bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silencing hippocampal CA2 reduces behavioral flexibility in spatial learning
Authors: Lehr Andrew B. , Hitti Frederick L. , Deibel Scott H. , Stöber Tristan M. 
Published: November 2022

AbstractThe hippocampus is a key structure involved in learning and remembering spatial information. However the extent to which hippocampal region CA2 is involved in these processes remains unclear. Here we show that chronically silencing dorsal CA2 impairs reversal learning in the Morris water maze. After platform relocation, CA2-silenced mice spent more time in the vicinity of the old platform location and less time in the new target quadrant. Accordingly, behavioral strategy analysis revealed increased perseverance in navigating to the old location during the first day and an increased use of non-spatial strategies during the second day of reversal learning. Confirming previous indirect indications, these results demonstrate that CA2 is recruited when mice must flexibly adapt their behavior as task contingencies change. We discuss how these findings can be explained by recent theories of CA2 function and outline testable predictions to understand the underlying neural mechanisms. Demonstrating a direct involvement of CA2 in spatial learning, this work lends further support to the notion that CA2 plays a fundamental role in hippocampal information processing.
Segregation of pathways leading to pexophagy
Authors: Barone Francesco G. , Urbé Sylvie , Clague Michael J. 
Published: November 2022

AbstractPeroxisomes are organelles with key roles in metabolism including long-chain fatty acid production. Their metabolic functions overlap and interconnect with mitochondria, with which they share an overlapping but distinct proteome. Both organelles are degraded by selective autophagy processes termed pexophagy and mitophagy. Whilst mitophagy has received intense attention, the pathways linked to pexophagy and associated tools are less well developed. We have identified the neddylation inhibitor, MLN4924, as a potent activator of pexophagy and show that this is mediated by the HIF1α-dependent upregulation of BNIP3L/NIX, a known adaptor for mitophagy. We show that this pathway is distinct from pexophagy induced by the USP30 deubiquitylase inhibitor, CMPD-39, for which we identify the adaptor NBR1 as a central player. Our work suggests a level of complexity to the regulation of peroxisome turnover that includes the capacity to co-ordinate with mitophagy, via NIX, which acts as a rheostat for both processes.
Acyl plastoquinol is a major substance that co-migrates with triacylglycerol in cyanobacteria
Authors: Mori-Moriyama Natsumi , Yoshitomi Toru , Sato Naoki 
Published: November 2022

AbstractVarious studies have suggested the presence of triacylglycerol in cyanobacteria, but no convincing evidence exists. We purified a substance co-migrating with triacylglycerol and determined its structure using mass spectrometry, gas chromatography, and1H- and13C-NMR. The major components were palmitoyl and stearoyl plastoquinols (acyl plastoquinol). Acyl plastoquinol has never been described before. The level of acyl plastoquinol was 0.4% of the total lipids. We still do not have clear evidence for the presence of triacylglycerol. If present, the maximum triacylglycerol level, must be at most 10% of acyl plastoquinol or less. TheSynechocystisSlr2103 protein was suggested to synthesize triacylglycerol, but the product could be acyl plastoquinol. The possible roles of this novel compound in photosynthesis should be a new focus of research.
RBPamp: Quantitative Modeling of Protein-RNA Interactionsin vitroPredictsin vivoBinding
Authors: Jens Marvin , McGurk Michael , Bundschuh Ralf , Burge Christopher B. 
Published: November 2022

AbstractRNA-binding proteins (RBPs) control the processing and function of cellular transcripts to effect post-transcriptional gene regulation. Sequence-specific binding of RBPs to millions of synthetic RNAs has been probed in vitro by RNA Bind-n-Seq (RBNS). Here we describe RBPamp, a bio-physically-based model of protein-RNA interactions and associated algorithm that inferred affinity spectra of 79 diverse human RBPs from RBNS data. RBPamp supports multiple motifs per RBP, models RBP concentration and binding site saturation, and accounts for the effects of RNA secondary structure. RBPamp affinities along transcripts are predictive of in vivo binding, as measured by eCLIP density. For many RBPs, average local eCLIP density increases monotonically with predicted affinity, and the shape of this relationship can suggest free protein concentrations and potential cooperativity. Together, these analyses demonstrate a powerful integrative approach for the quantitative dissection of RBP function.
Trait diversity metrics can perform well with highly incomplete datasets
Authors: Stewart Kerry , Carmona Carlos P. , Clements Chris , Venditti Chris , Tobias Joseph A. , González-Suárez Manuela 
Published: November 2022

AbstractCharacterizing changes in trait diversity at large spatial scales provides insight into the impact of human activity on ecosystem structure and function. However, the approach is often based on trait datasets that are incomplete and unrepresentative, with uncertain impacts on trait diversity estimates.To address this knowledge gap, we simulated random and biased removal of data from a near complete avian trait dataset (9579 species) and assessed whether trait diversity metrics were robust to data incompleteness with and without using imputation to fill data gaps. Specifically, we compared two commonly used metrics each calculated with two methods: trait richness (calculated with convex hulls and trait probabilities densities) and trait divergence (calculated with distance-based Rao and trait probability densities).Without imputation, estimates of global avian trait diversity (richness and divergence) were robust when 30-70% of species had missing data for four out of 11 continuous traits, depending on severity of bias and the method used. However, when missing traits were imputed based on present morphological trait data and phylogeny, trait diversity metrics consistently remained representative of the true value, even when 70% of species were missing data for four out of 11 traits and data were not missing at random (biased with respect to body mass). Trait probability densities and distance-based Rao were particularly robust to missingness and bias when combined with imputation, with convex hull-based trait richness being less reliable.Expanding global morphometric datasets to represent more taxa and traits, and to quantify intraspecific variation, remains a priority. In the meantime, our results show that widely used methods can successfully quantify large-scale trait diversity even when data are missing for two-thirds of species, so long as missing traits are estimated using imputation.
The enzyme Rnf completes the pathway for forming propionate during fermentation inPrevotella
Authors: Zhang Bo , Lingga Christopher , De Groot Hannah , Hackmann Timothy J. 
Published: November 2022

ABSTRACTPropionate is a microbial metabolite that is formed in the gastrointestinal tract, and it affects host physiology as a source of energy and signaling molecule. Despite the importance of propionate, the biochemical pathways responsible for its formation are not clear in all microbes. For the succinate pathway used during fermentation, a key enzyme appears to be missing—one that can oxidize ferredoxin and reduce NAD. Here we show that Rnf [ferredoxin--NAD(+) oxidoreductase (Na(+)-transporting)] is this key enzyme in two abundant bacteria of the rumen (Prevotella brevisandPrevotella ruminicola). We found these bacteria form propionate, succinate, and acetate with the classic succinate pathway. At first, this pathway appears unbalanced, forming reduced ferredoxin and oxidized NAD in excess. If this continued unabated, fermentation would halt within 1.5 s. We found these bacteria solve this problem by oxidizing ferredoxin and reducing NAD with Rnf. This is demonstrated using growth experiments, genomics, proteomics, and enzyme assays. Genomic and phenotypic data suggest many bacteria use Rnf similarly. We cataloged fermentation products of >1,400 species of prokaryotes, and nearly 10% formed propionate, succinate, and acetate. Over 40% of species carrying out this fermentation also had genes for Rnf. This work shows Rnf is important to propionate formation in many bacteria from the environment, and it provides fundamental knowledge for manipulating fermentative propionate production.
dipwmsearch: a python package for searching di-PWM motifs
Authors: Mille Marie , Ripoll Julie , Cazaux Bastien , Rivals Eric 
Published: November 2022

AbstractMotivationSeeking probabilistic motifs in a sequence is a common task to annotate putative transcription factor binding sites (TFBS). Useful motif representations include Position Weight Matrices (PWMs), dinucleotidic PWMs (di-PWMs), and Hidden Markov Models (HMMs). Dinucleotidic PWMs combine the simplicity of PWMs – a matrix form and a cumulative scoring function –, but also incoporate dependency between adjacent positions in the motif (unlike PWMs which disregard any dependency). For instance, to represent binding sites, the HOCOMOCO database provides di-PWM motifs derived from experimental data. Currently, two programs, SPRy-SARUS and MOODS, can search for di-PWMs in sequences.ResultsWe propose a Python package,dipwmsearch, which provides an original and efficient algorithm for this task (it first enumerates matching words for the di-PWM, and then search them at once in the sequence even if it contains IUPAC codes). The user benefits from an easy installation viaPypiorconda, a documented Python interface, and reusable example scripts that smooth the use of di-PWMs.Availability and Implementationdipwmsearchis available athttps://pypi.org/project/dipwmsearch/andhttps://gite.lirmm.fr/rivals/dipwmsearch/under Cecill license.
Interpersonal alignment of neural evidence accumulation to social exchange of confidence
Authors: Esmaily Jamal , Zabbah Sajjad , Bahrami Bahador , Ebrahimpour Reza 
Published: November 2022

AbstractPrivate, subjective beliefs about uncertainty have been found to have idiosyncratic computational and neural substrates yet, humans share such beliefs seamlessly and cooperate successfully. Bringing together decision making under uncertainty and interpersonal alignment in communication, in a discovery plus pre-registered replication design, we examined the neuro-computational basis of the relationship between privately-held and socially-shared uncertainty. Examining confidence-speed-accuracy trade-off in uncertainty-ridden perceptual decisions under social vs isolated context, we found that shared (i.e., reported confidence) and subjective (inferred from pupillometry) uncertainty dynamically followed social information. An attractor neural network model incorporating social information as top-down additive input captured the observed behaviour and spontaneously demonstrated the emergence of social alignment in virtual dyadic simulations. Electroencephalography showed that social exchange of confidence modulated the neural signature of perceptual evidence accumulation in the central parietal cortex and produced a sustained top-down flow of information from prefrontal to parietal cortex. Our findings offer a neural population model for interpersonal alignment of shared beliefs.
Temporal changes in the individual size distribution decouple long-term trends in abundance, biomass, and energy use of North American breeding bird communities
Authors: Diaz Renata M. , Ernest S. K. Morgan 
Published: November 2022

AbstractAimA core objective of contemporary biodiversity science is to understand long-term trends in the structure and function of ecological communities. Different currencies of ecological function – specifically, total abundance, total standing biomass, and total metabolic flux – are naturally linked, but may become decoupled if the underlying size structure of a system changes. Here, we seek to establish how changes in community size composition modulate long-term relationships between different currencies of ecological function for North American birds.LocationNorth America, north of Mexico.Time period1988-2018.Major taxa studiedBreeding birds.MethodsWe used species’ traits and allometric scaling to estimate individual size measurements and basal metabolic rate for birds observed in the North American Breeding Bird Survey. We compared the long-term trajectories for community-wide standing biomass and energy use to the long-term trends driven by changes in individual abundance alone. Finally, we used dissimilarity metrics to evaluate the link between changes in species and size composition and changes in the relationship between abundance- and size-driven dynamics.ResultsFor a substantial minority of communities, shifts in community size composition have decoupled the long-term dynamics of biomass, energy use, and individual abundance. While trends in abundance were dominated by decreases, trends in biomass were evenly divided between decreases and increases, and trends in energy use featured more increases than expected given changes in abundance alone. Communities with decoupled dynamics showed greater increases in community-wide mean body size than other communities, but did not differ from other communities in overall turnover in species or size composition.Main conclusionsSize- and abundance-based currencies of ecological function are linked, but not necessarily equivalent. For North American breeding birds, shifts in species composition favoring larger-bodied species may have partially offset declines in standing biomass driven by losses of individuals over the past 30 years.
RAD-TGTs: Measurement of cellular tensions via flow cytometry and DNA sequencing enabled by force-dependent rupture and delivery of DNA tension probes
Authors: Pawlak Matthew R. , Smiley Adam T. , Kelly Marcus D. , Shamsan Ghaidan A. , Anderson Sarah M. , Smeester Branden A. , Largaespada David A. , Odde David J. , Gordon Wendy R. 
Published: November 2022

AbstractMechanical force is a key driver of cellular processes and is dysregulated in many diseases. Measuring cellular tensions to elucidate mechanotransduction pathways typically involves high-resolution but low throughput imaging of surfaces and arduous experimental preparation of materials. We present here Rupture and Deliver DNA-duplex based molecular tension sensors-RAD-TGTs. RAD-TGTs consist of immobilized DNA duplexes conjugated to a ligand and indicator (fluorophore, barcode etc) which rupture in a force-dependent manner when cells are bound. Readout of rupture is performed in cells of interest using high throughput methods such as flow cytometry and leveraging covalent DNA-protein linking HUH-tags simplifies the preparation of the tension sensor to allow use of “off-the-shelf” oligos. We demonstrate that rupture and delivery is decreased by inhibitors of cytoskeletal dynamics and knockout of mechanosensing proteins. We also show that rupture and delivery correlates with ligand affinity. Excitingly, we demonstrate that rupture and delivery of barcoded DNA-duplexes can be quantified using DNA sequencing, propelling cellular force measurements into the -omics era.
Extracting Mitochondrial Cristae Characteristics from 3D Focused Ion Beam Scanning Electron Microscopy Data
Authors: Wang Chenhao , Østergaard Leif , Hasselholt Stine , Sporring Jon 
Published: November 2022

1AbstractMitochondria are the main suppliers of energy for cells and their bioenergetic function is regulated bymitochondrial dynamics: the constant changes in mitochondria size, shape, and cristae morphology to secure cell homeostasis. Although mitochondrial dysfunction is implicated in a wide range of diseases, our understanding of mitochondrial function remains limited by the complexity of inferring these spatial features from 2D electron microscopical (EM) images of intact tissue. Here, we present a semi-automatic method for segmentation and 3D reconstruction of mitochondria, cristae, and intracristal spaces based on 2D EM images of the murine hippocampus. We show that our method provides a more accurate characterization of mitochondrial ultrastructure in 3D than common 2D approaches and propose an operational index of mitochondria’s internal organization. We speculate that this tool may help increase our understanding of mitochondrial dynamics in health and disease.
Pipeline for transferring annotations between proteins beyond globular domains
Authors: Martínez-Pérez Elizabeth , Pajkos Mátyás , Tosatto Silvio C.E. , Gibson Toby J. , Dosztanyi Zsuzsanna , Marino-Buslje Cristina 
Published: November 2022

ABSTRACTBackgroundDisProt is the primary repository of Intrinsically Disordered Proteins. This database is manually curated and the annotations there have strong experimental support. Currently DisProt contains a relatively small number of proteins highlighting the importance of transferring verified disorder and other annotations, in such a way as to increase the number of proteins that could benefit from this valuable information. While the principles and practicalities of homology transfer are well-established for globular proteins, these are largely lacking for disordered proteins.MethodsWe used DisProt to evaluate the transferability of the annotation terms to orthologous proteins. For each protein, we looked for their orthologs, with the assumption that they will have a similar function. Then, for each protein and their orthologs we made multiple sequence alignments (MSAs). Global and regional quality of the MSAs was evaluated with the NorMD score.ResultsWe have designed a pipeline to obtain good quality MSAs and to transfer annotations from any protein to their orthologs. Applying the pipeline to DisProt proteins, from the 1931 entries with 5,623 annotations we can reach 97,555 orthologs and transfer a total of 301,190 terms by homology. We also provide a web server for consulting the results of DisProt proteins and execute the pipeline for any other protein. The server Homology Transfer IDP (HoTIDP) is accessible athttp://hotidp.leloir.org.ar.
Thermal acclimation in a non-migratory songbird occurs via changes to thermogenic capacity, but not conductance
Authors: Schweizer Rena M. , Romero Abimael , Tobalske Bret W. , Semenov Georgy , Carling Matt D. , Rice Amber M. , Taylor Scott A. , Cheviron Zachary A. 
Published: November 2022

AbstractThermoregulatory performance can be modified through changes in various subordinate traits, including thermal conductance, basal and summit metabolic rates, and body composition. We investigated physiological differences between black-capped chickadees (Poecile atricapillus) acclimated for six weeks to cold (−5°C) or control (25°C) environments (n = 7 per treatment) by measuring traits that affect thermal balance. We made repeated measurements of basal and summit metabolic rates via flow-through respirometry and body composition using quantitative magnetic resonance of live birds. At the end of the acclimation, we measured thermal conductance of the combined feathers and skins. Cold-acclimated birds had a higher summit metabolic rate, reflecting a greater capacity for endogenous heat generation, and an increased lean mass. However, birds did not alter their thermal conductance. These results suggest that, while birds can use multiple mechanisms to acclimate to their thermal environment, they use a subset of potential changes over varying timescales.
Technical Note: STRATIS: A Cloud-enabled Software Toolbox for Radiotherapy and Imaging Analysis
Authors: Apte Aditya P. , LoCastro Eve , Iyer Aditi , Jiang Jue , Oh Jung Hun , Veeraraghavan Harini , Shukla-Dave Amita , Deasy Joseph O. 
Published: November 2022

AbstractPurposeRecent advances in computational resources, including software libraries and hardware, have enabled the use of high-dimensional, multi-modal datasets to build Artificial Intelligence (AI) models and workflows for radiation therapy and image analysis. The purpose of Software Toolbox for RAdioTherapy and Imaging analysiS (STRATIS) is to provide cloud-enabled, easy-to-share software workflows to train and deploy AI models for transparency and multi-institutional collaboration.MethodSTRATIS leverages open source medical image informatics software for application-specific analysis. Jupyter notebooks for AI modeling workflows are provided with Python language as the base kernel. In addition to Python, workflows use software written in other languages, such as MATLAB, GNU-Octave, R, and C++, with the help of bridge libraries. The workflows can be run on a cloud platform, local workstation, or an institutional HPC cluster. Computational environments are provided in the form of publicly available docker images -and build scripts for local Anaconda environments. Utilities provided with STRATIS simplify bookkeeping of associations between imaging objects and allow chaining data processing operations defined via a setting file for AI models.ResultsWorkflows available on STRATIS can be broadly categorized into image segmentation, deformable image registration, and outcomes modeling for radiotherapy toxicity and tumor control using radiomics and dosimetry features. The STRATIS-forge GitHub organizationhttps://www.github.com/stratis-forgehosts build-scripts for Docker and Anaconda as well as Jupyter notebooks for analysis workflows. The software for building environments and workflow notebooks has open source-GNU-GPL copyright, and AI models retain the copyright chosen by their original developers.ConclusionSTRATIS enables researchers to deploy and share AI modeling workflows for radiotherapy and image analysis. STRATIS is publicly available on Terra.bio’s FireCloud platform with a pre-deployed computational environment and on GitHub organization for users pursuing local deployment.
Non-invasive disruption of the blood-brain barrier in the marmoset monkey
Authors: Szuzupak Diego , Choi Sang-Ho , Alikaya Aydin , Mou Yongshan , Silva Afonso C. , Schaeffer David J. 
Published: November 2022

AbstractThe common marmoset monkey (Callithrix jacchus) is a species of rising prominence in the neurosciences due to their small size, ease of handling, fast breeding, and their shared functional and structural brain characteristics with Old World primates. With increasing attention on modeling human brain diseases in marmosets, understanding how to deliver therapeutic or neurotropic agents to the marmoset brain non-invasively is of great preclinical importance. In other species, including humans, transcranial focused ultrasound (tFUS) aided by intravenously injected microbubbles has proven to be a transient, reliable, and safe method for disrupting the blood-brain barrier (BBB), allowing for the focal passage of therapeutic agents that do not otherwise readily traverse the tight endothelial junctions of the BBB. The critical gap that we address here is to document parameters to disrupt the BBB reliably and safely in marmosets using tFUS. By integrating our marmoset brain atlases and the use of a marmoset-specific stereotactic targeting system, we conducted a series of systematic transcranial sonication experiments in nine marmosets. We demonstrate the effects of center frequency, acoustic pressure, burst period and duration, establish a minimum microbubble dose, estimate microbubble clearance time, and estimate the duration that the BBB remained open to passage. Successful BBB disruption was reportedin vivowith MRI-based contrast agents, as well as Evans blue staining assessedex vivo. Histology (Hematoxylin and Eosin staining) and immunohistochemistry indicated that the BBB can be safely and reliably opened with the parameters derived from these experiments.