bluuebunny/crossref_metadata_2025_split huggingface dataset:
DCP: a pipeline toolbox for diffusion connectome
Authors: Huang Weijie , Shu Ni 
Published: April 2020

AbstractThe brain structure network constructed by diffusion tensor imaging (DTI) reflects the anatomical connections between brain regions, so the brain structure network can quantitatively describes the anatomical connectivity pattern of the entire brain. The structure network based diffusion tensor imaging is widely used in scientific research. While a number of post processing packages have been developed, fully automated processing of DTI datasets on Windows Operating System remains challenging. Here, we developed a MATLAB toolbox named “Diffusion Connectome Pipeline” (DCP) for fully automated constructing brain structure network. The processing modules of a few developed packages, including Diffusion Toolkit, DiffusionKit, SPM and MRIcron, were employed in DCP. Using any number of raw DTI datasets from different subjects, in either DICOM or NIfTI format, DCP can automatically perform a series of steps to construct network. In addition, DCP has a friendly graphical user interface (GUI) running on the Windows Operating System, allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, DCP is freely available athttps://www.nitrc.org/projects/dcp. This novel toolbox is expected to substantially simplify the image processing of DTI datasets and facilitate human brain structural connectome studies.
A hierarchy of functional states in working memory
Authors: Muhle-Karbe Paul S. , Myers Nicholas E. , Stokes Mark G. 
Published: April 2020

AbstractExtensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behaviour. We addressed this question by combining human electrophysiology with pattern analyses, cognitive modelling, and a task requiring maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for immediately and prospectively task-relevant items, and to examine their contribution to WM-based decisions. We identified two qualitatively different states: a functionally active state encoded only immediately task-relevant items and closely tracked the quality of evidence integration on the current trial. In contrast, prospectively relevant items were encoded in a functionally latent state that did not engage with ongoing processing but tracked memory precision at longer time scales. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision-circuits to guide flexible behaviour.
The influence of data type and functional traits on native bee phenology metrics: Opportunistic versus inventory records
Authors: Meiners Joan M. , Orr Michael C. , Kristina Riemer , Terry Griswold , Simonis Juniper L. 
Published: April 2020

ABSTRACTEfforts to understand activity patterns of bees, our most important pollinators, often rely on opportunistically collected museum records to model temporal shifts or declines. This type of data, however, may not be suitable for this purpose given high spatiotemporal variability of native bee activity. By comparing phenological metrics calculated from intensive systematic inventory data with those from opportunistic museum records for bee species spanning a range of functional traits, we explored biases and limitations of data types to determine best practices for bee monitoring and assessment. We compiled half a million records of wild bee occurrence from opportunistic museum collections and six systematic inventory efforts, focusing analyses on 45 well-represented species that spanned five functional traits: sociality, nesting habits, floral specialization, voltinism, and body size. We then used permutation tests to evaluate differences between data types in estimating three phenology metrics: flight duration, number of annual abundance peaks, and date of the highest peak. We used GLMs to test for patterns of data type significance across traits. All 45 species differed significantly in the value of at least one phenology metric depending on the data type used. The date of the highest abundance peak differed for 40 species, flight duration for 34 species, and the number of peaks for 15 species. The number of peaks was more likely to differ between data types for larger bees, and flight duration was more likely to differ for larger bees and specialist bees. Our results reveal a strong influence of data type on phenology metrics that necessitates consideration of data source when evaluating changes in phenological activity, possibly applicable to many taxa. Accurately assessing phenological change may require expanding wild bee monitoring and data sharing.
Signal diversification is associated with corollary discharge evolution in weakly electric fish
Authors: Fukutomi Matasaburo , Carlson Bruce A. 
Published: April 2020

ABSTRACTCommunication signal diversification is a driving force in the evolution of sensory and motor systems. However, little is known about the evolution of sensorimotor integration. Mormyrid fishes generate stereotyped electric pulses (electric organ discharge [EOD]) for communication and active sensing. The EOD has diversified extensively, especially in duration, which varies across species from 0.1 to over 10 ms. In the electrosensory hindbrain, a corollary discharge that signals the timing of EOD production provides brief, precisely timed inhibition that effectively blocks responses to self-generated EODs. However, corollary discharge inhibition has only been studied in a few species, all with short duration EODs. Here, we asked how corollary discharge inhibition has coevolved with the diversification of EOD duration. We addressed this question by comparing 7 mormyrid species having varied EOD duration. For each individual fish, we measured EOD duration and then measured corollary discharge inhibition by recording evoked potentials from midbrain electrosensory nuclei. We found that delays in the onset of corollary discharge inhibition were strongly correlated with EOD duration as well as delay to the first peak of the EOD. In addition, we showed that electrosensory receptors respond to self-generated EODs with spikes occurring in a narrow time window immediately following the first peak of the EOD. Direct comparison of time courses between the EOD and corollary discharge inhibition revealed that the inhibition overlaps the first peak of the EOD. Our results suggest that internal delays have shifted the timing of corollary discharge inhibition to optimally block responses to self-generated signals.SIGNIFICANCE STATEMENTCorollary discharges are internal copies of motor commands that are essential for brain function. For example, corollary discharge allows an animal to distinguish self-generated from external stimuli. Despite widespread diversity in behavior and its motor control, we know little about the evolution of corollary discharges. Mormyrid fishes generate stereotyped electric pulses used for communication and active sensing. In the electrosensory pathway that processes communication signals, a corollary discharge inhibits sensory responses to self-generated signals. We found that fish with long duration pulses have delayed corollary discharge inhibition, and that this time-shifted corollary discharge optimally blocks electrosensory responses to the fish’s own signal. Our study provides the first evidence for evolutionary change in sensorimotor integration related to diversification of communication signals.
The folding and unfolding behavior of ribonuclease H on the ribosome
Authors: Jensen Madeleine K. , Samelson Avi J. , Steward Annette , Clarke Jane , Marqusee Susan 
Published: April 2020

ABSTRACTThe health of a cell depends on accurate translation and proper protein folding; misfolding can lead to aggregation and disease. The first opportunity for a protein to fold occurs during translation, when the ribosome and surrounding environment can affect the energy landscape of the nascent chain. However, quantifying these environmental effects is challenging due to the ribosomal proteins and rRNA, which preclude most spectroscopic measurements of protein energetics. We have applied two gel-based approaches, pulse proteolysis and force-peptide arrest assays, to probe the folding and unfolding pathways of RNase H ribosome-stalled nascent chains. We find that ribosome-stalled RNase H has an increased unfolding rate compared to free RNase H, which completely accounts for observed changes in protein stability and indicates that the folding rate is unchanged. Using arrest peptide-based force-profile analysis, we assayed the force generated during the folding of RNase H on the ribosome. Surprisingly, we find that population of the RNase H folding intermediate is required to generate sufficient force to release the SecM stall and that readthrough of the stall sequence directly correlates with the stability of the folding intermediate. Together, these data imply that the folding pathway of RNase H is unchanged on the ribosome. Furthermore, our data indicate that the ribosome promotes unfolding while the nascent chain is proximal to the ribosome, which may limit the deleterious effects of misfolding and assist in folding fidelity.
Functional MRI of large scale activity in behaving mice
Authors: Fonseca Madalena S. , Bergomi Mattia G. , Mainen Zachary F. , Shemesh Noam 
Published: April 2020

ABSTRACTBehaviour involves complex dynamic interactions across many brain regions. Detecting whole-brain activity in mice performing sophisticated behavioural tasks could facilitate insights into distributed processing underlying behaviour, guide local targeting, and help bridge the disparate spatial scales between rodent and human studies. Here, we present a comprehensive approach for recording brain-wide activity with functional magnetic resonance imaging (fMRI) compatible with a wide range of behavioural paradigms and neuroscience questions. We introduce hardware and procedural advances to allow multi-sensory, multi-action behavioural paradigms in the scanner. We identify signal artefacts arising from task-related body movements and propose novel strategies to reduce them. We validate and explore our approach in a 4-odour classical conditioning and a visually-guided operant task, illustrating how it can be used to extract information so far inaccessible to rodent behaviour studies. Our work paves the way for future studies combining fMRI and local circuit techniques during complex behaviour to tackle multi-scale behavioural neuroscience questions.
A comprehensive benchmarking of WGS-based structural variant callers
Authors: Sarwal Varuni , Niehus Sebastian , Ayyala Ram , Chang Sei , Lu Angela , Darci-Maher Nicholas , Littman Russell , Chhugani Karishma , Soylev Arda , Comarova Zoia , Wesel Emily , Castellanos Jacqueline , Chikka Rahul , Distler Margaret G. , Eskin Eleazar , Flint Jonathan , Mangul Serghei 
Published: April 2020

AbstractAdvances in whole genome sequencing promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from whole genome sequencing (WGS) data presents a substantial number of challenges and a plethora of SV-detection methods have been developed. Currently, there is a paucity of evidence which investigators can use to select appropriate SV-detection tools. In this paper, we evaluated the performance of SV-detection tools using a comprehensive PCR-confirmed gold standard set of SVs. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of SV-detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance, as the SV-detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV-detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low and ultra-low pass sequencing data.
Visualizing the superfamily of metallo-β-lactamases through sequence similarity network neighborhood connectivity analysis
Authors: González Javier M. 
Published: April 2020

ABSTRACTThe superfamily of metallo-β-lactamases (MBL) comprises an ancient group of proteins found in all domains of life, sharing a characteristic αββα fold and a histidine-rich motif for binding of transition metal ions, with the ability to catalyze a variety of hydrolysis and redox reactions. Herein, structural homology and sequence similarity network (SSN) analysis are used to assist the phylogenetic reconstruction of the MBL superfamily, introducing tanglegrams to evaluate structure-function relationships. SSN neighborhood connectivity is applied for spotting protein families within SSN clusters, showing that 98 % of the superfamily remains to be explored experimentally. Further SSN research is suggested in order to determine their topological properties, which will be instrumental for the improvement of automated sequence annotation methods.
Maternally administered naltrexone and its major active metabolite 6β-naltrexol transport across the placental barrierin vitro
Authors: Pemathilaka Rajeendra L. , Reynolds David E. , Hashemi Nicole N. 
Published: April 2020

AbstractOpioid use disorder (OUD) has become a growing concern in the U.S. and has been a dominant presence among pregnant women, resulting in an unprecedented amount of prescription medications, particularly naltrexone (NTX), prescribed for pregnant women. Because of unknown potential harm that NTX can impose on the fetus and its premature brain, the needs for safety and regulation of NTX are still undetermined. To address this issue, a microfluidic device is fabricated to mimic structural phenotypes and physiological characteristic of anin vivoplacental barrier to evaluate near-transport simulations of NTX and its primary metabolite, 6β-naltrexol, across the placental barrier. Following transport analysis, cell layers are evaluated for possible gene-expressions released by anin vivohuman placenta during NTX and 6β-naltrexol placental exposure. When a 100 ng/mL dose of NTX and 6β-naltrexol (1:1) is administered to the maternal channel, the mean fetal concentration for co-culture models exhibited ~2.5 % of NTX and ~2.2% of 6β-naltrexol of the initial maternal concentration. To prototype and simulate fetal-brain exposure, perfusate from a fetal channel is directed to cultured N27 cells that are then evaluated for gene-expression.
Broad Host Range of SARS-CoV-2 Predicted by Comparative and Structural Analysis of ACE2 in Vertebrates
Authors: Damas Joana , Hughes Graham M. , Keough Kathleen C. , Painter Corrie A. , Persky Nicole S. , Corbo Marco , Hiller Michael , Koepfli Klaus-Peter , Pfenning Andreas R. , Zhao Huabin , Genereux Diane P. , Swofford Ross , Pollard Katherine S. , Ryder Oliver A. , Nweeia Martin T. , Lindblad-Toh Kerstin , Teeling Emma C. , Karlsson Elinor K. , Lewin Harris A. 
Published: April 2020

AbstractThe novel coronavirus SARS-CoV-2 is the cause of Coronavirus Disease-2019 (COVID-19). The main receptor of SARS-CoV-2, angiotensin I converting enzyme 2 (ACE2), is now undergoing extensive scrutiny to understand the routes of transmission and sensitivity in different species. Here, we utilized a unique dataset of 410 vertebrates, including 252 mammals, to study cross-species conservation of ACE2 and its likelihood to function as a SARS-CoV-2 receptor. We designed a five-category ranking score based on the conservation properties of 25 amino acids important for the binding between receptor and virus, classifying all species fromvery hightovery low. Only mammals fell into themediumtovery highcategories, and only catarrhine primates in thevery highcategory, suggesting that they are at high risk for SARS-CoV-2 infection. We employed a protein structural analysis to qualitatively assess whether amino acid changes at variable residues would be likely to disrupt ACE2/SARS-CoV-2 binding, and found the number of predicted unfavorable changes significantly correlated with the binding score. Extending this analysis to human population data, we found only rare (<0.1%) variants in 10/25 binding sites. In addition, we observed evidence of positive selection in ACE2 in multiple species, including bats. Utilized appropriately, our results may lead to the identification of intermediate host species for SARS-CoV-2, justify the selection of animal models of COVID-19, and assist the conservation of animals both in native habitats and in human care.
Regional genomic heritability mapping for agronomic traits in sugarcane
Authors: Pereira Vidigal Pedro Marcus , Momen Mehdi , de Almeida Costa Paulo Mafra , Pereira Barbosa Márcio Henrique , Morota Gota , Peternelli Luiz Alexandre 
Published: April 2020

AbstractBackgroundThe identification of genomic regions involved in agronomic traits is the primary concern for sugarcane breeders. Genome-wide association studies (GWAS) leverage the sequence variations to bridge phenotypes and genotypes. However, their effectiveness is limited in species with high ploidy and large genomes, such as sugarcane. As an alternative, a regional heritability mapping (RHM) method can be used to capture genetic signals that may be missed by GWAS by combining genetic variance from neighboring regions. We used RHM to screen the sugarcane genome aiming to identify regions with higher heritability associated with agronomic traits. We considered percentage of fiber in sugarcane bagasse (FB), apparent percentage of sugarcane sucrose (PC), tonnes of pol per hectare (TPH), and tonnes of stalks per hectare (TSH).MethodsSequence-capture data of 508 sugarcane (Saccharumspp.) clones from a breeding population under selection were processed for variant calling analysis using the sugarcane genome cultivar R570 as a reference. A set of 375,195 single nucleotide polymorphisms were selected after quality control. RHM was conducted by splitting the sugarcane genome into windows of 2 Mb length.ResultsWe selected the windows explaining > 20% of the total genomic heritability for TPH (64 windows - 5,654 genes) and TSH (72 windows - 6,050 genes), and > 15% for PC (16 windows - 1,517 genes) and FB (17 windows - 1,615 genes). The top five windows that explained the highest genomic heritability ranged from 20.8 to 24.6% for FB (629 genes), 18.0 to 22.0% for PC (452 genes), 53.8 to 66.0% for TPH (705 genes), and 59.5 to 67.4% for TSH (413 genes). The functional annotation of genes included in those top five windows revealed a set of genes that encode enzymes that integrate carbon metabolism, starch and sucrose metabolism, and phenylpropanoid biosynthesis pathways.ConclusionsThe selection of windows that explained the large proportions of genomic heritability allowed us to identify genomic regions containing a set of genes that are related to the agronomic traits in sugarcane. These windows spanned a region of 58.38Mb, which corresponds to 14.28% of the reference assembly in the sugarcane genome. We contend that RHM can be used as an alternative method for sugarcane breeders to reduce the complexity of the sugarcane genome.
The Readiness Potential reflects expectation, not uncertainty, in the timing of action
Authors: Travers Eoin , Friedemann Maja , Haggard Patrick 
Published: April 2020

AbstractActions are guided by a combination of external cues, internal intentions and stored knowledge. Self-initiatedvoluntary actions, produced without any immediate external cue, may be preceded by a slow EEG Readiness Potential (RP) that progressively increases prior to action. The cognitive significance of this neural event is controversial. Some accounts link the RP to the fact that timing of voluntary actions is generated endogenously, without external constraints, and perhaps even randomly. Other accounts take the RP as reflecting the unique role of planning, therefore of temporal expectation, in voluntary actions. In many previous experiments, actions are both unconstrained by external cues, but also potentially involve preplanning and anticipation. To separate these factors, we developed a reinforcement learning paradigm where participants learned, through trial and error, the optimal time to act. If the RP reflects freedom from external constraint, its amplitude should be greater early in learning, when participants do not yet know the best time to act. Conversely, if the RP reflects planning, it should be greater later on, when participants have learned, and know in advance, the time of action. We found that RP amplitudes grew with learning, suggesting that this neural activity reflects planning and anticipation for the forthcoming action, rather than freedom from external constraint.
A changing signaling environment induces multiciliated cell trans-differentiation during developmental remodeling
Authors: Tasca Alexia , Helmstädter Martin , Brislinger Magdalena , Haas Maximilian , Walentek Peter 
Published: April 2020

AbstractMulticiliated cells (MCCs) are extremely highly-differentiated, presenting >100 cilia and basal bodies. We analyzed how MCCs are lost from the airway-likeXenopusembryonic epidermis during developmental tissue remodeling. We found that some MCCs undergo apoptosis, but that the majority trans-differentiate into secretory cells. Trans-differentiation involves loss of ciliary gene expression, cilia retraction and lysosomal degradation. Apoptosis and trans-differentiation are both induced by a changing signaling environment through Notch, Jak/STAT, Thyroid hormone and mTOR signaling, and trans-differentiation can be inhibited by Rapamycin. This demonstrates that even cells with extreme differentiation features can undergo direct fate conversion. Our data further suggest that the reactivation of this developmental mechanism in adults can drive tissue remodeling in human chronic airway disease, a paradigm resembling cancer formation and progression.