bluuebunny/crossref_metadata_2025 huggingface dataset:
The Enemy of my Enemy is my Friend: Immune-Mediated Facilitation Contributes to Fitness of Co-Infecting Helminths
Authors: Dagostin Francesca , Vanalli Chiara M. , Boag Brian , Casagrandi Renato , Gatto Marino , Mari Lorenzo , Cattadori Isabella M.
Published: August 2021

Our conceptual understanding of immune-mediated interactions between parasites is rooted in the theory of community ecology. One of the limitations of this approach is that most of the theory and empirical evidence has focused on resource or immune-mediated parasite competition and yet, there is ample evidence of positive interactions between species that could be generated by immune-mediated facilitation. Here, we develop an immuno-epidemiological framework and apply it to longitudinal infection data of two gastrointestinal helminths that infect a population of free-living rabbits to investigate, through model testing, the mechanisms of immune-mediated facilitation in dual infections. Simulations show that weakened, species-specific IgA antibody responses and unequal, albeit low, IgA cross-reactions explain higher parasite intensities in dual compared to single infections, for both helminths. Simulations also show that rabbits with dual infections shed more free-living stages that survive fort longer in the environment, implying greater onward transmission than hosts with single infections. These findings support the hypothesis that the two helminths interact through immune-mediated facilitation which contributes to greater fitness and the long-term co-circulation of both species in the host population.
Locus-specific chromatin profiling of evolutionarily young transposable elements
Authors: Taylor Darren , Lowe Robert , Philippe Claude , Cheng Kevin C. L. , Grant Olivia A. , Zabet Nicolae Radu , Cristofari Gael , Branco Miguel R.
Published: August 2021

Despite a vast expansion in the availability of epigenomic data, our knowledge of the chromatin landscape at interspersed repeats remains highly limited by difficulties in mapping short-read sequencing data to these regions. In particular, little is known about the locus-specific regulation of evolutionarily young transposable elements (TEs), which have been implicated in genome stability, gene regulation and innate immunity in a variety of developmental and disease contexts. Here we propose an approach for generating locus-specific protein-DNA binding profiles at interspersed repeats, which leverages information on the spatial proximity between repetitive and non-repetitive genomic regions. We demonstrate that the combination of HiChIP and a newly developed mapping tool (PAtChER) yields accurate protein enrichment profiles at individual repetitive loci. Using this approach, we reveal previously unappreciated variation in the epigenetic profiles of young TE loci in mouse and human cells. Insights gained using our method will be invaluable for dissecting the molecular determinants of TE regulation and their impact on the genome.
Using Conspecific Playbacks to Investigate Contact Calling in Southeast Alaskan Humpback Whales
Authors: Fournet Michelle E.H. , Matthews Leanna P. , Bartlett Annie , Mastick Natalie , Sharpe Fred , Doyle Laurance , McCowan Brenda , Crutchfield James P. , Mellinger David K.
Published: August 2021

Humpback whales (Megaptera novaeangliae) produce calls across age and sex class and throughout their migratory range. Despite growing interest in calling behavior, the function of most calls is unknown. Among identified call types, the ‘whup’ is ubiquitous, and innate, and may serve as a contact call. We conducted an acoustic playback experiment combined with passive acoustic monitoring and visual observations to test the function of the whup on a Southeast Alaskan foraging ground. Using a before-during-after design, we broadcasted either a control sound or a unique whup call sequence. We investigated the change in whup rates (whups/whale/10 minutes) in response to treatment (whup or control) and period (before, during, or after). In 100% of the conspecific trials, whup rates increased during broadcasts, and whup rates were significantly higher than in before or after periods. There was no significant difference in whup rates between before and after periods during conspecific trials. In control trials, there were no significant differences in whup rates between before, during, or after periods. Neither whups nor control playbacks elicited an approach response. Humpback whale vocal responses to whup playbacks suggest that whups function as a contact call, but not necessarily as an aggregation signal.
Neural Basis of Acoustic Species Recognition in a Cryptic Species Complex
Authors: Gupta Saumya , Alluri Rishi K. , Rose Gary J. , Bee Mark A.
Published: August 2021

Sexual traits that promote species recognition are important drivers of reproductive isolation, especially among closely related species. Identifying neural processes that shape species differences in recognition is crucial for understanding the causal mechanisms of reproductive isolation. Temporal patterns are salient features of sexual signals that are widely used in species recognition by several taxa, including anurans. Recent advances in our understanding of temporal processing by the anuran auditory system provide an excellent opportunity to investigate the neural basis of species-specific recognition. The anuran inferior colliculus (IC) consists of neurons that are selective for temporal features of calls. Of potential relevance are auditory neurons known as interval-counting neurons (ICNs) that are often selective for the pulse rate of conspecific advertisement calls. Here, we took advantage of a species differences in temporal selectivity for pulsatile advertisement calls exhibited by two cryptic species of gray treefrog (Hyla chrysoscelis and Hyla versicolor) to test the hypothesis that ICNs mediate acoustic species recognition. We tested this hypothesis by examining the extent to which the threshold number of pulses required to elicit behavioral responses from females and neural responses from ICNs was similar within each species but potentially different between the two species. In support of our hypothesis, we found that a species difference in behavioral pulse number thresholds corresponded closely to a parallel species difference in neural pulse number thresholds. However, this relationship held only for ICNs that exhibited band-pass tuning for conspecific pulse rates. Together, these findings suggest that differences in temporal processing of a subset of ICNs provide a mechanistic explanation for reproductive isolation between two cryptic and syntopically breeding treefrog species.

Summary Statement

Temporal processing by a subset of midbrain auditory neurons plays key roles in decoding information about species identity in anurans.
An automatic diagnostic system for pediatric genetic disorders by linking genotype and phenotype information
Authors: Dong Xinran , Wu Bingbing , Wang Huijun , Yang Lin , Chen Xiang , Ni Qi , Wang Yaqiong , Liu Bo , Lu Yulan , Zhou Wenhao
Published: August 2021

Background

Quantitatively describe the phenotype spectrum of pediatric disorders has remarkable power to assist genetic diagnosis. Here, we developed a matrix which provide this quantitative description of genomic-phenotypic association and constructed an automatic system to assist the diagnose of pediatric genetic disorders.

Results

20,580 patients with genetic diagnostic conclusions from the Children’s Hospital of Fudan University during 2015 to 2019 were reviewed. Based on that, a phenotype spectrum matrix -- cGPS (clinical Gene’s Preferential Synopsis) -- was designed by Naïve Bayes model to quantitatively describe genes’ contribution to clinical phenotype categories. Further, for patients who have both genomic and phenotype data, we designed a ConsistencyScore based on cGPS. ConsistencyScore aimed to figure out genes that were more likely to be the genetic causal of the patient’s phenotype and to prioritize the causal gene among all candidates. When using the ConsistencyScore in each sample to predict the causal gene for patients, the AUC could reach 0.975 for ROC (95% CI 0.972-0.976 and 0.575 for precision-recall curve (95% CI 0.541-0.604). Further, the performance of ConsistencyScore was evaluated on another cohort with 2,323 patients, which could rank the causal gene of the patient as the first for 75.00% (95% CI 70.95%-79.07%) of the 296 positively genetic diagnosed patients. The causal gene of 97.64% (95% CI 95.95%-99.32%) patients could be ranked within top 10 by ConsistencyScore, which is much higher than existing algorithms (p <0.001).

Conclusions

cGPS and ConsistencyScore offer useful tools to prioritize disease-causing genes for pediatric disorders and show great potential in clinical applications.
Altered resting-state functional connectivity in hiPSC-derived neuronal networks from schizophrenia patients
Authors: Puvogel Sofía , Blanchard Kris , Casas Bárbara S. , Miller Robyn , Garrido Delia , Sanhueza Magdalena , Palma Verónica
Published: August 2021

Schizophrenia (SZ) is a complex mental disease thought to arise from abnormal neurodevelopment, characterized by an altered reality perception and widely associated with brain connectivity anomalies. Previous work has shown disrupted resting-state brain functional connectivity (FC) in SZ patients. We used Human Induced Pluripotent Stem Cells (hiPSC)-derived neuronal cultures to study SZ’s neural communicational dynamics during early development. We conducted gene and protein expression profiling, calcium imaging and mathematical modeling to evaluate FC. Along the neurodifferentiation process, SZ networks displayed altered expression of genes related to synaptic function, cell migration and cytoskeleton organization, suggesting alterations in excitatory/inhibitory balance. Resting-state FC in neuronal networks derived from healthy controls (HC) and SZ patients emerged as a dynamic phenomenon exhibiting “hub-states”, which are connectivity configurations reoccurring in time. Compared to HC, SZ networks were less thorough in exploring different FC configurations, changed configurations less often, presented a reduced repertoire of hub-states and spent longer uninterrupted time intervals in this less diverse universe of hubs. Our observations at a single cell resolution may reflect intrinsic dynamical principles ruling brain activity at rest and highlight the relevance of identifying multiscale connectivity properties between functional brain units. We propose that FC alterations in SZ patients are a consequence of an abnormal early development of synaptic communication dynamics, compromising network’s ability for rapid and efficient reorganization of neuronal activity patterns. Remarkably, these findings mirror resting-state brain FC in SZ patients, laying the groundwork for future studies among such different spatiotemporal domains, as are brains and neurons, in both health and disease.
Association between tocilizumab, sarilumab and all-cause mortality at 28 days in hospitalized patients with COVID-19: A network meta-analysis
Authors: Godolphin Peter J , Fisher David J , Berry Lindsay R , Derde Lennie PG , Diaz Janet V , Gordon Anthony C , Lorenzi Elizabeth , Marshall John C , Murthy Srinivas , Shankar-Hari Manu , Sterne Jonathan AC , Tierney Jayne F , Vale Claire L
Published: August 2021

Objective: To estimate pairwise associations between administration of tocilizumab, sarilumab and usual care or placebo with 28-day mortality, in COVID-19 patients receiving concomitant corticosteroids and non-invasive or mechanical ventilation, based on all available direct and indirect evidence.

Methods: Eligible trials randomized hospitalized patients with COVID-19 that compared either interleukin-6 receptor antagonist with usual care or placebo in a recent prospective meta-analysis (27 trials, 10930 patients) or that directly compared tocilizumab with sarilumab. Data were restricted to patients receiving corticosteroids and either non-invasive or invasive ventilation at randomization.

Pairwise associations between tocilizumab, sarilumab and usual care or placebo for all-cause mortality 28 days after randomization were estimated using a frequentist contrast-based network meta-analysis of odds ratios (ORs), implementing multivariate fixed-effects models that assume consistency between the direct and indirect evidence.

Results: One trial (REMAP-CAP) was identified that directly compared tocilizumab with sarilumab and supplied results on all-cause mortality at 28-days. This network meta-analysis was based on 898 eligible patients (278 deaths) from REMAP-CAP and 3710 eligible patients from 18 trials (1278 deaths) from the prospective meta-analysis. Summary ORs were similar for tocilizumab [0.82 [0.71-0.95, P=0.008]] and sarilumab [0.80 [0.61-1.04, P=0.09]] compared with usual care or placebo. The summary OR for 28-day mortality comparing tocilizumab with sarilumab was 1.03 [95%CI 0.81-1.32, P=0.80]. The P value for the global test for inconsistency was 0.28.

Conclusion: Administration of either tocilizumab or sarilumab was associated with lower 28-day all-cause mortality compared with usual care or placebo. The association is not dependent on the choice of interleukin-6 receptor antagonist.
Behavioural barriers to COVID-19 testing in Australia: Two national surveys to identify barriers and estimate prevalence by health literacy level
Authors: Bonner Carissa , Batcup Carys , Ayre Julie , Pickles Kristen , Cvejic Erin , Copp Tessa , Cornell Samuel , Dodd Rachael , Isautier Jennifer , Nickel Brooke , McCaffery Kirsten
Published: August 2021

Background

COVID-19 testing and contact tracing has been crucial in Australia’s prevention strategy. However, testing for COVID-19 is far from optimal, and behavioural barriers are unknown. Study 1 aimed to identify the range of barriers to testing. Study 2 aimed to estimate prevalence in a nationally relevant sample to target interventions.

Methods

Study 1: National longitudinal COVID-19 survey from April-November 2020. Testing barriers were included in the June survey (n=1369). Open responses were coded using the COM-B framework (capability-opportunity-motivation). Study 2: Barriers from Study 1 were presented to a new nationally representative sample in November to estimate prevalence (n=2869). Barrier prevalence was analysed by health literacy level using Chi square tests.

Results

Study 1: 49% strongly agreed to get tested for symptoms, and 69% would self-isolate. Concern about pain was the top barrier from a provided list (11%), but 32 additional barriers were identified from open responses and coded to the COM-B framework. Study 2: The most prevalent barriers were motivation issues (e.g. don’t believe symptoms are COVID-19: 28%, few local cases: 18%). Capability issues were also common (e.g. not sure symptoms are bad enough: 19%, not sure whether symptoms need testing: 15%). Many barriers were more prevalent amongst people with low compared to high health literacy, including motivation (preference to self isolate: 21% vs 12%, pain: 15% vs 9%) and capability (not sure symptom needs testing: 12% vs 8%, not sure how to test:11% vs 4%).

Conclusion

Even in a health system with free and widespread access to COVID-19 testing, motivation and capability barriers were prevalent issues, particularly for people with lower health literacy. This study highlights the important of diagnosing behaviour barriers to target public health interventions for COVID-19 and future pandemics.
Racial discrimination, low trust in the health system, and COVID-19 vaccine uptake: a longitudinal observational study of 633 UK adults from ethnic minority groups
Authors: Paul Elise , Fancourt Daisy , Razai Mohammad
Published: August 2021

Objective

To examine whether racial/ethnic discrimination predicts future COVID-19 vaccine refusal, and whether this association is explained by trust in government and the health system.

Design

Longitudinal observational study of racial/ethnic discrimination occurring since the start of the first lockdown (measured in July 2020) and later COVID-19 vaccine status.

Setting

UK (England, Scotland, Wales, and Northern Ireland)

Participants

633 adults belonging to ethnic minority groups who took part in the UCL COVID-19 Social Study.

Main outcome measure

COVID-19 vaccine refusal (vs accepted/waiting/had at least one dose) between 23 December 2020 and 14 June 2021.

Results

Nearly one in ten (6.7%) who had refused a COVID-19 vaccine had experienced racial/ethnic discrimination in a medical setting since the start of the pandemic and had experienced twice as many incidents of racial/ethnic discrimination than those who had accepted the vaccine. Structural equation modelling results indicated a nearly 4-fold (odds ratio [OR] = 3.9, 95% confidence interval [CI] = 1.4 to 10.9) total effect of racial/ethnic discrimination on refusing the vaccine was which was mediated by low trust in the health system to handle the pandemic (OR = 2.5, 95% CI = 1.1 to 5.4). Analyses adjusted for a range of demographic and COVID-19 related factors.

Conclusions

Findings underscore the importance of addressing racial/ethnic discrimination and the role the National Health Service in regaining trust from ethnic minority groups to increase COVID-19 vaccine uptake amongst ethnic minority adults.
A Learning Health System Approach to the COVID-19 Pandemic: System-Wide Changes in Clinical Practice and 30-Day Mortality Among Hospitalized Patients
Authors: McCreary Erin K. , Kip Kevin E. , Bariola J. Ryan , Schmidhofer Mark , Minnier Tami , Mayak Katelyn , Albin Debbie , Daley Jessica , Linstrum Kelsey , Hernandez Erik , Sackrowitz Rachel , Hughes Kailey , Horvat Christopher , Snyder Graham M. , McVerry Bryan J. , Yealy Donald M. , Huang David T. , Angus Derek C. , Marroquin Oscar C.
Published: August 2021

Introduction

Rapid, continuous implementation of credible scientific findings and regulatory approvals is often slow in large, diverse health systems. The COVID-19 pandemic created a new threat to this common “slow to learn and adapt” model in healthcare. We describe how UPMC committed to a rapid learning health system (LHS) model to respond to the COVID-19 pandemic.

Methods

An observational cohort study was conducted among 11,429 hospitalized patients from 22 hospitals (PA, NY) with a primary diagnosis of COVID-19 infection (March 19, 2020 – June 6, 2021). Sociodemographic and clinical data were captured from UPMC electronic medical record (EMR) systems. Patients were grouped into four time-defined patient “waves” based on nadir of daily hospital admissions, with wave 3 (September 20, 2020 – March 10, 2021) split at its zenith due to high volume with steep acceleration and deceleration. Outcomes included changes in clinical practice (e.g., use of corticosteroids, antivirals, and other therapies) in relation to timing of internal system analyses, scientific publications, and regulatory approvals, along with 30-day rate of mortality over time.

Results

Mean (SD) daily number of hospital admissions was 26 (28) with a maximum 7-day moving average of 107 patients. System-wide implementation of the use of dexamethasone, remdesivir, and tocilizumab occurred within days of release of corresponding seminal publications and regulatory actions. After adjustment for differences in patient clinical profiles over time, each month of hospital admission was associated with an estimated 5% lower odds of 30-day mortality (adjusted OR = 0.95, 95% confidence interval: 0.92 – 0.97, p < .001).

Conclusions

In our large LHS, near real-time changes in clinical management of COVID-19 patients happened promptly as scientific publications and regulatory approvals occurred throughout the pandemic. Alongside these changes, patients with COVID-19 experienced lower adjusted 30-day mortality following hospital admission over time.
Assessing the impact of community-based interventions on hypertension and diabetes management in three Minnesota communities: findings from the prospective evaluation of US HealthRise programs
Authors: Fullman Nancy , Cowling Krycia , Flor Luisa S , Wilson Shelley , Bhatt Paurvi , Bryant Miranda F , Camarda Joseph N , Colombara Danny V , Daly Jessica , Gabert Rose K , Harris Katie Panhorst , Johanns Casey K , Mandile Charlie , Marshall Susan , McNellan Claire R , Mulakaluri Vasudha , Phillips Bryan K , Reitsma Marissa B , Sadighi Naomi , Tamene Tsega , Thomson Blake , Wollum Alexandra , Gakidou Emmanuela
Published: August 2021

Background

Community-based health interventions are increasingly viewed as models of care that can bridge healthcare gaps experienced by underserved communities in the United States (US). With this study, we sought to assess the impact of such interventions, as implemented through the US HealthRise program, on hypertension and diabetes among underserved communities in Hennepin, Ramsey, and Rice Counties, Minnesota.

Methods and findings

HealthRise patient data from June 2016 to October 2018 were assessed relative to comparison patients in a difference-in-difference analysis, quantifying program impact on reducing systolic blood pressure (SBP) and hemoglobin A1c, as well as meeting clinical targets (< 140 mmHg for hypertension, < 8% Al1c for diabetes), beyond routine care. For hypertension, HealthRise participation was associated with SBP reductions in Rice (6.9 mmHg [95% confidence interval: 0.9–12.9]) and higher clinical target achievement in Hennepin (27.3 percentage-points [9.8–44.9]) and Rice (17.1 percentage-points [0.9 to 33.3]). For diabetes, HealthRise was associated with A1c decreases in Ramsey (1.3 [0.4–2.2]). Qualitative data showed the value of home visits alongside clinic-based services; however, challenges remained, including community health worker retention and program sustainability.

Conclusions

HealthRise participation had positive effects on improving hypertension and diabetes outcomes at some sites. While community-based health programs can help bridge healthcare gaps, they alone cannot fully address structural inequalities experienced by many underserved communities.
Socioeconomic and comorbid factors affecting mortality and length of stay in COVID-19
Authors: Delora Adam V. , Mills Ashlynn , Jacobson David , Cornett Brendon , Peacock W. Frank , Datta Anita , Jenks Shane
Published: August 2021

Background

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic exposed and exacerbated health disparities between socioeconomic groups. Our purpose was to determine which disparities are most prevalent and their impact on length of stay (LoS) and in hospital mortality in patients diagnosed with Covid-19.

Methods

De-Identified data for patients who tested positive for COVID-19 was abstracted from the HCA enterprise database. Data was binned into summary tables. A negative binomial regression with LoS as the dependent variable and a logistic regression of in-hospital mortality data, using age, insurance status, sex, comorbidities as the dependent variables, were performed.

Results

From March 1, 2020 to August 23, 2020, of 111,849 covid testing patient records, excluding those with missing data (n=7), without confirmed COVID-19 (n=27,225), and those from a carceral environment (n=1,861), left 84,624 eligible patients. Compared to the US population, the covid cohort had more black patients (23.17% vs 13.4%). Compared to the white cohort, the black cohort had higher private insurance rates (28.52% vs. 23.68%), shorter LoS (IRR=0.97 CI=0.95-0.99, P<0.01) and lower adjusted mortality (OR 0.81, 95% CI 0.75-0.97). Increasing age was associated with increased mortality and LoS. Patients with Medicare or Medicaid had longer LoS (IRR=1.07, 95% CI=1.04-1.09) and higher adjusted mortality rates (OR=1.11, 95% CI=1-1.23) than those with private insurance

Conclusion

Conclusions We found that when blacks have higher rates of private insurance, they have shorter hospitalizations and lower mortality than whites, when diagnosed with Covid-19. Some other psychiatric and medical conditions also significantly impacted outcomes in patients with Covid-19.

Key Points

Question

Which social determinants of health and comorbidities are most prevalent and their impact on length of stay and in-hospital mortality in patients diagnosed with Covid-19?

Findings

In this retrospective cohort of 84,624 with the black cohort having higher private insurance rates (28.52% vs. 23.68%), there was shorter LoS (IRR=0.97 CI=0.95-0.99, P<0.01) and lower adjusted mortality (OR 0.81, 95% CI 0.75-0.97). Age and several other medical and psychiatric comorbidities were also found to correlate with length of stay and mortality.

Meaning

The genetics of race is not important in predicting mortality and length of stay in COVID-19 patients, but age, comorbidities, and insurance status appear to have a significant difference in mortality and length of stay.
When do we need massive computations to perform detailed COVID-19 simulations?
Authors: Lutz Christopher B. , Giabbanelli Philippe J.
Published: August 2021

The COVID-19 pandemic has infected over 200 million people worldwide and killed more than 4 million as of August 2021. Many intervention strategies have been utilized by governments around the world, including masks, social distancing, and vaccinations. However, officials making decisions regarding interventions may have a limited time to act. Computer simulations can aid them by predicting future disease outcomes, but they also have limitations due to requirements on processing power or time. This paper examines whether a machine learning model can be trained on a small subset of simulation runs to inexpensively predict future disease trajectories very close to the original simulation results. Using four previously published agent-based models for COVID-19, this paper analyzes the predictions of decision tree regression machine learning models and compares them to the results of the original simulations. The results indicate that accurate machine learning meta-models can be generated from simulation models with no strong interventions (e.g., vaccines, lockdowns) using small amounts of simulation data. However, meta-models for simulation models that include strong interventions required much more training data to achieve a similar accuracy. This indicates that machine learning meta-models could be used in some scenarios to assist in faster decision making.
Predicting and measuring decision rules for social recognition in a Neotropical frog
Authors: Tumulty James P. , Fouilloux Chloe A. , Vallejos Johana Goyes , Bee Mark A.
Published: August 2021

Many animals use signals, such as vocalizations, to recognize familiar individuals. However, animals risk making recognition mistakes because the signal properties of different individuals often overlap due to within-individual variation in signal production. To understand the relationship between signal variation and decision rules for social recognition, we studied male golden rocket frogs, which recognize the calls of territory neighbors and respond less aggressively to a neighbor’s calls than to the calls of strangers. We quantified patterns of individual variation in acoustic properties of calls and predicted optimal discrimination thresholds using a signal detection theory model of receiver utility that incorporated signal variation, the payoffs of correct and incorrect decisions, and the rates of encounters with neighbors and strangers. We then experimentally determined thresholds for discriminating between neighbors and strangers using a habituation-discrimination experiment with territorial males in the field. Males required a threshold difference between 9% and 12% to discriminate between calls differing in temporal properties; this threshold matched those predicted by a signal detection theory model under ecologically realistic assumptions of infrequent encounters with strangers and relatively costly missed detections of strangers. We demonstrate empirically that receivers group continuous variation in vocalizations into discrete social categories and show that signal detection theory can be applied to investigate evolved decision rules.
Transcriptomic mapping of the inter-individual variability of cellular stress response activation in primary human hepatocytes
Authors: Niemeijer Marije , Wiecek Witold , Huppelschoten Suzanna , Bouwman Peter , Baze Audrey , Parmentier Céline , Richert Lysiane , Paules Richard S. , Bois Frederic Y. , van de Water Bob
Published: August 2021

Background & Aims

One of the early key events of drug-induced liver injury (DILI) is the activation of adaptive stress responses, a cellular mechanism to overcome stress. Given the diversity of DILI outcomes and lack in understanding of population variability, we mapped the inter-individual variability in stress response activation to improve DILI prediction.

Approach & Results

High-throughput transcriptome analysis of over 8,000 samples was performed in primary human hepatocytes of 50 individuals upon 8 to 24 h exposure to broad concentration ranges of stress inducers: tunicamycin to induce the unfolded protein response (UPR), diethyl maleate for the oxidative stress response, cisplatin for the DNA damage response and TNFα for NF-κB signalling. This allowed investigation of the inter-individual variability in concentration-dependent stress response activation, where the average of benchmark concentrations (BMCs) had a maximum difference of 864, 13, 13 and 259-fold between different hepatocytes for UPR, oxidative stress, DNA damage and NF-κB signalling-related genes, respectively. Hepatocytes from patients with liver disease resulted in less stress response activation. Using a population mixed-effect framework, the distribution of BMCs and maximum fold change were modelled, allowing simulation of smaller or larger PHH panel sizes. Small panel sizes systematically under-estimated the variance and resulted in low probabilities in estimating the correct variance for the human population. Moreover, estimated toxicodynamic variability factors were up to 2-fold higher than the standard uncertainty factor of 101/2 to account for population variability during risk assessment, exemplifying the need of data-driven variability factors.

Conclusions

Overall, by combining high-throughput transcriptome analysis and population modelling, improved understanding of variability in stress response activation across the human population could be established, thereby contributing towards improved prediction of DILI.
Spatial phylogenetics of Japanese ferns: Patterns, processes, and implications for conservation
Authors: Nitta Joel H. , Mishler Brent D. , Iwasaki Wataru , Ebihara Atsushi
Published: August 2021

Premise

Biodiversity is often only measured with species richness. However, this ignores evolutionary history and is not sufficient for making conservation decisions. Here, we characterize multiple facets and drivers of biodiversity to understand how these relate to bioregions and conservation status in the ferns of Japan.

Methods

We compiled a community dataset of 1,239 20 km × 20 km grid-cells including 672 taxa based on > 300,000 specimen records. We combined this with a phylogeny and functional traits to analyze taxonomic, phylogenetic, and functional diversity, and modeled biodiversity metrics in response to environmental factors and reproductive mode. Hierarchical clustering was used to delimit bioregions. Conservation status and threats were assessed by comparing the overlap of significantly diverse grid-cells with conservation zones and range maps of native Japanese deer.

Results

Taxonomic richness was highest at mid-latitudes. Phylogenetic and functional diversity and phylogenetic endemism were highest in small southern islands. Relative phylogenetic and functional diversity were high at high and low latitudes, and low at mid-latitudes. Grid-cells were grouped into three (phylogenetic) or four (taxonomic) major bioregions. Temperature and apomixis were identified as drivers of biodiversity patterns. Conservation status was generally high for grid-cells with significantly high biodiversity, but the threat due to herbivory by deer was greater for taxonomic richness than other metrics.

Conclusions

Our integrative approach reveals previously undetected patterns and drivers of biodiversity in the ferns of Japan. Future conservation efforts should recognize that threats can vary by biodiversity metric and consider multiple multiple metrics when establishing conservation priorities.
Goal-Dependent Hippocampal Representations Facilitate Self-Control
Authors: Edelson Micah G. , Hare Todd A.
Published: August 2021

Mnemonic influences on decision-making processes are important for linking past experiences and simulations of the future with current goals. The ways in which mnemonic information is represented may be especially critical in situations where one needs to overcome past rewarding experiences and exert self-control. We propose that self-control success or failure may depend on how information is retrieved from memory and how effectively this memory retrieval process can be modified to achieve a specific goal. We test our hypothesis using representational similarity analyses of human neuroimaging data during a dietary self-control task in which individuals must overcome taste temptations to choose healthy foods. We find that self-control is indeed associated with the way individuals represent taste information in the brain and how taste representations adapt to align with different goals. These results provide new insights into the processes leading to self-control success and indicate the need to update the classical view of self-control to continue to advance our understanding of its behavioral and neural underpinnings.
NKG2D signaling regulates IL-17A-producing γδT cells to promote cancer progression
Authors: Curio Sophie , Edwards Sarah C. , Suzuki Toshiyasu , McGovern Jenny , Triulzi Chiara , Yoshida Nagisa , Jonsson Gustav , Glauner Teresa , Rami Damiano , Purcell Rachel Violet , Coffelt Seth B. , Guerra Nadia
Published: August 2021

γδT cells are unconventional T cells particularly abundant in mucosal tissues that play an important role in tissue surveillance and homeostasis. γδT cell activation is mediated by the T cell receptor composed of γ and δ chains, as well as activating receptors for stress-induced ligands, such as NKG2D. Contrary to the well-established anti-tumor function of γδT cells, recent studies have shown that γδT cells can promote tumor development in certain contexts. However, the mechanisms leading to this diseasepromoting role remain poorly understood. Here, we show that mice lacking γδT cells survive longer in a mouse model of intestinal cancer, further supporting their pro-tumoral role. In a surprising conceptual twist, we found that these pro-tumor γδT cells are regulated by NKG2D signaling, a receptor normally associated with cancer cell killing. Germline deletion of Klrk1, the gene encoding NKG2D, reduced the frequency of γδT cells in the tumor microenvironment and delayed tumor progression. We further show that blocking NKG2D reduces the capability of γδT cells to produce IL-17A in the pre-metastatic lung and that co-culture of lung T cells with NKG2D ligand-expressing tumor cells specifically increases the frequency of γδT cells. Together, these data support the hypothesis that in a tumor microenvironment where NKG2D ligands are constitutively expressed, γδT cells accumulate in an NKG2D-dependent manner and drive tumor progression by secreting pro-inflammatory cytokines, such as IL-17A.
dsMTL - a computational framework for privacy-preserving, distributed multi-task machine learning
Authors: Cao Han , Zhang Youcheng , Baumbach Jan , Burton Paul R , Dwyer Dominic , Koutsouleris Nikolaos , Matschinske Julian , Marcon Yannick , Rajan Sivanesan , Rieg Thilo , Ryser-Welch Patricia , Späth Julian ,   The COMMITMENT consortium, Herrmann Carl , Schwarz Emanuel
Published: August 2021

Multitask learning allows the simultaneous learning of multiple ‘communicating’ algorithms. It is increasingly adopted for biomedical applications, such as the modeling of disease progression. As data protection regulations limit data sharing for such analyses, an implementation of multitask learning on geographically distributed data sources would be highly desirable. Here, we describe the development of dsMTL, a computational framework for privacy-preserving, distributed multi-task machine learning that includes three supervised and one unsupervised algorithms. dsMTL is implemented as a library for the R programming language and builds on the DataSHIELD platform that supports the federated analysis of sensitive individual-level data. We provide a comparative evaluation of dsMTL for the identification of biological signatures in distributed datasets using two case studies, and evaluate the computational performance of the supervised and unsupervised algorithms. dsMTL provides an easy- to-use framework for privacy-preserving, federated analysis of geographically distributed datasets, and has several application areas, including comorbidity modeling and translational research focused on the simultaneous prediction of different outcomes across datasets. dsMTL is available at https://github.com/transbioZI/dsMTLBase (server-side package) and https://github.com/transbioZI/dsMTLClient (client-side package).
Efficient decoding of large-scale neural population responses with Gaussian-process multiclass regression
Authors: Greenidge C. Daniel , Scholl Benjamin , Yates Jacob L. , Pillow Jonathan W.
Published: August 2021

Neural decoding methods provide a powerful tool for quantifying the information content of neural population codes and the limits imposed by correlations in neural activity. However, standard decoding methods are prone to overfitting and scale poorly to high-dimensional settings. Here, we introduce a novel decoding method to overcome these limitations. Our approach, the Gaussian process multi-class decoder (GPMD), is well-suited to decoding a continuous low-dimensional variable from high-dimensional population activity, and provides a platform for assessing the importance of correlations in neural population codes. The GPMD is a multinomial logistic regression model with a Gaussian process prior over the decoding weights. The prior includes hyperparameters that govern the smoothness of each neuron’s decoding weights, allowing automatic pruning of uninformative neurons during inference. We provide a variational inference method for fitting the GPMD to data, which scales to hundreds or thousands of neurons and performs well even in datasets with more neurons than trials. We apply the GPMD to recordings from primary visual cortex in three different species: monkey, ferret, and mouse. Our decoder achieves state-of-the-art accuracy on all three datasets, and substantially outperforms independent Bayesian decoding, showing that knowledge of the correlation structure is essential for optimal decoding in all three species.
Light Potentials of Photosynthetic Energy Storage in the Field: What limits the ability to use or dissipate rapidly increased light energy?
Authors: Kanazawa Atsuko , Chattopadhyay Abhijnan , Kuhlgert Sebastian , Tuitupou Hainite , Maiti Tapabrata , Kramer David M.
Published: August 2021

The responses of plant photosynthesis to rapid fluctuations in environmental conditions are thought to be critical for efficient capture of light energy. Such responses are not well represented under laboratory conditions, but have also been difficult to probe in complex field environments. We demonstrate an open science approach to this problem that combines multifaceted measurements of photosynthesis and environmental conditions, and an unsupervised statistical clustering approach. In a selected set of data on mint (Menthasp.), we show that the “light potential” for increasing linear electron flow (LEF) and nonphotochemical quenching (NPQ) upon rapid light increases are strongly suppressed in leaves previously exposed to low ambient PAR or low leaf temperatures, factors that can act both independently and cooperatively. Further analyses allowed us to test specific mechanisms. With decreasing leaf temperature or PAR, limitations to photosynthesis during high light fluctuations shifted from rapidly-induced NPQ to photosynthetic control (PCON) of electron flow at the cytochromeb6fcomplex. At low temperatures, high light induced lumen acidification, but did not induce NPQ, leading to accumulation of reduced electron transfer intermediates, a situation likely to induce photodamage, and represents a potential target for improving the efficiency and robustness of photosynthesis. Finally, we discuss the implications of the approach for open science efforts to understand and improve crop productivity.
Development of a flexible split prime editor using truncated reverse transcriptase
Authors: Zheng Chunwei , Liang Shun-Qing , Liu Bin , Liu Pengpeng , Kwan Suet-Yan , Wolfe Scot A. , Xue Wen
Published: August 2021

Prime Editor (PE) has tremendous promise for gene therapy. However, it remains a challenge to deliver PE (>6.3 kb) in vivo. Although PE can be split into two fragments and delivered using dual adeno-associated viruses (AAVs), choice of split sites within Cas9 – which affects editing efficiency – is limited due to the large size of PE. Furthermore, the potential effect of overexpressing RT in mammalian cells is largely unknown. Here, we developed a compact PE with complete deletion of the RNase H domain of reverse transcriptase (RT), which showed comparable editing to full-length PE. Using compact PE, we tested the effect of 4 different Cas9 split sites and found that the Glu 573 split site supports robust editing (up to 93% of full-length PE). The compact PE, but not PE2, abolished its binding to eRF1 and showed minimal effect on stop codon readthrough, which therefore might reduce the effects on protein biosynthesis. This study identifies a safe and efficient compact PE2 that enables flexible split-PE design to facilitate efficient delivery in vivo and advance the utility of prime editing.
Recurrent de novo single point mutation on the gene encoding Na+/K+ pump results in epilepsy
Authors: Li Hong-Ming , Hu Wen-Bao , Hong Chun-Gu , Duan Ran , Chen Meng-Lu , Cao Jia , Wang Zhen-Xing , Chen Chun-Yuan , Yin Fei , Hu Zhong-Hua , Li Jia-Da , Zhong Li-Hong , Xie Hui , Liu Zheng-Zhao
Published: August 2021

The etiology of epilepsy remains undefined in two-thirds of patients. Here, we identified a de novo mutation of ATP1A2 (c.2426 T>G, p.Leu809Arg), which encodes the α2 subunit of Na+/K+-ATPase, from a family with idiopathic epilepsy. This mutation caused seizures in the study patients. We generated the point mutation mouse model Atp1a2L809R, which recapitulated the epilepsy observed in the study patients. In Atp1a2L809R/WT mice, convulsions were observed and cognitive and memory function was impaired. This mutation affected the potassium binding function of the protein, disabling its ion transport ability, thereby increasing the frequency of nerve impulses. Our work revealed that ATP1A2L809R mutations cause a predisposition to epilepsy. Moreover, we first provide a point mutation mouse model for epilepsy research and drug screening.
Friend or Foe: Hybrid proline-rich proteins determine how plants interact with and respond to beneficial and pathogenic microbes
Authors: Banday Zeeshan Z. , Cecchini Nicolás M. , Scott Allison T. , Hu Ciara T. , Filzen Rachael C. , Agbo Elinam , Greenberg Jean T.
Published: August 2021

Plant plastids generate signals, including some derived from lipids, that need to be mobilized to effect signaling. We used informatics to discover potential plastid membrane proteins involved in microbial responses. Among these are proteins co-regulated with the systemic immunity component AZI1, a hybrid proline-rich protein (HyPRP) and HyPRP superfamily members. HyPRPs have a transmembrane domain, a proline-rich region (PRR) and a lipid transfer protein domain. The precise subcellular location(s) and function(s) is unknown for most HyPRP family members. As predicted by informatics, a subset of HyPRPs have a pool of protein that targets plastid outer envelope membranes (OEMs) via a mechanism that requires the PRR. Additionally, two HyPRPs may be associated with thylakoid membranes. Most of the plastid and non-plastid localized family members also have pools that localize to endoplasmic reticulum, plasma membrane or plasmodesmata. HyPRPs with plastid pools regulate, positively or negatively, systemic immunity against the pathogen Pseudomonas syringae. HyPRPs also regulate the interaction with the plant growth promoting rhizobacteria Pseudomonas simiae WCS417 in the roots to influence colonization, root system architecture and/or biomass. Thus, HyPRPs have broad and distinct roles in immune, development and growth responses to microbes and reside at sites that may facilitate signal molecule transport.
Combined use of Oxford Nanopore and Illumina sequencing yields insights into soybean structural variation biology
Authors: Lemay Marc-André , Sibbesen Jonas A. , Torkamaneh Davoud , Hamel Jérémie , Levesque Roger C. , Belzile François
Published: August 2021

Background

Structural variant (SV) discovery based on short reads is challenging due to their complex signatures and tendency to occur in repeated regions. The increasing availability of long-read technologies has greatly facilitated SV discovery, however these technologies remain too costly to apply routinely to population-level studies. Here, we combined short-read and long-read sequencing technologies to provide a comprehensive population-scale assessment of structural variation in a panel of Canadian soybean cultivars.

Results

We used Oxford Nanopore sequencing data (∼12X mean coverage) for 17 samples to both benchmark SV calls made from the Illumina data and predict SVs that were subsequently genotyped in a population of 102 samples using Illumina data. Benchmarking results show that variants discovered using Oxford Nanopore can be accurately genotyped from the Illumina data. We first use the genotyped SVs for population structure analysis and show that results are comparable to those based on single-nucleotide variants. We observe that the population frequency and distribution within the genome of SVs are constrained by the location of genes. Gene Ontology and PFAM domain enrichment analyses also confirm previous reports that genes harboring high-frequency SVs are enriched for functions in defense response. Finally, we discover polymorphic transposable elements from the SVs and report evidence of the recent activity of a Stowaway MITE.

Conclusions

Our results demonstrate that long-read and short-read sequencing technologies can be efficiently combined to enhance SV analysis in large populations, providing a reusable framework for their study in a wider range of samples and non-model species.