bluuebunny/crossref_metadata_2025_split huggingface dataset:
Labeling fibrin fibers with microparticle sized beads alter single fibrin fiber lysis, external clot lysis, and produce large fibrin aggregates upon lysis
Authors: Helms Christine Carlisle , Rimi Najnin 
Published: September 2021

AbstractBackgroundFluorescent beads are often used as a tool for visualizing fibrin fibers and can mimic the size of microparticles in the blood. Studies showed microparticles alter the appearance and behavior of whole blood clot systems.ObjectivesHere we investigate the effect of beads on fibrin fiber lysis and extensibility to enhance understanding of this common research technique and as a biomimetic system for fibrin-microparticle interaction.MethodsWe used fluorescence microscopy, atomic force microscopy (AFM), and scanning electron microscopy (SEM) to quantify changes in lysis, extensibility, and clot structure of fibrin fibers and clots in the presence and absence of beads.Results and ConclusionsFibrin clot structure and lysis were altered in the presence of beads. Fibrin clots formed with beads had a higher fiber density, smaller fibers, and smaller pores. The rate of lysis for clots was reduced when beads were present. Lysis of bead-labeled individual fibers showed that beads, at concentrations similar to those reported for microparticles in the blood, cause a subset of fibers to resist lysis. In the absence of beads, all fibers lyse. These results demonstrate that beads alter fiber lysis through both a change in fibrin clot structure as well as changes to individual fiber lysis behavior. Additionally, the lysis of clots with beads produced large fibrin aggregates. This data encourages researchers to use careful consideration when labeling fibrin fibers with fluorescent beads and suggests that particles binding fibrin(ogen) in the bloodstream may be an underappreciated mechanism increasing the risk of thrombosis.
Dominant negative effects ofSCN5Amissense variants
Authors: O’Neill Matthew J. , Muhammad Ayesha , Li Bian , Wada Yuko , Hall Lynn , Solus Joseph F. , Short Laura , Roden Dan M. , Glazer Andrew M. 
Published: September 2021

AbstractIntroductionUp to 30% of patients with Brugada Syndrome (BrS) carry loss-of-function (LoF) variants in the cardiac sodium channel geneSCN5A. Recent studies have suggested that theSCN5Aprotein product NaV1.5 can form dimers and exert dominant negative effects.MethodsWe identified 35 LoF variants (<10% peak current compared to wild type (WT)) and 15 partial LoF variants (10-50% peak current compared to WT) that we assessed for dominant negative behavior.SCN5Avariants were studied in HEK293T cells alone or in heterozygous co-expression with WTSCN5Ausing automated patch clamp. To assess clinical risk, we compared the prevalence of dominant negative vs. putative haploinsufficient (frameshift/splice site) variants in a BrS case consortium and the gnomAD population database.ResultsIn heterozygous expression with WT, 32/35 LoF variants and 6/15 partial LoF showed reduction to <75% of WT-alone peak INa, demonstrating a dominant negative effect. Carriers of dominant negative LoF missense variants had an enriched disease burden compared to putative haploinsufficient variant carriers (2.7-fold enrichment in BrS cases, p=0.019).ConclusionsMostSCN5Amissense LoF variants exert a dominant negative effect. Cohort analyses reveal that this class of variant confers an especially high burden of BrS.
Structural Mechanics of the Alpha-2-Macroglobulin Transformation
Authors: Arimura Yasuhiro , Funabiki Hironori 
Published: September 2021

SummaryAlpha-2-Macroglobulin (A2M) is the critical pan-protease inhibitor of the innate immune system. When proteases cleave the A2M bait region, global structural transformation of the A2M tetramer is triggered to entrap the protease. The structural basis behind the cleavage-induced transformation and the protease entrapment remains unclear. Here, we report cryo-EM structures of native- and intermediate-forms of the Xenopus laevis egg A2M homolog (A2Moo or ovomacroglobulin) tetramer at 3.7-4.1 Å and 6.4 Å resolution, respectively. In the native A2Moo tetramer, two pairs of dimers arrange into a cross-like configuration with four 60 Å-wide bait-exposing grooves. Each bait in the native form threads into an aperture formed by three macroglobulin domains (MG2, MG3, MG6). The bait is released from the narrowed aperture in the induced protomer of the intermediate form. We propose that the intact bait region works as a “latch-lock” to block futile A2M transformation until its protease-mediated cleavage.
Bifunctional Peptide that Anneals to Damaged Collagen and Clusters TGF-β Receptors Enhances Wound Healing
Authors: Chattopadhyay Sayani , Teixeira Leandro B. C. , Kiessling Laura L. , McAnulty Jonathan F. , Raines Ronald T. 
Published: September 2021

ABSTRACTTransforming growth factor-β (TGF-β) plays important roles in wound healing. The activity of TGF-β is initiated upon binding of the growth factor to extracellular domains of its receptors. We sought to facilitate activation by clustering these extracellular domains. To do so, we used a known peptide that binds to TGF-β receptors without diminishing their affinity for TGF-β. We conjugated this peptide to a collagen-mimetic peptide that can anneal to damaged collagen in a wound bed. We find that the conjugate enhances collagen deposition and wound closure in mice in a manner consistent with the clustering of TGF-β receptors. This strategy provides a means to upregulate the TGF-β signaling pathway without adding exogenous TGF-β and could inspire means to treat severe wounds.TOC Graphic
Zebrafish Information Network, the knowledgebase for Danio rerio research
Authors: Bradford Yvonne M. , Van Slyke Ceri E. , Singer Amy , Paddock Holly , Eagle Anne , Fashena David , Howe Douglas G. , Frazer Ken , Martin Ryan , Pich Christian , Ramachandran Sridhar , Ruzicka Leyla , Westerfield Monte 
Published: September 2021

AbstractThe Zebrafish Information Network (ZFIN, zfin.org) is the central repository for zebrafish genetic and genomic data. ZFIN expertly curates, integrates, and displays zebrafish data including genes, alleles, human disease models, gene expression, phenotype, gene function, orthology, morpholino, CRISPR, TALEN, and antibodies. ZFIN makes zebrafish research data Findable, Accessible, Interoperable, and Reusable (FAIR) through nomenclature, curatorial and annotation activities, web interfaces, and data downloads. ZFIN is a founding member of the Alliance of Genome Resources, providing zebrafish data for integration into the cross species platform as well as contributing to model organism data harmonization efforts.
Plasma S-Adenosylmethionine is Associated with Lung Injury in COVID-19
Authors: Kryukov Evgeny , Ivanov Alexander , Karpov Vladimir , Alexandrin Valery , Dygai Alexander , Kruglova Maria , Kostiuchenko Gennady , Kazakov Sergei , Kubatiev Aslan 
Published: September 2021

AbstractObjectiveS-Adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are indicators of global transmethylation and may play an important role as markers of severity of COVID-19.MethodsThe levels of plasma SAM and SAH were determined in patients admitted with COVID-19 (n = 56, mean age = 61). Lung injury was identified by computed tomography (CT) in accordance with the CT0-4 classification.ResultsSAM was found to be a potential marker of lung damage risk in COVID-19 patients (SAM > 80 nM; CT3,4 vs. CT 0-2: relative ratio (RR) was 3.0; p = 0.0029). SAM/SAH > 6.0 was also found to be a marker of lung injury (CT2-4 vs. CT0,1: RR = 3.47, p = 0.0004). Interleukin-6 (IL-6) levels were associated with SAM (ρ = 0.44, p = 0.01) and SAH (ρ = 0.534, p = 0.001) levels.ConclusionsHigh SAM levels and high methylation index are associated with the risk of lung injury in COVID-19 patients. The association of SAM and SAH with IL-6 indicates an important role of transmethylation in the development of cytokine imbalance in COVID-19 cases.
Low Gut Ruminococcaceae Levels are Associated with Occurrence of Antibiotic-associated Diarrhea
Authors: Gu Xiaoqiong , Sim Jean XY , Lee Wei Lin , Cui Liang , Chan Yvonne FZ , Chang Ega Danu , Teh Yii Ean , Zhang An-Ni , Armas Federica , Chandra Franciscus , Chen Hongjie , Zhao Shijie , Lee Zhanyi , Thompson Janelle R. , Ooi Eng Eong , Low Jenny G. , Alm Eric J. , Kalimuddin Shirin 
Published: September 2021

AbstractPatients receiving antibiotics often suffer from antibiotic-associated diarrhea (AAD). AAD is of clinical significance as it can result in premature antibiotic discontinuation and suboptimal treatment of infection. The drivers of AAD however, remain poorly understood. We sought to understand if differences in the gut microbiome, both at baseline and during antibiotic administration, would influence the development of AAD. We administered a 3-day course of oral amoxicillin-clavulanate to 30 healthy adult volunteers, and performed a detailed interrogation of their stool microbiome at baseline and up to 4-weeks post antibiotic administration, using 16S rRNA gene sequencing. Lower levels of Ruminococcaceae were significantly and consistently observed from baseline till Day 7 in participants who developed AAD. The probability of AAD could be predicted based on qPCR-derived levels of Faecalibacterium prausnitzii, the most dominant species within the Ruminococcaceae family. Overall, participants who developed AAD experienced a greater decrease in microbial diversity during antibiotic dosing. Our findings suggest that a lack of gut Ruminococcaceae at baseline influences development of AAD. In addition, quantification of F. prausnitzii in stool prior to antibiotic administration may help identify patients at risk of AAD, and aid clinicians in devising individualised treatment regimens to minimise such adverse effects.
Using one–to–many urine proteome comparisons to provide clues for fever of unknown origin
Authors: Zhao Chenyang , Wei Lilong , Wei Jing , Gao Youhe 
Published: September 2021

AbstractObjectiveTo provide diagnostic evidence and clues for patients with fever of unknown origin (FUO) through urine proteomics analysis.MethodsUrine samples of FUO were one–to–many analysed by using liquid chromatography tandem mass spectrometry(LC–MS/MS) to identify differential proteins and related biological pathways. One–to–many analysis means a comparative analysis of one sample to many controls.ResultsWe observed biological pathways related to fever, such as LXR/RXR activation, FXR/RXR activation and acute phase response signaling, etc., which indicates that urine can obviously distinguish disease from health status. In addition, we found that the results of each sample were different, which highlight the necessity of one–to–many analysis.ConclusionsThe combined method of urine proteomics and one–to–many analysis can provide clues for FUO, and might also be applied to the exploration of any unknown disease.
Determining cardiac structure by diffuse reflectance of different wavelengths
Authors: Gemmell Philip , Bishop Martin 
Published: September 2021

AbstractCatheter ablation in patients suffering from chronic arrhythmias requires detailed knowledge of the underlying cardiac anatomy; such real-time, high resolution mapping is currently unavailable in a clinical setting. We present here preliminary work towards a novel optical strategy based on diffuse optical reflectance to provide quantitative anatomical measurements of the cardiac structure, including tissue thickness and presence of scar. An in-depth literature search is conducted to collate available experimental data regarding optical parameters in cardiac tissue and scar. Computational simulations of photon movement through cardiac tissue using Monte Carlo modelling are performed, with analysis being focussed on the effects on surface emission profiles of (i) optical parameters; (ii) tissue thickness; (iii) presence of scar. Our results demonstrate (i) sensitivity of the approach to changes in optical parameters within tissue, (ii) difference of results depending on light wavelength. These suggest that this can be used to detect cardiac anatomical structure to a depth of ∼ 2 mm, for both thickness of cardiac tissue and presence of scar. This study demonstrates the feasibility of using diffuse optical reflectance to determine cardiac structure, enabling a potential route for high-resolution, real-time structural information to guide catheter ablation and similar surgeries.
AI-driven high-throughput automation of behavioral analysis and dual-channel wireless optogenetics for multiplexing brain dynamics
Authors: Kim Woo Seok , Liu Jianfeng , Li Qinbo , Hong Sungcheol , Qi Kezhuo , Cherukuri Rahul , Yoon Byung-Jun , Moscarello Justin , Choe Yoonsuck , Maren Stephen , Park Sung Il 
Published: September 2021

AbstractAdvances in behavioral optogenetics are limited by the absence of high-throughput pipelines for the automated analysis of behavior in freely behaving animals. Although a variety of AI algorithms has been proposed that enable automation of behavioral analysis, existing methods are generally low-throughput. In addition, optogenetic manipulation of neural circuits typically requires physical tethers to light sources, which limits the number of brain areas that can be targeted and thus constrains behavioral testing. Here, we develop a new wireless platform that combines a battery-free dual-channel optogenetic implant with an AI algorithm for high-throughput behavioral analysis. In our platform, a customized AI algorithm detected and quantified freezing behavior of rats that had undergone fear conditioning. Notably, our platform allows up to four enclosures to be monitored simultaneously. Wireless dual-channel optogenetic devices were implanted in the basolateral amygdala (BLA) to permit independent modulation of BLA principal neurons (red light, AAV-CaMKII-JAWS) or BLA interneurons (blue light, AAV-mDlx-ChR2) in freely behaving animals. In vivo validation with behaving rats demonstrates the utility of the telemetry system for large-scale optogenetic studies.SignificanceAI algorithms can enable automation of behavioral analysis and thereby facilitate the progress on behavioral optogenetics. Successful integration of advanced wireless dual-channel optoelectronic devices with biological systems can also yield new tools and techniques for neuroscience research, particularly in the context of techniques for optogenetics. Here, we propose a new approach that combines an advanced AI algorithm with a low power wireless telemetry system, yielding powerful capabilities in the understanding of brain functions and the evaluation of the behavioral consequences of neural circuit manipulations. In vivo studies using optimized systems demonstrate high-throughput automation of behavioral manipulation and analysis via AI-powered wireless telemetry.
Leveling up: improving power in fMRI by moving beyond cluster-level inference
Authors: Noble Stephanie , Mejia Amanda F. , Zalesky Andrew , Scheinost Dustin 
Published: September 2021

AbstractInference in neuroimaging commonly occurs at the level of “clusters” of neighboring voxels or connections, thought to reflect functionally specific brain areas. Yet increasingly large studies reveal effects that are shared throughout the brain, suggesting that reported clusters may only reflect the “tip of the iceberg” of underlying effects. Here, we empirically compare power of traditional levels of inference (edge and cluster) with broader levels of inference (network and whole-brain) by resampling functional connectivity data from the Human Connectome Project (n=40, 80, 120). Only network- and whole brain-level inference attained or surpassed “adequate” power (β=80%) to detect an average effect, with almost double the power for network-compared with cluster-level procedures at more typical sample sizes. Likewise, effects tended to be widespread, and more widespread pooling resulted in stronger magnitude effects. Power also substantially increased when controlling FDR rather than FWER. Importantly, there may be similar implications for task-based activation analyses where effects are also increasingly understood to be widespread. However, increased power with broader levels of inference may diminish the specificity to localize effects, especially for non-task contexts. These findings underscore the benefit of shifting the scale of inference to better capture the underlying signal, which may unlock opportunities for discovery in human neuroimaging.
Salt leverages polyethylene terephthalate hydrolase (PETase) enzymatic activity via the predicted conformational switch
Authors: Shiryaev Sergey A. , Cieplak Piotr , Chernov Andrei V. 
Published: September 2021

AbstractPlastic pollution spawned a global challenge caused by the environmental accumulation of polyethylene terephthalate (PET) plastics. Ongoing remediation efforts using microbial and engineered PET hydrolyzing enzymes (PETases) are hindered by slow depolymerization activities. Here, we report the optimized reaction conditions that leveraged the PETase hydrolase activity 2 to 3.8-fold in the presence of high NaCl concentrations. Molecular dynamics simulations (MDS) were applied to model salt-dependent conformational changes of the PETase enzyme bound to a 3-unit PET polymer. MDS demonstrated that PETase interaction with flanking polymer units exhibited a striking structural disparity at low and high salt concentrations. At low salt concentrations, flanking polymer units displayed significant bending. In contrast, flanking units extended at high salt concentrations, thus residues D206, H237, and S160 of the catalytic triad positioned in close vicinity of the scissile ester bond of the polymer substrate. The resulting high salt-specific enzyme/substrate geometry can potentially facilitate hydrolysis. We theorized that a salt-dependent conformational switch could attenuate the enzyme to a broad range of natural and artificial polymers consumed as carbon sources. Altogether, new knowledge may advance the engineering of PET hydrolase enzymes and benefit bioconversion programs.
State-dependent representations of mixtures by the olfactory bulb
Authors: Adefuin Aliya Mari , Lindeman Sander , Reinert Janine Kristin , Fukunaga Izumi 
Published: September 2021

AbstractSensory systems are often tasked to analyse complex signals from the environment, separating relevant from irrelevant parts. This process of decomposing signals is challenging when a mixture of signals does not equal the sum of its parts, leading to an unpredictable corruption of signal patterns. In olfaction, nonlinear summation is prevalent at various stages of sensory processing. Here, we investigate how the olfactory system deals with binary mixtures of odours under different brain states, using two-photon imaging of olfactory bulb (OB) output neurons. Unlike previous studies using anaesthetised animals, we found that mixture summation is more linear in the early phase of evoked responses in awake, head-fixed mice performing an odour detection task, due to dampened responses. Despite this, and responses being more variable, decoding analyses indicated that the data from behaving mice was well discriminable. Curiously, the time course of decoding accuracy did not correlate strictly with the linearity of summation. Further, a comparison with naïve mice indicated that learning to accurately perform the mixture detection task is not accompanied by more linear mixture summation. Finally, using a simulation, we demonstrate that, while saturating sublinearity tends to degrade the discriminability, the extent of the impairment may depend on other factors, including pattern decorrelation. Altogether, our results demonstrate that the mixture representation in the primary olfactory area is state-dependent, but the analytical perception may not strictly correlate with linearity in summation.
Dr. Sim: Similarity Learning for Transcriptional Phenotypic Drug discovery
Authors: Wei Zhiting , Zhu Sheng , Chen Xiaohan , Zhu Chenyu , Duan Bin , Liu Qi 
Published: September 2021

AbstractTranscriptional phenotypic drug discovery has achieved great success, and various compound perturbation-based data resources, such as Connectivity Map (CMap) and Library of Integrated Network-Based Cellular Signatures (LINCS), have been presented. Computational strategies fully mining these resources for phenotypic drug discovery have been proposed, and among them, a fundamental issue is to define the proper similarity between the transcriptional profiles to elucidate the drug mechanism of actions and identify new drug indications. Traditionally, this similarity has been defined in an unsupervised way, and due to the high dimensionality and the existence of high noise in those high-throughput data, it lacks robustness with limited performance. In our study, we present Dr. Sim, which is a general learning-based framework that automatically infers similarity measurement rather than being manually designed and can be used to characterize transcriptional phenotypic profiles for drug discovery with generalized good performance. We evaluated Dr. Sim on comprehensively publicly available in vitro and in vivo datasets in drug annotation and repositioning using high-throughput transcriptional perturbation data and indicated that Dr. Sim significantly outperforms the existing methods and is proved to be a conceptual improvement by learning transcriptional similarity to facilitate the broad utility of high-throughput transcriptional perturbation data for phenotypic drug discovery. The source code and usage of Dr. Sim is available at https://github.com/bm2-lab/DrSim/.
NF90 Interacts with Components of RISC and Modulates Association of Ago2 with mRNA
Authors: Grasso Giuseppa , Akkawi Charbel , Franckhauser Celine , Nait-Saidi Rima , Bello Maxime , Barbier Jérôme , Kiernan Rosemary 
Published: September 2021

ABSTRACTNuclear Factor 90 (NF90) is a double-stranded RNA-binding protein involved in a multitude of different cellular mechanisms such as transcription, translation, viral infection and mRNA stability. Recent data suggest that NF90 might influence the abundance of target mRNAs in the cytoplasm through miRNA- and Argonaute 2 (Ago2)-dependent activity. Here, we identified the interactome of NF90 in the cytoplasm, which revealed several components of the RNA-induced silencing complex (RISC) and associated factors. Co-immunoprecipitation analysis confirmed the interaction of NF90 with the RISC-associated RNA helicase, Moloney leukemia virus 10 (MOV10), and other proteins involved in RISC-mediated silencing, including Ago2. Furthermore, NF90 association with MOV10 and Ago2 was found to be RNA-dependent. Glycerol gradient sedimentation of NF90 immune complexes indicates that these proteins occur in the same protein complex. At target RNAs predicted to bind both NF90 and MOV10 in their 3’ UTRs, NF90 association was increased upon loss of MOV10 and vice versa, suggesting that the two proteins may compete for the binding of common target mRNAs. Interestingly, loss of NF90 led to an increase in association of Ago2 as well as a decrease in the abundance of the target mRNA. Similarly, during hypoxia, the binding of Ago2 to vascular endothelial growth factor (VEGF) mRNA increased after loss of NF90, while the level of VEGF mRNA decreased. These findings suggest a role for NF90 in the regulation of RISC-mediated silencing which stabilizes target mRNAs, such as VEGF, during cancer-induced hypoxia.