bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of autism spectrum disorder diagnosis using nonlinear measures of language-related EEG at 6 and 12 months
Authors: Peck Fleming C. , Gabard-Durnam Laurel J. , Wilkinson Carol L. , Bosl William , Tager-Flusberg Helen , Nelson Charles A.
Published: December 2020

Early identification of autism spectrum disorder (ASD) provides an opportunity for early intervention and improved outcomes. Use of electroencephalography (EEG) in infants has shown promise in predicting later ASD diagnoses and in identifying neural mechanisms underlying the disorder. Given the high co-morbidity with language impairment in ASD, we and others have speculated that infants who are later diagnosed with ASD have altered language learning, including phoneme discrimination. Phoneme learning occurs rapidly within the first postnatal year, so altered neural substrates either during or after the first year may serve as early, accurate indicators of later autism diagnosis. Using longitudinal EEG data collected during a passive phoneme task in infants with high familial risk for ASD, we compared predictive accuracy at 6-months (during phoneme learning) versus 12-months (after phoneme learning). Samples at both ages were matched in size and diagnoses (n=14 with later ASD; n= 40 without ASD). Using Pearson correlation feature selection and support vector machine with radial basis function classifier, 100% predictive diagnostic accuracy was observed at both ages. However, predictive features selected at the two ages differed and came from different scalp locations. We also report that performance across multiple machine learning algorithms was highly variable and declined when the 12-month sample size and behavioral heterogeneity was increased. These results demonstrate that speech processing EEG measures can facilitate earlier identification of ASD but emphasize the need for age-specific predictive models with large sample sizes in order to develop clinically relevant classification algorithms.
SARS-CoV-2 shifting transmission dynamics and hidden reservoirs limited the efficacy of public health interventions in Italy
Authors: Giovanetti Marta , Cella Eleonora , Benedetti Francesca , Magalis Brittany Rife , Fonseca Vagner , Fabris Silvia , Campisi Giovanni , Ciccozzi Alessandra , Angeletti Silvia , Borsetti Alessandra , Tambone Vittoradolfo , Sagnelli Caterina , Pascarella Stefano , Riva Alberto , Ceccarelli Giancarlo , Marcello Alessandro , Azarian Taj , Wilkinson Eduan , de Oliveira Tulio , Junior Alcantara Luiz Carlos , Cauda Roberto , Caruso Arnaldo , Dean Natalie E , Browne Cameron , Lourenco Jose , Salemi Marco , Zella Davide , Ciccozzi Massimo
Published: December 2020

We investigated SARS-CoV-2 transmission dynamics in Italy, one of the countries hit hardest by the pandemic, using phylodynamic analysis of viral genetic and epidemiological data. We observed the co-circulation of at least 13 different SARS-CoV-2 lineages over time, which were linked to multiple importations and characterized by large transmission clusters concomitant with a high number of infections. Subsequent implementation of a three-phase nationwide lockdown strategy greatly reduced infection numbers and hospitalizations. Yet we present evidence of sustained viral spread among sporadic clusters acting as “hidden reservoirs” during summer 2020. Mathematical modelling shows that increased mobility among residents eventually catalyzed the coalescence of such clusters, thus driving up the number of infections and initiating a new epidemic wave. Our results suggest that the efficacy of public health interventions is, ultimately, limited by the size and structure of epidemic reservoirs, which may warrant prioritization during vaccine deployment.
Antigen-based rapid diagnostic testing or alternatives for diagnosis of symptomatic COVID-19: A simulation-based net benefit analysis
Authors: Kendall Emily A , Arinaminpathy Nimalan , Sacks Jilian A , Manabe Yukari C , Dittrich Sabine , Schumacher Samuel G , Dowdy David W
Published: December 2020

Background

SARS-CoV-2 antigen-detection rapid diagnostic tests (Ag-RDTs) can diagnose COVID-19 rapidly and at low cost, but their lower sensitivity than nucleic acid amplification testing (NAAT) has limited clinical adoption.

Methods

We compared Ag-RDT, NAAT, and clinical judgment alone for diagnosing symptomatic COVID-19. We considered an outpatient setting (10% COVID-19 prevalence among the patients tested, 3-day NAAT turnaround) and a hospital setting (40% prevalence, 24-hour NAAT turnaround). We simulated transmission from cases and contacts and relationships between time, viral burden, transmission, and case detection. We compared diagnostic approaches using a measure of net benefit that incorporated both clinical and public health benefits and harms of intervention.

Results

In the outpatient setting, we estimated that using Ag-RDT instead of NAAT to test 200 individuals could have a net benefit equivalent to preventing all symptomatic transmission from one person with COVID-19 (one “transmission-equivalent”). In the hospital setting, net benefit analysis favored NAAT, and testing 25 patients with NAAT instead of Ag-RDT achieved one “transmission-equivalent” of incremental benefit. In both settings, Ag-RDT was preferred to NAAT if NAAT turnaround time exceeded two days. Both Ag-RDT and NAAT provided greater net benefit than management based on clinical judgment alone, unless intervention carried minimal harm and was provided equally regardless of diagnostic approach.

Conclusions

For diagnosis of symptomatic COVID-19, the speed of diagnosis with Ag-RDT is likely to outweigh its lower accuracy compared to NAAT wherever NAAT turnaround times are two days or longer. This advantage may be even greater if Ag-RDTs are also less expensive.
Competing Risks in Patients with Primary Prevention Implantable Cardioverters Defibrillators: Global Electrical Heterogeneity and Clinical Outcomes (GEHCO) Study
Authors: Waks Jonathan W. , Haq Kazi T. , Tompkins Christine , Rogers Albert J. , Ehdaie Ashkan , Bender Aron , Minnier Jessica , Dalouk Khidir , Howell Stacey , Peiris Achille , Raitt Merritt , Narayan Sanjiv M. , Chugh Sumeet S. , Tereshchenko Larisa G.
Published: December 2020

Background

Global electrical heterogeneity (GEH) is associated with sudden cardiac death in the general population.

Objective

To investigate whether GEH is associated with sustained ventricular tachycardia (VT)/ventricular fibrillation (VF) leading to appropriate implantable cardioverter-defibrillator (ICD) therapies in systolic heart failure (HF) patients with primary prevention ICDs.

Methods

We conducted a multicenter retrospective cohort study. GEH was measured by spatial ventricular gradient (SVG) direction and magnitude, QRS-T angle, and sum absolute QRST integral (SAIQRST) on pre-implant 12-lead ECGs. Survival analysis using cause-specific hazard functions compared the strength of associations with two competing outcomes: sustained VT/VF leading to appropriate ICD therapies and all-cause death without appropriate ICD therapies.

Results

We analyzed data from 2,668 patients (age 63±12y; 23% female; 78% white; 43% nonischemic cardiomyopathy (NICM); left ventricular ejection fraction 28±11% from 6 academic medical centers). After adjustment for demographic, clinical, device, and traditional ECG characteristics, SVG elevation (Hazard Ratio (HR) per 1 standard deviation (SD) 1.14 (95% CI 1.04-1.25);P=0.004), SVG azimuth (HR 1.12(1.01-1.24);P=0.039); SVG magnitude (HR per 1 SD 0.75 (0.66-0.85);P<0.0001), and QRS-T angle (HR per 1 SD 1.21 (95% CI 1.08-1.36);P=0.001) were associated with appropriate ICD therapies. The SVG azimuth was also associated with a lower competing risk of death (Pdifference=0.007): HR 0.91(0.82-1.02);P=0.095. SAIQRST had different associations in ischemic [HR 1.29(1.04-1.60)] and NICM [HR 0.78(0.62-0.96);Pinteraction=0.022].

Conclusion

In patients with primary prevention ICDs, GEH is independently associated with appropriate ICD therapies. The SVG vector points in distinctly different directions in patients with two competing outcomes.

Clinical Trial Registration

URL:www.clinicaltrials.govUnique identifier:NCT03210883.
Investigating the Effectiveness of Breast Cancer Supplemental Screening Considering Radiologists’ Bias
Authors: Molani Sevda , Madadi Mahboubeh , Williams Donna L.
Published: December 2020

Breast density is known to increase breast cancer risk and decrease mammography screening sensitivity. Breast density notification laws (enacted in 38 states as of September 2020), require physicians to inform women with high breast density of these potential risks. The laws usually require healthcare providers to notify patients of the possibility of using more sensitive supplemental screening tests (e.g., ultrasound). Since the enactment of the laws, there have been controversial debates over i) their implementations due to the potential radiologists bias in breast density classification of mammogram images and ii) the necessity of supplemental screenings for all patients with high breast density. In this study, we formulate a finite-horizon, discrete-time partially observable Markov chain (POMC) to investigate the effectiveness of supplemental screening and the impact of radiologists’ bias on patients’ outcomes. We consider the conditional probability of eventually detecting breast cancer in early states given that the patient develops breast cancer in her lifetime as the primary and the expected number of supplemental tests as the secondary patient’s outcome. Our results indicate that referring patients to a supplemental test solely based on their breast density may not necessarily improve their health outcomes and other risk factors need to be considered when making such referrals. Additionally, average-skilled radiologists’ performances are shown to be comparable with the performance of a perfect radiologist (i.e., 100% accuracy in breast density classification). However, a significant bias in breast density classification (i.e., consistent upgrading or downgrading of breast density classes) can negatively impact a patient’s health outcomes.
Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning
Authors: Patterson Bruce K , Guevara-Coto Jose , Yogendra Ram , Francisco Edgar , Long Emily , Pise Amruta , Rodrigues Hallison , Parikh Purvi , Mora Javier , Mora-Rodríguez Rodrigo A
Published: December 2020

Individuals with systemic symptoms long after COVID-19 has cleared represent approximately ~10% of all COVID-19 infected individuals. Here we present a bioinformatics approach to predict and model the phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 144 individuals including normal individuals and patients spanning the COVID-19 disease continuum. We collected plasma and isolated PBMCs from 29 normal individuals, 26 individuals with mild-moderate COVID-19, 25 individuals with severe COVID-19, and 64 individuals with Chronic COVID-19 symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients. Data was analyzed using machine learning methods to predict and distinguish the groups from each other.Using a multi-class deep neural network classifier to better fit our prediction model, we recapitulated a 100% precision, 100% recall and F1 score of 1 on the test set. Moreover, a first score specific for the chronic COVID-19 patients was defined asS1 = (IFN-γ + IL-2)/ CCL4-MIP-1β. Second, a score specific for the severe COVID-19 patients was defined asS2 = (10*IL-10 + IL-6) - (IL-2 + IL-8). Severe cases are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While chronic patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells.

Immunologic Modeling of Severity and Chronicity of COVID-19
Colorectal cancer screening within colonoscopy capacity constraints: can FIT-based programmes save more lives by trading-off more sensitive test cut-offs against longer screening intervals?
Authors: McFerran Ethna , O’Mahony James F. , Naber Steffie , Sharp Linda , Zauber Ann G. , Lansdorp-Vogelaar Iris , Kee Frank
Published: December 2020

Introduction

Colorectal cancer (CRC) prevention programmes using faecal immunochemical testing (FIT) as the primary screen typically rely on colonoscopy for secondary and surveillance testing. Colonoscopy capacity is an important constraint, limiting the number of primary tests offered. Many European programmes lack sufficient colonoscopy capacity to provide optimal screening intensity regarding screening age ranges, intervals and FIT cut-offs. It is currently unclear how to optimise programmes within colonoscopy capacity constraints.

Design

The MISCAN-Colon microsimulation model was used to determine if more effective CRC screening programmes can be identified within existing colonoscopy capacity. The model assessed 525 strategies of varying screening intervals, age ranges and FIT cut-offs, including previously unevaluated 4 and 5 year screening intervals. These strategies were compared with policy decisions taken in Ireland to provide CRC screening within available colonoscopy capacity. Outcomes estimated net costs, quality-adjusted-life-years and required colonoscopy numbers. The optimal strategies within finite colonoscopy capacity constraints were identified.

Results

Combining a reduced FIT cut-off of 10 µg Hb/g, an extended screening interval of 4 years and an age range of 60-72 years requires 6% fewer colonoscopies, reduces net costs by 23% while preventing 15% more CRC deaths and saving 16% more QALYs relative to current policy.

Conclusion

Previously overlooked longer screening intervals may balance optimal cancer prevention with finite colonoscopy capacity constraints. Simple changes to screening configurations could save lives, reduce costs, and relieve colonoscopy capacity pressures. These findings are directly relevant to CRC screening programmes across Europe that employ FIT-based testing and face colonoscopy capacity constraints.
Interventions to prevent neonatal healthcare-associated infections in low-resource settings: a systematic review
Authors: Fitzgerald Felicity C. , Zingg Walter , Chimhini Gwendoline , Chimhuya Simbarashe , Wittmann Stefanie , Brotherton Helen , Olaru Ioana D. , Neal Samuel R. , Russell Neal , Araujo da Silva André Ricardo , Sharland Mike , Seale Anna C , Cotton Mark F , Coffin Susan , Dramowski Angela
Published: December 2020

Background

Clinically suspected and laboratory-confirmed bloodstream infections are frequent causes of morbidity and mortality during neonatal care. The most effective infection prevention and control (IPC) interventions for neonates in low-and-middle-income countries (LMIC) are unknown.

Aim

To identify effective interventions in the prevention of hospital-acquired bloodstream infections in LMIC neonatal units.

Methods

Medline, PUBMED, The Cochrane Database of Systematic Reviews, EMBASE, and PsychInfo (January 2003 – October 2020) were searched to identify studies reporting single or bundled interventions for prevention of bloodstream infections in LMIC neonatal units.

Results

Our initial search identified 5206 articles; following application of filters, 27 publications met the inclusion and ICROMS assessment criteria and were summarised in the final analysis. No studies were carried out in low-income countries, only one in sub-Saharan Africa and just two in multiple countries. Of the 18 single intervention studies, most targeted skin (n=4) and gastrointestinal mucosal integrity (n=5). Whereas emollient therapy and lactoferrin achieved significant reductions in proven neonatal infection, glutamine and mixed probiotics showed no benefit. Chlorhexidine gluconate for cord care and kangaroo mother care reduced infection in individual single-centre studies. Of the nine studies evaluating bundles, most focused on prevention of device-associated infections and achieved significant reductions in catheter- and ventilator-associated infections.

Conclusion

There is a limited evidence-base for the effectiveness of IPC interventions in LMIC neonatal units; bundled interventions targeting device-associated infections were most effective. More multi-site studies with robust study designs are needed to inform IPC intervention strategies in low-resource neonatal units.

Sources of Support

FF is supported by the Academy of Medical Sciences, the funders of the Starter Grant for Clinical Lecturers scheme and UCL Great Ormond Street NIHR Biomedical Research Centre. AD is supported by the Fogarty International Center of the National Institutes of Health, Emerging Global Leader Award Number K43-TW010682.
Framework for enhancing the estimation of model parameters for data with a high level of uncertainty
Authors: Libotte Gustavo B. , dos Anjos Lucas , Almeida Regina C. , Malta Sandra M. C. , Silva Renato S.
Published: December 2020

Reliable data is essential to obtain adequate simulations for forecasting the dynamics of epidemics. In this context, several political, economic, and social factors may cause inconsistencies in the reported data, which reflect the capacity for realistic simulations and predictions. In the case of COVID-19, for example, such uncertainties are mainly motivated by large-scale underreporting of cases due to reduced testing capacity in some locations. In order to mitigate the effects of noise in the data used to estimate parameters of models, we propose strategies capable of improving the ability to predict the spread of the diseases. Using a compartmental model in a COVID-19 study case, we show that the regularization of data by means of Gaussian Process Regression can reduce the variability of successive forecasts, improving predictive ability. We also present the advantages of adopting parameters of compartmental models that vary over time, in detriment to the usual approach with constant values.
Assessing Global Covid-19 Cases Data through Compositional Data Analysis(CoDa)
Authors: Braga Luis P.V. , Feigenbaum Dina
Published: December 2020

Background

Covid-19 cases data pose an enormous challenge to any analysis. The evaluation of such a global pandemic requires matching reports that follow different procedures and even overcoming some countries’ censorship that restricts publications.

Methods

This work proposes a methodology that could assist future studies. Compositional Data Analysis (CoDa) is proposed as the proper approach as Covid-19 cases data is compositional in nature. Under this methodology, for each country three attributes were selected: cumulative number of deaths (D); cumulative number of recovered patients(R); present number of patients (A).

Results

After the operation called closure, with c=1, a ternary diagram and Log-Ratio plots, as well as, compositional statistics are presented. Cluster analysis is then applied, splitting the countries into discrete groups.

Conclusions

This methodology can also be applied to other data sets such as countries, cities, provinces or districts in order to help authorities and governmental agencies to improve their actions to fight against a pandemic.
Spaced training enhances memory and prefrontal ensemble stability in mice
Authors: Glas Annet , Hübener Mark , Bonhoeffer Tobias , Goltstein Pieter M.
Published: December 2020

Memory is substantially improved when learning is distributed over time, an effect called “spacing effect”. So far it has not been studied how spaced learning affects neuronal ensembles presumably underlying memory. In the present study, we investigate whether trial spacing increases the stability or size of neuronal ensembles. Mice were trained in the “everyday memory” task, an appetitive, naturalistic, delayed matching-to-place task. Spacing trials by 60 minutes produced more robust memories than training with shorter or longer intervals. c-Fos labeling and chemogenetic inactivation established the necessity of the dorsomedial prefrontal cortex (dmPFC) for successful memory storage.In vivocalcium imaging of excitatory dmPFC neurons revealed that longer trial spacing increased the similarity of the population activity pattern on subsequent encoding trials and upon retrieval. Conversely, trial spacing did not affect the size of the total neuronal ensemble or the size of subpopulations dedicated to specific task-related behaviors and events. Thus, spaced learning promotes reactivation of prefrontal neuronal ensembles processing episodic-like memories.
Intraspecific variation in immune gene expression and heritable symbiont density
Authors: Nichols Holly L. , Goldstein Elliott B. , Ziabari Omid Saleh , Parker Benjamin J.
Published: December 2020

Abstract

Host genetic variation plays an important role in the structure and function of heritable microbial communities. Recent studies have demonstrated that insects use immune mechanisms to regulate heritable symbionts. Here we test the hypothesis that variation in symbiont density within hosts is linked to intraspecific differences in the immune response to harboring symbionts. We show that pea aphids (Acyrthosiphon pisum) harboring the bacterial endosymbiontRegiella insecticola(but not all other species of symbionts) suppress expression of key immune genes. We then functionally link immune suppression with symbiont density using RNAi. The pea aphid species complex is comprised of multiple reproductively-isolated host plant-adapted populations. These ‘biotypes’ have distinct patterns of heritable symbiont infections: for example, aphids from theTrifoliumbiotype are strongly associated withRegiella. Using RNAseq, we compare patterns of gene expression in response toRegiellain aphid genotypes from multiple biotypes, and we show thatTrifoliumaphids experience no immune gene suppression fromRegiellaand host symbionts at lower densities. We then generated F1 hybrids between two biotypes and found that symbiont density and immune suppression are both intermediate in hybrids. We suggest that in this system,Regiellasymbionts are suppressing aphid immune mechanisms to increase their density, but that some hosts have adapted to prevent immune suppression in order to control symbiont numbers. The specific immune mechanisms suppressed byRegiellahave been previously demonstrated to combat pathogens in aphids, and thus this work highlights the immune system’s complex dual role in interacting with both beneficial and harmful microbes.

AuthorSummary

Heritable microbes are found in most insects including agriculturally and medically relevant pests. Explaining the variation in the distribution and abundance of symbionts in natural populations is critical to understanding these interactions. This work contributes to our mechanistic understanding of an important model of host-microbe symbiosis and suggests more broadly that variation in insect immune responses plays a role in intraspecific variation in host-symbiont interactions. Our work also suggests that antagonistic coevolution can play a role in host-microbe interactions even when microbes are transmitted vertically and provide a clear benefit to their hosts.
Mesophotic gorgonian corals evolve multiple times and faster than deep and shallow lineages
Authors: Sánchez Juan A. , González-Zapata Fanny L. , Prada Carlos , Dueñas Luisa F.
Published: December 2020

1.

Mesophotic Coral Ecosystems (MCEs) develop on a unique environment, where abrupt environmental changes take place. Using a time-calibrated molecular phylogeny (mtDNA: mtMutS), we examined the lineage membership of mesophotic gorgonian corals (Octocorallia: Cnidaria) in comparison to shallow and deep-sea lineages of the wider Caribbean-Gulf of Mexico and the Tropical Eastern Pacific. Our results show mesophotic gorgonians originating multiple times from old deep-sea octocoral lineages, whereas shallow-water species comprise younger lineages. The mesophotic gorgonian fauna in the studied areas are related to their zooxanthellate shallow-water counterparts in only two clades (Gorgoniidae and Plexauridae), where the shallow-deep gradient could serve as a driver of diversification. Interestingly, mesophotic clades have diversified faster than either shallow or deep clades. One of this groups with fast diversification is the family Ellisellidae, a major component of the mesophotic gorgonian coral assemblage worldwide.
Mutually inclusive mechanisms of drought-induced tree mortality
Authors: Hajek Peter , Link Roman M. , Nock Charles , Bauhus Jürgen , Gebauer Tobias , Gessler Arthur , Kovach Kyle , Messier Christian , Paquette Alain , Saurer Matthias , Scherer-Lorenzen Michael , Rose Laura , Schuldt Bernhard
Published: December 2020

An extreme summer drought caused unprecedented tree dieback across Central Europe in 2018, highlighting the need for a better mechanistic understanding of drought-induced tree mortality. While numerous physiological risk factors have been identified, the principal mechanisms, hydraulic failure and carbon starvation, are still debated. We studied 9,435 trees from 12 temperate species planted in a diversity experiment in 2013 to assess how hydraulic traits, carbon dynamics, pest infestation, tree height and neighbourhood competition influence individual mortality risk. We observed a reduced mortality risk for trees with wider hydraulic safety margins, while a rising sugar fraction of the non-structural carbohydrate pool and bark beetle infestation were associated with higher risk. Taller trees had a lower mortality risk. The sign and magnitude of neighbourhood effects on mortality risk depended on the species-identity of the involved trees, with most species having beneficial and some having deleterious effects on their neighbours. While severe tissue dehydration causing hydraulic failure precedes drought-induced tree mortality, we show that the probability of this event depends on a series of mutually inclusive processes including pest infestation and starch depletion for osmotic adjustment, and is modulated by the size and species identity of a tree and its neighbours.
Broad transcriptomic dysregulation across the cerebral cortex in ASD
Authors: Haney Jillian R. , Wamsley Brie , Chen George T. , Parhami Sepideh , Emani Prashant S. , Chang Nathan , Hoftman Gil D. , de Alba Diego , Kale Gaurav , Ramaswami Gokul , Hartl Christopher L. , Jin Ting , Wang Daifeng , Ou Jing , Wu Ye Emily , Parikshak Neelroop N. , Swarup Vivek , Belgard T. Grant , Gerstein Mark , Pasaniuc Bogdan , Gandal Michael J. , Geschwind Daniel H.
Published: December 2020

Classically, psychiatric disorders have been considered to lack defining pathology, but recent work has demonstrated consistent disruption at the molecular level, characterized by transcriptomic and epigenetic alterations.1–3In ASD, upregulation of microglial, astrocyte, and immune signaling genes, downregulation of specific synaptic genes, and attenuation of regional gene expression differences are observed.1,2,4–6However, whether these changes are limited to the cortical association areas profiled is unknown. Here, we perform RNA-sequencing (RNA-seq) on 725 brain samples spanning 11 distinct cortical areas in 112 ASD cases and neurotypical controls. We identify substantially more genes and isoforms that differentiate ASD from controls than previously observed. These alterations are pervasive and cortex-wide, but vary in magnitude across regions, roughly showing an anterior to posterior gradient, with the strongest signal in visual cortex, followed by parietal cortex and the temporal lobe. We find a notable enrichment of ASD genetic risk variants among cortex-wide downregulated synaptic plasticity genes and upregulated protein folding gene isoforms. Finally, using snRNA-seq, we determine that regional variation in the magnitude of transcriptomic dysregulation reflects changes in cellular proportion and cell-type-specific gene expression, particularly impacting L3/4 excitatory neurons. These results highlight widespread, genetically-driven neuronal dysfunction as a major component of ASD pathology in the cerebral cortex, extending beyond association cortices to involve primary sensory regions.
A COMPARATIVE STUDY OF ANAESTHETIC AGENTS ON HIGH VOLTAGE ACTIVATED CALCIUM CHANNEL CURRENTS IN IDENTIFIED MOLLUSCAN NEURONS
Authors: Morris Terrence J. , Hopkins Philip M. , Winlow William
Published: December 2020

Using the two electrode voltage clamp configuration, a high voltage activated whole-cell Ca2+channel current (IBa) was recorded from a cluster of neurosecretory ‘Light Yellow’ Cells (LYC) in the right parietal ganglion of the pond snailLymnaea stagnalis.

Recordings of IBafrom LYCs show a reversible concentration-dependent depression of current amplitude in the presence of the volatile anaesthetics halothane, isoflurane and sevoflurane, or the non-volatile anaesthetic pentobarbitone at clinical concentrations.

In the presence of the anaesthetics investigated, IBameasured at the end of the depolarizing test pulse showed proportionally greater depression than that at measured peak amplitude, as well as significant decrease in the rate of activation or increase in inactivation or both.

Within the range of concentrations used, the concentration-response plots for all the anaesthetics investigated correlate strongly to straight line functions, with linear regression R2values > 0.99 in all instances.

For volatile anaesthetics, the dose-response regression slopes for IBaincrease in magnitude, in order of gradient: sevoflurane, isoflurane and halothane, a sequence which reflects their order of clinical potency in terms of MAC value.
Preventive training interferes with mRNA-encoding myosin 7 and collagen I expression during pulmonary arterial hypertension
Authors: Mariano Thaoan Bruno , de Souza Castilho Anthony César , Sabela Ana Karenina Dias de Almeida , de Oliveira André Casanova , Cury Sarah Santiloni , Aguiar Andreo Fernando , Dias Raisa de Jesus Dutra , Cicogna Antonio Carlos , Okoshi Katashi , Justulin Junior Luis Antonio , Carvalho Robson Francisco , Pacagnelli Francis Lopes
Published: December 2020

To gain insight on the impact of preventive exercise during pulmonary arterial hypertension (PAH), we evaluated the gene expression of myosins and gene-encoding proteins associated with the extracellular matrix remodeling of right hypertrophied ventricles. We used 32 male Wistar rats, separated in four groups: Sedentary Control (S; n=8); Control with Training (T; n=8); Sedentary with Pulmonary Arterial Hypertension (SPAH; n=8); and Pulmonary Arterial Hypertension with Training (TPAH; n=8). The rats trained for thirteen weeks on a treadmill. They had two weeks of adaptation training. The PAH was induced by application of monocrotaline 60 mg/kg. Consequential right ventricular dysfunction was observed after the 10th week of training. Rats in the control group received saline application. At the end of the 13th week, echocardiography analysis confirmed cardiac dysfunction. Collagen content and organization was assessed through picrosirius red staining and fractal dimension (FD) analysis, respectively. Transcript abundance was estimated through reverse transcription-quantitative PCR (RT-qPCR). Cardiac dysfunction was confirmed by the reduction in maximum pulmonary artery velocity and pulmonary artery acceleration time. Through histomorphometric assessment, we found no differences in the interstitial collagen FD between groups. Regarding gene expression,myh7gene expression was upregulated in the TPAH group. However, this did not occur with the S group. PAH also increased the mRNA abundance ofcol1a1in the SPAH and TPAH groups. Moreover, the TPAH group showed a higher abundance of this gene when compared to the S group. With these findings, we concluded that preventive exercise had a positive impact on compensated hypertrophy during pulmonary hypertension. This can be explained in part by the modulation of the extracellular matrix and myosin gene expression in trained rats.
Identification of Celastrol as a novel HIV-1 Latency Reversal Agent by an Image-Based Screen
Authors: Liu Hongbing , Hu Pei-Wen , Dubrulle Julien , Stossi Fabio , Nikolai Bryan C. , Mancini Michael A. , Rice Andrew P.
Published: December 2020

Although current antiretroviral therapies (ART) are successful in controlling HIV-1 infection, a stable viral reservoir reactivates when ART is discontinued. Consequently, there is a major research effort to develop approaches to disrupt the latent viral reservoir and enhance the immune system’s ability to clear HIV-1. A number of small molecules, termed latency reversal agents (LRAs), have been identified which can reactivate latent HIV-1 in cell lines and patients’ cellsex vivo. However, clinical trials have suggested that combinations of LRAs will be required to efficiently reactivate HIV-1in vivo, especially LRAs that act synergistically by functioning through distinct pathways. To identify novel LRAs, we used an image-based assay to screen a natural compound library for the ability to induce a low level of aggregation of resting primary CD4+T cells from healthy donors. We identified celastrol as a novel LRA. Celastrol functions synergistically with other classes of LRA to reactivate latent HIV-1 in a Jurkat cell line, suggesting a novel mechanism in its LRA activity. Additionally, celastrol does not appear to activate resting CD4+T cells at levels at which it can reactivate latent HIV-1. Celastrol appears to represent a novel class of LRAs and it therefore can serve as a lead compound for LRA development.
Neural stem cell interkinetic nuclear migration is controlled by a phosphatidylinositol transfer protein/non-canonical planar cell polarity signaling axis
Authors: Xie Zhigang , Bankaitis Vytas A.
Published: December 2020

The mammalian neocortex undergoes explosive expansion during embryonic development. From an evolutionary perspective, higher complexity of the neocortex is accompanied by a prominent expansion in its lateral dimension so that the neocortical surface area is increased. Expansion in the radial dimension throughout evolution is limited so that neocortical thickness is strongly restricted1–3. The underlying mechanisms for restricting neocortical thickness remain unclear. Expansion of the developing mouse neocortex is driven by neurogenesis which is itself primarily fueled by neural stem cells (NSCs). NSCs form a pseudostratified epithelium and exhibit a hallmark cell cycle-dependent nuclear movement termed interkinetic nuclear migration (IKNM)2–4. While IKNM plays a critical role in cell fate determination, it remains a poorly understood process. Herein, we demonstrate IKNM relies on a phosphatidylinositol transfer protein (PITP)-noncanonical planar cell polarity (ncPCP) signaling axis that restricts radial expansion of the developing neocortex. Ablation of PITPα/PITPβ in NSCs compromised IKNM -- resulting in a thickened neocortex and perturbed curvature of its ventricular surface. Those phenotypic derangements in IKNM and neocortical morphogenesis were recapitulated in mouse embryos individually ablated for two ncPCP receptor gene activities and in a mosaic neocortex expressing a dominant-negative variant of a third ncPCP receptor. Finally, PITP signaling links to ncPCP pathway activity by promoting membrane trafficking of a subset of ncPCP receptors from the trans-Golgi network to the NSC cell surface. We conclude IKNM is a driving force for a special form of convergent extension regulated by coupling PITP-mediated phosphoinositide signaling with activity of the evolutionarily conserved ncPCP pathway.
Understanding Thioamitide Biosynthesis Using Pathway Engineering and Untargeted Metabolomics
Authors: Eyles Tom H. , Vior Natalia M. , Lacret Rodney , Truman Andrew W.
Published: December 2020

Thiostreptamide S4 is a thioamitide, a family of promising antitumour ribosomally synthesised and post-translationally modified peptides (RiPPs). The thioamitides are one of the most structurally complex RiPP families, yet very few thioamitide biosynthetic steps have been elucidated, even though the gene clusters of multiple thioamitides have been identified. We hypothesised that engineering the thiostreptamide S4 gene cluster in a heterologous host could provide insights into its biosynthesis when coupled with untargeted metabolomics and targeted mutations of the precursor peptide. Modified gene clusters were constructed, and in-depth metabolomics enabled a detailed understanding of the biosynthetic pathway, including the identification of an effector-like protein critical for amino acid dehydration. We use this biosynthetic understanding to bioinformatically identify new widespread families of RiPP biosynthetic gene clusters, paving the way for future RiPP discovery and engineering.
Retrograde And Anterograde Transport Of LAT-Vesicles During The Immunological Synapse Formation: Defining The Finely-Tuned Mechanism
Authors: Saez Juan José , Dogniaux Stéphanie , Shafaq-Zadah Massiullah , Johannes Ludger , Hivroz Claire , Zucchetti Andrés Ernesto
Published: December 2020

LAT is an important player of the signaling cascade induced by TCR activation. This adapter molecule is present at the plasma membrane of T lymphocytes and more abundantly in intracellular compartments. Upon T-cell activation the intracellular pool of LAT is recruited to the immune synapse (IS). We previously described two pathways controlling LAT trafficking: retrograde transport from endosomes to the TGN, and anterograde traffic from the Golgi to the IS. We address the specific role of 4 proteins, the GTPase Rab6, the t-SNARE syntaxin-16, the v-SNARE VAMP7 and the golgin GMAP210, in each pathway. Using different methods (endocytosis and Golgi trap assays, confocal and TIRF microscopy, TCR-signalosome pull down) we show that syntaxin-16 is regulating the retrograde transport of LAT whereas VAMP7 is regulating the anterograde transport. Moreover, GMAP210 and Rab6, known to contribute in both pathways, are in our cellular context specifically and respectively involved in anterograde and retrograde transport of LAT. Altogether, our data describe how retrograde and anterograde pathways coordinate LAT enrichment at the IS and point the Golgi as a central hub for the polarized recruitment of LAT to the IS. The role that this finely-tuned transport of signaling molecules plays in T-cell activation is discussed.
The timing network is engaged in the practice of internally driven tapping independently of the learning transfer from perceptual to motor timing
Authors: Sánchez-Moncada Itzamná , Concha Luis , Merchant Hugo
Published: December 2020

When we intensively train a timing skill, such as learning to play the piano, we do not only produce brain changes associated with task-specific learning, but also improve the performance on other temporal behaviors that depend on these tuned neural resources. Since the neural basis of time learning and generalization are still unknown, we measured the changes in neural activity associated with the transfer of learning from perceptual to motor timing. We found that intense training in an interval discrimination task increased the acuity of time perception in a group of subjects that also showed learning transfer, expressed as a reduction in tapping variability during an internally-driven periodic motor task. However, we also found subjects with no learning and generalization effects, and a third group with no signs of learning but with practice-based decreases in temporal variability in the motor task. Notably, these heterogeneous populations of subjects shared a common increase of activity in the medial premotor areas and the putamen in the post-with respect to the pre-training session of the tapping task. These findings support the idea that the core timing network is constantly refining its ability to time behaviors in different contexts and that practice is critical for keeping the neural clock attuned and properly functioning.
Development and validation of a combined species SNP array for the European seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata)
Authors: Peñaloza C. , Manousaki T. , Franch R. , Tsakogiannis A. , Sonesson A. , Aslam M. L. , Allal F. , Bargelloni L. , Houston R. D. , Tsigenopoulos C. S.
Published: December 2020

SNP arrays are powerful tools for high-resolution studies of the genetic basis of complex traits, facilitating both population genomic and selective breeding research. The European seabass (Dicentrarchus labrax) and the gilthead seabream (Sparus aurata) are the two most important fish species for Mediterranean aquaculture. While selective breeding programmes increasingly underpin stocky supply for this industry, genomic selection is not yet widespread. Genomic selection has major potential to expedite genetic gain, in particular for traits practically impossible to measure on selection candidates, such as disease resistance and fillet yield. The aim of our study was to design a combined-species 60K SNP array for both European seabass and gilthead seabream, and to validate its performance on farmed and wild populations from numerous locations throughout the species range. To achieve this, high coverage Illumina whole genome sequencing of pooled samples was performed for 24 populations of European seabass and 27 populations of gilthead seabream. This resulted in a database of ~20 million SNPs per species, which were then filtered to identify high-quality variants and create the final set for the development of the ‘MedFish’ SNP array. The array was then tested by genotyping a subset of the discovery populations and demonstrated a high conversion rate to functioning polymorphic assays on the array (92% in seabass: 89% in seabream) and repeatability (99.4 - 99.7%). The platform interrogates ~30K markers in each fish species, includes features such as SNPs previously shown to be associated with performance traits, and is enriched for SNPs predicted to alter protein function. The array was demonstrated to be effective at detecting population structure across a wide range of fish populations from diverse geographical origins, and to examine the extent of haplotype sharing among Mediterranean fish farms. Therefore, the MedFish array enables efficient and accurate high-throughput genotyping for genome-wide distributed SNPs on each fish species, and will facilitate stock management, population genomics approaches, and acceleration of selective breeding through genomic selection.
Biological network-inspired interpretable variational autoencoder
Authors: Seninge Lucas , Anastopoulos Ioannis , Ding Hongxu , Stuart Joshua
Published: December 2020

Deep learning architectures such as variational autoencoders have revolutionized the analysis of transcriptomics data. However, the latent space of these variational autoencoders offers little to no interpretability. To provide further biological insights, we introduce a novel sparse Variational Autoencoder architecture, VEGA (Vae Enhanced by Gene Annotations), whose decoder wiring is inspired by a priori characterized biological abstractions, providing direct interpretability to the latent variables. We demonstrate the interpretability and flexibility of VEGA in diverse biological contexts, by integrating various sources of biological abstractions such as pathways, gene regulatory networks and cell type identities in the latent space of our model. We show that our model could recapitulate the mechanism of cellular-specific response to treatments, the status of master regulators as well as jointly investigate the cell type and cellular state identity in developing cells. We envision the approach could serve as an explanatory biological model in contexts such as development and drug treatment experiments.
The evolution of social parasitism inFormicaants revealed by a global phylogeny
Authors: Borowiec Marek L. , Cover Stefan P. , Rabeling Christian
Published: December 2020

Studying the behavioral and life history transitions from a cooperative, eusocial life history to exploitative social parasitism allows for deciphering the conditions under which changes in behavior and social organization lead to diversification. The Holarctic ant genusFormicais ideally suited for studying the evolution of social parasitism because half of its 176 species are confirmed or suspected social parasites, which includes all three major classes of social parasitism known in ants. However, the life-history transitions associated with the evolution of social parasitism in this genus are largely unexplored. To test competing hypotheses regarding the origins and evolution of social parasitism, we reconstructed the first global phylogeny ofFormicaants and representative formicine outgroups. The genusFormicaoriginated in the Old World during the Oligocene (∼30 Ma ago) and dispersed multiple times to the New World. WithinFormica, the capacity for dependent colony foundation and temporary social parasitism arose once from a facultatively polygynous, independently colony founding ancestor. Within this parasitic clade, dulotic social parasitism evolved once from a facultatively temporary parasitic ancestor that likely practiced colony budding frequently. Permanent social parasitism evolved twice from temporary social parasitic ancestors that rarely practiced colony budding, demonstrating that obligate social parasitism can originate from different facultative parasitic backgrounds in socially polymorphic organisms. In contrast to inquiline ant species in other genera, the high social parasite diversity inFormicalikely originated via allopatric speciation, highlighting the diversity of convergent evolutionary trajectories resulting in nearly identical parasitic life history syndromes.
Quantifying a Frequency Modulation Response Biomarker in Responsive Neurostimulation
Authors: Venkatesh Praveen , Sneider Daniel , Danish Mohammed , Sisterson Nathaniel D. , Zaher Naoir , Urban Alexandra , Grover Pulkit , Richardson R. Mark , Kokkinos Vasileios
Published: December 2020

Objective

Responsive Neurostimulation (RNS) is an effective treatment for controlling seizures in patients with drug-resistant focal epilepsy who are not suitable candidates for resection surgery. A lack of tools for detecting and characterizing potential response biomarkers, however, contributes to a limited understanding of mechanisms by which RNS improves seizure control. We developed a method to quantify ictal frequency modulation, previously identified as a biomarker of clinical responsiveness to RNS.

Approach

Frequency modulation is characterized by shifts in power across spectral bands during ictal events, over several months of neurostimulation. This effect was quantified by partitioning each seizure pattern into segments with distinct spectral content and measuring the extent change from the baseline distribution of spectral content using the squared Earthmover’s distance.

Main results

We analyzed intracranial electroencephalography data from 13 patients who received RNS therapy, six of whom exhibited frequency modulation on expert evaluation. Subjects in the frequency modulation group had, on average, significantly larger and more sustained changes in their Earthmover’s distances (mean = 13.97×10-3± 1.197×10-3). In contrast, those subjects without expert-identified frequency modulation exhibited statistically insignificant or negligible distances (mean = 4.994×10-3± 0.732×10-3).

Significance

This method is the first step towards a quantitative, feedback-driven system for systematically optimizing RNS stimulation parameters, with an ultimate goal of truly personalized closed-loop therapy for epilepsy.