bluuebunny/crossref_metadata_2025_split huggingface dataset:
In Silico Evaluation of Plant Nitrification Suppression Effects on Agroecosystem Nitrogen Loss
Authors: Hartman Melannie D. , Burnham Mark , Parton William J. , Finzi Adrien , DeLucia Evan , Yang Wendy H. 
Published: March 2022

AbstractNitrification regulates potential for nitrogen (N) loss from ecosystems because it converts ammonium to nitrate, which is susceptible to leaching and gaseous emissions. Crops can suppress the microbes that perform nitrification by exuding nitrification-inhibiting compounds from their roots and taking up available ammonium, the substrate for nitrification. However, the effect of nitrification suppression on agroecosystem N losses remains poorly characterized, and a lack of temporal synchrony between nitrification, N losses, and nitrification suppression by plants could limit the effect of nitrification suppression. We used the DayCent-CABBI model to evaluate the effectiveness of the suppression of nitrification by sorghum to reduce N2O emissions and nitrate leaching in an energy sorghum/soybean rotation at the Energy Farm in Urbana-Champaign, IL. We simulated nitrification suppression at the measured levels (measNS) and at the maximum measured level applied to the entire growing season (maxNS), and we also explored ways to better utilize nitrification suppression by altering the timing of UAN fertilizer applications. Model experiments showed that most nitrification occurred immediately after fertilizer was applied, whereas nitrification suppression begins to ramp up more than a month after planting. On an annual basis, measNS experiments showed a 1-2% reduction in annual N2O emissions relative to no nitrification suppression (noNS), and maxNS experiments showed a 4-9% reduction in annual N2O emissions relative to noNS. Both nitrification suppression levels showed < 1% reduction in nitrate leaching. Altering the timing of fertilizer applications to better synchronize nitrification suppression with high soil ammonium levels had mixed effects on annual N2O emissions and nitrate leaching and sometimes resulted in increased N losses. The timing of simulated N2O emissions shifted with the timing of fertilization, and N2O emissions from denitrification increased when N2O emissions from nitrification decreased. Increasing N retention during the non-growing season may be more effective and growing-season nitrification suppression for reducing annual N losses in the rainfed Midwest, particularly for NO3- leaching in the early spring. Optimizing the timing of nitrification suppression alongside off-season N retention strategies would best improve the N sustainability of agroecosystems.
Social deficits induced by pervasive environmental stressors are prevented by microbial or dopaminergic modulation
Authors: Smith Caroline J. , Rendina Danielle N. , Kingsbury Marcy A. , Malacon Karen E. , Nguyen Dang M. , Tran Jessica J. , Devlin Benjamin A. , Clark Madeline J. , Raju Ravikiran M. , Burgett Lauren , Zhang Jason H. , Cetinbas Murat , Sadreyev Ruslan I. , Chen Kevin , Iyer Malvika S. , Bilbo Staci D. 
Published: March 2022

AbstractEnvironmental toxicant exposure, including air pollution, is increasing worldwide. However, toxicant exposures are not equitably distributed. Rather, low-income and minority communities bear the greatest burden, along with higher levels of psychosocial stress. Both air pollution and maternal stress during pregnancy have been linked to neurodevelopmental disorders such as autism, but biological mechanisms and targets for therapeutic intervention remain poorly understood. We demonstrate that combined prenatal exposure to air pollution (diesel exhaust particles, DEP) and maternal stress (MS) in mice induces social behavior deficits only in male offspring, in line with the male bias in autism. These behavioral deficits are accompanied by changes in microglia and dopaminergic circuits in the brain, along with changes in the structure of the gut epithelium and microbiome. Importantly, DEP/MS-induced social deficits in males are prevented by shifting the gut microbiome by cross-fostering at birth and reversed by chemogenetic activation of the dopamine system.
Identification of different classes of genome instability suppressor genes through analysis of DNA damage response markers
Authors: Li Bin-Zhong , Kolodner Richard D. , Putnam Christopher D. 
Published: March 2022

ABSTRACTGenetic studies inSaccharomyces cerevisiaehave identified 266 genes and predicted an additional 38 genes that suppress the accumulation of spontaneous gross chromosomal rearrangements (GCRs). Here we identified mutations that induce two DNA damage response (DDR) markers, Hug1 expression and Ddc2 foci, and combined these data with other published screens identifying mutations inducing other DDR markers, including Rad52 foci and Rnr3 expression. Together, these data identify four categories of mutations: most mutations were DDR- GCR-, 356 were DDR+ GCR-, 72 were DDR- GCR+, and 157 were DDR+ GCR+. These results indicate that induction of DDR markers alone, while allowing DDR analysis, is not a reliable indicator of increased genome instability. They also guide further analysis of mechanistically distinct groups of GCR-inducing mutations, such as mutations that increase levels of GCR-inducing DNA damage and mutations that result in mis-repair of normal levels of DNA damage resulting in GCRs.
Realtime morphological characterization and sorting of unlabeled viable cells using deep learning
Authors: Salek Mahyar , Li Nianzhen , Chou Hou-Pu , Saini Kiran , Jovic Andreja , Jacobs Kevin B. , Johnson Chassidy , Lee Esther J. , Chang Christina , Nguyen Phuc , Mei Jeanette , Pant Krishna P. , Wong-Thai Amy Y. , Smith Quillan F. , Huang Stephanie , Chow Ryan , Cruz Janifer , Walker Jeff , Chan Bryan , Musci Thomas J. , Ashley Euan A. , Masaeli Maddison (Mahdokht) 
Published: March 2022

AbstractPhenotyping of single cells has dramatically lagged advances in molecular characterization and remains a manual, subjective, and destructive process. We introduce COSMOS, a platform for phenotyping and enrichment of cells based on deep learning interpretation of high-content morphology data in realtime. By training models on an atlas of >1.5 billion images, we demonstrate enrichment of unlabeled cells up to 33,000 fold. We apply COSMOS to multicellular tissue biopsy samples demonstrating that it can identify malignant cells with similar accuracy to molecular approaches while enriching viable cells for functional evaluation. We show high-dimensional embedding vectors of morphology generated by COSMOS without any need for complex sample pre-processing, gating, or bioinformatics capabilities, which enables discovery of cellular phenotypes, and integration of morphology into multi-dimensional analyses.One sentence summaryA novel platform capable of high-throughput imaging and gently sorting cells using deep morphological assessment.
Longitudinal monitoring of SARS-CoV-2 neutralizing antibody titers and its impact on employee personal wellness decisions
Authors: Vandergaast Rianna , Carey Timothy , Suksanpaisan Lukkana , Lathrum Chase , Narjari Riya , Haselton Michelle , Schnebeck Luke , Wijesekara Aroshi , Duncan Andrew , Russell Luke , Naik Shruthi , Peng Kah-Whye , Lech Patrycja , Russell Stephen J. 
Published: March 2022

AbstractVirus neutralizing antibody (vnAb) titers are the strongest laboratory correlate of protection from SARS-CoV-2. Providing individuals with real-time measures of their vnAb titers is predicted to improve their ability to make personal wellness decisions. Yet, widespread commercial testing of SARS-CoV-2 vnAbs does not currently occur. Here, we examined whether knowing their vnAb titer impacted wellness decision-making among individuals. To this end, starting on January 1, 2021, we offered all employees from two companies free IMMUNO-COV™ testing and conducted a survey to assess their behaviors and decisions regarding booster vaccination. IMMUNO-COV is a clinically validated, surrogate virus assay that quantitates serum titers of SARS-CoV-2 vnAbs. To help participants gauge their level of protection based on their vnAb titer, we calibrated IMMUNO-COV titers to the World Health Organization (WHO) International Standard (IU/mL), making them comparable to published reports of correlates of protection, and we fit historical IMMUNO-COV vnAb titer values into predictive models of immune protection from COVID-19. As expected, data for the 56 program participants showed variability in vnAb titers post vaccination, rates vnAb decay, and fold-increases in vnAb titers after booster vaccination. Based on the participant survey, the majority (66%) of participants indicated that knowing their vnAb titer impacted their social behaviors and/or their decision on the timing of a booster vaccination. Several participants indicated that knowing their vnAb titer contributed to their peace of mind regarding their high level of protection from COVID-19. Together, these data demonstrate that regular determination of SARS-CoV-2 neutralizing antibody titers can significantly impact decisions regarding social interactions and timing of booster vaccinations.
Understanding multimorbidity trajectories in Scotland: an application of sequence analysis
Authors: Cezard G. , Sullivan F. , Keenan K. 
Published: March 2022

AbstractBACKGROUNDAlthough understanding how multiple conditions develop over time is of growing interest, there is currently little methodological development on the topic, especially in understanding how multimorbidity (the co-existence of at least two chronic conditions) develops longitudinally and in which order diseases occur. Therefore, we aim to describe how a longitudinal method, sequence analysis, can be used to understand the sequencing of common chronic diseases that lead to multimorbidity and the socio-demographic factors and health outcomes associated with typical disease trajectories.METHODSWe use the Scottish Longitudinal Study (SLS) linking the Scottish census 2001 to disease registries, hospitalisation and mortality records. SLS participants aged 40-74 years at baseline were followed over a 10-year period (2001-2011) for the onset of three commonly occurring diseases: diabetes, cardiovascular disease (CVD), and cancer. We focused on participants who transitioned to at least two of these conditions over the follow-up period (N=6,300). We use sequence analysis with optimal matching and hierarchical cluster analysis to understand the process of disease sequencing and to distinguish typical multimorbidity trajectories. Socio-demographic differences between specific disease trajectories were evaluated using multinomial logistic regression. Poisson and Cox regressions were used to assess differences in hospitalisation and mortality outcomes between typical trajectories.RESULTSIndividuals who transitioned to multimorbidity over 10 years were more likely to be older and living in more deprived areas than the rest of the population. We found seven typical trajectories: later fast transition to multimorbidity, CVD start with slow transition to multimorbidity, cancer start with slow transition to multimorbidity, diabetes start with slow transition to multimorbidity, fast transition to both diabetes and CVD, fast transition to multimorbidity and death, fast transition to both cancer and CVD. Those who quickly transitioned to multimorbidity and death were the most vulnerable, typically older, less educated, and more likely to live in more deprived areas. They also experienced higher number of hospitalisations and overnight stays while still alive.CONCLUSIONSSequence analysis can strengthen our understanding of typical disease trajectories when considering a few key diseases. This may have implications for more active clinical review of patients beginning quick transition trajectories.
Reconstitution of renal cyst formation in 3D culture reveals a role for AMOT and Yap1 in determining cyst size
Authors: Wells Clark D. , Lange Kevin , Thompson Abigail F. , Xu Wei Min , Clendenon Sherry G. , Underwood John S. , Harris Peter , Herbert Britney-Shea , Glazier James , Wandinger-Ness Angela , Bacallao Robert L. 
Published: March 2022

ABSTRACTDespite substantial progress in identifying and understanding causative mutations in autosomal dominant polycystic kidney disease (ADPKD), little is known about subsequent cellular events leading to cyst formation. In prior studies we reported that Cadherin 8, a type II Cadherin, expression is sufficient to induce cyst emergence from HK-2 cells grown as tubule arrays in collagen matrix (1). However, emergent cysts did not exhibit the luminal enlargement observed in ADPKD. In this communication, we reconstitute cyst emergence with consequent cyst lumen expansion in 3D culture by stable co-expression of Cadherin 8 in combination with a constitutively active mutant of YAP1, the key effector of the HIPPO pathway. Specifically, immortalized cells derived from ADPKD cyst epithelia formed cysts with substantially larger lumen sizes when transduced with YAP1-5SA. Conversely, expression of the YAP1 inhibitor, AMOTL1, in these cells resulted in their forming cysts with smaller lumens than control cells. Our data show that cyst formation results from a sequential two-step process consisting of cyst initiation and subsequent cyst expansion. Taken together, cyst initiation induced by Cadherin 8 expression is proposed to result from decreased cell-cell adhesion while cyst expansion is driven by increased Yap1 activity.
Arabidopsis PFA-DSP-type phosphohydrolases target specific inositol pyrophosphate messengers
Authors: Gaugler Philipp , Schneider Robin , Liu Guizhen , Qiu Danye , Weber Jonathan , Schmid Jochen , Jork Nikolaus , Häner Markus , Ritter Kevin , Fernández-Rebollo Nicolás , Giehl Ricardo F.H. , Trung Minh Nguyen , Yadav Ranjana , Fiedler Dorothea , Gaugler Verena , Jessen Henning J. , Schaaf Gabriel , Laha Debabrata 
Published: March 2022

ABSTRACTInositol pyrophosphates are signaling molecules containing at least one phosphoanhydride bond that regulate a wide range of cellular processes in eukaryotes. With a cyclic array of phosphate esters and diphosphate groups around myo-inositol, these molecular messengers possess the highest charge density found in nature. Recent work deciphering inositol pyrophosphate biosynthesis in Arabidopsis revealed important functions of these messengers in nutrient sensing, hormone signaling and plant immunity. However, despite the rapid hydrolysis of these molecules in plant extracts, very little is known about the molecular identity of the phosphohydrolases that convert these messengers back to their inositol polyphosphate precursors. Here, we investigate whether Arabidopsis Plant and Fungi Atypical Dual Specificity Phosphatases (PFA-DSP1-5) catalyze inositol pyrophosphate phosphohydrolase activity. We find that recombinant proteins of all five Arabidopsis PFA-DSP homologs display phosphohydrolase activity with a high specificity for the 5-β-phosphate of inositol pyrophosphates. We further show that heterologous expression of Arabidopsis PFA-DSP1-5 rescues wortmannin-sensitivity and deranged inositol pyrophosphate homeostasis caused by the deficiency of the PFA-DSP-type inositol pyrophosphate phosphohydrolase Siw14 in yeast. Heterologous expression in Nicotiana benthamiana leaves provided evidence that Arabidopsis PFA-DSP1 also displays 5-β-phosphate specific inositol pyrophosphate phosphohydrolase activity in planta. Our findings lay the biochemical basis and provide the genetic tools to uncover the roles of inositol pyrophosphates in plant physiology and plant development.
Modeling of individual neurophysiological brain connectivity
Authors: Kulik S.D. , Douw L. , van Dellen E. , Steenwijk M.D. , Geurts J.J.G. , Stam C.J. , Hillebrand A. , Schoonheim M.M. , Tewarie P. 
Published: March 2022

AbstractIntroductionComputational models are often used to assess how functional connectivity (FC) patterns emerge from neuronal population dynamics and anatomical connections in the brain. However, group averaged data is often used in this context and it remains unclear whether individual predictions of FC patterns using this approach can be made. Here, we assess the value of using individualized structural data for simulation of individual whole-brain FC.MethodsThe Jansen and Rit neural mass model was employed, where masses were coupled using individual structural connectivity (SC) obtained from diffusion weighted imaging. Simulated FC was correlated to individual magnetoencephalography-derived empirical FC. FC was estimated using both phase-based (phase lag index (PLI), phase locking value (PLV)) and amplitude-based (amplitude envelope correlation (AEC)) metrics to analyze the goodness-of-fit of different metrics for individual predictions. Prediction of individual FC was compared against the prediction of group averaged FC. We further tested whether SC of a different participant could equally well predict a participants FC pattern.ResultsThe AEC provided a significantly better match between individually simulated and empirical FC than phase-based metrics. Simulations with individual SC provided higher correlations between simulated and empirical FC compared to using the group-averaged SC. However, using SC from other participants resulted in similar correlations between simulated and empirical FC compared to using participants own SC.DiscussionThis work underlines the added value of FC simulations based on individual instead of group-averaged SC, and could aid in a better understanding of mechanisms underlying individual functional network trajectories in neurological disease.Impact statementIn this work, we investigated how well individual empirical functional connectivity can be simulated using the individual’s structural connectivity matrix combined with neural mass modeling. Our research highlights the potential added value of using individual simulations of functional connectivity, and could aid in a better understanding of mechanisms underlying individual functional network trajectories in neurological disease. Moreover, individualized prediction of disease trajectories could enhance patient care and may provide better treatment options.
A Duplex Structure of SARM1 Octamers Induced by a New Inhibitor
Authors: Khazma Tami , Golan-Vaishenker Yarden , Guez-Haddad Julia , Grossman Atira , Sain Radhika , Plotnikov Alexander , Zalk Ran , Yaron Avraham , Hons Michael , Opatowsky Yarden 
Published: March 2022

AbstractIn recent years, there has been growing interest in SARM1 as a potential breakthrough drug target for treating various pathologies of axon degeneration. SARM1-mediated axon degeneration relies on its TIR domain NADase activity, but recent structural data suggest that the non-catalytic ARM domain could also serve as a pharmacological site as it has an allosteric inhibitory function. Here, we screened for synthetic small molecules that inhibit SARM1 by stabilizing the ARM-dependent inactive, compact octamer ring conformation, and tested a selected set of these compounds in a DRG axon degeneration assay. Using cryo-EM, we found that one of the newly discovered inhibitors, a Calmidazolium designated TK106, not only stabilizes the previously reported inhibited conformation of the octamer, but also promotes the formation of a meta-stable structure: a duplex of octamers (16 protomers), which we have now determined to 4.0 Å resolution. In the duplex, each ARM domain protomer is not only engaged in lateral interactions with neighboring protomers but is further stabilized by contralateral contacts with the opposing octamer ring. Mutagenesis of the duplex contact sites leads to SARM1 activation in cultured cells. Based on our data we propose that the duplex assembly constitutes an additional auto-inhibition mechanism that tightly prevents pre-mature activation and axon degeneration.
Political practitioners’ perspectives on political management: the importance of people and power
Authors: Lees-Marshment Jennifer , Bendle Neil Thomas 
Published: March 2022

PurposePolitical management is about getting things done in campaigns, parties and government. Political organizations can use management concepts such as strategic planning, human resources and organizational design to help them achieve their goals. Research into specifically how management is used by political practitioners – political staffers and politicians – in government is limited. This study aims to fill that gap.Design/methodology/approachThe authors review the limited literature on political management, outline interview methodology, results and conclude with overall lessons drawn out using the qualitative data analysis software NVivo.FindingsThis study identifies the aspects of political management that political practitioners saw as the most important, the difference between managing in business and politics, and why.Research limitations/implicationsThis study provides suggestions for what future empirical research should focus on, noting a focus on informal behavior that relate to people and power that are not seen from outside the organization.Originality/valueThe perspectives of high-level practitioners help give a view to what political management really is.
Evolutionary bet‐hedging reconsidered: What is the mean–variance trade‐off of fitness?
Authors: Yasui Yukio 
Published: March 2022

AbstractIn traditional theories, bet‐hedging in evolutionary biology is defined as a trade‐off between the within‐generation arithmetic mean fitness (AMF) of a genotype and between‐generation variance (BGV) in AMF across generations. The rationale of this definition is that a bet‐hedger genotype suppresses the BGV to increase between‐generation geometric mean fitness (GMF; an index of long‐term sustainability), which in turn entails costs in terms of AMF. However, too strict interpretation of this definition causes confusion among empirical researchers. For example, in empirical studies comparing a putative bet‐hedger (e.g., producing a generalist phenotype or mixture of various phenotypes) and non‐bet‐hedger control (e.g., producing only a specialist phenotype), reviewers sometimes request that a necessary condition of bet‐hedging is that the bet‐hedger candidate shows a smaller arithmetic mean of AMFs obtained from multiple generations and larger GMF than the control. However, the cost of bet‐hedging is incurred at the potential genotypic level and thus the decrease of AMF mean is not necessarily observed at the phenotypic level (especially if bet‐hedger individuals have good conditions). Moreover, contrary to previous arguments, the “fine‐grained” environments would promote bet‐hedging because even monomorphic specialist genotypes increase GMF if their population size is sufficiently large. Computer simulations support these views. I try to shift the definition of bet‐hedging from the trade‐off‐based one to the GMF‐based one: bet‐hedging is any strategy to increase the between‐generational GMF to avoid extinction of its controlling genotype against unpredictable environmental fluctuation. Under this new light, bet‐hedging will be a universal law of biology.