bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temporal filters in response to presynaptic spike trains: Interplay of cellular, synaptic and short-term plasticity time scales
Authors: Mondal Yugarshi , Pena Rodrigo F. O. , Rotstein Horacio G. 
Published: September 2021

AbstractTemporal filters, the ability of postsynaptic neurons to preferentially select certain presynaptic input patterns over others, have been shown to be associated with the notion of information filtering and coding of sensory inputs. Short-term plasticity (depression and facilitation; STP) has been proposed to be an important player in the generation of temporal filters. We carry out a systematic modeling, analysis and computational study to understand how characteristic postsynaptic (low-, high- and band-pass) temporal filters are generated in response to periodic presynaptic spike trains in the presence STP. We investi-gate how the dynamic properties of these filters depend on the interplay of a hierarchy of processes, including the arrival of the presynaptic spikes, the activation of STP, its effect on the excitatory synaptic connection efficacy, and the response of the postsynaptic cell. These mechanisms involve the inter-play of a collection of time scales that operate at the single-event level (roughly, during each presynaptic interspike-interval) and control the long-term development of the temporal filters over multiple presynaptic events. These time scales are generated at the levels of the presynaptic cell (captured by the presynaptic interspike-intervals), short-term depression and facilitation, synaptic dynamics and the post-synaptic cellular currents. We develop mathematical tools to link the single-event time scales with the time scales governing the long-term dynamics of the resulting temporal filters for a relatively simple model where depression and facilitation interact at the level of the synaptic efficacy change. We extend our results and tools to account for more complex models. These include multiple STP time scales and non-periodic presynaptic inputs. The results and ideas we develop have implications for the understanding of the generation of temporal filters in complex networks for which the simple feedforward network we investigate here is a building block.
Donor Macrophages Modulate Rejection after Heart Transplantation
Authors: Kopecky BJ , Dun H , Amrute JM , Lin CY , Bredemeyer AL , Terada Y , Bayguinov PO , Koenig AL , Frye CC , Fitzpatrick JAJ , Kreisel D , Lavine KJ 
Published: September 2021

AbstractBackgroundCellular rejection after heart transplantation imparts significant morbidity and mortality. Current immunosuppressive strategies are imperfect, target recipient T-cells, and have a multitude of adverse effects. The innate immune response plays an essential role in the recruitment and activation of T-cells. Targeting the donor innate immune response would represent the earliest interventional opportunity within the immune response cascade. There is limited knowledge regarding donor immune cell types and functions in the setting of cardiac transplantation and no current therapeutics exist for targeting these cell populations.MethodsUsing genetic lineage tracing, cell ablation, and conditional gene deletion, we examined donor mononuclear phagocyte diversity and function during acute cellular rejection of transplanted hearts in mice. We performed single cell RNA sequencing on donor and recipient macrophages, dendritic cells, and monocytes at multiple timepoints after transplantation. Based on our single cell RNA sequencing data, we evaluated the functional relevance of donor CCR2+and CCR2-macrophages using selective cell ablation strategies in donor grafts prior to transplant. Finally, we perform functional validation of our single cell-derived hypothesis that donor macrophages signal through MYD88 to facilitate cellular rejection.ResultsDonor macrophages persisted in the transplanted heart and co-existed with recipient monocyte-derived macrophages. Single-cell RNA sequencing identified donor CCR2+and CCR2-macrophage populations and revealed remarkable diversity amongst recipient monocytes, macrophages, and dendritic cells. Temporal analysis demonstrated that donor CCR2+and CCR2-macrophages were transcriptionally distinct, underwent significant morphologic changes, and displayed unique activation signatures after transplantation. While selective depletion of donor CCR2-macrophages reduced allograft survival, depletion of donor CCR2+macrophages prolonged allograft survival. Pathway analysis revealed that donor CCR2+macrophages were being activated through MYD88/NF-ĸβ signaling. Deletion of MYD88 in donor macrophages resulted in reduced antigen presenting cell recruitment, decreased emergence of allograft reactive T-cells, and extended allograft survival.ConclusionsDistinct populations of donor and recipient macrophages co-exist within the transplanted heart. Donor CCR2+macrophages are key mediators of allograft rejection and inhibition of MYD88 signaling in donor macrophages is sufficient to suppress rejection and extend allograft survival. This highlights the therapeutic potential of donor heart-based interventions.
Serotype-based evaluation of an optogenetic construct in rat cortical astrocytes
Authors: Balachandar Lakshmini , Borrego Diana , Diaz Jorge Riera 
Published: September 2021

AbstractOptogenetics is a modern technique which has been recently expanded to non-neuronal cell types, e.g., astrocytes, and involves targeted gene delivery of light-sensitive ion channels like Channelrhodopsin-2 (ChR2). Optogenetic regulation of astrocytic activity can be used for therapeutic intervention of several neurological disorders. Astrocytic gene delivery, viz adeno-associated viral (AAV) vectors, have proven to be robust, time-, and cost-efficient contrary to the generation of transgenic animal models. When transducing astrocytes with an AAV vector, it is imperative to perform a serotype evaluation of the AAV vector due to variability in serotype transduction efficiency depending on species, target region and construct length. Rats have been a very successful animal model for studying a variety of brain disorders, from which ChR2-based intervention of astrocytes will benefit. However, the most efficient AAV capsid serotype targeting astrocytes for ChR2 expression in the in vivo rat brain cortex has not been characterized. To address this, we have evaluated AAV serotypes 1, 5, and 8 of the vector AAV-GFAP-hChR2(H134)-mCherry targeting astrocytes in the rat brain neocortex. Results show that serotype 8 exhibits promising transduction patterns, as it has demonstrated the highest tangential and radial viral spread in the rat brain. Our research will facilitate translational research for future applications of optogenetics involving the transduction of rat brain cortical astrocytes.
Non-lesional and Lesional Lupus Skin Share Inflammatory Phenotypes that Drive Activation of CD16+ Dendritic Cells
Authors: Billi Allison C. , Ma Feiyang , Plazyo Olesya , Gharaee-Kermani Mehrnaz , Wasikowski Rachael , Hile Grace A. , Xing Xianying , Yee Christine M. , Rizvi Syed M. , Maz Mitra P. , Wen Fei , Tsoi Lam C. , Pellegrini Matteo , Modlin Robert L. , Gudjonsson Johann E. , Kahlenberg J. Michelle 
Published: September 2021

ABSTRACTCutaneous lupus erythematosus (CLE) is a disfiguring and poorly understood condition frequently associated with systemic lupus. Studies to date suggest that non-lesional keratinocytes play a role in disease predisposition, but this has not been investigated in a comprehensive manner or in the context of other cell populations. To investigate CLE immunopathogenesis, normal-appearing skin, lesional skin, and circulating immune cells from lupus patients were analyzed via integrated single-cell RNA-sequencing and spatial-seq. We demonstrate that normal-appearing skin of lupus patients represents a type I interferon-rich, ‘prelesional’ environment that skews gene transcription in all major skin cell types and dramatically distorts cell-cell communication. Further, we show that lupus-enriched CD16+ dendritic cells undergo robust interferon education in the skin, thereby gaining pro-inflammatory phenotypes. Together, our data provide a comprehensive characterization of lesional and non-lesional skin in lupus and identify a role for skin education of CD16+ dendritic cells in CLE pathogenesis.
Activity-dependent modulation of NMDA receptors by endogenous zinc shapes dendritic function in cortical neurons
Authors: Morabito Annunziato , Zerlaut Yann , Serraz Benjamin , Sala Romain , Paoletti Pierre , Rebola Nelson 
Published: September 2021

SUMMARYActivation of NMDA receptors (NMDARs) has been proposed to be a key component of single neuron computations in vivo. However is unknown if specific mechanisms control the function of such receptors and modulate input-output transformations performed by cortical neurons under in vivo-like conditions. Here we found that in layer 2/3 pyramidal neurons (L2/3 PNs), repeated synaptic stimulation results in an activity-dependent decrease in NMDARs activity by vesicular zinc. Such a mechanism shifted the threshold for dendritic non-linearities and strongly reduced LTP induction. Modulation of NMDARs was cell- and pathway-specific, being present selectively in L2/3-L2/3 connections but absent in ascending bottom-up inputs originating from L4 neurons. Numerical simulations highlighted that activity-dependent modulation of NMDARs has an important influence in dendritic computations endowing L2/3 PN dendrites with the ability to sustain dendritic non-linear integrations constant across different regimes of synaptic activity like those found in vivo. The present results therefore provide a new perspective on the action of vesicular zinc in cortical circuits by highlighting the role of this endogenous ion in normalizing dendritic integration of PNs during a constantly changing synaptic input pattern.
Taxonomy Analysis in Bacterial Kingdom based on Protein Domain: A Comparison Study
Authors: Wang Boqian , Zhou Jianglin , Jin Yuan , Hu Mingda , Zhao Yunxiang , Wang Xin , Yang Haoyi , Gong Xingfei , Zhang Fengwei , Zhang Zehan , Kang Fuqiang , Liang Long , Yue Junjie , Ren Hongguang 
Published: September 2021

AbstractThe taxonomy research on the bacterial kingdom is important and can be usually conducted by the analysis on conserved genes, 16s rRNA, protein domain, and so on. Comparatively, the protein domains maintain a most direct relationship with phenotypes. In this paper, based on the protein domain, we propose a 3-step framework to standardize the classification process of bacteria. Different model candidates are involved and discussed in each step. By comparing the classification results with existing taxonomy, we select the most appropriate candidate to improve the framework, and furthermore, discuss their biological significance. Finally, we put forward taxonomy suggestions based on the best classification results.Significance StatementWe standardize a 3-step framework to carry out bacterial taxonomy research based on protein domain. Furthermore, we filter out the best solution in each step that can together generate the most appropriate classification result, and at the same time, we discuss the biological significant it indicates. Finally, we propose suggestions on NCBI bacterial taxonomy based on the classification results.
Single-cell profiling reveals periventricular CD56bright NK cell accumulation in multiple sclerosis
Authors: Rodríguez-Lorenzo Sabela , van Olst Lynn , Rodriguez-Mogeda Carla , Kamermans Alwin , van der Pol Susanne M.A. , Rodríguez Ernesto , Kooij Gijs , de Vries Helga E. 
Published: September 2021

AbstractMultiple sclerosis (MS) is a chronic demyelinating disease characterised by immune cell infiltration resulting in lesions that preferentially affect periventricular areas of the brain. Despite research efforts to define the role of various immune cells in MS pathogenesis, the focus has been on a few immune cell populations while full-spectrum analysis, encompassing others such as natural killer (NK) cells, has not been performed. Here, we used single-cell mass cytometry (CyTOF) to profile the immune landscape of brain periventricular areas – septum and choroid plexus – and blood from MS donors and controls with and without other neurological diseases. Using a 37-marker panel, we revealed the infiltration of T cells and antibody-secreting cells in periventricular brain regions and identified a novel NK cell signature specific to MS. CD56bright NK cells accumulated in the septum of MS donors, displaying an activated and migratory phenotype that was similar to that of CD56bright NK cells in their circulation. We validated this signature by multiplex immunohistochemistry and found that NK cells with high expression of granzyme K, which is typical of the CD56bright subset, accumulated in both periventricular lesions and the choroid plexus. Together, our multi-tissue single-cell data suggests that CD56bright NK cells infiltrate the periventricular brain regions in MS patients via both the blood-brain and blood-CSF barriers and brings NK cells to the spotlight of MS pathology.
The dissociable effects of reward on sequential motor behaviour
Authors: Sporn Sebastian , Chen Xiuli , Galea Joseph M 
Published: September 2021

AbstractReward has consistently been shown to enhance motor performance however its beneficial effects appear to be largely unspecific. While reward has been shown to invigorate performance, it also enhances learning and/or retention. Therefore, a mechanistic account of the effects of reward on motor behaviour is lacking. Here we tested the hypothesis that these distinct reward-based improvements are driven by dissociable reward types: explicit reward (i.e. money) and performance feedback (i.e. points). Experiment 1 showed that explicit reward instantaneously improved movement times (MT) using a novel sequential reaching task. In contrast, performance-based feedback led to learning-related improvements. Importantly, pairing both maximised MT performance gains and accelerated movement fusion. Fusion describes an optimisation process during which neighbouring sequential movements blend together to form singular actions. Results from experiment 2 served as a replication and showed that fusion led to enhanced performance speed whilst also improving movement efficiency through increased smoothness. Finally, experiment 3 showed that these improvements in performance persist for 24 hours even without reward availability. This highlights the dissociable impact of explicit reward and performance feedback, with their combination maximising performance gains and leading to stable improvements in the speed and efficiency of sequential actions.
Extensive Chromatin Structure-Function Association Revealed by Accurate Compartmentalization Characterization
Authors: Wen Zi , Zhang Weihan , Zhong Quan , Xu Jinsheng , Hou Chunhui , Qin Zhaohui , Li Li 
Published: September 2021

AbstractChromosome conformation capture-based experiments have shown that eukaryotic chromosomes are partitioned into A and B compartments conventionally identified by the first eigenvector (EV1) of dimension reduction methods. However, many genomic regions show marginal EV1 values, indicating the ambiguity of A/B compartment scheme on these regions. We develop MOSAIC (MOdularity and Singular vAlue decomposition-based Identification of Compartments), an accurate compartmental state detection scheme. MOSAIC reveals that those ambiguous regions segregate into two additional compartmental states, which typically correspond to small genomic regions flanked by large canonical A/B compartments with opposite activities. They are denoted as micro-compartments accordingly. In contrast to the canonical A/B compartments, micro-compartments cover ~30% of the genome and are highly dynamic between cell types. More importantly, distinguishing the micro-compartments underpins accurate characterization of chromatin structure-function relationship. By applying MOSAIC to GM12878 and K562 cells, we identify CD86, ILDR1 and GATA2 which show concordance between gene expression and compartmental states beyond the scheme of A/B compartments. Taken together, MOSAIC uncovers fine-scale and dynamic structures underlying canonical A/B compartments. Our results suggest dynamic chromatin compartmentalization is underlying transcriptional regulation and disease.
Group size planning of breedings of gene-modified animals
Authors: Milchevskaya Vladislava , Bugnon Philippe , ten Buren Emiel B.J. , Brand Frank , Tresch Achim , Buch Thorsten 
Published: September 2021

AbstractAnimal breeding is time-consuming, costly, and affected by stochastic events related to Mendelian genetics, fertility, and litter size. Careful planning is mandatory to ensure a successful outcome using the least number of animals, hence adhering to the 3Rs of animal welfare. We have developed an R package, accessible also through an interactive website, that optimizes breeding design and provides a comprehensive report suitable for any breeder of genetically defined traits.
AF-vapeR: A multivariate genome scan for detecting parallel evolution using allele frequency change vectors
Authors: Whiting James R. , Paris Josephine R. , van der Zee Mijke J. , Fraser Bonnie A. 
Published: September 2021

ABSTRACTThe repeatability of evolution at the genetic level has been demonstrated to vary along a continuum from complete parallelism to divergence. In order to better understand why this continuum exists within and among systems, hypotheses must be tested using high confidence sets of candidate loci for repeatability. Despite this, few methods have been developed to scan SNP data for signatures specifically associated with repeatability, as opposed to local adaptation.Here we present AF-vapeR (Allele Frequency Vector Analysis of Parallel Evolutionary Responses), an approach designed to identify genome regions exhibiting highly correlated allele frequency changes within haplotypes and among replicated allele frequency change vectors. The method divides the genome into windows of an equivalent number of SNPs, and within each window performs eigen decomposition over normalised allele frequency change vectors (AFV), each derived from a replicated pair of populations/species. Properties of the resulting eigenvalue distribution can be used to compare regions of the genome for those exhibiting strong parallelism, and can also be compared against a null distribution derived from randomly permuted AFV. Further, the shape of the eigenvalue distribution can reveal multiple axes of parallelism within datasets.We demonstrate the utility of this approach to detect different modes of parallel evolution using simulations, and also demonstrate a reduction in error rate compared with intersecting FST outliers. Lastly, we apply AF-vapeR to three previously published datasets (stickleback, guppies, and Galapagos finches) which comprise a range of sampling and sequencing strategies, and lineage ages. We detect known parallel regions whilst also identifying novel candidates.The main benefits of this approach include a reduced false-negative rate under many conditions, an emphasis on signals associated specifically with repeatable evolution as opposed to local adaptation, and an opportunity to identify different modes of parallel evolution at the first instance.
Multi-objective prioritisation of candidate epitopes for diagnostic test development
Authors: Cerny Roman , Ashford Jodie , Reis-Cunha João , Campelo Felipe 
Published: September 2021

AbstractBackgroundThe development of peptide-based diagnostic tests requires the identification of epitopes that are at the same time highly immunogenic and, ideally, unique to the pathogen of interest, to minimise the chances of cross-reactivity. Existing computational pipelines for the prediction of linear B-cell epitopes tend to focus exclusively on the first objective, leaving considerations of cross-reactivity to later stages of test development.ResultsWe present a multi-objective approach to the prioritisation of candidate epitopes for experimental validation, in the context of diagnostic test development. The dual objectives of uniqueness (measured as dissimilarity from known epitope sequences from other pathogens) and predicted immunogenicity (measured as the probability score returned by the prediction model) are considered simultaneously. Validation was performed using data from three distinct pathogens (namely the nematode Onchocerca volvulus, the Epstein-Barr Virus and the Hepatitis C Virus), with predictions derived using an organism-specific prediction approach. The multi-objective rankings returned sets of non-dominated solutions as potential targets for the development of diagnostic tests with lower probability of false positives due to cross-reactivity.ConclusionsThe application of the proposed approach to three test pathogens led to the identification of 20 new potential epitopes, with both high probability and a high degree of exclusivity to the target organisms. The results indicate the potential of the proposed approach to provide enhanced filtering and ranking of potential candidates, highlighting potential cross-reactivities and including this information into the test development process right from the target identification and prioritisation step.
Evaluation of cell segmentation methods without reference segmentations
Authors: Chen Haoran , Murphy Robert F. 
Published: September 2021

AbstractCell segmentation is a cornerstone of many bioimage informatics studies and inaccurate segmentation introduces error in downstream analysis. Evaluating segmentation results is thus a necessary step for developing segmentation methods as well as for choosing the most appropriate method for a particular type of sample. The evaluation process has typically involved comparison of segmentations to those generated by humans, which can be expensive and subject to unknown bias. We present here an approach to evaluating cell segmentation methods without relying upon comparison to results from humans. For this, we defined a number of segmentation quality metrics that can be applied to multichannel fluorescence images. We calculated these metrics for 14 previously-described segmentation methods applied to datasets from 4 multiplexed microscope modalities covering 5 tissues. Using principal component analysis to combine the metrics we defined an overall cell segmentation quality score and ranked the segmentation methods. We found that two deep learning-based methods performed the best overall, but that results for all methods could be significantly improved by postprocessing to ensure proper matching of cell and nuclear masks. Our evaluation tool is available as open source and all code and data are available in a Reproducible Research Archive.