bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relationship of sociodemographic and lifestyle factors and diet habits with metabolic syndrome (MetS) in a multi-ethnic Asian population
Authors: Iqbal Saleem Perwaiz , Ramadas Amutha , Fatt Quek Kia , Shin Ho Loon , Onn Wong Yin , Kadir Khalid Abdul 
Published: October 2019

AbstractObjectivesLiterature shows a high prevalence of MetS among Malaysians, varying across major ethnicities. As sociodemographic characteristics, lifestyle factors and diet habits of such communities have been reported to be diverse, the study objective was to investigate the association of various sociodemographic characteristics, lifestyle factors and diet habits on MetS overall and among the three major ethnic communities in Malaysia.Materials and MethodsWe conducted a cross-sectional study among 481 Malaysians of age 18 years and above living in Johor, Malaysia. Information on demographics, lifestyle and diet habits was collected using a structured questionnaire. MetS was diagnosed among the subjects using the Harmonized criteria. Multiple logistic regression was used to analyse associations between sociodemographic and lifestyle factors and dietary behaviours with MetS.ResultsMetS was found among 32.2% of the respondents, more prevalent among the Indians (51.9%), followed by Malays (36.7%) and Chinese (20.2%). Overall, increasing age (AOR=2.44[95%CI=1.27-4.70] at 40-49 years vs. AOR=4.14[95%CI=1.97-8.69] at 60 years and above) and Indian ethnicity (AOR=1.95[95%CI=1.12-3.38)] increased, while higher education (AOR = 0.44[95%CI = 0.20-0.94] reduced the odds of MetS in this population. Quick finishing of meals (AOR=2.17[95%CI=1.02-4.60]) and low physical activity (AOR=4.76[95%CI=1.49-15.26]) was associated with an increased odds of MetS among the Malays and Chinese, respectively.ConclusionThe population in Johor is diverse in these factors, and some of these are associated with MetS in certain ethnicities. In light of such differences, ethnic specific measures are needed to reduce the prevalence of MetS in this population.
The fodder grass resources for ruminants: A indigenous treasure of local communities of Thal desert Punjab, Pakistan
Authors: Shaheen Humaira , Qureshi Rahmatuallah , Qaseem Mirza Faisal , Bruschi Piero 
Published: October 2019

AbstractIndigenous people have been using their regional grasses for rearing their animals for centuries. The present study is the first recorded traditional knowledge of grasses and feeding system for livestock from the Thal desert in Pakistan. Snowball method was used to identify key informants. Information was collected from 232 informants from six districts of Thal Desert through semi-structural questionnaire and site visits. The data was analyzed through Smith’s salience index and Composite Salience using ANTHROPAC package in R software. On the whole 61 grasses were recorded from the study area and most of the species belongs to the Poaceae family (52 species). Based on palatability grasses were categorized into three major groups i.e. (A) High priority, (B) Medium priority and (C) Low priority. Species in Group A, abundantly present in the study area, highly palatable forage for all ruminants. 232(141M +91W) local informants were interviewed. Informants were grouped into three major age categories: 20–35 (48 informants), 36–50 (116 informants) and 51–67 years (68 informants). ANTHROPAC frequency analysis conformed the Smith’s salience index and Composite Salience; Cynodon dactylon was the favorite species (6.46 SI, 0.6460 CS) followed by Cymbopogon jwarancusa (5.133 SI, 0.5133 CS) and Sorghum sp. was the third most salient species (5.121 SI, 0.5121 CS). Grasses were mostly available during the season of August and October and had also ethnoveterinary importance. This document about the traditional feeding of livestock from Thal Desert can strengthen the value of conserving our traditional knowledge, which was poorly documented before.
Nanopatterned Thermoresponsive Functionalization of Substrates via Nanosphere Lithography
Authors: Mireles Marcela , Soule Cody W. , Delgadillo Luis F. , Gaborski Thomas R. 
Published: October 2019

1AbstractSelf-assembled monolayers (SAMs) have been widely utilized as a way of tailoring surface chemistry through the adsorption of organic molecules to different materials. SAMs are easy to prepare and offer a wide variety of organic molecules that afford additional or improved properties to the coated material. Spatial control of SAM placement has been achieved over many length-scales, even at the nanoscale. However, nanopatterned SAMs are usually prepared through serial processes utilizing atomic scanning probes or soft-lithography utilizing elastomeric masters. These techniques are expensive or not repeatable. Here we present the use of nanospheres for the creation of nanopatterned Au:Cu films which spatially control the grafting of a thermoresponsive SAM made from poly(N-isopropyl acrylamide) (PNIPAM). Chemical characterization validates the presence of PNIPAM and environmental atomic force microscopy showed its response to temperature which was evidenced by a change in stiffness. Our approach represents an affordable large area methodology for repeatable spatial control of SAMs at the nanoscale.
Atypical processing of uncertainty in individuals at risk for psychosis
Authors: Cole David M. , Diaconescu Andreea O. , Pfeiffer Ulrich J. , Brodersen Kay H. , Mathys Christoph D. , Julkowski Dominika , Ruhrmann Stephan , Schilbach Leonhard , Tittgemeyer Marc , Vogeley Kai , Stephan Klaas E. 
Published: October 2019

AbstractBackgroundCurrent theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in at-risk mental state (ARMS) individuals.MethodsNon-medicated ARMS individuals (n=13) and control participants (n=13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour – with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental ‘volatility’ – and used these computational quantities for analyses of fMRI data.ResultsComputational modelling of ARMS individuals’ behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of ARMS individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in ARMS was negatively associated with clinical measures of global functioning.ConclusionsOur results suggest a multi-faceted learning abnormality in ARMS individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation.
Stable task information from an unstable neural population
Authors: Rule Michael E. , Loback Adrianna R. , Raman Dhruva V. , Driscoll Laura , Harvey Christopher D. , O’Leary Timothy 
Published: October 2019

AbstractOver days and weeks, neural activity representing an animal’s position and movement in sensorimotor cortex has been found to continually reconfigure or ‘drift’ during repeated trials of learned tasks, with no obvious change in behavior. This challenges classical theories which assume stable engrams underlie stable behavior. However, it is not known whether this drift occurs systematically, allowing downstream circuits to extract consistent information. We show that drift is systematically constrained far above chance, facilitating a linear weighted readout of behavioural variables. However, a significant component of drift continually degrades a fixed readout, implying that drift is not confined to a null coding space. We calculate the amount of plasticity required to compensate drift independently of any learning rule, and find that this is within physiologically achievable bounds. We demonstrate that a simple, biologically plausible local learning rule can achieve these bounds, accurately decoding behavior over many days.
Neuronal activity in the premotor cortex of monkeys reflects both cue salience and motivation for action generation and inhibition
Authors: Giamundo Margherita , Giarrocco Franco , Brunamonti Emiliano , Fabbrini Francesco , Pani Pierpaolo , Ferraina Stefano 
Published: October 2019

ABSTRACTAnimals adopt different strategies, promoting certain actions and withholding inconvenient ones, to achieve their goals. The motivation to obtain them is the main drive that determines the behavioural performance. While much work has focused on understanding how motor cortices control actions, their role on motivated behaviours remains unclear. We recorded from dorsal premotor cortex (PMd) of monkeys performing a modified version of the stop-signal task, in which the motivation to perform/withhold an action was manipulated by presenting cues that informed on the probability to obtain different amounts of reward in relation to the motor outcome. According to the motivational context, animals performance adapted to maximize reward. Neuronal activity displayed a cue salience related modulation at trial start and, while the behavioural response approached, reflected more the motivation to start/cancel the action. These findings reveal multiple representations of motivation-related signals in PMd, highlighting its involvement in the control of finalized actions.SIGNIFICATIVE STATEMENTThe motivation to obtain rewards drives how animals act over their environment. To explore the involvement of motor cortices in motivated behaviours, we recorded high-resolution neuronal activity in the premotor cortex of monkeys performing a task that manipulated the motivation to generate/withhold a movement through different cued reward probabilities. Our results show the presence of neuronal signals dynamically reflecting a cue related activity, in the time immediately following its presentation, and a motivation related activity in performing (or cancelling) a motor program, while the behavioural response approached. The encoding of multiple reward-related signals in motor regions, leads to consider an important role of premotor areas in the reward circuitry.
Astrocyte redox dysregulation causes prefrontal hypoactivity: sulforaphane treats non-ictal pathophysiology in ALDH7A1-mediated epilepsy
Authors: Faust Travis E. , Xin Wendy , Lee Brian , Agarwal Amit , Saha Sneha , Palen Trexy , Cash-Padgett Tyler , Wood Daniel , Bonci Antonello , Fahey Jed W. , Jaaro-Peled Hanna , Bergles Dwight E. , Sawa Akira 
Published: October 2019

AbstractMutations in the astrocyte-enriched enzyme aldehyde dehydrogenase 7a1 (ALDH7A1) cause a neonatal epilepsy accompanied by treatment-resistant, inter-ictal neuropsychiatric symptoms. Nevertheless, the mechanistic impact of ALDH7A1 dysfunction in the brain remains elusive. We generated ALDH7A1 knockout mice and report that constitutive global ALDH7A1 depletion increases chemoconvulsant sensitivity and altered mood-associated behaviors. However, contrary to our expectation, astrocyte-specific ALDH7A1 depletion only affects mood-associated behaviors. Accordingly, in astrocyte-specific ALDH7A1 knockout mice, we show enhanced redox-sensitive microdomain Ca2+signaling in astrocytes and both elevated synaptic inhibitory tone and increased dendritic spine density in prelimbic pyramidal neurons. Sulforaphane (SFN), an indirect antioxidant and dietary supplement, has been explored as a possible treatment to ameliorate neuropsychiatric manifestations in autism and schizophrenia, at least at the clinical levels, but its mechanism in the brain is unclear. Here we show that SFN rescues both the physiological and behavioral changes by targeting astrocytic redox imbalance in ALDH7A1 knockout mice, implicating astrocyte redox changes in creating cortical excitatory-inhibitory imbalance and mood alteration.
Cryo-EM Structures of the XPF-ERCC1 Endonuclease Reveal an Auto-Inhibited Conformation and the Basis for Activation
Authors: Jones Morgan , Beuron Fabienne , Borg Aaron , Nans Andrea , Earl Christopher , Briggs David C. , Bowles Maureen , Morris Edward P. , Linch Mark , McDonald Neil Q. 
Published: October 2019

AbstractThe structure-specific endonuclease XPF-ERCC1 participates in multiple DNA damage repair pathways including nucleotide excision repair (NER) and inter-strand crosslink repair (ICLR). How XPF-ERCC1 is catalytically activated by DNA junction substrates is not currently understood. We report cryo-electron microscopy structures of both DNA-free and DNA-bound human XPF-ERCC1. DNA-free XPF-ERCC1 adopts an auto-inhibited conformation in which the XPF helical domain masks ERCC1 DNA-binding elements and restricts access to the XPF catalytic site. Binding of a model DNA junction separates the XPF helical and ERCC1 (HhH)2 domains, promoting activation. Using these structural data, we propose a model for a 5’-NER incision complex involving XPF-ERCC1-XPA and a DNA junction substrate. Structure-function data suggest xeroderma pigmentosum patient mutations often compromise the structural integrity of XPF-ERCC1. Fanconi anaemia patient mutations often display substantial in-vitro activity but are resistant to activation by ICLR recruitment factor SLX4. Our data provide insights into XPF-ERCC1 architecture and catalytic activation.
Testing gene-environment interactions for rare and/or common variants in sequencing association studies
Authors: Zhao Zihan , Zhang Jianjun , Sha Qiuying , Hao Han 
Published: October 2019

AbstractThe risk of many complex diseases is determined by a complex interplay of genetic and environmental factors. Advanced next generation sequencing technology makes identification of gene-environment (GE) interactions for both common and rare variants possible. However, most existing methods focus on testing the main effects of common and/or rare genetic variants. There are limited methods developed to test the effects of GE interactions for rare variants only or rare and common variants simultaneously. In this study, we develop novel approaches to test the effects of GE interactions of rare and/or common risk, and/or protective variants in sequencing association studies. We propose two approaches: 1) testing the effects of an optimally weighted combination of GE interactions for rare variants (TOW-GE); 2) testing the effects of a weighted combination of GE interactions for both rare and common variants (variable weight TOW-GE, VW-TOW-GE). Extensive simulation studies based on the Genetic Analysis Workshop 17 data show that the type I error rates of the proposed methods are well controlled. Compared to the existing interaction sequence kernel association test (ISKAT), TOW-GE is more powerful when there are GE interactions’ effects for rare risk and/or protective variants; VW-TOW-GE is more powerful when there are GE interactions’ effects for both rare and common risk and protective variants. Both TOW-GE and VW-TOW-GE are robust to the directions of effects of causal GE interactions. We demonstrate the applications of TOW-GE and VW-TOW-GE using an imputed data from the COPDGene Study.
SpikeInterface, a unified framework for spike sorting
Authors: Buccino Alessio P. , Hurwitz Cole L. , Garcia Samuel , Magland Jeremy , Siegle Joshua H. , Hurwitz Roger , Hennig Matthias H. 
Published: October 2019

AbstractMuch development has been directed towards improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to facilitate straightforward comparison and adoption of different approaches. With a few lines of code, researchers can reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs; and more. In this paper, we provide an overview of SpikeInterface and, with applications to real and simulated datasets, demonstrate how it can be utilized to reduce the burden of manual curation and to more comprehensively benchmark automated spike sorters.
MYPT1 O-GlcNAc modification controls the sensitivity of fibroblasts to sphingosine-1-phosphate mediated cellular contraction
Authors: Pedowitz Nichole J. , Batt Anna R. , Darabedian Narek , Pratt Matthew R. 
Published: October 2019

ABSTRACTMany intracellular proteins can be modified by N-acetylglucosamine, a posttranslational modification known as O-GlcNAc. Because this modification is found on serine and threonine side-chains, O-GlcNAc has the potential to dynamically regulate cellular signaling pathways through interplay with phosphorylation. Here, we discover and characterize one such example. First, we find that O-GlcNAc levels control the sensitivity of fibroblasts to actin contraction induced by the signaling lipid sphingosine-1-phosphate (S1P). In follow-up mechanistic investigations, we show that this O-GlcNAc dependence lies in the signaling pathway through the S1PR2 receptor and subsequent activation of the Rho and Rho kinase. This pathway typically culminates in the phosphorylation of myosin light chain (MLC), resulting in myosin activation and cellular contraction. We discovered that O-GlcNAc modification of the phosphatase subunit MYPT1 inhibits this pathway by blocking MYPT1 phosphorylation, maintaining its activity and causing the dephosphorylation of MLC. Therefore, MYTP1 O-GlcNAc levels function to regulate the sensitivity of cells to S1P-mediated cellular contraction. Finally, we demonstrate that O-GlcNAc levels alter the sensitivity of primary human dermal fibroblasts in a collagen matrix model of wound healing. Our findings have important implications for the role of O-GlcNAc in fibroblast motility and differentiation, particularly in diabetic wound healing, where increased levels of the modification may inhibit S1P-mediated healing phenotypes in fibroblasts.
Chemogenetic inhibition in the dorsal striatum reveals regional specificity of direct and indirect pathway control of action sequencing
Authors: Garr Eric , Delamater Andrew R. 
Published: October 2019

AbstractAnimals engage in intricate action sequences that are constructed during instrumental learning. There is broad consensus that the basal ganglia play a crucial role in the formation and fluid performance of action sequences. To investigate the role of the basal ganglia direct and indirect pathways in action sequencing, we virally expressed Cre-dependent Gi-DREADDs in either the dorsomedial (DMS) or dorsolateral (DLS) striatum during and/or after action sequence learning in D1 and D2 Cre rats. Action sequence performance in D1 Cre rats was slowed down early in training when DREADDs were activated in the DMS, but sped up when activated in the DLS. Acquisition of the reinforced sequence was hindered when DREADDs were activated in the DLS of D2 Cre rats. Outcome devaluation tests conducted after training revealed that the goal-directed control of action sequence rates was immune to chemogenetic inhibition—rats suppressed the rate of sequence performance when rewards were devalued. Sequence initiation latencies were generally sensitive to outcome devaluation, except in the case where DREADD activation was removed in D2 Cre rats that previously experienced DREADD activation in the DMS during training. Sequence completion latencies were generally not sensitive to outcome devaluation, except in the case where D1 Cre rats experienced DREADD activation in the DMS during training and test. Collectively, these results suggest that the indirect pathway originating from the DLS is part of a circuit involved in the effective reinforcement of action sequences, while the direct and indirect pathways originating from the DMS contribute to the goal-directed control of sequence completion and initiation, respectively.
Boost in Test-Retest Reliability in Resting State fMRI with Predictive Modeling
Authors: Taxali Aman , Angstadt Mike , Rutherford Saige , Sripada Chandra 
Published: October 2019

AbstractRecent studies found low test-retest reliability in fMRI, raising serious concerns among researchers, but these studies mostly focused on reliability of individual fMRI features (e.g., individual connections in resting state connectivity maps). Meanwhile, neuroimaging researchers increasingly employ multivariate predictive models that aggregate information across a large number of features to predict outcomes of interest, but the test-retest reliability of predicted outcomes of these models has not previously been systematically studied. Here we apply ten predictive modeling methods to resting state connectivity maps from the Human Connectome Project dataset to predict 61 outcome variables. Compared to mean reliability of individual resting state connections, we find mean reliability of the predicted outcomes of predictive models is substantially higher for all ten modeling methods assessed. Moreover, improvement was consistently observed across all scanning and processing choices (i.e., scan lengths, censoring thresholds, volume-versus surface-based processing). For the most reliable methods, reliability of predicted outcomes was mostly, though not exclusively, in the “good” range (above 0.60).Finally, we identified three mechanisms that help to explain why predicted outcomes of predictive models have higher reliability than individual imaging features. We conclude that researchers can potentially achieve higher test-retest reliability by making greater use of predictive models.