bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mutational robustness changes during long-term adaptation in laboratory budding yeast populations
Authors: Johnson Milo S. , Desai Michael M. 
Published: December 2021

AbstractAs an adapting population traverses the fitness landscape, its local neighborhood (i.e., the collection of fitness effects of single-step mutations) can change shape because of interactions with mutations acquired during evolution. These changes to the distribution of fitness effects can affect both the rate of adaptation and the accumulation of deleterious mutations. However, while numerous models of fitness landscapes have been proposed in the literature, empirical data on how this distribution changes during evolution remains limited. In this study, we directly measure how the fitness landscape neighborhood changes during laboratory adaptation. Using a barcode-based mutagenesis system, we measure the fitness effects of 91 specific gene disruption mutations in genetic backgrounds spanning 8,000-10,000 generations of evolution in two constant environments. We find that the mean of the distribution of fitness effects decreases in one environment, indicating a reduction in mutational robustness, but does not change in the other. We show that these distribution-level patterns result from biases in variable patterns of epistasis at the level of individual mutations, including fitness-correlated and idiosyncratic epistasis.
Phospho-proteomics reveals that RSK signaling is required for proliferation of natural killer cells stimulated with IL-2 or IL-15
Authors: MacMullan Melanie A. , Wang Pin , Graham Nicholas A. 
Published: December 2021

AbstractNatural killer (NK) cells are cytotoxic lymphocytes that play a critical role in the innate immune system. Although cytokine signaling is crucial for the development, expansion, and cytotoxicity of NK cells, the signaling pathways stimulated by cytokines are not well understood. Here, we sought to compare the early signaling dynamics induced by the cytokines interleukin (IL)-2 and IL-15 using liquid chromatography-mass spectrometry (LC-MS)-based phospho-proteomics. Following stimulation of the immortalized NK cell line NK-92 with IL-2 or IL-15 for 5, 10, 15, or 30 minutes, we identified 8,692 phospho-peptides from 3,023 proteins. Comparing the kinetic profiles of 3,619 fully quantified phospho-peptides, we found that IL-2 and IL-15 induced highly similar signaling in NK-92 cells. Among the IL-2/IL-15-regulated phospho-sites were both well-known signaling events like the JAK/STAT pathway and novel signaling events with potential functional significance including LCP1 Ser5, PAK2 Ser141, and STK17B Ser12. Using bioinformatic approaches, we sought to identify kinases regulated by IL-2/IL-15 stimulation and found that the p90 ribosomal S6 kinase (p90RSK) family was activated by both cytokines. Using pharmacological inhibitors, we then discovered that RSK signaling is required for IL-2 and IL-15-induced proliferation in NK-92 cells. Taken together, our analysis represents the first phospho-proteomic characterization of cytokine signaling in NK cells and increases our understanding of how cytokine signaling regulates NK cell function.
A deep learning approach to real-time HIV outbreak detection using genetic data
Authors: Kupperman Michael D. , Leitner Thomas , Ke Ruian 
Published: December 2021

AbstractPathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands.Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0≥ 3, and overall a specificity exceeding 85% and sensitivity better than 70%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.Author summaryThe analysis of pathogen genomic data to analyze epidemics at scale is constrained by the computational cost associated with phylogenetic tree reconstruction. As a fast and efficient alternative, we employed convolutional neural networks to analyze evolutionary pairwise distance matrices as images to perform classifications of the current epidemiological situation of a growing public health sequence database. We used simulated data to train and test our model, and as validation we accurately mapped the start and end of two linked well-documented HIV-1 outbreaks in the backdrop of ongoing slower HIV spread. Thus, our new approach is efficient, accurate, scalable, and can analyze data in real time.
Nutrigenomic Regulation of Sensory Plasticity
Authors: Sung Hayeon , Vaziri Anoumid , Wilinski Daniel , Woerner Riley K.R. , Freddolino Peter L. , Dus Monica 
Published: December 2021

AbstractDiet profoundly influences brain physiology, but how nutritional information is transmuted into neural activity and behavior changes remains elusive. Here we show that the metabolic enzyme O-GlcNAc Transferase (OGT) moonlights on the chromatin of the D. melanogaster gustatory neurons to instruct changes in chromatin accessibility and transcription that underlie sensory adaptations to a high sugar diet. OGT works synergistically with the Mitogen Activated Kinase/Extracellular signal Regulated Kinase (MAPK/ERK) rolled and its effector stripe (also known as EGR2 or Krox20) to integrate activity information. OGT also cooperates with the epigenetic silencer Polycomb Repressive Complex 2.1 (PRC2.1) to decrease chromatin accessibility and repress transcription in the high sugar diet. This integration of nutritional and activity information changes the taste neurons’ responses to sugar and flies’ ability to sense sweetness. Our findings reveal how nutrigenomic signaling generates cell-specific responses to global nutrient variations.
Environmental carcinogens disproportionally mutate genes implicated in neurodevelopmental disorders
Authors: Baker Brennan H. , Zhang Shaoyi , Simon Jeremy M. , McLarnan Sarah M. , Chung Wendy K. , Pearson Brandon L. 
Published: December 2021

AbstractDe novo mutations contribute to a large proportion of sporadic psychiatric and developmental disorders, yet the potential role of environmental carcinogens as drivers of causal de novo mutations in neurodevelopmental disorders is poorly studied. We demonstrate that several mutagens, including polycyclic aromatic hydrocarbons (PAHs), disproportionately mutate genes related to neurodevelopmental disorders including autism spectrum disorders (ASD), schizophrenia, and attention deficit hyperactivity disorder (ADHD). Other disease genes including amyotrophic lateral sclerosis (ALS), Alzheimer’s disease, congenital heart disease, orofacial clefts, and coronary artery disease were generally not mutated more than expected. Our findings support a new paradigm of neurodevelopmental disease etiology driven by a contribution of environmentally induced rather than random mutations.
MixEHR-Guided: A guided multi-modal topic modeling approach for large-scale automatic phenotyping using the electronic health record
Authors: Ahuja Yuri , Zou Yuesong , Verma Aman , Buckeridge David , Li Yue 
Published: December 2021

AbstractElectronic Health Records (EHRs) contain rich clinical data collected at the point of the care, and their increasing adoption offers exciting opportunities for clinical informatics, disease risk prediction, and personalized treatment recommendation. However, effective use of EHR data for research and clinical decision support is often hampered by a lack of reliable disease labels. To compile gold-standard labels, researchers often rely on clinical experts to develop rule-based phenotyping algorithms from billing codes and other surrogate features. This process is tedious and error-prone due to recall and observer biases in how codes and measures are selected, and some phenotypes are incompletely captured by a handful of surrogate features. To address this challenge, we present a novel automatic phenotyping model called MixEHR-Guided (MixEHR-G), a multimodal hierarchical Bayesian topic model that efficiently models the EHR generative process by identifying latent phenotype structure in the data. Unlike existing topic modeling algorithms wherein the inferred topics are not identifiable, MixEHR-G uses prior information from informative surrogate features to align topics with known phenotypes. We applied MixEHR-G to an openly-available EHR dataset of 38,597 intensive care patients (MIMIC-III) in Boston, USA and to administrative claims data for a population-based cohort (PopHR) of 1.3 million people in Quebec, Canada. Qualitatively, we demonstrate that MixEHR-G learns interpretable phenotypes and yields meaningful insights about phenotype similarities, comorbidities, and epidemiological associations. Quantitatively, MixEHR-G outperforms existing unsupervised phenotyping methods on a phenotype label annotation task, and it can accurately estimate relative phenotype prevalence functions without gold-standard phenotype information. Altogether, MixEHR-G is an important step towards building an interpretable and automated phenotyping system using EHR data.
Hilltopping influences spatial dynamics in a patchy population of tiger moths
Authors: Pepi Adam , Grof-Tisza Patrick , Holyoak Marcel , Karban Richard 
Published: December 2021

AbstractDispersal is a key driver of spatial population dynamics. Dispersal behavior may be shaped by many factors, such as mate-finding, the spatial distribution of resources, or wind and currents, yet most models of spatial dynamics assume random dispersal. We examined the spatial dynamics of a day-flying moth species (Arctia virginalis) that forms mating aggregations on hilltops (‘hilltopping’) based on long-term adult and larval population censuses. Using time-series models, we compared spatial population dynamics resulting from empirically-founded hilltop-based connectivity indices, and modeled the interactive effects of temperature, precipitation, and density dependence. Model comparisons supported hilltop-based connectivity metrics over random connectivity, suggesting an effect of hilltopping behavior on dynamics. We also found strong interactive effects of temperature and precipitation on dynamics. Simulations based on fitted time series models showed lower patch occupancy and regional synchrony, and higher colonization and extinction rates when hilltopping was included, with potential implications for the probability of persistence of the patch network. Overall, our results show the potential for dispersal behavior to have important effects on spatial population dynamics and persistence, and we advocate inclusion of such non-random dispersal in metapopulation models.
Benefits of integrated screening and vaccination for infection control
Authors: Rabil Marie Jeanne , Tunc Sait , Bish Douglas R. , Bish Ebru K. 
Published: December 2021

AbstractImportanceScreening and vaccination are essential in the fight against infectious diseases, but need to be integrated and customized based on community and disease characteristics.ObjectiveTo develop effective screening and vaccination strategies, customized for a college campus, to reduce COVID-19 infections, hospitalizations, deaths, and peak hospitalizations.Design, Setting, and ParticipantsWe construct a compartmental model of disease spread for vaccination and routine screening, and study the efficacy of four mitigation strategies (routine screening only, vaccination only, vaccination with partial routine screening, vaccination with full routine screening), and a no-intervention strategy. The study setting is a hypothetical college campus of 5,000 students and 455 faculty members, with 11 undetected, asymptotic SARS-CoV-2 infections at the start of an 80-day semester. For sensitivity analysis, we vary the screening frequency, daily vaccination rate, initial vaccination coverage, and screening and vaccination compliance; and consider three scenarios that represent low/medium/high transmission rates and test efficacy. Model parameters come from publicly available or published sources.ResultsWith low initial vaccination coverage, even aggressive vaccination and screening result in a high number of infections: 1,024/2,040 (1,532/1,773) with routine daily (every other day) screening of the unvaccinated; 275/895 with daily screening extended to the newly vaccinated in base- and worst-case scenarios, with reproduction numbers 4.75 and 6.75, respectively, representative of COVID-19 Delta variant. With the emergence of the Omicron variant, the reproduction number may increase and/or effective vaccine coverage may decrease if a booster shot is needed to maximize vaccine efficacy.ConclusionIntegrated vaccination and routine screening can allow for a safe opening of a college when initial vaccination coverage is sufficiently high. The interventions need to be customized considering the initial vaccination coverage, estimated compliance, screening and vaccination capacity, disease transmission and adverse outcome rates, and the number of infections/peak hospitalizations the college is willing to tolerate.
The landowner role in beginning farmer/rancher land access: predictors of landowners' views of extrafamilial farm transfer to a BFR
Authors: Valliant Julia C.D. , Dickinson Stephanie , Zhang Yijia , Golzarri-Arroyo Lilian , Farmer James R. 
Published: December 2021

PurposeBeginning farmers and ranchers (BFRs) are more likely to access land through an unrelated landowner than through family. Thus, farm and ranch owners who might transfer their land or businesses out of family are potential sources of land access for BFRs and are the most frequent participants in incentive programs to facilitate land transfer to BFRs. To assist in identifying landowners who might transfer out of family, the paper aims to explore similarities and differences between landowners according to their expectations for intra-familial versus extra-familial farm transfer.Design/methodology/approachPairwise and regression analysis of USA Midwestern and Plains landowners' responses to an online survey (n = 322).FindingsLandowners who might transfer out of family were likely to need the proceeds from a land sale to finance their retirement. Landowners' financial needs interacted with their widespread interest in transferring to a BFR such that 97% of owners who expected extra-familial transfer wanted to transfer to a BFR. There were also statistical patterns around the size of owners' landholdings in relation to their transfer plans.Research limitations/implicationsThis exploratory inquiry suggests patterns for future research to examine, especially around landowners' juxtaposition of their retirement income and their interest in transferring to a BFR and how to align these priorities and values.Originality/valueBy exploring the characteristics of landowners who are the most likely to provide land access to BFRs, the authors begin to examine how to target these owners in program outreach. Patterns for further exploration point to landowners' financial needs in relation to their interest in helping a BFR to get started in agriculture.
Exploring the design risk factors for modular integrated construction projects
Authors: Wuni Ibrahim Yahaya , Shen Geoffrey Qiping , Antwi-Afari Maxwell Fordjour 
Published: December 2021

Purpose
Modular integrated construction (MiC) is considered as a process innovation to improve the performance of construction projects. However, effective delivery of MiC projects requires management of risks and uncertainties throughout its delivery chain. Although the design stage of MiC projects is usually managed with limited knowledge based on highly uncertain data and associated with epistemic uncertainties, MiC design risks have not received adequate research attention relative to other stages. The purpose of this paper is to conduct a knowledge-based evaluation and ranking of the design risk factors (DRFs) for MiC projects.

Design/methodology/approach
The paper reviewed the relevant literature to identify potential DRFs and validated their relevance through pilot expert review. The paper then used questionnaires to gather data from international MiC experts from 18 countries and statistically analyzed the data set.

Findings
Analysis results showed that the five most significant DRFs for MiC projects include unsuitability of design for the MiC method; late involvement of suppliers, fabricators and contractors; inaccurate information, defective design and change order; design information gap between the designer and fabricator; and lack of bespoke MiC design codes and guidelines. A correlation analysis showed that majority of the DRFs have statistically significant positive relationships and could inform practitioners on the dynamic links between the DRFs.

Practical implications
The paper provides useful insight and knowledge to MiC practitioners and researchers on the risk factors that could compromise the success of MiC project designs and may inform design risk management. The dynamic linkages among the DRFs instruct the need to adopt a system-thinking philosophy in MiC project design.

Originality/value
This paper presents the first study that specifically evaluates and prioritizes the risk events at the design stage of MiC projects. It sets forth recommendations for addressing the identified DRFs for MiC projects.
Is it possible to improve the international business action towards the sustainable development goals?
Authors: Celone Andrea , Cammarano Antonello , Caputo Mauro , Michelino Francesca 
Published: December 2021

PurposeThe purpose of this paper is to investigate possible improvements in the pursuit of the sustainable development goals (SDGs) by multinational enterprises (MNEs) through an analysis of the literature.Design/methodology/approachA critical framework based on Gleicher’s formula for change is provided after conducting a systematic literature review.FindingsThe best way to pursue the SDGs is through an integrated approach that recognises the importance of MNEs in terms of possibilities and power of action. Working towards the SDGs appears to be largely limited by three aspects of the problem: its complexity and wickedness, the genuine interest in reaching some SDGs, at the expense of profit and low foresight.Research limitations/implicationsA fundamental limitation of the study concerns, as in most of the literature on the matter, the impossibility of providing an optimal solution to the problem of meeting the SDGs, given their nature. However, formulating the best definition of the problem and its characteristics can contribute to making its management better.Social implicationsThis study has social implications due to the extreme importance that many SDGs have with regard to democracy and social equity, beyond their environmental and economic aspects.Originality/valueThe claimed contribution is the value brought by the synthesis of several points of view, through the interdisciplinary analysis of the research question. The novelty consists in organising the literature according to the formula for change.
Determinants of the exit value in European venture capital-backed technology startups
Authors: Montanaro Benedetta , Cavallo Angelo , Giudici Giancarlo , Ghezzi Antonio 
Published: December 2021

Purpose
This study aims to analyze the impact of different exit alternatives, investor presence and founders’ human capital on the exit value of European venture capital (VC)-backed high technology startups.

Design/methodology/approach
The empirical analysis is based on a sample of 107 European firms that obtained an exit through Merger&Acquisition (M&A) or an initial public offering (IPO) between 2010 and 2017, backed by VC investors.

Findings
This study provides empirical evidence on how different exit alternatives, investor heterogeneity and founders’ human capital may affect the exit value of European VC-backed startups. Exiting through an IPO and retaining a larger equity stake are positively correlated with the exit value. The presence of business angels and non-governmental VC firms is associated with larger valuations. Founders’ previous education was positively correlated with the exit value.

Originality/value
Exit strategies in technology startups are essential to capitalize investors’ efforts and reinvest cash into new ventures, supporting the development of entrepreneurial ecosystems and countries’ competitiveness. The results of this study provide interesting hints for policymakers and contribute to an in-depth understanding of the drivers of exit valuation for startups.
Canard-induced mixed mode oscillations as a mechanism for the Bonhoeffer-van der Pol circuit under parametric perturbation
Authors: Yu Yue , Zhang Cong , Chen Zhenyu , Zhang Zhengdi 
Published: December 2021

Purpose
This paper aims to investigate the singular Hopf bifurcation and mixed mode oscillations (MMOs) in the perturbed Bonhoeffer-van der Pol (BVP) circuit. There is a singular periodic orbit constructed by the switching between the stable focus and large amplitude relaxation cycles. Using a generalized fast/slow analysis, the authors show the generation mechanism of two distinct kinds of MMOs.

Design/methodology/approach
The parametric modulation can be used to generate complicated dynamics. The BVP circuit is constructed as an example for second-order differential equation with periodic perturbation. Then the authors draw the bifurcation parameter diagram in terms of a containing two attractive regions, i.e. the stable relaxation cycle and the stable focus. The transition mechanism and characteristic features are investigated intensively by one-fast/two-slow analysis combined with bifurcation theory.

Findings
Periodic perturbation can suppress nonlinear circuit dynamic to a singular periodic orbit. The combination of these small oscillations with the large amplitude oscillations that occur due to canard cycles yields such MMOs. The results connect the theory of the singular Hopf bifurcation enabling easier calculations of where the oscillations occur.

Originality/value
By treating the perturbation as the second slow variable, the authors obtain that the MMOs are due to the canards in a supercritical case or in a subcritical case. This study can reveal the transition mechanism for multi-time scale characteristics in perturbed circuit. The information gained from such results can be extended to periodically perturbed circuits.