bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the Neurotropic and Anti-inflammatory Effects of Neuroelectrode Functionalisation with a Heparan Sulphate Mimetic
Authors: Vallejo-Giraldo Catalina , Mohand Idir Ouidja , Huynh Minh Bao , Trotier Alexandre , Krukiewicz Katarzyna , Pallipurath Anuradha R , Flannery Andrea , Kilcoyne Michelle , Pandit Abhay , Papy-Garcia Dulce , Biggs Manus Jonathan Paul 
Published: May 2021

AbstractFurther in the search for biomimicry of the properties analogous to neural tissues, and with an ultimate goal of mitigating electrode deterioration via reactive host cell response and glial scar formation, the bio-functionalisation of PEDOT:PTS neural coating is here presented using a heparan mimetic termed (HM) F6. A sulphated mimetic polyanion, with a potential role in neuromodulation in neurodegenerative diseases, and used here for the first time as neural coating.This work acts as a first step towards the use of HM biological dopants, to enhance neuroelectrode functionality, to promote neural outgrowth and to maintain minimal glial scar formation in vitro at the neural-interface. Further, this study opens new possibilities for the evaluation of glycan mimetics in neuroelectrode functionalisation.
Early life gut microbiome dynamics mediate maternal effects on infant growth in vervet monkeys
Authors: Petrullo Lauren , Baniel Alice , Jorgensen Matthew J. , Sams Sierra , Snyder-Mackler Noah , Lu Amy 
Published: May 2021

ABSTRACTBackgroundMaternal parity is associated with variation in infant growth across mammals, but the mechanisms underlying this relationship are unclear. Given emerging links between growth and the microbiome, and the importance of maternal microbiota in establishing this community, the assembly of the infant gut microbiome may be a mediator of parity effects on infant growth.ResultsHere, we analyzed 118 fecal and milk samples from mother-infant vervet monkey dyads across the first 6 months postpartum in a population with high growth-associated infant mortality. Despite poorer milk production, infants born to low parity females were larger at 6 months of age than their counterparts and exhibited divergent patterns in gut microbiome assembly. Gut microbiome alpha diversity increased rapidly from the first days of life to 4 months old in all infants, but infants born to low parity females exhibited reduced gut microbiome alpha diversity during early life. At the taxonomic level, infants broadly exhibited a shift fromBacteroides fragilistoPrevotelladominance. Infants of low parity females housed moreB. fragilisin their guts, andB. fragilisdominance drove reduced alpha diversity. Maternal vertical transmission to the infant gut was greater from milk than from the maternal gut, and was greatest among infants born to low parity females.B. fragiliswas 15-fold more abundant in milk than in the maternal gut and was greater in the milk of low parity females, suggesting that milk may be the primary maternal reservoir ofB. fragilis. Path analyses demonstrated that both infant gut alpha diversity andB. fragilismediated parity effects on postnatal growth: infants were larger at 6 months old if they exhibited reduced alpha diversity and a greater relative abundance ofB. fragilisduring early life.ConclusionThe first days of life are a critical period of infant gut microbiome organization during which the establishment of a less diverse, milk-oriented microbial community abundant inB. fragilispromotes growth among infants born to reproductively inexperienced females.
Impacts on the structure-function relationship of SARS-CoV-2 spike by B.1.1.7 mutations
Authors: Yang Tzu-Jing , Yu Pei-Yu , Chang Yuan-Chih , Liang Kang-Hao , Tso Hsian-Cheng , Ho Meng-Ru , Chen Wan-Yu , Lin Hsiu-Ting , Wu Han-Chung , Hsu Shang-Te Danny 
Published: May 2021

AbstractThe UK variant of the severe acute respiratory syndrome coronavirus (SARS-CoV-2), known as B.1.1.7, harbors several point mutations and deletions on the spike (s) protein, which potentially alter its structural epitopes to evade host immunity while enhancing host receptor binding. Here we report the cryo-EM structures of the S protein of B.1.1.7 in its apo form and in the receptor ACE2-bound form. One or two of the three receptor binding domains (RBDs) were in the open conformation but no fully closed form was observed. In the ACE-bound form, all three RBDs were engaged in receptor binding. The B.1.1.7-specific A570D mutation introduced a salt bridge switch that could modulate the opening and closing of the RBD. Furthermore, the N501Y mutation in the RBD introduced a favorable π-π interaction manifested in enhanced ACE2 binding affinity. The N501Y mutation abolished the neutralization activity of one of the three potent neutralizing antibodies (nAbs). Cryo-EM showed that the cocktail of other two nAbs simultaneously bound to all three RBDs. Furthermore, the nAb cocktail synergistically neutralized different SARS-CoV-2 pseudovirus strains, including the B.1.1.7.
Novel Interpretable Tissue-Specific and Multi-Tissue Transcriptomic Clocks to Infer Aging Mechanisms
Authors: Gupta Aayush , Lu Mindren , Sun Jessica 
Published: May 2021

1.AbstractAging is characterized as a progressive decline in fitness that ultimately results in death. We set out to build both tissue-specific and multi-tissue transcriptomic clocks to make global tissue age predictions in individuals from GTEx. Existing work in the field primarily uses epigenetic clocks as predictors of age, but these models have known issues and are significantly less interpretable than their transcriptomic counterparts. Due to their transcriptomic nature, we can use these models to directly infer mechanisms of aging from their features. Linear regression remains the current standard analysis technique, but we improved upon its baseline performance with modern techniques, exploring both XGBoost and MLPs. We also experimented with using deconvolved cell data for predictions, which account for cellular composition and reduce signal distortion from rare cell types. Since it is known that the heterogeneity of cell types in particular tissues can lead to noise in these models, we proposed using deconvolution as a potential remedy for this problem.Our results found that MLPs are not well suited for the task due to a lack of training data, but the use of XGBoost is effective at improving the baseline performance of predictions of existing tissue-specific clocks. These models allowed us to directly compute genes most important to age prediction in our models, and we showed that multiple genes found have been independently identified elsewhere to show evidence of correlation with age. Given the small size of our datasets, we were unable to make conclusive determinations about multi-tissue predictors, but preliminary results suggest that the technique shows promise and is worthy of future investigation. Likewise, given our limited deconvolved cell data, we did not currently observe strong results, but we again note that this is an area in need of further investigation.By improving upon the performance of existing models, we demonstrated that a novel machine learning technique, XGBoost, can be an effective technique to further our understanding of aging mechanisms by extraction of the most relevant genes found in those models. This is significant because the genetic causes of aging are still not fully understood, and research in the field of aging is lacking in comparison to other domains. As the problem of identifying tissues that age at different rates is of specific interest, our tissue-specific models potentially have other applications in this domain, including informing pathologies in tissues that are found to be aging faster, or analyzing how people with similar ages can have vastly different tissue ages. An extended technical presentation of this work can be found here, and a highly simplified non-technical overview presentation can be found here.
Dissecting the clonality of I1 plasmids using ORF-based binarized structure network analysis of plasmids (OSNAp)
Authors: Suzuki Masahiro , Norizuki Chihiro , Wachino Jun-ichi , Kawamura Kumiko , Nagano Noriyuki , Nagano Yukiko , Hayashi Wataru , Kimura Kouji , Doi Yohei , Arakawa Yoshichika 
Published: May 2021

AbstractPhylogenetic relationship of 97 I1 plasmids harboring blaCTX-M genes encoding extended-spectrum beta-lactamase (ESBL) was analyzed using the ORF-based binarized structure network analysis of plasmids (OSNAp). The majority of plasmids carrying blaCTX-M-1 or blaCTX-M-8, ESBL genes primarily associated with domestic animals, were clonal. On the other hand, plasmids carrying blaCTX-M-14 or blaCTX-M-15, identified from both humans and domestic animals, were diverse in their contents. The findings suggest that circulation of I1 plasmids among humans and animals may contribute to their diversity.
Nanopore Sequencing of SARS-CoV-2: Comparison of Short and Long PCR-tiling Amplicon Protocols
Authors: Brejová Broňa , Boršová Kristína , Hodorová Viktória , Čabanová Viktória , Gafurov Askar , Fričová Dominika , Neboháčová Martina , Vinař Tomáš , Klempa Boris , Nosek Jozef 
Published: May 2021

AbstractSurveillance of the SARS-CoV-2 variants including the quickly spreading mutants by rapid and near real-time sequencing of the viral genome provides an important tool for effective health policy decision making in the ongoing COVID-19 pandemic. Here we evaluated PCR-tiling of short (∼400-bp) and long (∼2 and ∼2.5-kb) amplicons combined with nanopore sequencing on a MinION device for analysis of the SARS-CoV-2 genome sequences. Analysis of several sequencing runs demonstrated that using the long amplicon schemes outperforms the original protocol based on the 400-bp amplicons. It also illustrated common artefacts and problems associated with this approach, such as uneven genome coverage, variable fraction of discarded sequencing reads, as well as the reads derived from the viral sub-genomic RNAs and/or human and bacterial contamination.
Injectable Progranulin-derivative Atsttrin loaded Protein Engineered Gels for Post Traumatic Osteoarthritis
Authors: Katyal Priya , Hettinghouse Aubryanna , Meleties Michael , Chen Changhong , Cui Min , Sun Guodong , Hasan Sadaf , Menon Rajiv , Lin Bonnie , Regatte Ravinder , Liu Chuan-ju , Montclare Jin Kim 
Published: May 2021

AbstractProtein-based biomaterials offer several advantages over synthetic materials, owing to their unique stimuli-responsive properties, biocompatibility and modular nature. We have successfully developed protein block polymers that consist of elastin like polypeptide (E) and the coiled-coil domain of cartilage oligomeric matrix protein (C). Here, we demonstrate that E5C, a construct consisting of five repeats of E and a single domain of C, is capable of forming a porous networked gel at physiological temperature, making it an excellent candidate for injectable biomaterials. Combination of E5C with Atsttrin, a chondroprotective engineered derivative of anti-inflammatory growth factor progranulin (PGRN), provides a unique biochemical and biomechanical environment to protect against post-traumatic osteoarthritis (PTOA) onset and progression. E5C gel was demonstrated to provide prolonged release of Atsttrin and inhibit chondrocyte catabolism while facilitating anabolic signaling in vitro. We also provide in vivo evidence that prophylactic and therapeutic application of Atsttrin-loaded E5C hydrogels protected against PTOA onset and progression in a rabbit anterior cruciate ligament transection model. Collectively, we have developed a unique protein-based gel capable of minimally invasive, sustained delivery of prospective therapeutics, particularly the PGRN-derivative Atsttrin, for prevention of OA onset and progression.
Fluorescence-Activated Droplet Sorting of Polyethylene Terephthalate-degrading Enzymes
Authors: Qiao Yuxin , Hu Ran , Chen Dongwei , Wang Li , Fu Ye , Li Chunli , Dong Zhiyang , Weng Yunxuan , Du Wenbin 
Published: May 2021

AbstractEnzymes that can decompose synthetic plastics such as polyethylene terephthalate (PET) are urgently needed. However, a bottleneck remains due to a lack of techniques for detecting and sorting environmental microorganisms with vast diversity and abundance. Here, we developed a fluorescence-activated droplet sorting (FADS) pipeline for high-throughput screening of PET-degrading microorganisms or enzymes (PETases). The pipeline comprises three steps: generation and incubation of droplets encapsulating single cells, picoinjection of fluorescein dibenzoate (FDBz) as the fluorogenic probe, and screening of droplets to obtain PET-degrading cells. We characterized critical factors associated with this method, including specificity and sensitivity for discriminating PETase from other enzymes. We then optimized its performance and compatibility with environmental samples. The system was used to screen a wastewater sample from a PET textile mill. We successfully obtained PET-degrading species from nine different genera. Moreover, two putative PETases from isolates Kineococcus endophyticus Un-5 and Staphylococcus epidermidis Un-C2-8 were genetically derived, heterologously expressed, and preliminarily validated for PET-degrading activities. We speculate that the FADS pipeline can be widely adopted to discover new PET-degrading microorganisms and enzymes in various environments and may be utilized in the directed evolution of PETases using synthetic biology.
Single-cell epigenomic tracing of lifelong endothelial cell plasticity across mouse organs
Authors: Yu Xianhong , Liu Yaxi , Liu Xiaoge , Xiong Haiqing , He Aibin 
Published: May 2021

AbstractEndothelial cells (ECs) across ages and tissues are highly heterogeneous in developmental origins, structures, functions, and cellular plasticity. Here, we applied CoBATCH for single-cell epigenomic tracing of dynamic EC lineage histories in five mouse organs from development to ageing. Our analyses showed that epigenomic memory reflects both developmental origins and tissue-restricted specialization of EC sublineages but with varying time lengths across organs. To gain insights into cellular plasticity of ECs, we identified bivalent chromatin occupancy of otherwise mutually exclusive EC- (ERG) and mesenchymal-specific (TWIST1/SNAI1) transcription factors promoting endothelial-to-mesenchymal transition. We further revealed that pseudotime trajectories by histone modifications H3K36me3 and H3K27ac faithfully recapitulate short- and long-range EC fate change over senescence, respectively. Together, our data provide a unique exploration of chromatin-level cell fate regulation of organotypic EC lineages across the lifespan.One-Sentence SummarySingle-cell chromatin binding is examined for tracing endothelial cell lineages in mouse organs across the lifespan.
Predicting the N400 ERP component using the Sentence Gestalt model trained on a large scale corpus
Authors: Lopopolo Alessandro , Rabovsky Milena 
Published: May 2021

AbstractThe N400 component of the event related brain potential is widely used to investigate language and meaning processing. However, despite much research the component’s functional basis remains actively debated. Recent work showed that the update of the predictive representation of sentence meaning (semantic update, or SU) generated by the Sentence Gestalt model (McClelland, St. John, & Taraban, 1989) consistently displayed a similar pattern to the N400 amplitude in a series of conditions known to modulate this event-related potential. These results led Rabovsky, Hansen, and McClelland (2018) to suggest that the N400 might reflect change in a probabilistic representation of meaning corresponding to an implicit semantic prediction error. However, a limitation of this work is that the model was trained on a small artificial training corpus and thus could not be presented with the same naturalistic stimuli presented in empirical experiments. In the present study, we overcome this limitation and directly model the amplitude of the N400 elicited during naturalistic sentence processing by using as predictor the SU generated by a Sentence Gestalt model trained on a large corpus of texts. The results reported in this paper corroborate the hypothesis that the N400 component reflects the change in a probabilistic representation of meaning after every word presentation. Further analyses demonstrate that the SU of the Sentence Gestalt model and the amplitude of the N400 are influenced similarly by the stochastic and positional properties of the linguistic input.
The effect of magnesium on calcium binding to cardiac troponin C related hypertrophic cardiomyopathy mutants
Authors: Rayani Kaveh , Hantz Eric , Haji-Ghassemi Omid , Li Alison Yueh , Spuches Anne Marie , Van Petegem Filip , Solaro R John , Lindert Steffen , Tibbits Glen F 
Published: May 2021

AbstractCardiac troponin C (cTnC) is the calcium (Ca2+) sensing component of the troponin complex. Binding of Ca2+ to cTnC triggers a cascade of myofilament conformational changes that culminate in force production. Mutations in cTnC linked to hypertrophic myocardial myopathy (HCM) induce a a greater degree and duration of Ca2+ binding, which may underly the hypertrophic phenotype. Recent evidence from our laboratories demonstrated novel modifications of cTnC Ca2+ binding by cellular magnesium (Mg2+) that we hypothesize may be of significance in promoting HCM.Regulation of contraction has long been thought to occur exclusively through Ca2+ binding to site II of cTnC. However, abundant cellular Mg2+ is a potential competitor for binding to the same sites; work by several groups also suggests this is possible. We have used isothermal titration calorimetry (ITC) to explore the thermodynamic properties associated with the interaction between Ca2+/Mg2+ and site II of cTnC; these experiments demonstrated that physiological concentrations of Mg2+ may compete with Ca2+ to bind site II of cTnC.In experiments reported here, we studied a series of mutations in cTnC thought to be causal in HCM. Three mutants (A8V, L29Q, and A31S) slightly elevated the affinity for both Ca2+ and Mg2+, whereas other mutants (L48Q, Q50R, and C84Y), that are closer to the C-terminal domain and surrounding the EF hand binding motif of site II had a more significant effect on affinity and the thermodynamics of the binding interaction.To the best of our knowledge, this work is the first to explore the role of Mg2+ in modifying the Ca2+ affinity ofcTnC mutations linked to HCM. Our results indicate a physiologically significant role for cellular Mg2+ at baseline conditions and when elevated on the control of the dynamics of contraction by modifications in the Ca2+ binding properties of cTnC.
Chlorophyll fluorescence: How the quality of information about PAM instrument parameters may affect our research
Authors: Nies Tim , Niu Yuxi , Ebenhöh Oliver , Matsubara Shizue , Matuszyńska Anna 
Published: May 2021

AbstractChlorophyll a fluorescence is a powerful indicator of photosynthetic energy conversion in plants and photosynthetic microorganisms. One of the most widely used measurement techniques is Pulse Amplitude Modulation (PAM) fluorometry. Unfortunately, parameter settings of PAM instruments are often not completely described in scientific articles although their variations, however small these may seem, can influence measurements. We show the effects of parameter settings on PAM measurements. We first simulated fluorescence signals using a previously published computational model of photosynthesis. Then, we validated our findings experimentally. Our analysis demonstrates how the kinetics of non-photochemical quenching (NPQ) induction and relaxation are affected by different settings of PAM instrument parameters. Neglecting these parameters may mislead data interpretation and derived hypotheses, hamper independent validation of the results, and cause problems for mathematical formulation of underlying processes. Given the uncertainties inflicted by this neglect, we urge PAM users to provide detailed documentation of measurement protocols. Moreover, to ensure accessibility to the required information, we advocate minimum information standards that can serve both experimental and computational biologists in our efforts to advance system-wide understanding of biological processes. Such specification will enable launching a standardized database for plant and data science communities.HighlightPAM fluorometry measurement is sensitive to instrument settings and protocols. Yet, protocols are published incompletely. We urge to reach an agreement on minimal protocol information of PAM experiments to be shared publicly.
A novel cholinergic neural pathway and its role in the drug relapse
Authors: He Teng , Chen Wenwen , Fan Yu , Xu Xing , Wang Zilin , Li Nanqin , Guo Hao , Lu Xue , Ge Feifei , Guan Xiaowei 
Published: May 2021

AbstractThe lateral parabrachial nucleus (LPB) is critical hub implicated in the control of food intake, reward and aversion. Here, we identified a novel cholinergic projection from choline acetyltransferase (ChAT)-positive neurons in external portion of the lateral parabrachial nucleus (eLPBChAT) to γ–aminobutyric acid (GABA) neurons in central nucleus of amygdala (CeAGABA), activation of which could block methamphetamine (METH)-primed conditioned place preference (CPP) in mice.
Mechanistic Gene Networks Inferred from Single-Cell Data are Better Predictors than Neural Networks
Authors: Han Jung Min , Perera Sudheesha , Wunderlich Zeba , Periwal Vipul 
Published: May 2021

AbstractWith advances in single-cell techniques, measuring gene dynamics at cellular resolution has become practicable. In contrast, the increased complexity of data has made it more challenging computationally to unravel underlying biological mechanisms. Thus, it is critical to develop novel computational methods capable of dealing with such complexity and of providing predictive deductions from such data. Many methods have been developed to address such challenges, each with its own advantages and limitations. We present an iterative regression algorithm for inferring a mechanistic gene network from single-cell data. Using this regression, we infer a developmental model for the gene dynamics in Drosophila melanogaster blastoderm embryo. Our results show that the predictive power of the inferred model is higher than that of other models inferred with least squares and ridge regressions.Furthermore, model predictions of the gene dynamics are more accurate than predictions made with neural networks. This holds true even in the limit of small sample sizes. We compare predictions for various gene knockouts with published experimental results, finding substantial agreement. We also make predictions for gene dynamics under various gene network perturbations, impossible in non-mechanistic models.