bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gliding in the Amazonian canopy: adaptive evolution of flight inMorphobutterflies
Authors: Le Roy Camille , Amadori Dario , Charberet Samuel , Windt Jaap , Muijres Florian T. , Llaurens Violaine , Debat Vincent 
Published: March 2021

AbstractThe diversity of flying animals suggests that countless combinations of morphologies and behaviors have evolved with specific lifestyles, thereby exploiting diverse aerodynamic mechanisms. Elucidating how morphology, flight behavior and aerodynamic properties together diversify with contrasted ecologies remains however seldom accomplished. Here, we studied the adaptive co-divergence in wing shape, flight behavior and aerodynamic efficiency amongMorphobutterflies living in different forest strata, by combining high-speed videography in the field with morphometric analyses and aerodynamic modelling. By comparing canopy and understory species, we show that adaptation to an open canopy environment resulted in increased glide efficiency. Moreover, this enhanced glide efficiency was achieved by different canopy species through strikingly distinct combinations of flight behavior, wing shape and aerodynamic mechanisms, highlighting the multiple pathways of adaptive evolution.One Sentence SummaryBy combining high-speed videography, geometric morphometrics and computational aerodynamic modelling, our study of wild AmazonianMorphobutterflies reveals a strong contrast between the efficient gliding flight of canopy species and the powerful flapping flight of understory species, pointing at a combined adaptive divergence of wing shape and flight behavior among sympatric species flying in different forest strata.
Emergence of directional bias in tau deposition from axonal transport dynamics
Authors: Torok Justin , Maia Pedro D. , Verma Parul , Mezias Christopher , Raj Ashish 
Published: March 2021

AbstractDefects in axonal transport may partly underpin the differences between the observed pathophysiology of Alzheimer’s disease (AD) and that of other non-amyloidogenic tauopathies. Particularly, pathological tau variants may have molecular properties that dysregulate motor proteins responsible for the anterograde-directed transport of tau in a disease-specific fashion. Here we develop the first computational model of tau-modified axonal transport that produces directional biases in the spread of tau pathology. We simulated the spatiotemporal profiles of soluble and insoluble tau species in a multicompartment, two-neuron system using biologically plausible parameters and time scales. Changes in the balance of tau transport feedback parameters can elicit anterograde and retrograde biases in the distributions of soluble and insoluble tau between compartments in the system. Aggregation and fragmentation parameters can also perturb this balance, suggesting a complex interplay between these distinct molecular processes. Critically, we show that the model faithfully recreates the characteristic network spread biases in both AD-like and non-AD-like mouse tauopathy models. Tau transport feedback may therefore help link microscopic differences in tau conformational states and the resulting variety in clinical presentations.Author SummaryThe misfolding and spread of the axonal protein tau is a hallmark of the pathology of many neurodegenerative disorders, including Alzheimer’s disease and frontotemporal lobar dementia. How tau misfolding causes disorders with distinct neuropathology and clinical presentations is the subject of ongoing research. Although current evidence suggests that the specific conformations tau adopts affect where it spreads throughout the brain, a mechanistic explanation has remained elusive. Here we propose that the conformer-specific dysregulation of axonal transport can lead to directionally biased spread, and we employ a mathematical model to explore how tau spreads between neurons in the context of this transport feedback mechanism. We find that conformation-specific feedback is flexible enough to explain bias in either direction and thoroughly explore how this bias emerges as a function of the model’s key parameters. Further, the model reproduces the temporal evolution of directionality observed in two classes ofin vivotauopathy models, demonstrating that transport feedback is sufficient to explain differential tau spread as a function of conformation.
Paraxial mesoderm organoids model development of human somites
Authors: Budjan Christoph , Liu Shichen , Ranga Adrian , Gayen Senjuti , Pourquie Olivier , Hormoz Sahand 
Published: March 2021

AbstractDuring the development of the vertebrate embryo, segmented structures called somites are periodically formed from the presomitic mesoderm (PSM), and give rise to the vertebral column. While somite formation has been studied in several animal models, it is less clear how well this process is conserved in humans. Recent progress has made it possible to study aspects of human paraxial mesoderm development such as the human segmentation clockin vitrousing human pluripotent stem cells (hPSCs), however, somite formation has not been observed in these monolayer cultures. Here, we describe the generation of human paraxial mesoderm (PM) organoids from hPSCs (termed Somitoids), which recapitulate the molecular, morphological and functional features of paraxial mesoderm development, including formation of somite-like structuresin vitro. Using a quantitative image-based screen, we identify critical parameters such as initial cell number and signaling modulations that reproducibly yielded somite formation in our organoid system. In addition, using single-cell RNA sequencing and 3D imaging, we show that PM organoids both transcriptionally and morphologically resemble theirin vivocounterparts and can be differentiated into somite derivatives. Our organoid system is reproducible and scalable, allowing for the systematic and quantitative analysis of human spinal cord development and diseasein vitro.
Implementing QR Codes in Academia to Improve Sample Tracking, Data Accessibility, and Traceability in Multicampus Interdisciplinary Collaborations
Authors: Hernandez Cristian , Aslankoohi Elham , Frolikov Pavel , Kurniawan Sri , Rolandi Marco 
Published: March 2021

AbstractWith the growing number of multicampus interdisciplinary projects in academic institutions, there is an increasing need for tracking systems that make device and sample data and associated results instantly accessible to all collaborators involved. This need has become particularly salient with the COVID pandemic and consequent travel restrictions that have hampered in person meetings and laboratory visits. We report a Quick Response (QR) code tracking system that integrates project management tools for seamless communication and tracking of materials and devices between three manufacturing sites (cleanrooms) and six research laboratories across five universities. We use this system to track the design, fabrication, and quality control of bioelectronic devices (in the cleanroom and engineering laboratories),in vitroexperimental results (in a biology laboratory), andin vivotesting (in the school of medicine). Setting up a tracking system for multisite interdisciplinary teams improves traceability, efficiency, and the quality of produced results making it easier to accomplish project milestones on a tight timeline. This tracking system is particularly useful to track device issues and ensure engineering device consistency when working with expensive biological samplesin vitroand animalsin vivoto reduce waste of biological and animal resources associated with device failure.
The Dual-Antigen Ad5 COVID-19 Vaccine Delivered as an Intranasal Plus Subcutaneous Prime Elicits Th1 Dominant T-Cell and Humoral Responses in CD-1 Mice
Authors: Rice Adrian , Verma Mohit , Shin Annie , Zakin Lise , Sieling Peter , Tanaka Shiho , Balint Joseph , Dinkins Kyle , Adisetiyo Helty , Morimoto Brett , Higashide Wendy , Taft Justin , Patel Rosheel , Buta Sofija , Martin-Fernandez Marta , Bogunovic Dusan , Spilman Patricia , Gabitzsch Elizabeth , Safrit Jeffrey T. , Rabizadeh Shahrooz , Niazi Kayvan , Soon-Shiong Patrick 
Published: March 2021

ABSTRACTIn response to the need for an efficacious, thermally-stable COVID-19 vaccine that can elicit both humoral and cell-mediated T-cell responses, we have developed a dual-antigen human adenovirus serotype 5 (hAd5) COVID-19 vaccine in formulations suitable for subcutaneous (SC), intranasal (IN), or oral delivery. The vaccine expresses both the SARS-CoV-2 spike (S) and nucleocapsid (N) proteins using an hAd5 platform with E1, E2b, and E3 sequences deleted (hAd5[E1-, E2b-, E3-]) that is effective even in the presence of hAd5 immunity. In the vaccine, S is modified (S-Fusion) for enhanced cell-surface display to elicit humoral responses and N is modified with an Enhanced T-cell Stimulation Domain (N-ETSD) to direct N to the endosomal/lysosomal pathway to increase MHC I and II presentation. Initial studies using subcutaneous (SC) prime and SC boost vaccination of CD-1 mice demonstrated that the hAd5 S-Fusion + N-ETSD vaccine elicits T-helper cell 1 (Th1) dominant T-cell and humoral responses to both S and N. We then compared SC to IN prime vaccination with either an SC or IN boost post-SC prime and an IN boost after IN prime. These studies reveal that IN prime/IN boost is as effective at generating Th1 dominant humoral responses to both S and N as the other combinations, but that the SC prime with either an IN or SC boost elicits greater T cell responses. In a third study to assess the power of the two routes of delivery when used together, we used a combined SC plus IN prime with or without a boost and found the combined prime alone to be as effective as the combined prime with either an SC or IN boost in generating both humoral and T-cell responses. The findings here in CD-1 mice demonstrate that combined SC and IN prime-only delivery has the potential to provide broad immunity – including mucosal immunity – against SARS-CoV-2 and supports further testing of this delivery approach in additional animal models and clinical trials.
scTenifoldKnk: an efficient virtual knockout tool for gene function predictions via single-cell gene regulatory network perturbation
Authors: Osorio Daniel , Zhong Yan , Li Guanxun , Xu Qian , Yang Yongjian , Tian Yanan , Chapkin Robert S. , Huang Jianhua Z. , Cai James J. 
Published: March 2021

Bigger PictureGene knockout (KO) experiments, using genetically altered animals, are a proven powerful approach to elucidate the role of a gene in a biological process. However, systematic KO experiments targeting many genes are usually prohibitive due to limited experimental and animal resources. Here, we present scTenifoldKnk, an efficient virtual KO tool that allows the systematic deletion of many genes individually. scTenifoldKnk uses single-cell RNA sequencing (scRNAseq) data from wild-type (WT) samples to predict gene function in a cell type-specific manner. We show that predictions made by scTenifoldKnk recapitulate findings from real-animal KO experiments. scTenifoldKnk has proven to be a powerful and effective approach for elucidating gene function, prioritizing KO targets, predicting experimental outcomes before real-animal KO experiments are conducted.HighlightsscTenifoldKnk performs virtual KO experiments using scRNAseq data.scTenifoldKnk only requires data from WT samples; no data is needed from KO samples.Predictions made by scTenifoldKnk recapitulate findings from real-animal KO experiments.Data Science Maturity LeveleTOC blurbscTenifoldKnk is a machine learning workflow performing virtual KO experiments to predict gene function. It constructs gene regulatory networks using single-cell RNA sequencing data from wild-type samples and then computationally deletes target genes. Real-data applications demonstrate that scTenifoldKnk recapitulates findings of real-animal KO experiments and accurately predicts gene function in analyzed cells.SummaryGene knockout (KO) experiments are a proven, powerful approach for studying gene function. However, systematic KO experiments targeting a large number of genes are usually prohibitive due to the limit of experimental and animal resources. Here, we present scTenifoldKnk, an efficient virtual KO tool that enables systematic KO investigation of gene function using data from single-cell RNA sequencing (scRNAseq). In scTenifoldKnk analysis, a gene regulatory network (GRN) is first constructed from scRNAseq data of wild-type samples, and a target gene is then virtually deleted from the constructed GRN. Manifold alignment is used to align the resulting reduced GRN to the original GRN to identify differentially regulated genes, which are used to infer target gene functions in analyzed cells. We demonstrate that the scTenifoldKnk-based virtual KO analysis recapitulates the main findings of real-animal KO experiments and recovers the expected functions of genes in relevant cell types.
Linking habitat and population dynamics to inform conservation benchmarks for data-limited salmon stocks
Authors: Atlas William I. , Holt Carrie A. , Selbie Daniel T. , Connors Brendan M. , Cox-Rogers Steve , Carr-Harris Charmaine , Hertz Eric , Moore Jonathan W. 
Published: March 2021

AbstractManagement of data-limited populations is a key challenge to the sustainability of fisheries around the world. For example, sockeye salmon (Oncorhynchus nerka) spawn and rear in many remote coastal watersheds of British Columbia (BC), Canada, making population assessment a challenge. Estimating conservation and management targets for these populations is particularly relevant given their importance to First Nations and commercial fisheries. Most sockeye salmon have obligate lake-rearing as juveniles, and total abundance is typically limited by production in rearing lakes. Although methods have been developed to estimate population capacity based on nursery lake photosynthetic rate (PR) and lake area or volume, they have not yet been widely incorporated into stock-recruit analyses. We tested the value of combining lake-based capacity estimates with traditional stock-recruit based approaches to assess population status using a hierarchical-Bayesian stock-recruit model for 70 populations across coastal BC. This analysis revealed regional variation in sockeye population productivity (Ricker α), with coastal stocks exhibiting lower mean productivity than those in interior watersheds. Using moderately-informative PR estimates of capacity as priors reduced model uncertainty, with a more than five-fold reduction in credible interval width for estimates of conservation benchmarks (e.g. SMAX- spawner abundance at carrying capacity). We estimated that almost half of these remote sockeye stocks are below one commonly applied conservation benchmarks (SMSY), despite substantial reductions in fishing pressure in recent decades. Thus, habitat-based capacity estimates can dramatically reduce scientific uncertainty in model estimates of management targets that underpin sustainable sockeye fisheries. More generally, our analysis reveals opportunities to integrate spatial analyses of habitat characteristics with population models to inform conservation and management of exploited species where population data are limited.
Within- and transgenerational plasticity of a temperate salmonid in response to thermal acclimation and acute temperature stress
Authors: Penney Chantelle M. , Tabh Joshua K. R. , Wilson Chris C. , Burness Gary 
Published: March 2021

ABSTRACTEnvironmental temperatures associated with climate change are rising too rapidly for many species to adapt, threatening the persistence of taxa with limited capacities for thermal acclimation. We investigated the capacity for within- and transgenerational responses to increasing environmental temperatures in brook trout (Salvelinus fontinalis), a cold-adapted salmonid. Adult fish were acclimated to temperatures within (10□) and above (21□) their thermal optimum for six months before spawning, then mated in a full factorial breeding design to produce offspring from cold- and warm-acclimated parents as well as bidirectional crosses between parents from both temperature treatments. Offspring families were subdivided and reared at two acclimation temperatures (15□ and 19□) representing their current environment and a projected climate change scenario. Offspring thermal physiology was measured as the rate of oxygen consumption (MO2) during an acute change in temperature (+2□ h-1) to observe their MO2-temperature relationship. We also recorded resting MO2, the highest achieved (peak) MO2, and critical thermal maximum (CTM) as performance metrics. Within-generation plasticity was greater than transgenerational plasticity, with offspring acclimation temperature having demonstrable effects on peak MO2and CTM. Transgenerational plasticity was evident as an elevated resting MO2and the MO2-temperature relationship in offspring from warm-acclimated parents. Both parents contributed to offspring thermal responses, although the paternal effect was stronger. Although brook trout exhibit both within- and transgenerational plasticity for thermal physiology, it is unlikely that these will be sufficient for coping with long-term changes to environmental temperatures resulting from climate change.SummaryBrook trout (Salvelinus fontinalis) exhibit within-generation and transgenerational plasticity for thermal performance, although neither response appears sufficient to cope with long-term climate change effects.
Vibrio choleraeParE2 toxin modulates its operon transcription by stabilization of an antitoxin DNA ruler
Authors: Garcia-Rodriguez Gabriela , Girardin Yana , Singh Ranjan Kumar , Volkov Alexander N. , Konijnenberg Albert , Sobott Frank , Charlier Daniel , Loris Remy 
Published: March 2021

AbstractTheparDE2operon ofVibrio choleraeencodes a type II TA system, which is one of three loci in the superintegron of small chromosome II that show modest similarity to theparDEoperon of plasmid RK2. ParE2, like plasmid RK2-encoded ParE, inhibits DNA gyrase, an essential topoisomerase that is also the target of quinolone antibacterial agents. Mechanistic understanding on ParE2 toxin inhibition by direct interaction with its cognate antitoxin and transcriptional autoregulation of the TA system are currently lacking. ParD2, the ribbon-helix-helix (RHH) antitoxin, auto-represses theparDE2promoter. This repression is enhanced by ParE2, which therefore functions as a transcriptional co-repressor. Here we present protein-DNA interaction studies and high-resolution X-ray structures of the ParD2:ParE2 complex and isolated ParD2 antitoxin, revealing the basis of toxin inhibition and autoregulation of the TA operon by conditional cooperativity. Native mass spectrometry, SAXS and MALS studies confirm the presence of different oligomerization states of ParD2 in solution and the role of the DNA-binding hexameric ParD26:ParE22assembly in transcriptional repression.
Proteome plasticity in response to persistent environmental change
Authors: Domnauer Matthew , Zheng Fan , Li Liying , Zhang Yanxiao , Chang Catherine E. , Unruh Jay R. , Conkright-Fincham Julie , McCroskey Scott , Florens Laurence , Zhang Ying , Seidel Christopher , Fong Benjamin , Schilling Birgit , Sharma Rishi , Ramanathan Arvind , Si Kausik , Zhou Chuankai 
Published: March 2021

SummaryTemperature is a variable component of the environment and all organisms must deal with or adapt to temperature change. Acute temperature change activates cellular stress responses resulting in the refolding or removal of damaged proteins. However, how organisms adapt to long-term temperature change remains largely unexplored. Here, we report that budding yeast responds to long-term high temperature challenge by switching from chaperone induction to the reduction of temperature sensitive proteins and re-localizing a portion of its proteome. Surprisingly, we also find many proteins adopt an alternative conformation. Using Fet3p as an example, we find that the temperature-dependent conformational difference is accompanied by distinct thermostability, subcellular localization, and importantly, cellular functions. We postulate that in addition to the known mechanisms of adaptation, conformational plasticity allows some polypeptides to acquire new biophysical properties and functions when environmental change endures.
Deep neural network analysis employing diffusion basis spectrum imaging metrics as classifiers improves prostate cancer detection and grading
Authors: Ye Zezhong , Yang Qingsong , Lin Joshua , Sun Peng , Shao Chengwei , Yu Yongwei , Chen Luguang , Zhu Yasheng , Wu Anthony T. , George Ajit , Song Chunyu , Yang Ruimeng , Zhan Jie , Gary Sam E. , Viox Jeffrey D. , Wang Zhen , Wang Minjie , Chen Yukun , Kim Eric H. , Ippolito Joseph E. , Lu Jianping , Song Sheng-Kwei 
Published: March 2021

AbstractStructural and cellular complexity of prostatic histopathology limits the accuracy of noninvasive detection and grading of prostate cancer (PCa). We addressed this limitation by employing a novel diffusion basis spectrum imaging (DBSI) to derive structurally-specific diffusion fingerprints reflecting various underlying prostatic structural and cellular components. We further developed diffusion histology imaging (DHI) by combining DBSI-derived structural fingerprints with a deep neural network (DNN) algorithm to more accurately classify different histopathological features and predict tumor grade in PCa. We examined 243 patients suspected with PCa usingin vivoDBSI. Thein vivoDBSI-derived diffusion metrics detected coexisting prostatic pathologies distinguishing inflammation, PCa, and benign prostatic hyperplasia. DHI distinguished PCa from benign peripheral and transition zone tissues with over 95% sensitivity and specificity. DHI also demonstrated over 90% sensitivity and specificity for Gleason score noninvasively. We present DHI as a novel diagnostic tool capable of noninvasive detection and grading of PCa.One sentence summaryDiffusion histology imaging noninvasively and accurately detects and grades prostate cancer.
A non-invasive brain-machine interface via independent control of individual motor units
Authors: Formento Emanuele , Botros Paul , Carmena Jose M. 
Published: March 2021

AbstractBrain-machine interfaces (BMIs) have the potential to augment human functions and restore independence in people with disabilities, yet a compromise between non-invasiveness and performance limits their relevance. Here, we demonstrate a BMI controlled by individual motor units non-invasively recorded from the biceps brachii. Through real-time auditory and visual neurofeedback of motor unit activity, 8 participants learned to skillfully and independently control three motor units in order to complete a two-dimensional center-out task, with marked improvements in control over 6 days of training. Concomitantly, dimensionality of the motor unit population increased significantly relative to naturalistic behaviors, largely violating recruitment orders displayed during stereotyped, isometric muscle contractions. Finally, participants demonstrated the potential of a motor unit BMI to power general applications by navigating a virtual keyboard in a spelling task, achieving performances comparable to spelling-tailored non-invasive BMIs that leverage less flexible control strategies to improve performance. These results highlight a largely unexplored level of flexibility of the sensorimotor system and show that this can be exploited to create a versatile, skillfully-controllable non-invasive BMI that has great potential to both provide translational benefit and augment motor functions.