bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-target effects of ten essential oils on the egg parasitoidTrichogramma evanescens
Authors: van Oudenhove Louise , Cazier Aurélie , Fillaud Marine , Lavoir Anne-Violette , Fatnassi Hicham , Pérez Guy , Calcagno Vincent 
Published: January 2022

AbstractEssential oils (EOs) are increasingly used as biopesticides due to their insecticidal potential. This study addresses their non-target effects on a biological control agent: the egg parasitoidTrichogramma evanescens. In particular, we tested whether EOs affected parasitoid fitness either directly, by decreasing pre-imaginal survival, or indirectly, by disrupting parasitoids’ orientation abilities. The effect of Anise, Fennel, Sweet orange, Basil, Coriander, Oregano, Peppermint, Mugwort, Rosemary and Thyme EOs were studied on five strains ofT. evanescens. Specific experimental setups were developed, and data obtained from image analysis were interpreted with phenomenological models fitted with Bayesian inference. Results highlight the fumigant toxicity of EOs on parasitoid development. Anise, Fennel, Basil, Coriander, Oregano, Peppermint and Thyme EOs are particularly toxic and drastically reduce the emergence rate ofT. evanescens. Most EOs also affect parasitoid behavior: (i) Basil, Coriander, Oregano, Peppermint, Mugwort and Thyme EOs are highly repellent for naive female parasitoids; (ii) Anise and Fennel EOs can have repellent or attractive effects depending on strains; and (iii) Sweet orange, Oregano and Rosemary EOs have no detectable impact on orientation behavior. This study shows that EOs fumigation have non-target effects on egg parasitoids. This highlights the need to cautiously precise the deployment framework of biopesticides in an agroecological perspective.
Utilizing citizen science to model the distribution ofAedes aegypti([Diptera]: [Culicidae]) in West Africa
Authors: Freeman Elizabeth A. , Carlton Elizabeth J. , Paull Sara , Dadzie Samuel , Buchwald Andrea 
Published: January 2022

AbstractIn a rapidly urbanizing region such as West Africa,Aedesmosquitoes pose an emerging threat of infectious disease that is compounded by limited vector surveillance. Citizen science has been proposed as a way to fill surveillance gaps by training local residents to collect and share information on disease vectors. Increasing citizen science efforts can begin to bridge the gaps in our current knowledge ofAedesdistribution while engaging locals with mosquito control and public health efforts. Understanding the distribution of disease vectors in West Africa can inform researchers and public health officials on where to conduct disease surveillance and focus public health interventions. We aimed to compare citizen science data to published literature observations ofAedesmosquitoes and to quantify how incorporating citizen science changes our understanding ofAedesmosquito distribution in West Africa. We utilized citizen science data collected through NASA’s GLOBE Observer mobile phone application and data from a previously published literature review onAedesmosquito distribution to examine the contribution of citizen science to understanding the distribution ofAe. aegyptiin West Africa using Maximum Entropy modeling. Combining citizen science and literature-derived observations improved the fit of the model compared to models created by each data source alone, but did not alleviate location bias within the models, likely due to lack of widespread observations. UnderstandingAe. aegyptidistribution will require greater investment inAedesmosquito surveillance in the region, and citizen science should be utilized as a tool in this mission to increase the reach of surveillance.
Deciphering the evolution of microbial interactions: in silico studies of two-member microbial communities
Authors: Sambamoorthy Gayathri , Raman Karthik 
Published: January 2022

AbstractMicrobes thrive in communities, embedded in a complex web of interactions. These interactions, particularly metabolic interactions, play a crucial role in maintaining the community structure and function. As the organisms thrive and evolve, a variety of evolutionary processes alter the interactions among the organisms in the community, although the community function remains intact. In this work, we simulate the evolution of two-member microbial communities in silico to study how evolutionary forces can shape the interactions between organisms. We employ genome-scale metabolic models of organisms from the human gut, which exhibit a range of interaction patterns, from mutualism to parasitism. We observe that the evolution of microbial interactions varies depending upon the starting interaction and also on the metabolic capabilities of the organisms in the community. We find that evolutionary constraints play a significant role in shaping the dependencies of organisms in the community. Evolution of microbial communities yields fitness benefits in only a small fraction of the communities, and is also dependent on the interaction type of the wild-type communities. The metabolites cross-fed in the wild-type communities appear in only less than 50% of the evolved communities. A wide range of new metabolites are cross-fed as the communities evolve. Further, the dynamics of microbial interactions are not specific to the interaction of the wild-type community but vary depending on the organisms present in the community. Our approach of evolving microbial communities in silico provides an exciting glimpse of the dynamics of microbial interactions and offers several avenues for future investigations.
Glucose-stimulated calcium dynamics in beta cells from C57BL/6J, C57BL/6N, and NMRI mice: A systematic comparison of activation, activity, and deactivation properties in tissue slices
Authors: Pohorec Viljem , Bombek Lidija Križančić , Klemen Maša Skelin , Dolenšek Jurij , Stožer Andraž 
Published: January 2022

ABSTRACTAlthough mice are a very instrumental model in islet beta cell research, possible phenotypic differences between strains and substrains are largely neglected in the scientific community. In this study, we show important phenotypic differences in beta cell responses to glucose between NMRI, C57BL/6J, and C57BL/6N mice, i.e., the three most commonly used strains. High-resolution multicellular confocal imaging of beta cells in acute pancreas tissue slices was used to measure and quantitatively compare the calcium dynamics in response to a wide range of glucose concentrations. Strain- and substrain-specific features were found in all three phases of beta cell responses to glucose: a shift in the dose-response curve characterizing the delay to activation and deactivation in response to stimulus onset and termination, respectively, and distinct concentration-encoding principles during the plateau phase in terms of frequency, duration, and active time changes with increasing glucose concentrations. Our results underline the significance of carefully choosing and reporting the strain to enable comparison and increase reproducibility, emphasize the importance of analyzing a number of different beta cell physiological parameters characterizing the response to glucose, and provide a valuable standard for future studies on beta cell calcium dynamics in health and disease.
DeepGOZero: Improving protein function prediction from sequence and zero-shot learning based on ontology axioms
Authors: Kulmanov Maxat , Hoehndorf Robert 
Published: January 2022

AbstractMotivationProtein functions are often described using the Gene Ontology (GO) which is an ontology consisting of over 50,000 classes and a large set of formal axioms. Predicting the functions of proteins is one of the key challenges in computational biology and a variety of machine learning methods have been developed for this purpose. However, these methods usually require significant amount of training data and cannot make predictions for GO classes which have only few or no experimental annotations.ResultsWe developed DeepGOZero, a machine learning model which improves predictions for functions with no or only a small number of annotations. To achieve this goal, we rely on a model-theoretic approach for learning ontology embeddings and combine it with neural networks for protein function prediction. DeepGOZero can exploit formal axioms in the GO to make zero-shot predictions, i.e., predict protein functions even if not a single protein in the training phase was associated with that function. Furthermore, the zero-shot prediction method employed by DeepGOZero is generic and can be applied whenever associations with ontology classes need to be predicted.Availabilityhttp://github.com/bio-ontology-research-group/deepgozeroContactrobert.hoehndorf@kaust.edu.sa
White Matter Brain Structure Predicts Language Performance and Learning Success
Authors: Sánchez Stella M. , Schmidt Helmut , Gallardo Guillermo , Anwander Alfred , Brauer Jens , Friederici Angela D. , Knösche Thomas R. 
Published: January 2022

AbstractIndividual differences in the ability to deal with language have long been discussed. The neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants’ native language as well as the improvement thereof by multi-day training. We identified specific network motifs that indeed related white matter tractography to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance suggesting a predisposition for the individual ability to process syntactically complex sentences, which manifests itself in the white matter brain structure. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brain’s white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.
Significant organic carbon acquisition byProchlorococcusin the oceans
Authors: Wu Zhen , Aharonovich Dikla , Roth-Rosenberg Dalit , Weissberg Osnat , Luzzatto-Knaan Tal , Vogts Angela , Zoccarato Luca , Eigemann Falk , Grossart Hans-Peter , Voss Maren , Follows Michael J. , Sher Daniel 
Published: January 2022

AbstractMarine phytoplankton are responsible for about half of the photosynthesis on Earth. Many are mixotrophs, combining photosynthesis with heterotrophic assimilation of organic carbon but the relative contribution of these two carbon sources is not well quantified. Here, single-cell measurements reveal thatProchlorococcusat the base of the photic zone in the Eastern Mediterranean Sea are obtaining only ~20% of carbon required for growth by photosynthesis. Consistently, laboratory-calibrated evaluations ofProchlorococcusphotosynthesis indicate that carbon fixation is systematically too low to support publishedin situgrowth rates in the deep photic layer of the Pacific Ocean. Furthermore, agent-based model simulations show that mixotrophic cells maintain realistic growth rates and populations 10s of meters deeper than obligate photo-autotrophs, deepening the nutricline and Deep Chlorophyll Maximum by ~20 m. Time-series ofProchlorococcusecotype-abundance from the subtropical North Atlantic and North Pacific suggest that up to 30% of theProchlorococcuscells live where light intensity is not enough to sustain obligate photo-autotrophic populations during warm, stratified periods. Together, these data and models suggest that mixotrophy underpins the ecological success of a large fraction of the globalProchlorococcuspopulation and its collective genetic diversity.
A semi-supervised Bayesian mixture modelling approach for joint batch correction and classification
Authors: Coleman Stephen , Nicholls Kath , Dopico Xaquin Castro , Karlsson Hedestam Gunilla B. , Kirk Paul D.W. , Wallace Chris 
Published: January 2022

AbstractSystematic differences between batches of samples present significant challenges when analysing biological data. Suchbatch effectsare well-studied and are liable to occur in any setting where multiple batches are assayed. Many existing methods for accounting for these have focused on high-dimensional data such as RNA-seq and have assumptions that reflect this. Here we focus on batch-correction in low-dimensional classification problems. We propose a semi-supervised Bayesian generative classifier based on mixture models that jointly predicts class labels and models batch effects. Our model allows observations to be probabilistically assigned to classes in a way that incorporates uncertainty arising from batch effects. By simultaneously inferring the classification and the batch-correction our method is more robust to dependence between batch and class than pre-processing steps such as ComBat. We explore two choices for the within-class densities: the multivariate normal and the multivariatet. A simulation study demonstrates that our method performs well compared to popular off-the-shelf machine learning methods and is also quick; performing 15,000 iterations on a dataset of 750 samples with 2 measurements each in 11.7 seconds for the MVN mixture model and 14.7 seconds for the MVT mixture model. We further validate our model on gene expression data where cell type (class) is known and simulate batch effects. We apply our model to two datasets generated using the enzyme-linked immunosorbent assay (ELISA), a spectrophotometric assay often used to screen for antibodies. The examples we consider were collected in 2020 and measure seropositivity for SARS-CoV-2. We use our model to estimate seroprevalence in the populations studied. We implement the models in C++ using a Metropolis-within-Gibbs algorithm, available in the R packagebatchmix. Scripts to recreate our analysis are athttps://github.com/stcolema/BatchClassifierPaper.
Using intracerebral microdialysis to probe the efficacy of repurposed drugs in Alzheimer’s disease pathology
Authors: Bjorkli Christiana , Hemler Mary , Julian Joshua B. , Sandvig Axel , Sandvig Ioanna 
Published: January 2022

AbstractAll disease-targeting drug trials completed to date have fallen short of meeting the clinical endpoint of significantly slowing cognitive decline in Alzheimer’s disease patients. Even the recently approved drug Aducanumab, has proven effective in removing amyloid-β, but does not reduce cognitive decline. This emphasizes the urgent need for novel therapeutic approaches that could reduce several AD neuropathologies simultaneously, eventually leading to improved cognitive performance. To validate whether our mouse model replicates AD neuropathology as observed in patients, we characterized the 3xTg AD mouse model to avoid premature translation of successful results. In this study we have repurposed two FDA-approved drugs, Fasudil and Lonafarnib, targeting the Wnt signaling and endosomal-lysosomal pathway respectively, to test their potential to attenuate AD pathology. Using intracerebral microdialysis, we simultaneously infused these disease-targeting drugs between 1-2 weeks, separately and also in combination, while collecting cerebrospinal fluid. We found that Fasudil reduces intracellular amyloid-β in young, and amyloid plaques in old animals, and overall cerebrospinal fluid amyloid-β. Lonafarnib reduces tau neuropathology and cerebrospinal fluid tau biomarkers in young and old animals. Co-infusion of both drugs was more effective in reducing intracellular amyloid-β than either drug alone, and appeared to improve contextual memory performance. However, an unexpected finding was that Lonafarnib treatment increased amyloid plaque size, suggesting that activating the endosomal-lysosomal system may inadvertently increase amyloid-β pathology if administered too late in the AD continuum. Taken together, these findings lend support to the application of repurposed drugs to attenuate AD neuropathology at various therapeutic time windows.One Sentence SummaryHere we circumvented the blood-brain barrier for drug delivery aimed at attenuating AD neuropathology.
Comparative analysis of cattle breeds as satellite cell donors for cultured beef
Authors: Melzener Lea , Ding Shijie , Hueber Rui , Messmer Tobias , Zhou Guanghong , Post Mark J , Flack Joshua E 
Published: January 2022

AbstractBackgroundCultured meat is a promising new field with the potential for considerable environmental and animal welfare benefits. One technological approach to cultured meat production utilises the proliferative and differentiative capacity of muscle-derived satellite cells (SCs) to produce large volumes of cultured muscle tissue from small biopsies of donor animals. Differing genotypes between cattle breeds lead to predictable phenotypic traits, resulting in breeds being favoured for their respective meat or milk production characteristics in the livestock industry. However, whilst these breeds show significant differences in muscle growth, it is unclear whether the physiological differences observed between them in vivo are reflected in differences in SC behaviour in vitro, particularly with respect to proliferation, differentiation and cellular longevity, and hence whether particular breeds might represent preferred SC donors for a cultured beef bioprocess.ResultsComparing SCs isolated from five breeds (Belgian Blue, Holstein Friesian, Galloway, Limousin and Simmental), we found that the proliferation rates were largely unaffected by the donor breed. In contrast, potentially meaningful differences were observed in the kinetics and extent of myogenic differentiation. Furthermore, whilst differentiation dropped for all breeds with increasing population doublings (PDs), SCs from Belgian Blue and Limousin cattle showed significantly longer retention of differentiation capacity over long-term passaging.ConclusionSCs from all breeds were able to proliferate and differentiate, although Limousin and (particularly) Belgian Blue cattle, both breeds commonly used for traditional meat production, may represent preferred donors for cultured beef production.
Proteasome dysfunction disrupts adipogenesis and induces inflammation via ATF3
Authors: Willemsen Nienke , Arigoni Isabel , Studencka-Turski Maja , Krüger Elke , Bartelt Alexander 
Published: January 2022

AbstractObjectiveRegulation of proteasomal activity is an essential component of cellular proteostasis and function. This is evident in patients with mutations in proteasome subunits and regulators, who suffer from proteasome-associated autoinflammatory syndromes (PRAAS). These patients display lipodystrophy and fevers, which may be partly related to adipocyte malfunction and abnormal thermogenesis in adipose tissue. However, the cell-intrinsic pathways that could underlie these symptoms are unclear. Here, we investigate the impact of two proteasome subunits implicated in PRAAS, Psmb4 and Psmb8, on differentiation, function and proteostasis of brown adipocytes.MethodsIn immortalized mouse brown pre-adipocytes, levels of Psmb4, Psmb8, and downstream effectors genes were downregulated through reverse transfection with siRNA. Adipocytes were differentiated and analyzed with various assays of adipogenesis, lipogenesis, lipolysis, inflammation, and respiration.ResultsLoss of Psmb4, but not Psmb8, disrupted proteostasis and adipogenesis. Proteasome function was reduced upon Psmb4 loss, but partly recovered by the activation of Nuclear factor, erythroid-2, like-1 (Nfe2l1). In addition, cells displayed higher levels of surrogate inflammation and stress markers, including Activating transcription factor-3 (Atf3). Simultaneous silencing of Psmb4 and Atf3 lowered inflammation and restored adipogenesis.ConclusionsOur study shows that Psmb4 is required for adipocyte development and function in cultured adipocytes. These results imply that in humans with PSMB4 mutations, PRAAS-associated lipodystrophy is partly caused by disturbed adipogenesis. While we uncover a role for Nfe2l1 in the maintenance of proteostasis under these conditions, Atf3 is a key effector of inflammation and blocking adipogenesis. In conclusion, our work highlights how proteasome dysfunction is sensed and mitigated by the integrated stress response in adipocytes with potential relevance for PRAAS patients and beyond.Highlights-PRAAS-associated PSMB4 is required for brown adipocyte differentiation-Loss of PSMB4 activates NFE2L1 to counteract proteasome dysfunction-The ATF3 pathway regulates adipocyte dysfunction and inflammation-Loss of ATF3 restores adipogenesis in cells with loss of PSMB4Graphical abstract