bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of egg production dynamics on the functional response of parasitoids
Authors: Aguirre María , Logarzo Guillermo , Triapitsyn Serguei , Diaz-Soltero Hilda , Hight Stephen , Bruzzone Octavio 
Published: March 2023

ABSTRACTFunctional response describes the number of hosts attacked by a parasitoid in relation to host densities and plays an important role by connecting behavioral-level processes with community-level processes. Most functional response studies were carried out using simple experimental designs where the insects were confined to a plain and small arena with different host densities during a fixed period of time. With these designs, other factors that might affect the functional response of parasitoids were not analyzed, such as fecundity, age, and experience. We proposed a series of latent-variables Markovian models that comprised an integrated approach of functional response and egg production models to estimate the realized lifetime reproductive success of adult parasitoids. As a case study, we used the parasitoidsAnagyrus cachamaiandA. lapachosus(Hymenoptera: Encyrtidae), two candidate agents for neoclassical biocontrol of the Puerto Rican cactus pest mealybug,Hypogeococcussp. (Hemiptera: Pseudococcidae).Anagyrus cachamaiandA. lapachosuspresented a type III functional response. However, the two parasitoids behaved differently: forA. cachamai, the number of parasitized hosts decreased with female age and depended on the number of mature eggs that were available for oviposition, whereasA. lapachosushost parasitism increased with female age and was modulated by its daily egg load and previous experience. The tested species were assessed according to their physiology and prior experience. We estimated the number of mature eggs after emergence, egg production on the first day, egg production rate, proportion of eggs resorbed, egg resorption threshold, and egg storage capacity. The methodology presented may have large applicability in pest control, invasive species management, and conservation biology, as it has the potential to increase our understanding of the reproductive biology of a wide variety of species, ultimately leading to improved management strategies.
Beyond performance, competence, and recognition: Forging a science researcher identity in the context of research training
Authors: Pfeifer Mariel A. , Zajic C.J. , Isaacs Jared M. , Erickson Olivia A. , Dolan Erin L. 
Published: March 2023

AbstractBackgroundStudying science identity development has been useful for understanding students’ continuation in science-related education and career paths. Yet, how science contexts shape students’ science identity development, especially as students engage in research at the undergraduate and graduate level, is still largely unexplored. Here we integrate science identity and professional identity theories to investigate how research training shapes science identity. We focus on a specialized form of science identity we call science researcher identity. We characterize how the features of an individual’s research experience, and their personal characteristics interact to influence whether and how they see themselves as a science researcher. We accomplished this in two phases of qualitative research. First, we surveyed 548 undergraduate researchers about how their research experience influenced their identity as a scientist. Then we interviewed 30 early career researchers, including undergraduate, postbaccalaureate, and doctoral students, about their views of themselves as researchers and how elements of their research training shaped their views.ResultsEarly career researchers (ECRs) viewed themselves as either science students or science researchers. How ECRs recognized themselves depended on how they viewed the purpose of their daily work and the extent to which they perceived autonomy and intellectual responsibility in their research. Individual-level factors, including research and researcher conceptions, research skill perceptions, and career intentions, influenced whether ECRs identified as science students or science researchers. ECRs also recognized themselves more or less as researchers based on contextual factors like the nature of their work, social interactions, and their perceptions of the norms within their research group and institution. ECRs considered how individual and contextual factors affected their science researcher identity through a lens we call ‘sense-making.’ We further detail the processes ECRs use to make sense of their science identity and the factors that influence it.ConclusionsWe synthesized our findings to form a conceptual model of science researcher identity development, which hypothesizes relationships among constructs related to science identity and professional identity development. Our results advance theory related to science identity, offer avenues for future investigation, and inform efforts to promote science researcher identity development.
A dynamic foot model for predictive simulations of gait reveals causal relations between foot structure and whole body mechanics
Authors: D’Hondt Lars , De Groote Friedl , Afschrift Maarten 
Published: March 2023

AbstractThe unique structure of the human foot is seen as a crucial adaptation for bipedalism. Its arched shape makes it possible to stiffen the foot to withstand high loads when pushing off, without compromising the range of motion. Experimental studies demonstrated that manipulating foot stiffness had considerable effects on gait. In clinical practise, altered foot structure is associated with pathological gait. Yet our understanding of how foot structure influences gait mechanics is still poor. Here we used predictive simulations to explore causal relations between foot properties and whole-body gait. Our dynamic three-segment foot model with longitudinal arch improved gait predictions compared to one- and two-segment foot models and can explain measured ankle-foot kinematics and energetics. We identified three properties of the ankle-foot complex that are crucial for healthy walking: (1) compliant Achilles tendon, (2) stiff heel pad, (3) the ability to stiffen the foot. The latter requires sufficient arch height and contributions of plantar fascia, intrinsic and extrinsic foot muscles. Insufficient foot stiffness results in walking patterns with reduced push-off power. During terminal stance plantar fascia and intrinsic foot muscles transfer energy from the metatarsophalangeal to midtarsal joint, which further increases push-off power.
Memory Th1 cells modulate heterologous diseases through innate function
Authors: Rakebrandt Nikolas , Yassini Nima , Kolz Anna , Schorer Michelle , Lambert Katharina , Rauld Celine , Balazs Zsolt , Krauthammer Michael , Carballido José M. , Peters Anneli , Joller Nicole 
Published: March 2023

AbstractThrough immune memory, infections have a lasting effect on the host. While memory cells enable accelerated and enhanced responses upon re-challenge with the same pathogen, their impact on susceptibility to unrelated diseases is unclear. We identify a subset of memory T helper 1 (Th1) cells termed innate acting memory T (TIA) cells that originate from a viral infection and produce IFN-γ with innate kinetics upon heterologous challengein vivo. Activation of memory TIAcells is induced in response to IL-12 in combination with IL-18 or IL-33 but is TCR-independent. Rapid IFN-γ production by memory TIAcells is protective in subsequent heterologous challenge with the bacterial pathogenLegionella pneumophila. In contrast, antigen-independent re-activation of CD4+memory TIAcells accelerates disease onset in an autoimmune model of multiple sclerosis. Our findings demonstrate that memory Th1 cells can acquire additional TCR-independent functionality to mount rapid, innate-like responses that modulate susceptibility to heterologous challenges.
Early language dissociation in bilingual minds: Non-invasive magnetoencephalography evidence through a machine learning approach
Authors: Molinaro Nicola , Nara Sanjeev , Carreiras Manuel 
Published: March 2023

AbstractIs language selection in balanced bilinguals decodable from neural activity? Previous research employing various neuroimaging methods has not yielded a conclusive answer to this issue. However, direct brain stimulation studies in bilinguals have detected different brain regions related to language production in separate languages. In the present MEG study, we addressed this question in a group of proficient Spanish-Basque bilinguals (N=45), who performed two tasks (picture naming and word reading). They were asked to name the line drawing or read the word out loud, either in Basque or Spanish, if the ink turned from black to green after one second (randomly, in 10% of trials). Sensor-level evoked activity was similar and could not be differentiated for the two languages in either task. Crucially however, decoding analyses classified the language used in both tasks, starting ∼100 ms after stimulus onset. Searchlight analyses revealed that activity detected in the right occipital-temporal sensors contributed the most to language decoding in the picture naming task, while the left occipital-temporal sensors contributed the most to decoding in word reading. The cross-task decoding analysis highlighted robust generalization effects from the picture naming to the word reading task in a later time interval. The present findings bridge the gap between non-invasive and invasive experimental evidence on bilingual lexical processing and provide novel evidence about the role of the two hemispheres in activating each language for picture naming and word reading.
A haplotype resolved chromosome-scale assembly of North American wild appleMalus fuscaand comparative genomics of the fire blightMfu10locus. Genome of the Pacific CrabappleMalus fusca
Authors: Mansfeld Ben N. , Yocca Alan , Ou Shujun , Harkess Alex , Burchard Erik , Gutierrez Benjamin , Nocker Steve van , Gottschalk Christopher 
Published: March 2023

AbstractThe Pacific crabapple (Malus fusca) is a wild relative of the commercial apple (Malus×domestica). With a range extending from Alaska to Northern California,M. fuscais extremely hardy and disease resistant. The species represents an untapped genetic resource for development of new apple cultivars with enhanced stress resistance. However, gene discovery and utilization ofM. fuscahas been hampered by the lack of genomic resources. Here, we present a high-quality, haplotype-resolved, chromosome-scale genome assembly and annotation forM. fusca. The genome was assembled using high-fidelity long-reads and scaffolded using genetic maps and high-throughput chromatin conformation capture sequencing, resulting in one of the most contiguous apple genomes to date. We annotated the genome using public transcriptomic data from the same species taken from diverse plant structures and developmental stages. Using this assembly, we explored haplotypic structural variation within the genome ofM. fusca,identifying thousands of large variants. We further showed high sequence co-linearity with other domesticated and wildMalusspecies. Finally, we resolve a known quantitative trait locus associated with resistance to fire blight (Erwinia amylovora). Insights gained from the assembly of a reference-quality genome of this hardy wild apple relative will be invaluable as a tool to facilitate DNA-informed introgression breeding.
The intricate triangular interaction between protective microbe, pathogen, and host genetics determines fitness of the metaorganism
Authors: Griem-Krey Hanne , Petersen Carola , Hamerich Inga K. , Schulenburg Hinrich 
Published: March 2023

AbstractThe microbiota shapes host biology in numerous ways. One example is protection against pathogens, which is likely critical for host fitness in consideration of the ubiquity of pathogens. The host itself can affect abundance of microbiota or pathogens, which has usually been characterised in separate studies. To date, however, it is unclear how the host influences the interaction with both simultaneously and how this triangular interaction determines fitness of the host-microbe assemblage, the so-called metaorganism. To address this current knowledge gap, we focused on a triangular model interaction, consisting of the nematodeCaenorhabditis elegans, its immune-protective symbiontPseudomonas luridaMYb11, and its pathogenBacillus thuringiensisBt679. We combined the two microbes withC. elegansmutants with altered immunity and/or microbial colonisation, and found that (i) under pathogen stress, immunocompetence has a larger influence on metaorganism fitness than colonisation with the protective microbe, (ii) in almost all cases, MYb11 still improves fitness, and (iii) disruption of p38 MAPK signalling, which contributes centrally to immunity against Bt679, completely reverses the protective effect of MYb11, which further reduces nematode survival and fitness upon infection with Bt679. Our study highlights the complex interplay between host genetics, protective microbe, and pathogen in shaping metaorganism biology.
Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results
Authors: Baron Cantin , Cherkaoui Sarah , Therrien-Laperriere Sandra , Ilboudo Yann , Poujol Raphaël , Mehanna Pamela , Garrett Melanie E. , Telen Marilyn J. , Ashley-Koch Allison E. , Bartolucci Pablo , Rioux John D. , Lettre Guillaume , Des Rosiers Christine , Ruiz Matthieu , Hussin Julie G. 
Published: March 2023

SUMMARYStudies combining metabolomics and genetics, known as metabolite genome-wide association studies (mGWAS), have provided valuable insights into our understanding of the genetic control of metabolite levels. However, the biological interpretation of these associations remains challenging due to a lack of existing tools to annotate mGWAS gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we computed the shortest reactional distance (SRD) based on the curated knowledge of the KEGG database to explore its utility in enhancing the biological interpretation of results from three independent mGWAS, including a case study on sickle cell disease patients. Results show that, in reported mGWAS pairs, there is an excess of small SRD values and that SRD values and p-values significantly correlate, even beyond the standard conservative thresholds. The added-value of SRD annotation is shown for identification of potential false negative hits, exemplified by the finding of gene-metabolite associations with SRD ≤1 that did not reach standard genome-wide significance cut-off. The wider use of this statistic as an mGWAS annotation would prevent the exclusion of biologically relevant associations and can also identify errors or gaps in current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs that can be used to integrate statistical evidence to biological networks.
Are increasing honey bee colony losses attributed toVarroa destructorin New Zealand driven by miticide resistance?
Authors: McGruddy Rose A. , Bulgarella Mariana , Felden Antoine , Baty James W. , Haywood John , Stahlmann-Brown Philip , Lester Philip J. 
Published: March 2023

AbstractThe most devastating pest to honey bees (Apis mellifera) worldwide is the parasitic miteVarroa destructor. The development of miticide-resistant mite populations has been a major driver of colony loss in many countries. We investigated the threat Varroa poses to honey bee populations in New Zealand and tested the effectiveness of the two most popular chemical treatments used by beekeepers. Colony losses reported by New Zealand beekeepers have risen over five consecutive years from 2017 to 2021, as have the proportion of losses attributed to Varroa, with this parasite found to be the main driver of colony loss in 2021. Varroa resistance to miticide treatments flumethrin and amitraz was tested. The concentration of flumethrin required to kill 50% of the mites (LC50) was 156 μg/g, 13 times greater than the adjusted LC50value of 12 μg/g observed in a trial also conducted in New Zealand in 2003, thus indicating evidence of developing mite resistance to flumethrin in New Zealand. Molecular analyses searching for mutations in the Varroa genome known to be associated with flumethrin resistance found no evidence of such mutations, suggesting that any extant resistance to flumethrin has evolved independently in New Zealand. No evidence of resistance to amitraz was found, as the LC50value of 12 μg/g was lower than what was observed in the 2003 trial (110 μg/g). Further development of integrated pest management, such as gene-silencing RNA interference (RNAi) and selective breeding of Varroa-resistant bees, is needed to effectively manage a parasite that threatens global agriculture.
An experimental framework to assess biomolecular condensates in bacteria
Authors: Hoang Y , Azaldegui Christopher A. , Ghalmi Maria , Biteen Julie S. , Vecchiarelli Anthony G. 
Published: March 2023

AbstractHigh-resolution imaging of biomolecular condensates in living cells is essential for correlating their properties to those observed throughin vitroassays. However, such experiments are limited in bacteria due to resolution limitations. Here we present an experimental framework that probes the formation, reversibility, and dynamics of condensate-forming proteins inEscherichia colias a means to determine the nature of biomolecular condensates in bacteria. We demonstrate that condensates form after passing a threshold concentration, maintain a soluble fraction, dissolve upon shifts in temperature and concentration, and exhibit dynamics consistent with internal rearrangement and exchange between condensed and soluble fractions. We also discovered that an established marker for insoluble protein aggregates, IbpA, has different colocalization patterns with bacterial condensates and aggregates, demonstrating its applicability as a reporter to differentiate the twoin vivo. Overall, this framework provides a generalizable, accessible, and rigorous set of experiments to probe the nature of biomolecular condensates on the sub-micron scale in bacterial cells.
Building and validating 5-feature models to predict preeclampsia onset time from electronic health record data
Authors: Ballard Hailey K , Yang Xiaotong , Mahadevan Aditya , Lemas Dominick J , Garmire Lana X 
Published: March 2023

AbstractBackgroundPreeclampsia is a potentially fatal complication during pregnancy, characterized by high blood pressure and presence of proteins in the urine. Due to its complexity, prediction of preeclampsia onset is often difficult and inaccurate.MethodsThis study aims to create quantitative models to predict the onset gestational age of preeclampsia using electronic health records. We retrospectively collected 1178 preeclamptic pregnancy records from the University of Michigan Health System(UM) as the discovery cohort, and 881 records from the University of Florida Health System(UF) as the validation cohort. We constructed two Cox-proportional hazards models with Lasso regularization: one baseline model utilizing maternal and pregnancy characteristics, and the other full model with additional lab results, vital signs, and medications in the first 20 weeks of pregnancy. We built the models using 80% of the UM data and subsequently tested them on the remaining 20% UM data and validated with UF data. We further stratified the patients into high and low risk groups for preeclampsia onset risk assessment.FindingsThe baseline model reached C-indices of 0·64 and 0·61 in the 20% UM testing data and the UF validation data, respectively, while the full model increased these C-indices to 0·69 and 0·61 respectively. Both the baseline and full models contain five selective features, among which number of fetuses in the pregnancy, hypertension and parity are shared between the two models with similar hazard ratios. In the baseline model, history of complicated type II diabetes and a mood/anxiety disorder during the first 20 weeks of pregnancy were important. In the full model, maximum diastolic blood pressure in early pregnancy was the predominant feature.InterpretationElectronic health record data provide useful information to predict gestational age of preeclampsia onset. Stratification of the cohorts using five-predictor Cox-PH models provide clinicians with convenient tools to assess the patients’ onset time of preeclampsia.FundingThis study was supported by grants through the NIEHS, NICHD, NIDDK, and NCATS.
An explainable deep learning classifier of bovine mastitis based on whole genome sequence data - circumventing the p>>>n problem
Authors: Kotlarz K. , Mielczarek M. , Biecek P. , Wojdak-Maksymiec K. , Suchocki T. , Topolski P. , Jagusiak W. , Szyda J. 
Published: March 2023

AbstractThe most serious drawback underlying the biological annotation of Whole Genome Sequence data is the p>>n problem, meaning that the number of polymorphic variants (p) is much larger than the number of available phenotypic records (n). Therefore, the major aim of the study was to propose a way to circumvent the problem by combining a LASSO logistic regression model with Deep Learning (DL). That was illustrated by a practical biological problem of classification of cows into mastitis-susceptible or mastitis-resistant, based on genotypes of Single Nucleotide Polymorphisms (SNPs) identified in their WGS. Among several DL architectures proposed via optimisation of DL hyperparameters using the Optuna software, imposed on different SNP sub-sets defined by LASSO logistic regressions with different penalty values, the architecture with 204,642 SNPs was selected as the best one. This architecture was composed of 2 layers with respectively 7 and 46 units per layer as well as respective drop-out rates of 0.210 and 0.358. The classification of the test data set resulted in the AUC=0.750, accuracy=0.650, sensitivity=0.600, and specificity=0.700 was selected as the best model and thus proceeded to genomic and functional annotations. Significant SNPs were selected based on the SHapley Additive exPlanation values transformed to Z-scores to assess the underlying type I-error. These SNPs were annotated to genes. As a final result, a single GO term related to the biological process and thirteen GO terms related to the molecular function were significantly enriched in the gene set that corresponded to the significant SNPs.Author SummaryOur objective is to distinguish between cows that are susceptible and resistant to bovine mastitis by analysing their genomic data. However, we face a significant challenge due to the large number of single nucleotide polymorphisms (SNPs) and limited sample size. To address this challenge, we utilize two methods: feature selection algorithms and deep learning. We experiment with various ways of implementing these techniques and evaluate their performance on a validation set. Our findings reveal that the optimal approach can accurately predict a cow’s susceptibility or resistance status around 65% of the time. Additionally, we employ a technique to identify the most crucial SNPs and their biological functions. Our results indicate that some of these SNPs are related to immune response or protein synthesis pathways, implying that they may affect the cow’s health and productivity.