bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing synthetic refocusing to deconvolution for the extraction of neuronal calcium transients from light-fields
Authors: Howe Carmel L. , Quicke Peter , Song Pingfan , Jadan Herman Verinaz , Dragotti Pier Luigi , Foust Amanda J. 
Published: September 2020

AbstractSignificanceLight-field microscopy (LFM) enables fast, light-efficient, volumetric imaging of neuronal activity with calcium indicators. Calcium transients differ in temporal signal-to-noise ratio (tSNR) and spatial confinement when extracted from volumes reconstructed by different algorithms.AimWe evaluated the capabilities and limitations of two light-field reconstruction algorithms for calcium fluorescence imaging.ApproachWe acquired light-field image series from neurons either bulk-labeled or filled intracellularly with the red-emitting calcium dye CaSiR-1 in acute mouse brain slices. We compared the tSNR and spatial confinement of calcium signals extracted from volumes reconstructed with synthetic refocusing and Richardson-Lucy 3D deconvolution with and without total variation regularization.ResultsBoth synthetic refocusing and Richardson-Lucy deconvolution resolved calcium signals from single cells and neuronal dendrites in three dimensions. Increasing deconvolution iteration number improved spatial confinement but reduced tSNR compared to synthetic refocusing. Volumetric light-field imaging did not decrease calcium signal tSNR compared to interleaved, widefield image series acquired in matched planes.ConclusionsLFM enables high-volume rate, volumetric imaging of calcium transients in single cells (bulk-labeled), somata and dendrites (intracellular loaded). The trade-offs identified for tSNR, spatial confinement, and computational cost indicate which of synthetic refocusing or deconvolution can better realize the scientific requirements of future LFM calcium imaging applications.
pmparser and PMDB: resources for large-scale, open studies of the biomedical literature
Authors: Schoenbachler Joshua L. , Hughey Jacob J. 
Published: September 2020

AbstractPubMed is an invaluable resource for the biomedical community. Although PubMed is freely available, the existing API is not designed for large-scale analyses and the XML structure of the underlying data is inconvenient for complex queries. We developed an R package called pmparser to convert the data in PubMed to a relational database. Our implementation of the database, called PMDB, currently contains data on over 31 million PubMed Identifiers (PMIDs) and is updated regularly. Together, pmparser and PMDB can enable large-scale, reproducible, and transparent analyses of the biomedical literature. pmparser is licensed under GPL-2 and available athttps://pmparser.hugheylab.org. PMDB is stored in PostgreSQL and compressed dumps are available on Zenodo (https://doi.org/10.5281/zenodo.4008109).
Investigating motor preparatory processes and conscious volition using machine learning
Authors: Hall Siobhan , van den Heever Dawie , Vinding Mikkel C. , Morris Linzette 
Published: September 2020

AbstractBackgroundConscious volition is a broad term and is difficult to reduce to a single empirical paradigm. It encompasses many areas of cognition, including decision-making and empirical studies can be done on these components. This work follows on the seminal work of Libetet al. (1983) which focused on brain activity preceding motor activity and conscious awareness of the intention to move. Previous results have subsequently faced criticism, particularly methods used to average out EEG data over all the trials and the readiness potential not being present on an individual trial basis. This following study aims to address these criticisms.ObjectivesTo use machine learning to investigate brain activity preceding left/right hand movements with relation to conscious intent and motor action.MethodologyThe data collection involved the recreation of the Libet experiment, with electroencephalography (EEG) data being collected. An addition made in this study was the choice between “left” and “right” while observing the Libet clock to subjectively mark the moment of conscious awareness. Twenty-one participants were included (four females, all right-handed). A deep (machine) learning model known as a convolutional neural network (CNN) was used for the EEG data analysis.ResultsSubjectively reported conscious intent preceded the action by 108 ms. The CNN model was able to predict the decision “left” or “right” as early as 4.45 seconds before the action with a test accuracy of 98%.ConclusionThis study has shown motor preparatory processes start up to 4.45 seconds before conscious awareness of a decision to move.
Diversity, phylogeny and DNA barcoding of brachyuran crabs in artificially created mangrove environments
Authors: Manikantan Ganesh , PrasannaKumar Chinnamani , Vijaylaxmi J. , Pugazhvendan S. R. , Prasanthi Narra 
Published: September 2020

AbstractGlobally, at the rate of 1-2 percent per annum, mangrove coverings are disappearing and 35 percent have been lost in the last 20 years due to changes in climate and human activities. No mangrove-associated crabs were found when the mangroves were artificially transplanted 25 years ago in the Vellar estuary. This mangrove ecosystem was sampled for brachyuran biodiversity estimation, species abundance, composition and evaluation of the effectiveness of DNA barcoding in brachyuran crabs species identification. A total of 2844 crabs were collected, representing 35 species within 8 families belonging to 20 genera. Four brachyuran crab species, that is,Uca lactae, U. Triangularis, Selatium brockii, andNeosarmatium asiaticumaccount for >70% of the total abundance. An approximate 87.5% of crab species estimated to occur by various species estimator were recovered in the present study. BetweenUca lacteaandU. triangularis, the maximum association index value was observed (97.7%). Cluster analysis grouped the sampled stations according to the types of mangrove species, clearly influencing the structure and composition of the brachyuran crabs. In general, vegetative cover composed of multiple species of mangroves is preferred for the abundance of all collected crabs species, and particularlyNeosarmatium asiaticum. Analysis of DNA barcoding indicates that 40% of the brachyuran species gathered in this sample were first barcoded. The advent of new high-throughput sequencing technologies will change biomonitoring applications and surveys drastically in the near future, making reference datasets like ours relevant.
Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases
Authors: Weeks Elle M. , Ulirsch Jacob C. , Cheng Nathan Y. , Trippe Brian L. , Fine Rebecca S. , Miao Jenkai , Patwardhan Tejal A. , Kanai Masahiro , Nasser Joseph , Fulco Charles P. , Tashman Katherine C. , Aguet Francois , Li Taibo , Ordovas-Montanes Jose , Smillie Christopher S. , Biton Moshe , Shalek Alex K. , Ananthakrishnan Ashwin N. , Xavier Ramnik J. , Regev Aviv , Gupta Rajat M. , Lage Kasper , Ardlie Kristin G. , Hirschhorn Joel N. , Lander Eric S. , Engreitz Jesse M. , Finucane Hilary K. 
Published: September 2020

ABSTRACTGenome-wide association studies (GWAS) are a valuable tool for understanding the biology of complex traits, but the associations found rarely point directly to causal genes. Here, we introduce a new method to identify the causal genes by integrating GWAS summary statistics with gene expression, biological pathway, and predicted protein-protein interaction data. We further propose an approach that effectively leverages both polygenic and locus-specific genetic signals by combining results across multiple gene prioritization methods, increasing confidence in prioritized genes. Using a large set of gold standard genes to evaluate our approach, we prioritize 8,402 unique gene-trait pairs with greater than 75% estimated precision across 113 complex traits and diseases, including known genes such as SORT1 for LDL cholesterol, SMIM1 for red blood cell count, and DRD2 for schizophrenia, as well as novel genes such as TTC39B for cholelithiasis. Our results demonstrate that a polygenic approach is a powerful tool for gene prioritization and, in combination with locus-specific signal, improves upon existing methods.
Prison population reductions and COVID-19: A latent profile analysis synthesizing recent evidence from the Texas state prison system
Authors: Vest Noel , Johnson Oshea , Nowotny Kathryn , Brinkley-Rubinstein Lauren 
Published: September 2020

ABSTRACTImportancePeople in prison are particularly vulnerable to infectious disease due to close living conditions and the lack of protective equipment. Public health professionals and prison administrators seek information to guide best practices regarding prison population to capacity rates for the COVID-19 outbreak.ObjectiveUsing latent profile analysis, we sought to characterize Texas prisons on levels of COVID-19 cases and deaths among incarcerated residents, and COVID-19 cases among prison staff.DesignThis observational study was a secondary data analysis of publicly available data from the Texas Department of Criminal Justice (TBDJ). Data were downloaded and analyzed on July 24, 2020. This project was completed in collaboration with the COVID Prison Project.SettingOne-hundred and three prisons in the state of Texas.ParticipantsThe unit of analysis is the individual prison units that comprise the TDCJ.ExposuresNoneMain Outcomes and MeasuresLatent profiles on levels of incarcerated resident COVID-19 cases, staff COVID-19 cases, and incarcerated resident COVID-19 deaths.ResultsWe identified relevant profiles from the data: a low outbreak profile, a high outbreak profile, and a high death profile. Additionally, current prison population and level of employee staffing predicted membership in the high outbreak and high death profiles when compared to the low outbreak profile.Conclusions and RelevanceHousing persons at 85% of prison capacity may minimize the risk of infection and death related to COVID-19. Implementing this 85% standard as an absolute minimum should be prioritized at prisons across the US.KEY POINTSQuestionIs there a population to capacity ratio for prisons to successfully reduce the number of COVID-19 infections and deaths among its incarcerated populations?FindingsThe prisons that were most effective in reducing prison outbreaks and deaths operated at 85% of their current capacity.MeaningPrisons should operate at 85% of capacity or less to successfully minimize the harmful effects of COVID-19 on incarcerated populations.
“Organ-in-a-column” coupled on-line with liquid chromatography-mass spectrometry
Authors: Kogler Stian , Aizenshtadt Aleksandra , Harrison Sean , Skottvoll Frøydis Sved , Berg Henriette Engen , Abadpour Shadab , Scholz Hanne , Sullivan Gareth , Thiede Bernd , Lundanes Elsa , Bogen Inger Lise , Krauss Stefan , Røberg-Larsen Hanne , Wilson Steven Ray 
Published: September 2020

AbstractOrganoids, i.e. laboratory-grown organ models developed from stem cells, are emerging tools for studying organ physiology, disease modeling and drug development. On-line analysis of organoids with mass spectrometry would provide analytical versatility and automation. To achieve these features with robust hardware, we have loaded liquid chromatography column housings with induced pluripotent stem cell (iPSC) derived liver organoids and coupled the “organ-in-a-column” units on-line with liquid chromatography-mass spectrometry (LC-MS). Liver organoids were co-loaded with glass beads to achieve an even distribution of organoids throughout the column while preventing clogging. The liver organoids were interrogated “on column” with heroin, followed by on-line monitoring of the drug’s phase 1 metabolism. Enzymatic metabolism of heroin produced in the “organ-in-a-column” units was detected and monitored using a triple quadrupole MS instrument, serving as a proof-of-concept for on-line coupling of liver organoids and mass spectrometry. Taken together, the technology allows direct integration of liver organoids with LC-MS, allowing selective and automated tracking of drug metabolism over time.
Action-value processing underlies the role of the dorsal anterior cingulate cortex in performance monitoring during self-regulation of affect
Authors: Bush Keith A. , James G. Andrew , Privratsky Anthony A. , Fialkowski Kevin P. , Kilts Clinton D. 
Published: September 2020

AbstractIn this study, we merged methods from engineering control theory, machine learning, and human neuroimaging to critically test the putative role of the dorsal anterior cingulate cortex (dACC) in goal-directed performance monitoring during an emotion regulation task. Healthy adult participants (n=94) underwent cued-recall and re-experiencing of their responses to affective image stimuli with concurrent functional magnetic resonance imaging and psychophysiological response recording. During cued-recall/re-experiencing trials, participants engaged in explicit self-regulation of their momentary affective state to match a pre-defined affective goal state. Within these trials, neural decoding methods measured affect processing from fMRI BOLD signals across the orthogonal affective dimensions of valence and arousal. Participants’ affective brain states were independently validated via facial electromyography (valence) and electrodermal activity (arousal) responses. The decoded affective states were then used to contrast four computational models of performance monitoring (i.e., error, predicted response outcome, action-value, and conflict) by their relative abilities to explain emotion regulation task-related dACC activation. We found that the dACC most plausibly encodes action-value for both valence and arousal processing. We also confirmed that dACC activation directly encodes affective arousal and also likely encodes recruitment of attention and regulation resources. Beyond its contribution to improving our understanding of the roles that the dACC plays in emotion regulation, this study introduced a novel analytical framework through which affect processing and regulation may be functionally dissociated, thereby permitting mechanistic analysis of real-world emotion regulation strategies, e.g., distraction and reappraisal, which are widely employed in cognitive behavioral therapy to address clinical deficits in emotion regulation.
Pseudomonas aeruginosainduced acute emphysema through bacterial secretion in mice
Authors: Zhu Yajie , Pan Shuming 
Published: September 2020

AbstractPulmonary emphysema is the major pathological feature of chronic obstructive pulmonary disease (COPD). Although the pathogenesis of emphysema is still not completely understood, but until now a bacterial cause has not really been considered. Recently, we found that the secretion from Pseudomonas aeruginosa could cause severe lung emphysema in mice rapidly. Since the bacterium is ubiquitous and secrets proteases, we hypothesized that direct P. aeruginosa airway infection would have a similar effect. To address this issue, we applied a unilateral lung injury model. First, we observed the dynamic pathophysiology change of acute emphysema. P. aeruginosa secretion was extracted and instilled intratracheally into the left lungs of C57BL/6 and C3H/HeJ mice, while the right lungs were saved as self-control. Alveolar diameter and lung compliance were measured. Later, we tested the effect of P. aeruginosa inoculation in normal C57BL/6 mice, immunosuppressed C57BL/6 mice, and C3H/HeJ (TLR4 deficient) mice. P. aeruginosa secretion extract caused acute panacinar emphysema and decreased dynamic lung compliance. Different types of emphysema are transformable. However, the P. aeruginosa infection could only elicit emphysema in immunosuppressed C57BL/6 mice and C3H/HeJ mice, indicating that normal immunity is essential to protect the hosts from emphysema. Emphysema induced by P. aeruginosa in mice recapitulates all the main features of human emphysema and COPD. Our finding filled a major gap in COPD pathogenesis. We believeP. aeruginosais the underlying cause of COPD.
GEM-based metabolic profiling for Human Bone Osteosarcoma under different glucose and glutamine availability
Authors: Weglarz-Tomczak Ewelina , Rijlaarsdam Demi J. , Tomczak Jakub M. , Brul Stanley 
Published: September 2020

AbstractCancer cell metabolism is dependent on cell-intrinsic factors like genetics, and cell-extrinsic factors like nutrient availability. In this context, understanding how these two aspects interact and how diet influences cellular metabolism is important for developing personalized treatment. In order to achieve this goal, genome-scale metabolic models (GEMs) are used, however, genetics and nutrient availability are rarely considered together. Here, we propose an integrated metabolic profiling, a framework that allows to enrich GEMs with metabolic gene expression data and information about nutrients. First, the RNA-seq is converted into Reaction Activity Score (RAS) to further scale reaction bounds. Second, nutrient availability is converted to Maximal Uptake Rate (MUR) to modify exchange reactions in a GEM. We applied our framework to the human osteosarcoma cell line (U2OS). Osteosarcoma is a common and primary malignant form of bone cancer with poor prognosis, and, as indicated in our study, a glutamine-dependent type of cancer.
B Cell Division Capacity in Germinal Centers Depends on Myc Transcript Stabilization Through m6A mRNA Methylation and IGF2BP3 Functions
Authors: Grenov Amalie C. , Moss Lihee , Edelheit Sarit , Cordiner Ross , Schmiedel Dominik , Biram Adi , Hanna Jacob H , Jensen Torben H , Schwartz Schraga , Shulman Ziv 
Published: September 2020

AbstractLong-lasting immunity from pathogens depends on the generation of protective antibodies through the germinal center (GC) reaction. The Myc gene produces highly short-lived transcripts which are essential for generation of high-affinity antibodies. mRNA lifetime is regulated by N6-methyladenosine (m6A)-modification of mRNAs through METTL3 activity; however, the role of this machinery in the GC remains unclear. Here, we find that m6A-modification of mRNAs is required for GC maintenance through Myc mRNA stabilization by the atypical m6A-interactor, IGF2BP3. MYC expression, activation of MYC transcriptional programs and cell-cycle progression were diminished in METTL3-deficient GC B cells. METTL3 attenuated Myc-transcript decay and overexpression of MYC in METTL3-deficient GC B cells restored the GC reaction. IGF2BP3 which was induced by CD40-signaling, reinforced MYC expression and MYC-related gene programs in GC B cells. Our findings explain how GC responses are maintained through regulation of Myc-transcript lifetime and expose new targets for manipulation in MYC-driven lymphoma.One Sentence SummaryGerminal centers depend on the m6A-machinery
cytomapper: an R/Bioconductor package for visualisation of highly multiplexed imaging data
Authors: Eling Nils , Damond Nicolas , Hoch Tobias , Bodenmiller Bernd 
Published: September 2020

SUMMARYHighly multiplexed imaging technologies enable spatial profiling of dozens of biomarkersin situ. Standard data processing pipelines quantify cell-specific features and generate object segmentation masks as well as multi-channel images. Therefore, multiplexed imaging data can be visualised across two layers of information: pixel-intensities represent the spatial expression of biomarkers across an image while segmented objects visualise cellular morphology, interactions and cell phenotypes in their microenvironment.Here we describecytomapper, a computational tool that enables visualisation of pixel- and cell-level information obtained by multiplexed imaging. The package is written in the statistical programming language R, integrates with the image and single-cell analysis infrastructure of the Bioconductor project, and allows visualisation of single to hundreds of images in parallel. Usingcytomapper, expression of multiple markers is displayed as composite images, segmentation masks are coloured based on cellular features, and selected cells can be outlined in images based on their cell type, among other functions. We illustrate the utility ofcytomapperby analysing 100 images obtained by imaging mass cytometry from a cohort of type 1 diabetes patients and healthy individuals. In addition,cytomapperincludes a Shiny application that allows hierarchical gating of cells based on marker expression and visualisation of selected cells in corresponding images. Together,cytomapperoffers tools for diverse image and single-cell visualisation approaches and supports robust cell phenotyping via gating.
Therapeutic assessment of targeting ASNS combined with L-Asparaginase treatment in solid tumors and investigation of resistance mechanisms
Authors: Apfel Verena , Begue Damien , Cordo Valentina , Holzer Laura , Martinuzzi Laetitia , Buhles Alexandra , Kerr Grainne , Barbosa Ines , Naumann Ulrike , Piquet Michelle , Ruddy David , Weiss Andreas , Ferretti Stephane , Almeida Reinaldo , Bonenfant Debora , Tordella Luca , Galli Giorgio G. 
Published: September 2020

AbstractAsparagine deprivation by L-Asparaginase (L-ASNase) is an effective therapeutic strategy in Acute Lymphoblastic Leukemia, with resistance occurring due to upregulation of ASNS, the only human enzyme synthetizing Asparagine1. L-Asparaginase efficacy in solid tumors is limited by dose-related toxicities2. Large-scale loss of function genetic in vitro screens identified ASNS as a cancer dependency in several solid malignancies3,4. Here we evaluate the therapeutic potential of targeting ASNS in melanoma cells. While we confirm in-vitro dependency on ASNS silencing, this is largely dispensable for in vivo tumor growth, even in face of asparagine deprivation, prompting us characterize such resistance mechanism to devise novel therapeutic strategies. Usingex vivoquantitative proteome and transcriptome profiling, we characterize the compensatory mechanism elicited by ASNS knockout melanoma cells allowing their survival. Mechanistically, a genome-wide CRISPR screen revealed that such resistance mechanism is elicited by a dual axis: GCN2-ATF4 aimed at restoring amino acids levels and MAPK-BCLXL to promote survival. Importantly, pharmacological inhibition of such nodes synergizes with L-Asparaginase-mediated Asparagine deprivation in ASNS deficient cells suggesting novel potential therapeutic combinations in melanoma.