Importantly, analysis of publicly available transcriptomic data showed that the downregulation of NEIL2 is specific for MSS compared to MSI CRCs. We thus conclude that the pathogenic bacterial infection-induced downregulation of NEIL2, and consequent accumulation of DNA damage, play critical roles in the progression of CRC.
Simple Assay, Kinetics, and Biochemical Trends for Soil Microbial Catalases
Authors: Chabot Michael , Morales Ernesto , Cummings Jacob , Rios Nicholas , Giatpaiboon Scott , Mogul Rakesh 
Published: June 2020

AbstractIn this report, we expand upon the enzymology and biochemical ecology of soil catalases through development and application of a simple kinetic model and assay based upon volume displacement. Through this approach, we (A) directly relate apparent Michaelis-Menten terms to the catalase reaction mechanism, (B) obtain upper estimates of the intrinsic rate constants for the catalase communityand moles of catalase per 16S rRNA gene copy number, (C) utilize catalase specific activities (SAs) to obtain biomass estimates of soil and permafrost communities (LOD, ~104copy number gdw−1), and (D) relate kinetic trends to changes in bacterial community structure. This model represents a novel approach to the kinetic treatment of soil catalases, while simultaneously incorporating barometric adjustments to afford comparisons across field measurements. As per our model, and when compared to garden soils, biological soil crusts exhibited ~2-fold lower values for, ≥105-fold higher catalase moles per biomass (250-1200 zmol copy number−1), and ~104-fold higher SAs per biomass (74-230 fkat copy number−1). However, the highest SAs were obtained from permafrost and high-elevation soil communities (5900-6700 fkat copy number−1). In sum, these total trends suggest that microbial communities which experience higher degrees of native oxidative stress possess higher basal intracellular catalase concentrations and SAs per biomass, and that differing kinetic profiles across catalase communities are indicative of phylum and/or genus-level changes in community structure. For microbial ecology, therefore, these measures effectively serve as markers for microbial activity and abundance, and additionally provide insights into the community responses to exogenous stress.ImportanceThe efficient management of oxidative stresses arising from environmental pressures are central to the homeostasis of soil microbial communities. Among the enzymes that manage oxidative stress are catalases, which degrade hydrogen peroxide into oxygen gas and water. In this report, we detail the development and application of a simple kinetic model and assay to measure catalase reaction rates and estimate soil biomass. Our assay is based upon volume displacement, and is low-cost, field-amenable, and suitable for scientists and educators from all disciplines. Our results suggest that microbial communities that experience higher degrees of native oxidative stress possess higher basal intracellular catalase concentrations and specific activities when expressed per biomass. For microbial ecology, therefore, these measures serve as biochemical markers for microbial activity and abundance, and provide insights into the community responses to exogenous stress; thereby providing a novel means to study active microbial communities in soils and permafrost.