bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linking movement and dive data to prey distribution models: new insights in foraging behaviour and potential pitfalls of movement analyses
Authors: Florko Katie R.N. , Shuert Courtney R. , Cheung William W.L. , Ferguson Steven H. , Jonsen Ian D. , Rosen David A.S. , Sumaila U. Rashid , Tai Travis C. , Yurkowski David J. , Auger-Méthé Marie 
Published: November 2022

AbstractBackgroundAnimal movement data are regularly used to infer foraging behaviour and relationships to environmental characteristics, often to help identify critical habitat. To characterize foraging, movement models make a set of assumptions rooted in theory, for example, time spent foraging in an area increases with higher prey density.MethodsWe assessed the validity of these assumptions by associating horizontal movement and diving of satellite-telemetered ringed seals (Pusa hispida) – an opportunistic predator – in Hudson Bay, Canada, to modelled prey data and environmental proxies.ResultsModelled prey biomass data performed better than their environmental proxies (e.g., sea surface temperature) for explaining seal movement, however movement was not related to foraging effort. Counter to theory, seals appeared to forage more in areas with relatively lower prey diversity and biomass, potentially due to reduced foraging efficiency in those areas.ConclusionsOur study highlights the need to validate movement analyses with prey data to effectively estimate the relationship between prey availability and foraging behaviour.
Structural insights into perilipin 3 membrane association in response to diacylglycerol accumulation
Authors: Choi Yong Mi , Ajjaji Dalila , Fleming Kaelin D. , Borbat Peter P. , Jenkins Meredith L. , Moeller Brandon E. , Fernando Shaveen , Bhatia Surita R. , Freed Jack H. , Burke John E. , Thiam Abdou Rachid , Airola Michael V. 
Published: November 2022

ABSTRACTLipid droplets (LDs) are dynamic organelles that contain an oil core mainly composed of triglycerides (TAG) that is surrounded by a phospholipid monolayer and LD-associated proteins called perilipins (PLINs). During LD biogenesis, perilipin 3 (PLIN3) is recruited to nascent LDs as they emerge from the endoplasmic reticulum. Here, we analyzed how lipid composition affects PLIN3 recruitment to membrane bilayers and LDs, and the structural changes that occur upon membrane binding. We found the TAG precursors phosphatidic acid and diacylglycerol (DAG) recruit PLIN3 to membrane bilayers and define an expanded Perilipin-ADRP-Tip47 (PAT) domain that preferentially binds DAG enriched membranes. Membrane binding induces a disorder/order transition of alpha helices within the PAT domain and 11-mer repeats, with intramolecular distance measurements consistent with the expanded PAT domain adopting a folded but dynamic structure upon membrane binding. In cells, PLIN3 is recruited to DAG enriched ER membranes, and this requires both the PAT domain and 11-mer repeats. This provides molecular details of PLIN3 recruitment to nascent LDs and identifies a function of the PAT domain of PLIN3 in DAG binding.
Holistic profiling of the venom from the lethal spiderPhoneutria nigriventerby combining high-throughput ion channel screens with venomics
Authors: Cardoso FC , Walker AA , King GF , Gomez MV 
Published: November 2022

AbstractSpider venoms are a unique source of bioactive peptides, many of which display remarkable biological stability and neuroactivity.Phoneutria nigriventer, often referred to as the Brazilian wandering spider, banana spider or “armed” spider, is endemic to South America and amongst the most dangerous venomous spiders in the world. There are 4,000 envenomation accidents withP. nigriventereach year in Brazil, which can lead to symptoms including priapism, hypertension, blurred vision, sweating, and vomiting. In addition to its clinical relevance,P. nigriventervenom contains peptides that provide therapeutic effects in a range of disease models. In this study, we explored the neuroactivity and molecular diversityP. nigriventervenom using fractionation-guided high-throughput cellular assays coupled to proteomics and multi-pharmacology activity to broaden the knowledge about this venom and its therapeutic potential and provide a proof-of-concept for an investigative pipeline to study spider-venom derived neuroactive peptides. We coupled proteomics with ion channel assays using a neuroblastoma cell line to identify venom compounds that modulate the activity of voltage-gated sodium and calcium channels, as well as the nicotinic acetylcholine receptor. Our data revealed thatP. nigriventervenom is highly complex compared to other neurotoxin-rich venoms and contains potent modulators of voltage-gated ion channels which were classified into four families of neuroactive peptides based on their activity and structures. In addition to the reportedP. nigriventerneuroactive peptides, we identified at least 27 novel cysteine-rich venom peptides for which their activity and molecular target remains to be determined. Our findings provide a platform for studying the bioactivity of known and novel neuroactive components in the venom ofP. nigriventerand other spiders and suggests that our discovery pipeline can be used to identify ion channel-targeting venom peptides with potential as pharmacological tools and to drug leads.
CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures
Authors: Sanchez-Fernandez Ana , Rumetshofer Elisabeth , Hochreiter Sepp , Klambauer Günter 
Published: November 2022

AbstractCurrently, bioimaging databases cannot be queried by chemical structures that induce the phenotypic effects captured by an image. Through the advent of the contrastive learning paradigm, images and text could be embedded into the same space. We build on this contrastive learning paradigm, to present a novel retrieval system that is able to identify the correct bioimage given a chemical structure out of a database of∼2,000 candidate images with a top-1 accuracy>70 times higher than a random baseline. Additionally, the learned embeddings of our method are highly transferable to various relevant downstream tasks in drug discovery, including activity prediction, microscopy image classification and mechanism of action identification.
PlantTribes2: tools for comparative gene family analysis in plant genomics
Authors: Wafula Eric K. , Zhang Huiting , Kuster Gregory Von , Leebens-Mack James H. , Honaas Loren A. , dePamphilis Claude W. 
Published: November 2022

AbstractPlant genome-scale resources are being generated at an increasing rate as sequencing technologies continue to improve and raw data costs continue to fall; however, the cost of downstream analyses remains large. This has resulted in a considerable range of genome assembly and annotation qualities across plant genomes due to their varying sizes, complexity, and the technology used for the assembly and annotation. To effectively work across genomes, researchers increasingly rely on comparative genomic approaches that integrate across plant community resources and data types. Such efforts have aided the genome annotation process and yielded novel insights into the evolutionary history of genomes and gene families, including complex non-model organisms. The essential tools to achieve these insights rely on gene family analysis at a genome-scale, but they are not well integrated for rapid analysis of new data, and the learning curve can be steep. Here we present PlantTribes2, a scalable, easily accessible, highly customizable, and broadly applicable gene family analysis framework with multiple entry points including user provided data. It uses objective classifications of annotated protein sequences from existing, high-quality plant genomes for comparative and evolutionary studies. PlantTribes2 can improve transcript models and then sort them, either genome-scale annotations or individual gene coding sequences, into pre-computed orthologous gene family clusters with rich functional annotation information. Then, for gene families of interest, PlantTribes2 performs downstream analyses and customizable visualizations including, (1) multiple sequence alignment, (2) gene family phylogeny, (3) estimation of synonymous and non-synonymous substitution rates among homologous sequences, and (4) inference of large-scale duplication events. We give examples of PlantTribes2 applications in functional genomic studies of economically important plant families, namely transcriptomics in the weedy Orobanchaceae and a core orthogroup analysis (CROG) in Rosaceae. PlantTribes2 is freely available for use within the main public Galaxy instance and can be downloaded from GitHub or Bioconda. Importantly, PlantTribes2 can be readily adapted for use with genomic and transcriptomic data from any kind of organism.
SBMLKinetics: A Tool for Annotation-Independent Classification of Reaction Kinetics for SBML Models
Authors: Xu Jin 
Published: November 2022

AbstractBackgroundReaction networks are widely used as mechanistic models in systems biology to reveal principles of biological systems. Reactions are governed by kinetic laws that describe reaction rates. Selecting the appropriate kinetic laws is difficult for many modelers. There exist tools that attempt to find the correct kinetic laws based on annotations. Here, I developed annotation-independent technologies that assist modelers by focusing on finding kinetic laws commonly used for similar reactions.ResultsRecommending kinetic laws and other analyses of reaction networks can be viewed as a classification problem. Existing approaches to determining similar reactions rely heavily on having good annotations, a condition that is often unsatisfied in model repositories such as BioModels. I developed an annotation-independent approach to find similar reactions via reaction classifications. I proposed a two-dimensional kinetics classification scheme (2DK) that analyzed reactions along the dimensions of kinetics type (K type) and reaction type (R type). I identified approximately ten mutually exclusive K types, including zeroth order, mass action, Michaelis-Menten, Hill kinetics, and others. R types were organized by the number of distinct reactants and the number of distinct products in reactions. I constructed a tool, SBMLKinetics, that inputted a collection of SBML models and then calculated reaction classifications as the probability of each 2DK class. The effectiveness of 2DK was evaluated on BioModels, and the scheme classified over 95% of the reactions.Conclusions2DK had many applications. It provided adata-drivenannotation-independent approach to recommending kinetic laws by using type common for the kind of models in combination with the R type of the reactions. Alternatively, 2DK could also be used to alert users that a kinetic law was unusual for the K type and R type. Last, 2DK provided a way to analyze groups of models to compare their kinetic laws. I applied 2DK to BioModels to compare the kinetics of signaling networks with the kinetics of metabolic networks and found significant differences in K type distributions.
DeepBryo: a web app for AI-assisted morphometric characterization of cheilostome bryozoans
Authors: Di Martino Emanuela , Berning Björn , Gordon Dennis P , Kuklinski Piotr , Liow Lee Hsiang , Ramsfjell Mali H , Ribeiro Henrique L , Smith Abigail M , Taylor Paul D , Voje Kjetil L , Waeschenbach Andrea , Porto Arthur 
Published: November 2022

AbstractBryozoans are becoming an increasingly popular study system in macroevolutionary, ecological, and paleobiological research. Members of this colonial invertebrate phylum are notable for displaying an exceptional degree of division of labor in the form of specialized modules (polymorphs), which allow for the inference of individual allocation of resources to reproduction, defense, and growth using simple morphometric tools. However, morphometric characterizations of bryozoans are notoriously labored, due to the high number of structures often captured per image, as well as the need for specialized knowledge necessary for classifying individual skeletal structures within those images.We here introduce DeepBryo, a web application for deep learning-based morphometric characterization of cheilostome bryozoans. DeepBryo requires a single image as input and performs measurements automatically using instance segmentation algorithms. DeepBryo is capable of detecting objects belonging to six classes and outputting fourteen morphological shape measurements for each object based on the inferred segmentation maps. The users can visualize the predictions, check for errors, and directly filter model outputs on the web browser. Measurements can then be downloaded as a comma-separated values file.DeepBryo has been trained and validated on a total of 72,412 structures, belonging to six different object classes in 935 SEM images of cheilostome bryozoans belonging to 109 different families. The model shows high (>0.8) recall and precision for zooid-level structures. Its misclassification rate is low (~4%) and largely concentrated in a single object class (opesia). The model’s estimated structure-level area, height, and width measurements are statistically indistinguishable from those obtained via manual annotation (r2varying from 0.89 to 0.98) and show no detectable bias. DeepBryo reduces the person-hours required for characterizing the zooids in individual colonies to less than 1% of the time required for manual annotation at no significant loss of measurement accuracy.Our results indicate that DeepBryo enables cost-, labor,- and time-efficient morphometric characterization of cheilostome bryozoans. DeepBryo can greatly increase the scale of macroevolutionary, ecological, taxonomic, and paleobiological analyses, as well as the accessibility of deep learning tools for this emerging model system. Finally, DeepBryo provides the building blocks necessary for adapting the current application to other study groups.
Toxicity impacts on human adipose MSCs acutely exposed to Aroclor and non-Aroclor mixtures of PCBs
Authors: Behan-Bush Riley M. , Liszewski Jesse N. , Schrodt Michael V. , Vats Bhavya , Li Xueshu , Lehmler Hans-Joachim , Klingelhutz Aloysius J. , Ankrum James A. 
Published: November 2022

ABSTRACTPCBs accumulate in adipose where they may impact the growth and function of cells within the tissue. This is particularly concerning during adolescence when adipocytes expand rapidly. Herein we sought to understand how exposure to PCB mixtures found in U.S. schools affects human adipose mesenchymal stem/stromal cell (MSC) health and function. We investigated how exposure to Aroclor 1016 and Aroclor 1254, as well as a newly characterized non-Aroclor mixture that resembles the PCB profile found in cabinets, Cabinet Mixture, affects adipose MSC growth, viability, and function in vitro. We found that exposure to all three mixtures resulted in two distinct types of toxicity. At PCB concentrations >20 μM, the majority of MSCs die, while at 1-10 μM MSCs remained viable but display numerous alterations to their phenotype. At these sublethal concentrations, MSC rate of expansion slowed, and morphology changed. Further assessment revealed PCB-exposed MSCs had impaired adipogenesis and a modest decrease in immunosuppressive capabilities. Thus, exposure to PCB mixtures found in schools negatively impacts the health and function of adipose MSCs. This work has implications for human health due to MSCs’ role in supporting the growth and maintenance of adipose tissue.SYNOPSISPCB mixtures found in schools are toxic to human adipose mesenchymal stem/stromal cells, stunting their growth and altering their function in ways that could contribute to metabolic diseases.
NMY-2, TOE-2 and PIG-1 RegulateC. elegansAsymmetric Cell Divisions
Authors: Robinson Joseph , Teuliere Jerome , Yoo Shinja , Garriga Gian 
Published: November 2022

AbstractAsymmetric cell division (ACD) is an important mechanism that generates cellular diversity during development. Not only do asymmetric cell divisions produce daughter cells of different fates, many can produce daughters of different sizes, which we refer to as Daughter Cell Size Asymmetry (DCSA). InC. elegans, apoptotic cells are frequently produced by asymmetric divisions that exhibit DCSA, where the smaller daughter dies. We focus here on the divisions of the Q.a and Q.p neuroblasts, which produce apoptotic cells and divide with opposite polarity using both distinct and overlapping mechanisms. The PIG-1/MELK and TOE-2 proteins both regulate DCSA and specify the apoptotic cell fate in both the Q.a and Q.p divisions. In many asymmetric cell divisions, the non-muscle myosin NMY-2 is involved in properly positioning the cleavage furrow to produce daughters of unequal size. It was previously reported that NMY-2 is asymmetrically distributed and required for the DCSA of Q.a but not Q.p. In this study, we examined endogenously tagged reporters of NMY-2, TOE-2, and PIG-1 and found that all were asymmetric at the cortex during both the Q.a and Q.p divisions. TOE-2 and NMY-2 were biased toward the side of the dividing cell that would produce the smaller daughter, whereas PIG-1 was biased toward the side that would produce the larger daughter. We used temperature-sensitivenmy-2mutants to determine the role ofnmy-2in these divisions and found that these mutants only displayed DCSA defects in the Q.p division. We generated double mutant combinations between thenmy-2mutations and mutations intoe-2andpig-1. Thenmy-2mutations did not significantly alter the DCSA of thetoe-2andpig-1mutants but did alter the fate of the Q.a and Q.p daughters. This finding suggests that NMY-2 functions together with TOE-2 and PIG-1 to regulate DCSA but plays an independent role in specifying the fate of the Q.a and Q.p descendants.
Rapid Single-Shot Synthesis of the 217 Amino Acid-Long N-Terminal Domain of Pyocin S2
Authors: Saebi Azin , Brown Joseph S. , Marando Victoria M. , Hartrampf Nina , Chumbler Nicole M. , Hanna Stephanie , Poskus Mackenzie , Loas Andrei , Kiessling Laura L. , Hung Deborah T. , Pentelute Bradley L. 
Published: November 2022

AbstractThe impermeable outer membrane ofPseudomonas aeruginosais bypassed by antibacterial proteins known as S-type pyocins. Because of their properties, pyocins are investigated as a potential new class of antimicrobials againstPseudomonasinfections. Their production and modification, however, remains challenging. To address this limitation, we employed automated fast-flow peptide synthesis (AFPS) for the rapid production of a pyocin S2 import domain. The N-terminal domain sequence (PyS2NTD) was synthesized in under 10 hours and purified to yield milligrams quantities of the desired product. To our knowledge, the 217 amino acid sequence of PyS2NTDis among the longest peptides produced from a “single-shot” synthesis, i.e., made in a single stepwise route without the use of ligation techniques. Biophysical characterization of the PyS2NTDwith circular dichroism was consistent with the literature reports. Fluorescently labeled PyS2NTDbinds toP. aeruginosaexpressing the cognate ferripyoverdine receptor (FpvA) and is taken up into the periplasm. This selective uptake was validated with confocal and super resolution microscopy, flow cytometry, and fluorescence recovery after photobleaching (FRAP). These modified, synthetic S-type pyocins domains can be used to probe import mechanisms ofP. aeruginosaand leveraged to develop selective antimicrobial agents that bypass the outer membrane.
Adult consequences of repeated nicotine vapor inhalation in adolescent rats
Authors: Gutierrez Arnold , Nguyen Jacques D. , Creehan Kevin M. , Grant Yanabel , Taffe Michael A. 
Published: November 2022

AbstractIntroductionThere has been a recent resurgence in nicotine inhalation in adolescents due to the popularity and availability of Electronic Nicotine Delivery Systems (ENDS). Almost five times as many US high-school seniors inhale nicotine vapor daily compared with those who smoke tobacco. This study was conducted to determine the impact of repeated adolescent vapor inhalation of nicotine on behavior in adulthood.MethodsMale and female Sprague-Dawley rats were exposed to 30-minute sessions of ENDS vapor inhalation, twice daily, from Post-Natal Day (PND) 31 to PND 40. Conditions included vapor from the propylene glycol (PG) vehicle or nicotine (30 mg/mL in the PG). Animals were assessed for effects of nicotine on open field (PND 74-105) and wheel activity (PND 126-180) and for the self-administration of nicotine vapor (PND 285-395). Plasma levels of nicotine and cotinine were assessed in separate groups of male and female Wistar and Sprague-Dawley rats after a single nicotine inhalation session.ResultsGroup mean plasma nicotine ranged from 39 to 59 ng/mL post-session with minimal strain differences detected. Adolescent nicotine exposure modestly enhanced sensitivity to the locomotor stimulating effects of nicotine (0.1-0.8 mg/kg, s.c.) in an open field in female rats, but didn’t change effects of nicotine on wheel activity. Female rats exposed to nicotine (30 mg/mL) vapor as adolescents responded more vigorously than PG exposed females for nicotine vapor in a FR5 challenge.ConclusionsRepeated adolescent nicotine vapor inhalation leads to enhanced liability for nicotine self-administration in adulthood in female rats, but minimal change in spontaneous locomotor behavior.
Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis
Authors: Creagh Andrew P. , Hamy Valentin , Yuan Hang , Mertes Gert , Tomlinson Ryan , Chen Wen-Hung , Williams Rachel , Llop Christopher , Yee Christopher , Duh Mei Sheng , Doherty Aiden , Garcia-Gancedo Luis , Clifton David A. 
Published: November 2022

ABSTRACTDigital measures of health status captured during daily life could greatly augment current in-clinic assessments for rheumatoid arthritis (RA), to enable better assessment of disease progression and impact. This work presents results from weaRAble-PRO, a 14-day observational study, which aimed to investigate how digital health technologies (DHT), such as smartphones and wearables, could augment patient reported outcomes (PRO) to determine RA status and severity in a study of 30 moderate-to-severe RA patients, compared to 30 matched healthy controls (HC). Sensor-based measures of health status, mobility, dexterity, fatigue, and other RA specific symptoms were extracted from daily iPhone guided tests (GT), as well as actigraphy and heart rate sensor data, which was passively recorded from patients’ Apple smartwatch continuously over the study duration. We subsequently developed a machine learning (ML) framework to distinguish RA status and to estimate RA severity. It was found that daily wearable sensor-outcomes robustly distinguished RA from HC participants (F1, 0.807). Furthermore, by day 7 of the study (half-way), a sufficient volume of data had been collected to reliably capture the characteristics of RA participants. In addition, we observed that the detection of RA severity levels could be improved by augmenting standard patient reported outcomes with sensor-based features (F1, 0.833) in comparison to using PRO assessments alone (F1, 0.759), and that the combination of modalities could reliability measure continuous RA severity, as determined by the clinician-assessed RAPID-3 score at baseline (r2, 0.692; RMSE, 1.33). The ability to measure the impact of disease during daily life—through objective and remote digital outcomes—paves the way forward to enable the development of more patient-centric and personalised measurements for use in RA clinical trials.