bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linear summation of metabotropic postsynaptic potentials follows coactivation of neurogliaform interneurons
Authors: Ozsvár Attila , Komlósi Gergely , Oláh Gáspár , Baka Judith , Molnár Gábor , Tamás Gábor 
Published: December 2020

SummarySummation of ionotropic receptor-mediated responses is critical in neuronal computation by shaping input-output characteristics of neurons. However, arithmetics of summation for metabotropic signals are not known. We characterized the combined ionotropic and metabotropic output of neocortical neurogliaform cells (NGFCs) using electrophysiological and anatomical methods. These experiments revealed that GABA receptors are activated up to 1.8 microns from release sites and confirmed coactivation of putative NGFCs in superficial cortical layers in vivo. Triple recordings from presynaptic NGFCs converging to a postsynaptic neuron revealed sublinear summation of ionotropic GABAAresponses and linear summation of metabotropic GABABresponses. Based on a model combining distances of volume transmission from release sites and distributions of all NGFC axon terminals, we postulate that 2 to 3 NGFCs provide input to a point in the neuropil. We suggest that interactions of metabotropic GABAergic responses remain linear even if most superficial layer interneurons specialized to recruit GABABreceptors are simultaneously active.
Synchrony of Non-isochronous Signals in an Acoustically Communicating Katydid
Authors: Nityananda Vivek , Balakrishnan Rohini 
Published: December 2020

SummaryThe ability to entrain to auditory stimuli has been a powerful method to investigate the comparative rhythm abilities of different animals. While synchrony to regular (isochronous) rhythms is well documented, synchrony to non-isochronous stimuli, with multiple components at unequal time intervals, is rarer. Several katydid species with isochronous calls have been shown to achieve synchrony as part of their natural calling interactions in multi-individual choruses. Yet no study so far has demonstrated synchrony in any insect with a non-isochronous call. Using natural calling behaviour and playback experiments, we investigated acoustic synchrony and the mechanisms underlying it in the katydid speciesMecopoda‘Two Part Caller’. This species has a complex non-isochronous call consisting of a long trill followed by two or more chirps. We found that individual males synchronized trills and, to a lesser extent, chirps. Further investigation of trill synchrony showed that timing of trills is modified by external trills but not chirps. Chirp synchrony is modified by external chirps but also by trills. We suggest a two-oscillator model underlying synchrony in this species and discuss the implications for the evolution of acoustic synchrony.
Quantifying the influence of space on social group structure
Authors: Evans Julian , Liechti Jonas I. , Silk Matthew J. , Bonhoeffer Sebastian , König Barbara 
Published: December 2020

AbstractWhen studying social behaviour, it can be important to determine whether the behaviour being recorded is actually driven by the social preferences of individuals. Many studies of animal social networks therefore attempt to disentangle social preferences from spatial preferences or restrictions. As such, there are a large number of techniques with which to test whether results from network analysis can be explained by random interactions, or interactions driven by similarities in space use. Selecting which of these methods to use will require determining to what extent space might influence social structure. Here we present a simple method (Social Spatial Community Assignment Test) to quantify the similarity between social and spatial group structure. We then apply this method to both simulated and empirical data of social interactions to demonstrate that it can successfully tease apart social and spatial explanations for groups. We first show that it can resolve the relative importance of space and social preferences in three simulated datasets in which interaction patterns are driven purely by space use, purely by social preferences or a mixture of the two. We then apply it to empirical data from a long-term study of free-ranging house mice. We find that while social structure is similar to spatial structure, there is still evidence for individuals possessing social preferences, with the importance of these preferences fluctuating between seasons. Our method provides a robust way of assessing the overlap between spatial and social structure, which will be invaluable to researchers when investigating the underlying drivers of social structure in wild populations.
SOMDE: A scalable method for identifying spatially variable genes with self-organizing map
Authors: Hao Minsheng , Hua Kui , Zhang Xuegong 
Published: December 2020

AbstractRecent developments of spatial transcriptomic sequencing technologies provide powerful tools for understanding cells in the physical context of tissue micro-environments. A fundamental task in spatial gene expression analysis is to identify genes with spatially variable expression patterns, or spatially variable genes (SVgenes). Several computational methods have been developed for this task. Their high computational complexity limited their scalability to the latest and future large-scale spatial expression data.We present SOMDE, an efficient method for identifying SVgenes in large-scale spatial expression data. SOMDE uses self-organizing map (SOM) to cluster neighboring cells into nodes, and then uses a Gaussian Process to fit the node-level spatial gene expression to identify SVgenes. Experiments show that SOMDE is about 5-50 times faster than existing methods with comparable results. The adjustable resolution of SOMDE makes it the only method that can give results in ∼5 minutes in large datasets of more than 20,000 sequencing sites. SOMDE is available as a python package on PyPI athttps://pypi.org/project/somdefree for academic use.
Long-lasting impact of starvation experience on fly activity and place preference
Authors: Mahishi Deepthi , Triphan Tilman , Hesse Ricarda , Huetteroth Wolf 
Published: December 2020

AbstractAnimal behaviours are demonstrably governed by sensory stimulation, previous experience and internal states like hunger. With increasing hunger, priorities shift towards foraging and feeding. During foraging, flies are known to employ efficient path integration strategies. However, general long-term activity patterns for both hungry and satiated flies in conditions of foraging remain to be better understood. Similarly, little is known about how chronic contact chemosensory stimulation affects locomotion. To address these questions, we have developed a novel, simplistic fly activity tracking setup – the Panopticon. Using a 3D-printed Petri dish inset, our assay allows recording of walking behaviour, of several flies in parallel, with all arena surfaces covered by a uniform substrate layer. We tested two constellations of providing food: i) in single patches, and ii) omnipresent within the substrate layer. Fly tracking is done with FIJI, further assessment, analysis and presentation is done with a custom-built MATLAB analysis framework. We find that starvation history leads to a long-lasting reduction in locomotion, as well as a delayed place preference for food patches not driven by immediate hunger motivation.
Epilepsy kinase CDKL5 is a DNA damage sensor which controls transcriptional activity at DNA breaks
Authors: Khanam Taran , Muñoz Ivan , Weiland Florian , Carroll Thomas , Borsos Barbara N , Pantazi Vasiliki , Slean Meghan , Novak Miroslav , Toth Rachel , Appleton Paul , Pankotai Tibor , Zhou Houjiang , Rouse John 
Published: December 2020

Mutation of theCDKL5kinase gene leads to the seizure-prone neurodevelopmental condition CDD (CDKL5 deficiency disorder) and is the most common genetic cause of childhood epilepsy. However, the phospho-targets and roles of CDKL5 are poorly understood, especially in the nucleus. We reveal CDKL5 as a sensor of DNA damage in actively transcribed regions of the nucleus, which phosphorylates transcriptional regulators such as Elongin A (ELOA) on a specific consensus motif. Recruitment of CDKL5 and ELOA to DNA damage sites, and subsequent ELOA phosphorylation, requires both active transcription and synthesis of poly–ADP ribose to which CDKL5 can bind. Critically, CDKL5 is essential for transcriptional control at DNA breaks. Therefore, CDKL5 is a DNA damage-sensing regulator of transcription, with implications for CDKL5-related human diseases.One sentence summaryCDKL5 is a DNA damage-sensing kinase that modulates transcriptional activity near DNA breaks.
EVALUATING METHODS AND PROTOCOLS OF FERRITIN-BASED MAGNETOGENETICS
Authors: Hernández-Morales Miriam , Han Victor , Kramer Richard H , Liu Chunlei 
Published: December 2020

SummaryFeRIC (Ferritin iron Redistribution to Ion Channels) is a magnetogenetic technique that uses radio frequency (RF) alternating magnetic fields to activate the transient receptor potential channels, TRPV1 and TRPV4, coupled to cellular ferritins. In cells expressing ferritin-tagged TRPV, RF stimulation increases the cytosolic Ca2+levels via a biochemical pathway. The interaction between RF and ferritin increases the free cytosolic iron levels that in turn, trigger chemical reactions producing reactive oxygen species and oxidized lipids that activate the ferritin-tagged TRPV. In this pathway, it is expected that experimental factors that disturb the ferritin expression, the ferritin iron load, the TRPV functional expression, or the cellular redox state will impact the efficiency of RF in activating ferritin-tagged TRPV. Here, we examined several experimental factors that either enhance or abolish the RF control of ferritin-tagged TRPV. The findings may help optimize and establish reproducible magnetogenetic protocols.
Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study
Authors: Batta Ishaan , Abrol Anees , Fu Zening , Preda Adrian , van Erp Theo G.M. , Calhoun Vince D. 
Published: December 2020

ABSTRACTRevealing associations among various structural and functional patterns of the brain can yield highly informative results about the healthy and disordered brain. Studies using neuroimaging data have more recently begun to utilize the information within as well as across various functional and anatomical domains (i.e., groups of brain networks). However, most whole-brain approaches assume similar complexity of interactions throughout the brain. Here we investigate the hypothesis that interactions between brain networks capture varying amounts of complexity, and that we can better capture this information by varying the complexity of the model subspace structure based on available training data. To do this, we employ a Bayesian optimization-based framework known as the Tree Parzen Estimator (TPE) to identify, exploit and analyze patterns of variation in the information encoded by temporal information extracted from functional magnetic resonance imaging (fMRI) subdomains of the brain. Using a repeated cross-validation procedure on a schizophrenia classification task, we demonstrate evidence that interactions between specific functional subdomains are better characterized by more sophisticated model architectures compared to less complicated ones required by the others for optimally contributing towards classification and understanding the brain’s functional interactions. We show that functional subdomains known to be involved in schizophrenia require more complex architectures to optimally unravel discriminatory information about the disorder. Our study points to the need for adaptive, hierarchical learning frameworks that cater differently to the features from different subdomains, not only for a better prediction but also for enabling the identification of features predicting the outcome of interest.
Activity-based urinary biomarkers of response and resistance to checkpoint blockade immunotherapy
Authors: Mac Quoc D. , Xu Congmin , Bowen James R. , Sivakumar Anirudh , Phuengkham Hathaichanok , Su Fang-Yi , Stentz Samuel Z. , Sim Hyoungjun , Harris Adrian M. , Li Tonia T. , Qiu Peng , Kwong Gabriel A. 
Published: December 2020

AbstractImmune checkpoint blockade (ICB) therapy has transformed cancer treatment, yet most patients do not derive clinical benefit and responders can acquire resistance to therapy. Noninvasive biomarkers are needed to indicate early on-treatment response and resistance mechanisms. Here we developedImmuNeSensors for monItorinG cHeckpoint blockadeTherapy (INSIGHT), which comprises a library of mass-barcoded peptide substrates conjugated to αPD1 antibodies, as therapeutic sensors. Following systemic administration, INSIGHT carries out the dual role of reinvigorating T cell function and profiling T cell and tumor proteases by the release of cleaved peptides into urine for noninvasive detection by mass spectrometry. We show that an αPD1 therapeutic sensor for Granzyme B discriminates early treatment responses before tumor volumes significantly diverge from isotype controls in murine models of colorectal cancer. To differentiate mechanisms of resistance by multivariate analysis, we design a mass-barcoded, 14-plex INSIGHT library to profile proteases differentially expressed by tumors harboring B2m or Jak1 loss-of-function mutations. We find that binary classifiers trained on urine samples indicate response to αPD-1 therapy as early as the start of the second dose, and discriminate B2m from Jak1 resistance with high sensitivity and specificity (AUROCs > 0.9). Our data supports the use of activity-based biomarkers for early on-treatment response assessment and classification of refractory tumors based on resistance mechanisms.
Enhancing Task fMRI Preprocessing via Individualized Model-Based Filtering of Intrinsic Activity Dynamics
Authors: Singh Matthew F. , Wang Anxu , Cole Michael , Ching ShiNung , Braver Todd S. 
Published: December 2020

AbstractBrain responses recorded during fMRI are thought to reflect both rapid, stimulus-evoked activity and the propagation of spontaneous activity through brain networks. In the current work we describe a method to improve the estimation of task-evoked brain activity by first “filtering-out” the intrinsic propagation of pre-event activity from the BOLD signal. We do so using Mesoscale Individualized NeuroDynamic (MINDy; [1]) models built from individualized resting-state data (MINDy-based Filtering). After filtering, time-series are analyzed using conventional techniques. Results demonstrate that this simple operation significantly improves the statistical power and temporal precision of estimated group-level effects. Moreover, use of MINDy-based filtering increased the similarity of neural activation profiles and prediction of individual differences in behavior across tasks measuring the same construct (cognitive control).Thus, by subtracting the propagation of previous activity, we obtain better estimates of task-related neural activity.
Tuning electrical stimulation of the cervical vagus nerve for abdominal signaling while reducing cardiovascular side effects
Authors: Horn Charles C. , Forssell Mats , Sciullo Michael , Harms Jonathan E. , Fulton Stephanie , Mou Chenchen , Sun Fan , Simpson Tyler W. , Xiao Gutian , Fisher Lee E. , Bettinger Christopher , Fedder Gary K. 
Published: December 2020

AbstractElectrical vagus nerve stimulation (VNS) has the potential to treat a wide variety of diseases by modulating afferent and efferent communication to the heart, lungs, esophagus, stomach, and intestines. Although distal vagal nerve branches, close to end organs, could provide a selective therapeutic approach, these locations are often surgically inaccessible. In contrast, the cervical vagus nerve has been targeted for decades using surgically implantable cuff electrodes to treat epileptic seizures and depression; however, to date, clinical implementation of VNS has relied on an electrode with contacts that fully wrap around the nerve, producing non-selective activation of the entire nerve. Here we demonstrate selective cervical VNS using cuff electrodes with multiple contacts around the nerve circumference to target different functional pathways. These flexible probes were adjusted to the diameter of the nerve using an adhesive hydrogel wrap to create a robust electrode interface. Our approach was verified in a rat model by demonstrating that cervical VNS produces neural activity in the abdominal vagus nerve while limiting effects on the cardiovascular system (i.e., changes in heart rate or blood pressure). This study demonstrates the potential for selective cervical VNS as a therapeutic approach for modulating distal nerve branches while reducing off target effects. This methodology could potentially be refined to treat gastrointestinal, metabolic, inflammatory, cardiovascular, and respiratory diseases amenable to vagal neuromodulatory control.
LLAMA: a robust and scalable machine learning pipeline for analysis of cell surface projections in large scale 4D microscopy data
Authors: Lefevre James G. , Koh Yvette W. H. , Wall Adam A. , Condon Nicholas D. , Stow Jennifer L. , Hamilton Nicholas A. 
Published: December 2020

abstractWe present LLAMA, a pipeline for systematic analysis of terabyte scale 4D microscopy datasets. Analysis of individual biological structures in imaging at this scale requires efficient and robust methods which do not require human micromanagement or editing of outputs. To meet this challenge, we use a machine learning method for semantic segmentation, followed by a robust and configurable object separation and tracking algorithm, and the generation of detailed object level statistics. Advanced visualisation is a key element of LLAMA: we provide a specialised software tool which supports quality control and optimisation as well as visualisation of outputs. LLAMA was used in a quantitative analysis of macrophage surface membrane projections (filopodia, ruffles, tent-pole ruffles) examining the differential effects of two interventions: lipopolysaccharide (LPS) and macrophage colony stimulating factor (CSF-1). Distinct patterns of increased activity were identified. In addition, a continuity of behaviour was found between tent pole ruffling and wave-like ruffling, further defining the role of filopodia in ruffling.
LJA: Assembling Long and Accurate Reads Using Multiplex de Bruijn Graphs
Authors: Bankevich Anton , Bzikadze Andrey , Kolmogorov Mikhail , Antipov Dmitry , Pevzner Pavel A. 
Published: December 2020

AbstractAlthough most existing genome assemblers are based on the de Bruijn graphs, it remains unclear how to construct these graphs for large genomes and largek-mer sizes. This algorithmic challenge has become particularly important with the emergence of long high-fidelity (HiFi) reads that were recently utilized to generate a semi-manual telomere-to-telomere assembly of the human genome and to get a glimpse into biomedically important regions that evaded all previous attempts to sequence them. To enable automated assemblies of long and accurate reads, we developed a fast LJA algorithm that reduces the error rate in these reads by three orders of magnitude (making them nearly error-free) and constructs the de Bruijn graph for large genomes and largek-mer sizes. Since the de Bruijn graph constructed for a fixedk-mer size is typically either too tangled or too fragmented, LJA uses a new concept of a multiplex de Bruijn graph with varyingk-mer sizes. We demonstrate that LJA improves on the state-of-the-art assemblers with respect to both accuracy and contiguity and enables automated telomere-to-telomere assemblies of entire human chromosomes.
Three-dimensional spatial transcriptomics uncovers cell type dynamics in the rheumatoid arthritis synovium
Authors: Vickovic Sanja , Schapiro Denis , Carlberg Konstantin , Lötstedt Britta , Larsson Ludvig , Korotkova Marina , Hensvold Aase H , Catrina Anca I , Sorger Peter K , Malmström Vivianne , Regev Aviv , Ståhl Patrik L 
Published: December 2020

AbstractThe inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics to study local cellular interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-seq data coupled to quantitative and cell type-specific chemokine-driven dynamics at and around organized structures of infiltrating leukocyte cells in the synovium.
Canonical neural networks perform active inference
Authors: Isomura Takuya , Shimazaki Hideaki , Friston Karl 
Published: December 2020

AbstractThis work considers a class of canonical neural networks comprising rate coding models, wherein neural activity and plasticity minimise a common cost function—and plasticity is modulated with a certain delay. We show that such neural networks implicitly perform active inference and learning to minimise the risk associated with future outcomes. Mathematical analyses demonstrate that this biological optimisation can be cast as maximisation of model evidence, or equivalently minimisation of variational free energy, under the well-known form of a partially observed Markov decision process model. This equivalence indicates that the delayed modulation of Hebbian plasticity—accompanied with adaptation of firing thresholds—is a sufficient neuronal substrate to attain Bayes optimal control. We corroborated this proposition using numerical analyses of maze tasks. This theory offers a universal characterisation of canonical neural networks in terms of Bayesian belief updating and provides insight into the neuronal mechanisms underlying planning and adaptive behavioural control.
Non-cell autonomous inhibition of the Hedgehog response due to impaired cholesterol synthesis requires Ptch1/2 function
Authors: Jägers Carina , Roelink Henk 
Published: December 2020

AbstractCongenital birth defects due to mutations of enzymes involved cholesterol synthesis, like Smith-Lemli-Opitz syndrome (SLOS) and Lathosterolosis are characterized by an accumulation of cholesterol precursors. The phenotype of both SLOS and Lathosterolosis have similarities to syndromes associated with abnormal Sonic hedgehog (Shh) signaling, consistent with the observation that cholesterol precursors and their derivative can inhibit Shh signaling. Two types of multipass membrane proteins play central roles in Shh signal transduction, the putative Resistance, Nodulation and Division (RND) antiporters Patched (Ptch)1 and −2, and the G-protein coupled receptor Smoothened (Smo). Sterols have been suggested as cargo for Ptch1/2, while Smo activity can affected both positively and negatively by steroidal molecules. We demonstrate that embryonic stem cells with mutations in the7-dehydroxycholesterol reductase(7Dhcr) orsterol-C5-desaturase(Sc5d) gene reduce the Hh response in adjacent wildtype cells when grown in mosaic organoids. This non-cell autonomous inhibitory activity of the mutant cells requires the presence of both Ptch1 and Ptch2. These observations support a model in which late cholesterol precursors that accumulate in cells lacking 7Dhcr are the cargo for Ptch1 and Ptch2 efflux activity and mediate the non-cell autonomous inhibition of Smo.