bluuebunny/crossref_metadata_2025_split huggingface dataset:
Update in therapeutic strategies for Parkinson's disease
Authors: Kulisevsky Jaime , Oliveira Lais , Fox Susan H. 
Published: May 2018

Purpose of review
To review recent advances in therapeutics for motor and nonmotor symptoms of Parkinson's disease.

Recent findings
Neuroprotection remains a large area of investigation with preliminary safety data on alpha synuclein immunotherapy and glucagon-like peptide-1 agonists. Novel Monoamine Oxidase B and Caetchol-O-methyltransferase-inhibitors for motor fluctuations have shown benefit and are recently approved for clinical use. Long-acting amantadine has also been approved to reduce dyskinesia. Alternative delivery strategies (sublingual, inhaled) dopaminergics may prove useful for rapid reversal of Parkinson's disease motor symptoms. Advanced therapies (surgery and infusional therapies) continue to be useful in subgroups of patients for motor complications with improved safety and also benefit on some nonmotor symptoms, including neuropsychiatric issues. Specific therapeutics for cognition, swallowing, sleep, and mood disorders had moderate to limited benefits. Exercise-based therapy appears beneficial at all stages of Parkinson's disease.

Summary
The motor symptoms of Parkinson's disease can be reasonably treated and managed. However, therapies to slow or prevent disease progression remain a focus of research. Despite increased studies, treating nonmotor symptoms remains a challenge and an ongoing priority.
Dystonia as a network disorder: a concept in evolution
Authors: Schirinzi Tommaso , Sciamanna Giuseppe , Mercuri Nicola B. , Pisani Antonio 
Published: May 2018

Purpose of review
This survey takes into consideration the most recent advances in both human degenerative ataxias, disorders with a well established cerebellar origin, and discoveries from dystonia rodent models aimed at discussing the pathogenesis of dystonia.

Recent findings
One common recurrent term that emerges when describing dystonia is heterogeneity. Indeed, dystonia encompasses a wide group of ‘hyperkinetic’ movement disorders, with heterogeneous causes, classification, anatomical and physiological substrates. In addition, the clinical heterogeneity of age at onset, symptom distribution and appearance of non-motor symptoms has supported the concept of dystonia as ‘network’ disorder. Pathophysiological alterations are thought to arise from dysfunction at cortico-thalamic-basal ganglia level, whereas, more recently, a role for cerebellar pathways emerged. Results from human and animal studies thus fuel the evolving concept of the network disorder.

Summary
Current evidence suggests the involvement of multiple brain regions and cellular mechanisms, as part of the neural dysfunction observed at system level in dystonia.
The patchy tremor landscape: recent advances in pathophysiology
Authors: Nieuwhof Freek , Panyakaew Pattamon , van de Warrenburg Bart P. , Gallea Cecile , Helmich Rick C. 
Published: May 2018

Purpose of review
We focus on new insights in the pathophysiology of Parkinson's disease tremor, essential tremor, tremor in dystonia, and orthostatic tremor.

Recent findings
Neuroimaging findings suggest that Parkinson's disease resting tremor is associated with dopaminergic dysfunction, serotonergic dysfunction, or both. Not all tremors in Parkinson's disease have the same pathophysiology: postural tremor in Parkinson's disease can be subdivided into pure postural tremor, which involves nondopaminergic mechanisms, and re-emergent tremor, which has a dopaminergic basis. Unlike Parkinson's disease tremor, essential tremor has an electrophysiological signature suggestive of a single (or several tightly coupled) oscillators. Visual feedback increases essential tremor and enhances cerebral activity in the cerebello-thalamo-cortical circuit, supplementary motor area, and parietal cortex. Little is known about dystonic tremor but the available evidence suggests that both the basal ganglia and the cerebellum play a role. Finally, recent work in orthostatic tremor points towards the role of the pontine tegmentum and dysfunctional cerebellar-SMA circuitry.

Summary
Many pathological tremors involve the cerebello-thalamo-cortical circuitry, and the clinical and pathophysiological boundaries between tremor disorders are not always clear. Differences between tremor disorders – or even individual patients – may be explained by the specific balance of neurotransmitter degeneration, by distinct circuit dynamics, or by the role of regions interconnected to the cerebello-thalamo-cortical circuit.
Measuring Clinically Relevant Knee Motions With A Self-Calibrated Wearable Sensor
Authors: Hullfish Todd J. , Qu Feini , Stoeckl Brendan D. , Gebhard Peter M. , Mauck Robert L. , Baxter Josh R. 
Published: May 2018

AbstractLow-cost sensors provide a unique opportunity to continuously monitor patient progress during rehabilitation; however, these sensors have yet to demonstrate the fidelity and lack the calibration paradigms necessary to be viable tools for clinical research. Therefore, the purpose of this study was to validate a low-cost wearable sensor that accurately measured peak knee extension during clinical exercises and needed no additional equipment for calibration. Knee flexion was quantified using a 9-axis motion sensor and directly compared to motion capture data. Peak extension values during seated knee extensions were accurate within 5 degrees across all subjects (RMS error: 2.6 degrees, P = 0.29) but less accurate during sit-to-stand exercises (RMS error: 16.6 degrees, P = 0.48). Knee flexion during gait strongly correlated (0.84 ≤ rxy ≤ 0.99) with motion capture measurements but demonstrated average errors of 10 degrees. This study demonstrated a low-cost sensor that satisfied our criteria: a simple calibration procedure resulting in accurate measures of joint function during clinical exercises, making it a feasible tool for continuous patient monitoring to guide regenerative rehabilitation.
Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images
Authors: King Marcie L. , Groen Iris I. A. , Steel Adam , Kravitz Dwight J. , Baker Chris I. 
Published: May 2018

AbstractNumerous factors have been reported to underlie the representation of complex images in high-level human visual cortex, including categories (e.g. faces, objects, scenes), animacy, and real-world size, but the extent to which this organization is reflected in behavioral judgments of real-world stimuli is unclear. Here, we compared representations derived from explicit similarity judgments and ultra-high field (7T) fMRI of human visual cortex for multiple exemplars of a diverse set of naturalistic images from 48 object and scene categories. Behavioral judgements revealed a coarse division between man-made (including humans) and natural (including animals) images, with clear groupings of conceptually-related categories (e.g. transportation, animals), while these conceptual groupings were largely absent in the fMRI representations. Instead, fMRI responses tended to reflect a separation of both human and non-human faces/bodies from all other categories. This pattern yielded a statistically significant, but surprisingly limited correlation between the two representational spaces. Further, comparison of the behavioral and fMRI representational spaces with those derived from the layers of a deep neural network (DNN) showed a strong correspondence with behavior in the top-most layer and with fMRI in the mid-level layers. These results suggest that there is no simple mapping between responses in high-level visual cortex and behavior – each domain reflects different visual properties of the images and responses in high-level visual cortex may correspond to intermediate stages of processing between basic visual features and the conceptual categories that dominate the behavioral response.Significance StatementIt is commonly assumed there is a correspondence between behavioral judgments of complex visual stimuli and the response of high-level visual cortex. We directly compared these representations across a diverse set of naturalistic object and scene categories and found a surprisingly and strikingly different representational structure. Further, both types of representation showed good correspondence with a deep neural network, but each correlated most strongly with different layers. These results show that behavioral judgments reflect more conceptual properties and visual cortical fMRI responses capture more general visual features. Collectively, our findings highlight that great care must be taken in mapping the response of visual cortex onto behavior, which clearly reflect different information.
The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities
Authors: Baldini Federico , Heinken Almut , Heirendt Laurent , Magnusdottir Stefania , Fleming Ronan M.T. , Thiele Ines 
Published: May 2018

MotivationThe application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes.ResultsTo address this shortage, we created a comprehensive toolbox to model i) microbe-microbe and host-microbe metabolic interactions, and ii) microbial communities using microbial genome-scale metabolic reconstructions and metagenomic data. The Microbiome Modeling Toolbox extends the functionality of the COBRA Toolbox.AvailabilityThe Microbiome Modeling Toolbox and the tutorials athttps://git.io/microbiomeModelingToolbox.
Silencing cuticular pigmentation genes enables RNA FISH in intact chemosensory appendagess
Authors: Pentzold Stefan , Grabe Veit , Ogonkov Andrei , Schmidt Lydia , Boland Wilhelm , Burse Antje 
Published: May 2018

AbstractOptical imaging of gene expression by RNA-fluorescentin situhybridisation (FISH) in whole-mount sensory appendages of insects is often impeded by their highly pigmented cuticle. Since most chemical bleaching agents are incompatible with imaging fluorescent-labelled nucleotides, we developed a RNA interference-based method for clearing cuticular pigmentation that allows imaging of fluorescent mRNA in whole-mount appendages of insects. Silencing key genes of the tyrosine-derived pigmentation pathway by injecting dsRNA oflaccase2ortyrosine hydroxylasein two leaf beetles species (Chrysomela populi, Phaedon cochleariae) resulted in clearance of the highly pigmented cuticle and in significant decreased light absorbance. Intact chemosensory appendages (palps, antennae and legs) from RNAi-cleared individuals were used to image expression and spatial distribution of antisense mRNA of two chemosensory genes (gustatory receptor, odorant-binding protein) via RNA FISH and confocal laser scanning microscopy. Imaging of these genes did neither work for RNAi-controls (dsGfp) due to retained pigmentation, nor for FISH-controls using sense mRNA. Furthermore, we show that several chemical bleaching agents are not feasible with FISH, either due to significant degradation of polynucleotides, lack of clearing efficacy or long incubation times. Overall, silencing pigmentation genes is a significant improvement over bleaching agents allowing fluorescence imaging in whole-mount appendages and organs.
Energetic stress and infection generate immunity-fecundity tradeoffs in Drosophila
Authors: Buchanan Justin L. , Meiklejohn Colin D. , Montooth Kristi L. 
Published: May 2018

AbstractPhysiological responses to short-term environmental stress, such as infection, can have long-term consequences for fitness, particularly if the responses are inappropriate or nutrient resources are limited. Genetic variation affecting energy acquisition, storage, and usage can limit cellular energy availability and may influence resource-allocation tradeoffs even when environmental nutrients are plentiful. Here, we utilize well-characterized Drosophila mitochondrial-nuclear genotypes to test whether disrupted energy metabolism interferes with nutrient-sensing pathways, and whether this disruption has consequences for tradeoffs between immunity and fecundity. We find that this energetically compromised genotype is resistant to rapamycin – a drug that stimulates nutrient-sensing pathways that are activated when resources are limited. Resource limitation also compromises survival in energetically-compromised genotypes, suggesting that this genotype may have little excess energetic capacity and fewer cellular nutrients, even when environmental nutrients are not limiting. Accordingly, we find that immune function is compromised in this genotype, but only in females, and that these females experience immunity-fecundity tradeoffs that are not evident in genotypic controls with normal energy metabolism. Thus, genetic variation in energy metabolism may act to limit the resources available for allocation to life-history traits in ways that generate tradeoffs even when environmental resources are not limiting.
Intrinsically regulated learning is modulated by synaptic dopamine availability
Authors: Ripollés Pablo , Ferreri Laura , Mas-Herrero Ernest , Alicart Helena , Gómez-Andrés Alba , Marco-Pallarés Josep , Antonijoan Rosa , Noesselt Toemme , Valle Marta , Riba Jordi , Rodriguez-Fornells Antoni 
Published: May 2018

ABSTRACTWe recently provided evidence that an intrinsic reward-related signal—triggered by successful learning in absence of any external feedback—modulated the entrance of new information into long-term memory via the activation of the dopaminergic midbrain, hippocampus, and ventral striatum (the SN/VTA-Hippocampal loop; Ripollés et al., 2016). Here, we used a double-blind, within-subject randomized pharmacological intervention to test whether this learning process is indeed dopamine-dependent. A group of healthy individuals completed three behavioural sessions of our learning task after the intake of different pharmacological treatments: a dopaminergic precursor, a dopamine receptor antagonist or a placebo. Results show that the pharmacological intervention bidirectionally modulated behavioral measures of both learning and pleasantness, inducing memory benefits after 24 hours only for those participants with a high sensitivity to reward. These results provide causal evidence for a dopamine-dependent mechanism instrumental in intrinsically regulated learning, and further suggest that subject-specific dopamine sensitivity drastically alters learning success.
Refining fine-mapping: effect sizes and regional heritability
Authors: Benner Christian , Havulinna Aki S. , Salomaa Veikko , Ripatti Samuli , Pirinen Matti 
Published: May 2018

AbstractRecent statistical approaches have shown that the set of all available genetic variants explains considerably more phenotypic variance of complex traits and diseases than the individual variants that are robustly associated with these phenotypes. However, rapidly increasing sample sizes constantly improve detection and prioritization of individual variants driving the associations between genomic regions and phenotypes. Therefore, it is useful to routinely estimate how much phenotypic variance the detected variants explain for each region by taking into account the correlation structure of variants and the uncertainty in their causal status. Here we extend the FINEMAP software to estimate the effect sizes and regional heritability under the probabilistic model that assumes a handful of causal variants per each region. Using the UK Biobank data to simulate GWAS regions with only a few causal variants, we demonstrate that FINEMAP provides higher precision and enables more detailed decomposition of regional heritability into individual variants than the variance component model implemented in BOLT or the fixed-effect model implemented in HESS. Using data from 51 serum biomarkers and four lipid traits from the FINRISK study, we estimate that FINEMAP captures on average 24% more regional heritability than the variant with the lowest P-value alone and 20% less than BOLT. Our simulations suggest how an upward bias of BOLT and a downward bias of FINEMAP could together explain the observed difference between the methods. We conclude that FINEMAP enables computationally efficient estimation of effect sizes and regional heritability in the era of biobank scale data.
Binocular Integration Manifests as a Transient Spiking Increase Followed by Selective Suppression in Primary Visual Cortex
Authors: Cox Michele A. , Dougherty Kacie , Westerberg Jacob A. , Schall Michelle S. , Maier Alexander 
Published: May 2018

AbstractResearch throughout the past decades revealed that neurons in primate primary visual cortex (V1) rapidly integrate the two eyes’ separate signals into a combined binocular response. The exact mechanisms giving underlying this binocular integration remain elusive. One open question is whether binocular integration occurs at a single stage of sensory processing or in a sequence of computational steps. To address this question, we examined the temporal dynamics of binocular integration across V1’s laminar microcircuit of awake behaving monkeys. We find that V1 processes binocular stimuli in a dynamic sequence that comprises at least two distinct phases: A transient phase, lasting 50-150ms from stimulus onset, in which neuronal population responses are significantly enhanced for binocular stimulation compared to monocular stimulation, followed by a sustained phase characterized by widespread suppression in which feature-specific computations emerge. In the sustained phase, incongruent binocular stimulation resulted in response reduction relative to monocular stimulation across the V1 population. By contrast, sustained responses for binocular congruent stimulation were either reduced or enhanced relative to monocular responses depending on the neurons’ selectivity for one or both eyes (i.e., ocularity). These results suggest that binocular integration in V1 occurs in at least two sequential steps, with an initial additive combination of the two eyes’ signals followed by the establishment of interocular concordance and discordance.Significance StatementOur two eyes provide two separate streams of visual information that are merged in the primary visual cortex (V1). Previous work showed that stimulating both eyes rather than one eye may either increase or decrease activity in V1, depending on the nature of the stimuli. Here we show that V1 binocular responses change over time, with an early phase of general excitation and followed by stimulus-dependent response suppression. These results provide important new insights into the neural machinery that supports the combination of the two eye’s perspectives into a single coherent view.
A stochastic epigenetic switch controls the dynamics of T-cell lineage commitment
Authors: Ng Kenneth K.H. , Yui Mary A. , Mehta Arnav , Siu Sharmayne , Irwin Blythe , Pease Shirley , Hirose Satoshi , Elowitz Michael B. , Rothenberg Ellen V. , Kueh Hao Yuan 
Published: May 2018

SummaryCell fate decisions occur through the switch-like, irreversible activation of fate-specifying genes. These activation events are often assumed to be tightly-coupled to changes in upstream transcription factors, but could also be constrained by cis-epigenetic mechanisms at individual gene loci. Here, we studied the activation of Bcl11b, which controls T-cell fate commitment. To disentangle cis and trans effects, we generated mice where two Bcl11b copies are tagged with distinguishable fluorescent proteins. Quantitative live microscopy of progenitors from these mice revealed that Bcl11b turned on after a stochastic delay averaging multiple days, which varied not only between cells but also between Bcl11b alleles within the same cell. Genetic perturbations, together with mathematical modeling, showed that a distal enhancer controls the rate of epigenetic activation, while a parallel Notch-dependent trans-acting step stimulates expression from activated loci. These results show that developmental fate transitions can be controlled by stochastic cis-acting events on individual loci.
Co-transcriptional loading of RNA export factors shapes the human transcriptome
Authors: Viphakone Nicolas , Sudbery Ian M , Heath Catherine G. , Sims David , Wilson Stuart A. 
Published: May 2018

ABSTRACTDuring gene expression, RNA export factors are mainly known for driving nucleocytoplasmic transport. Whilst early studies suggested that the Exon Junction Complex provides a binding platform for them, subsequent work proposed that they are only recruited by the Cap-Binding Complex to the 5’ end of RNAs, as part of TREX. Using iCLIP, we show that the export receptor Nxf1 and two TREX subunits, Alyref and Chtop, are actually recruited to the whole mRNA co-transcriptionally via splicing but before 3’-end processing. Consequently, Alyref alters splicing decisions and Chtop regulates alternative polyadenylation. Alyref is recruited to the 5’-end of RNAs by CBC and our data reveal subsequent binding to RNAs near EJCs. We demonstrate eIF4A3 stimulates Alyref deposition not only on spliced RNAs close to EJC sites, but also single exon transcripts. Our study reveals mechanistic insights into the co-transcriptional recruitment of mRNA export factors and how this shapes the human transcriptome.
How does the presence of neural probes affect extracellular potentials?
Authors: Buccino Alessio Paolo , Kuchta Miroslav , Jæger Karoline Horgmo , Ness Torbjørn Vefferstad , Berthet Pierre , Mardal Kent-Andre , Cauwenberghs Gert , Tveito Aslak 
Published: May 2018

AbstractObjectiveMechanistic modeling of neurons is an essential component of computational neuroscience that enables scientists to simulate, explain, and explore neural activity. The conventional approach to simulation of extracellular neural recordings first computes transmembrane currents using the cable equation and then sums their contribution to model the extracellular potential. This two-step approach relies on the assumption that the extracellular space is an infinite and homogeneous conductive medium, while measurements are performed using neural probes. The main purpose of this paper is to assess to what extent the presence of the neural probes of varying shape and size impacts the extracellular field and how to correct for them.ApproachWe apply a detailed modeling framework allowing explicit representation of the neuron and the probe to study the effect of the probes and thereby estimate the effect of ignoring it. We use meshes with simplified neurons and different types of probe and compare the extracellular action potentials with and without the probe in the extracellular space. We then compare various solutions to account for the probes’ presence and introduce an efficient probe correction method to include theprobe effectin modeling of extracellular potentials.Main resultsOur computations show that microwires hardly influence the extracellular electric field and their effect can therefore be ignored. In contrast, Multi-Electrode Arrays (MEAs) significantly affect the extracellular field by magnifying the recorded potential. While MEAs behave similarly to infinite insulated planes, we find that their effect strongly depends on the neuron-probe alignment and probe orientation.SignificanceIgnoring theprobe effectmight be deleterious in some applications, such as neural localization and parameterization of neural models from extracellular recordings. Moreover, the presence of the probe can improve the interpretation of extracellular recordings, by providing a more accurate estimation of the extracellular potential generated by neuronal models.