bluuebunny/crossref_metadata_2025 huggingface dataset:
From infection to immunity: understanding the response to SARS-CoV2 through in-silico modeling
Authors: Castiglione Filippo , Deb Debashrito , Srivastava Anurag P. , Liò Pietro , Liso Arcangelo
Published: December 2020

Background

Immune system conditions of the patient is a key factor in COVID-19 infection survival. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies.

Aim

The dynamics of the insurgence of immunity is at the core of the both SARS-CoV-2 vaccine development and therapies. This paper addresses a fundamental question in the management of the infection: can we describe the insurgence (and the span) of immunity in COVID-19? The in-silico model developed here answers this question at individual (personalized) and population levels.

We simulate the immune response to SARS-CoV-2 and analyze the impact of infecting viral load, affinity to the ACE2 receptor and age in the artificially infected population on the course of the disease.

Methods

We use a stochastic agent-based immune simulation platform to construct a virtual cohort of infected individuals with age-dependent varying degree of immune competence. We use a parameter setting to reproduce known inter-patient variability and general epidemiological statistics.

Results

We reproducein-silicoa number of clinical observations and we identify critical factors in the statistical evolution of the infection. In particular we evidence the importance of the humoral response over the cytotoxic response and find that the antibody titers measured after day 25 from the infection is a prognostic factor for determining the clinical outcome of the infection.

Our modeling framework uses COVID-19 infection to demonstrate the actionable effectiveness of simulating the immune response at individual and population levels. The model developed is able to explain and interpret observed patterns of infection and makes verifiable temporal predictions.

Within the limitations imposed by the simulated environment, this work proposes in a quantitative way that the great variability observed in the patient outcomes in real life can be the mere result of subtle variability in the infecting viral load and immune competence in the population.

In this work we i) show the power of model predictions, ii) identify the clinical end points that could be more suitable for computational modeling of COVID-19 immune response, iii) define the resolution and amount of data required to empower this class of models for translational medicine purposes and, iv) we exemplify how computational modeling of immune response provides an important view to discuss hypothesis and design new experiments, in particular paving the way to further investigations about the duration of vaccine-elicited immunity especially in the view of the blundering effect of immunesenescence.
Extending the proteomic characterization ofCandida albicansexposed to stress and apoptotic inducers through data-independent acquisition mass spectrometry
Authors: Amador-García Ahinara , Zapico Inés , Malmström Johan , Monteoliva Lucía , Gil Concha
Published: December 2020

Candida albicansis a commensal fungus that causes systemic infections in immunosuppressed patients. In order to deal with the changing environment during commensalism or infection,C. albicansmust reprogram its proteome. Characterizing the stress-induced changes in the proteome thatC. albicansuses to survive should be very useful in the development of new antifungal drugs. We studied theC. albicansglobal proteome after exposure to hydrogen peroxide (H2O2) and acetic acid (AA), using a DIA-MS strategy. More than 2000C. albicansproteins were quantified using an ion library previously constructed using DDA-MS.C. albicansresponded to treatment with H2O2with an increase in the abundance of many proteins involved in the oxidative stress response, protein folding and proteasome-dependent catabolism, which led to an increased proteasome activity. The data revealed a previously unknown key role for Prn1, a protein similar to pirins, in the oxidative stress response. Treatment with AA resulted in a general decrease in the abundance of proteins involved in amino acid biosynthesis, protein folding, and rRNA processing. Almost all proteasome proteins declined, as did proteasome activity. Apoptosis was observed after treatment with H2O2, but not AA. A targeted proteomic study of 32 proteins related to apoptosis in yeast supported the results found by DIA-MS and allowed the creation of an efficient method to quantify relevant proteins after treatment with stressors (H2O2, AA, and amphotericin B). This approach also uncovered a main role for Oye32, an oxidoreductase, suggesting this protein as a possible apoptotic marker common to many stressors.

IMPORTANCE

Fungal infections are a worldwide health problem especially in immunocompromised patients and patients with chronic disorders. Invasive candidiasis, mainly caused byC. albicans, are among the most common fungal diseases. Despite the existence of treatments to combat candidiasis the spectra of drugs available are limited. For the discovery of new drug targets is essential to know the pathogen response to different stress conditions. Our study provides a global vision of proteomic remodeling inC. albicansafter exposure to different agents such as hydrogen peroxide, acetic acid and amphotericin B that can cause apoptotic cell death. This results revealed the significance of many proteins related to oxidative stress response and proteasome activity among others. Of note, the discovery of Prn1 as a key protein in the defence against oxidative stress as well the increase in the abundance of Oye32 protein when apoptotic process occurred point out them as possible drug targets.
How optimal allocation of limited testing capacity changes epidemic dynamics
Authors: Calabrese Justin M. , Demers Jeffery
Published: December 2020

Insufficient testing capacity continues to be a critical bottleneck in the worldwide fight against COVID-19. Optimizing the deployment of limited testing resources has therefore emerged as a keystone problem in pandemic response planning. Here, we use a modified SEIR model to optimize testing strategies under a constraint of limited testing capacity. We define pre-symptomatic, asymptomatic, and symptomatic infected classes, and assume that positively tested individuals are immediately moved into quarantine. We further define two types of testing. Clinical testing focuses only on the symptomatic class. Non-clinical testing detects pre- and asymptomatic individuals from the general population, and an “information” parameter governs the degree to which such testing can be focused on high infection risk individuals. We then solve for the optimal mix of clinical and non-clinical testing as a function of both testing capacity and the information parameter. We find that purely clinical testing is optimal at very low testing capacities, supporting early guidance to ration tests for the sickest patients. Additionally, we find that a mix of clinical and non-clinical testing becomes optimal as testing capacity increases. At high but empirically observed testing capacities, a mix of clinical testing and unfocused (information=0) non-clinical testing becomes optimal. We further highlight the advantages of early implementation of testing programs, and of combining optimized testing with contact reduction interventions such as lockdowns, social distancing, and masking.
A longitudinal study of the impact of human mobility on the incidence of COVID-19 in India
Authors: Praharaj Sarbeswar , Han Hoon
Published: December 2020

Human mobility plays a crucial role in determining how fast and where infectious diseases can spread. This study aims to investigate visit to which category of places among grocery, retail, parks, workplaces, residential, and transit stations is more associated with the incidence of COVID-19 in India. A longitudinal analysis of generalized estimating equation (GEE) with a Poisson log-linear model is employed to analyze the daily mobility rate and reported new cases of COVID-19 between March 14 and September 11, 2020. This study finds that mobility to places of grocery (food and vegetable markets, drug stores etc.) and retail (restaurants, cafes, shopping centres etc.) is significantly associated (at p<0.01) with the incidence of COVID-19. In contrast, visits to parks, transit stations and mobility within residential neighbourhoods are not statistically significant (p>0.05) in changing COVID-19 cases over time. These findings highlight that instead of blanket lockdown restrictions, authorities should adopt a place-based approach focusing on vulnerable hotspot locations to contain the COVID-19 and any future infectious disease.
Chromosome dynamics and spatial organization during the non-binary cell cycle of a predatory bacterium
Authors: Kaljević Jovana , Saaki Terrens N. V. , Govers Sander K. , Remy Ophélie , van Raaphorst Renske , Lamot Thomas , Laloux Géraldine
Published: December 2020

In bacteria, the dynamics of chromosome replication and segregation are tightly coordinated with cell cycle progression, and largely rely on specific spatiotemporal arrangement of the chromosome. Whereas these key processes are mostly investigated in species that divide by binary fission, they remain mysterious in bacteria producing larger number of descendants. Here, we establish the predatory bacteriumBdellovibrio bacteriovorusas a model to investigate the non-binary processing of a circular chromosome. Our data reveal its extreme compaction in a dense polarized nucleoid. We also show that a first binary-like cycle of replication and asymmetric segregation is followed by multiple asynchronous rounds of replication and progressive ParABS-dependent partitioning, uncoupled from cell division. Surprisingly, ParB localization at the centromere is cell-cycle regulated. Altogether, our findings support a model of complex chromosome choreography, leading to the generation of variable numbers of offspring, highlighting the adaptation of conserved mechanisms to achieve non-binary reproduction in bacteria.
Standardizing a Protocol for Studying pH-dependent Transient Conformations using Computer Simulations
Authors: Singh Ruhar , Lynn Andrew M
Published: December 2020

1.

Understanding pH-dependent protein stability is important in biological - transport, storage, and delivery, in vivoconditions such as aggregation potential in neurodegenerative disease, and in studying the folding/unfolding of proteins. Using computer simulations, we can replace complex experimental determination and provide an atomistic-level interpretation of the cause and effect of pH on protein stability. Here, we standardize a method that provides a framework through which we examined pH-dependent transient conformations during unfolding simulations of proteins. Constant pH simulations utilized in the prediction of pKa values of charged groups of the peptide. The calculated pKa values employed to fix the appropriate protonation state of the amino acid to simulate the effect of pH on the system. Trajectories from multiple high-temperature MD simulations of the protein sample the conformational space during unfolding for a given pH state. The ensemble of conformations is analyzed from its free energy landscape to identify transient and stable conformations both at a given pH and between different pH. As a test system RN80, a protein fragment analog of the C-peptide from bovine pancreatic ribonuclease-A used to measure the accuracy of the predictions from simulations. Experimental measures of the helix content determined as a function of pH display a bell-shaped curve, i.e. RN80 alpha-helix formation is maximum at pH5 with a subsequent loss in helicity at higher and lower pH. The main forces stabilizing the alpha-helix are a salt-bridge formed between Glu-2 and Arg-10 and cation-pi-interaction between Tyr-8 and His-12. Our protocol includes constant pH calculations, optimal high-temperature simulations, and Free Energy landscape analysis exhibited the agreement with the experimental observations.
ScoreNet: A Neural network-based post-processing model for identifying epileptic seizure onset and offset in EEGs
Authors: Boonyakitanont Poomipat , Lek-uthai Apiwat , Songsiri Jitkomut
Published: December 2020

We design an algorithm to automatically detect epileptic seizure onsets and offsets from scalp EEGs. The proposed scheme consists of two sequential steps: detecting seizure episodes from long EEG recordings, and determining seizure onsets and offsets of the detected episodes. We introduce a neural network-based model calledScoreNetto carry out the second step by better predicting the seizure probability of pre-detected seizure epochs to determine seizure onsets and offsets. A cost function calledlog-dice losswith a similar meaning to the F1score is proposed to handle the natural data imbalance inherent in EEG signals signifying seizure events. ScoreNet is then verified on the CHB-MIT Scalp EEG database in combination with several classifiers including random forest, CNN, and logistic regression. As a result, ScoreNet improves seizure detection performance over lone epoch-based seizure classification methods; F1scores increase significantly from 16–37% to 53–70%, and false positive rates per hour decrease from 0.53–5.24 to 0.05–0.61. This method provides clinically acceptable latencies of detecting seizure onset and offset of less than 10 seconds. In addition, aneffective latency indexis proposed as a metric for detection latency whose scoring considers undetected events to provide better insight into onset and offset detection than conventional time-based metrics.
In vitro assessment of the capacity of pesticides to act as agonists/antagonists of the thyroid hormone nuclear receptors
Authors: Zekri Yanis , Agnol Laure Dall , Flamant Frédéric , Guyot Romain
Published: December 2020

Several in vitro tests, including transcriptome analysis of neural cells, were performed to assess the capacity of 33 pesticides to act as thyroid hormone disruptors (THD). Although some pesticides elicit a cellular response, which interferes with thyroid hormone signaling, we found no evidence that they can act as receptor agonists or antagonists. We conclude that the nuclear receptors of thyroid hormone are not common targets of THD, and that pesticide neurodevelopmental toxicity is not explained by a general alteration of neural cell response to thyroid hormone.
Africanized honey bees in Colombia exhibit high prevalence but low level of infestation ofVarroamites and low prevalence of pathogenic viruses
Authors: Tibatá Víctor Manuel , Sanchez Andrés , Young-Palmer Evan , Junca Howard , Solarte Victor Manuel , Madella Shayne , Ariza Fernando , Figueroa Judith , Corona Miguel
Published: December 2020

The global spread of the ectoparasitic miteVarroa destructorhas promoted the spread and virulence of highly infectious honey bee viruses. This phenomenon is considered the leading cause for the increased number of colony losses experienced by the mite-susceptible European honey bee populations in the Northern Hemisphere. Most of the honey bee populations in Central and South America are Africanized honey bees, which are considered more resistant toVarroacompared to European honey bees. However, the relationship betweenVarroalevels and spread of honey bee viruses in Africanized honey bees remains unknown. In this study, we determinedVarroaprevalence and infestation levels as well as the prevalence of seven major honey bee viruses in Africanized honey bees from three regions of Colombia. We found that althoughVarroaexhibited high prevalence (92%), its infestation levels were low (4.6%) considering that these populations never received acaricide treatments. We also detected four viruses in the three regions analyzed, but all hives were asymptomatic, and virus prevalence was considerably lower than those found in other countries with higher rates of mite-associated colony loss (DWV 19.88%, BQCV 17.39%, SBV 23.4 %, ABPV 10.56%). Our findings indicate that AHBs possess natural resistance toVarroathat does not prevent the spread of this parasite among their population, but restrains mite population growth and suppresses the prevalence and pathogenicity of mite-associated viruses.
Survival and growth of saprotrophic and mycorrhizal fungi in recalcitrant amine, amide and ammonium containing media
Authors: Stenholm Åke , Backlund Anders , Holmström Sara , Backlund Maria , Hedeland Mikael , Fransson Petra
Published: December 2020

The elimination of hazardous compounds in chemical wastes can be a complex and technically demanding task. In the search for environmental-friendly technologies, fungal mediated remediation and removal procedures are of concern. In this study, we investigated whether there are fungal species that can survive and grow on solely amine-containing compounds. One compound containing a primary amine group; 2-diethylaminoethanol, one compound with a primary amide group; 2,6-dichlorobenzamide (BAM), and a third compound containing a quaternary ammonium group; N3-trimethyl(2-oxiranyl)methanaminium chloride, were selected. The choice of these compounds was motivated by their excessive use in large scale manufacturing of protein separation media (2-diethylaminoethanol and the quaternary amine). 2,6-dichlorobenzamide, the degradation product of the herbicide 2,6-dichlorobenzonitrile (dichlobenil), was chosen since it is an extremely recalcitrant compound. Utilising part of the large fungal diversity in Northern European forests, a screening study using 48 fungal isolates from 42 fungal species, including saprotrophic and mycorrhizal fungi, was performed to test for growth responses to the chosen compounds. The ericoid mycorrhizal fungusRhizoscyphus ericaeshowed the best overall growth on 2-diethylaminoethanol and BAM in the 1-20 gL-1concentration range. A 3500% and 450% increase in biomass, respectively, was observed. For N3-trimethyl(2-oxiranyl)methanaminium chloride, the peak growth occurred at 1 gL-1. In a second experiment, including three of the most promising species (Laccaria laccata, Hygrophorus camarophyllusandRhizoscyphus ericae) from the screening experiment, a simulated process water containing 1.9% (w/v) 2-diethylaminoethanol and 0.8% (w/v) N3-trimethyl(2-oxiranyl)methanaminium chloride was used.Laccaria laccatashowed the best biomass growth increase (380%) relative to a growth control, while the growth increase forRhizoscyphus ericaeandH. camarophylluswere 292% and 136% respectively, showing that also mycorrhizal fungal species can use amine- and amide-containing substrates as nutrients. These results show the potential of certain fungal species to be used in alternative green wastewater treatment procedures.
Effects of Transport and Altitude on Hormones and Oxidative Stress Parameters in Sheep
Authors: Tozlu Çelık Hilal , Aslan Fatih Ahmet , Us Altay Diler , Kahvecı Metehan Eser , Konanç Kalbiye , Noyan Tevfik , Ayhan Sertaç
Published: December 2020

With this study, it was aimed to determine the stress effects that can be caused by transporting and altitude in sheep. Karayaka sheep were used in the study. The live weight of the sheep (n=30) while hungry was determined before transport and sea level. Average live weight was determined as 55.64 ± 4.66 kg. Blood samples were collected just before (sea level) and just after transport (1500 meters above sea level). Transportation distance was approximately 182 km and duration was 5 hours. According to the findings, cortisol was not affected by transport stress and altitude (p>0.05) and Triiyodotironin (T3) (p<0.039) and Tyrosine (T4) (p<0.000) were affected significantly. Malondialchehyche (MDA), which is one of the oxidative stress parameters, was significantly affected (p<0.039) and Protein Carbonyl (PC) values were not affected by transport and altitude (p>0.184). As a result of this study, it was determined that transportation and altitude in sheep causes stress. Stress-reducing measures should be taken in the exposure of sheep to altitude differences and in transportation. Antioxidant nutritional supplements should be made in order not to negatively affect the meat quality in sheep.
A new genome-wide method to identify genes with bimodal gene expression
Authors: Justino Josivan Ribeiro , Reis Clovis F. , Fonseca Andre Faustino , de Souza Sandro Jose , Stransky Beatriz
Published: December 2020

A new method is presented to detect bimodality in gene expression data using the Gaussian Mixture Models to cluster samples in each mode. We have used the method to search for bimodal genes in data from 25 tumor types available from The Cancer Genome Atlas. The method identified 554 genes with bimodal gene expression, of which 46 were identified in more than one cancer type. To further illustrate the impact of the method, we show that 96 out of the 554 genes with bimodal expression patterns presented different prognosis when patients belonging to the two expression peaks are compared. The software to execute the method and the corresponding documentation are available athttps://github.com/LabBiosystemUFRN/Bimodality_Genes.
Principled simulation of agent-based models in epidemiology
Authors: Wu Sean L. , Dolgert Andrew J. , Lewnard Joseph A. , Marshall John M. , Smith David L.
Published: December 2020

After more than a century of sustained work by mathematicians, biologists, epidemiologists, probabilists, and other experts, dynamic models have become a vital tool for understanding and describing epidemics and disease transmission systems. Such models fulfill a variety of crucial roles including data integration, estimation of disease burden, forecasting trends, counterfactual evaluation, and parameter estimation. These models often incorporate myriad details, from age and social structure to inform population mixing patterns, commuting and migration, and immunological dynamics, among others. This complexity can be daunting, so many researchers have turned to stochastic simulation using agent-based models. Developing agent-based models, however, can present formidable technical challenges. In particular, depending on how the model updates state, unwanted or even unnoticed approximations can be introduced into a simulation model. In this article, we present computational methods for approximating continuous time discrete event stochastic processes based on a discrete time step to speed up complicated simulations which also converges to the true process as the time step goes to zero. Our stochastic models is constructed via hazard functions, and only those hazards which are dependent on the state of other agents (such as infection) are approximated, whereas hazards governing dynamics internal to an agent (such as immune response) are simulated exactly. By partitioning hazards as being either dependent or internal, a generic algorithm can be presented which is applicable to many models of contagion processes, with natural areas of extension and optimization.

Author summary

Stochastic simulation of epidemics is crucial to a variety of tasks in public health, encompassing intervention evaluation, trend forecasting, and estimation of epidemic parameters, among others. In many situations, due to model complexity, time constraints, unavailability or unfamiliarity with existing software, or other reasons, agent-based models are used to simulate epidemic processes. However, many simulation algorithms aread hoc, which may introduce unwanted or unnoticed approximations. We present a method to build approximate, agent-based models from mathematical descriptions of stochastic epidemic processes which will improve simulation speed and converge to exact simulation techniques in limiting cases. The simplicity and generality of our method should be widely applicable to various problems in mathematical epidemiology and its connection to other methods developed in chemical physics should inspire future work and elaboration.
N-glycolylneuraminic acid binding of avian H7 influenza A viruses
Authors: Spruit Cindy M. , Zhu Xueyong , Broszeit Frederik , Han Alvin X. , van der Woude Roosmarijn , Bouwman Kim M. , Luu Michel M. T. , Russell Colin A. , Wilson Ian A. , Boons Geert-Jan , de Vries Robert P.
Published: December 2020

Influenza A viruses initiate infection by binding to glycans with terminal sialic acids present on the cell surface. Hosts of influenza A viruses variably express two major forms of sialic acid, N-acetylneuraminic acid (NeuAc) and N-glycolylneuraminic acid (NeuGc). NeuGc is produced in the majority of mammals including horses, pigs, and mice, but is absent in humans, ferrets, and birds. Intriguingly, the only known naturally occurring influenza A viruses that exclusively bind NeuGc are the extinct highly pathogenic equine H7N7 viruses. We determined the crystal structure of a representative equine H7 hemagglutinin (HA) in complex with its NeuGc ligand and observed a high similarity in the receptor-binding domain with an avian H7 HA. To determine the molecular basis for NeuAc and NeuGc specificity, we performed systematic mutational analyses, based on the structural insights, on two distant avian H7 HAs. We found that mutation A135E is key for binding α2,3-linked NeuGc but does not abolish NeuAc binding. Interestingly, additional mutations S128T, I130V, or a combination of T189A and K193R, converted from NeuAc to NeuGc specificity as determined by glycan microarrays. However, specific binding to NeuGc-terminal glycans on our glycan array did not always correspond with full NeuGc specificity on chicken and equine erythrocytes and tracheal epithelium sections. Phylogenetic analysis of avian and equine H7 HAs that investigated the amino acids at positions 128, 130, 135, 189, and 193 reveals a clear distinction between equine and avian residues. The highest variability in amino acids (four different residues) is observed at key position 135, of which only the equine glutamic acid leads to binding of NeuGc. The results demonstrate that avian H7 viruses, although genetically distinct from equine H7 viruses, can bind NeuGc after the introduction of two to three mutations, providing insights into the adaptation of H7 viruses to NeuGc receptors.

Author summary

Influenza A viruses cause millions of cases of severe illness and deaths annually. To initiate infection and replicate, the virus first needs to bind to a structure on the cell surface, like a key fitting in a lock. For influenza A virus, these ‘keys’ (receptors) on the cell surface are chains of sugar molecules (glycans). The terminal sugar on these glycans is often either N-acetylneuraminic acid (NeuAc) or N-glycolylneuraminic acid (NeuGc). Most influenza A viruses bind NeuAc, but a small minority binds NeuGc. NeuGc is present in species like horses, pigs, and mice, but not in humans, ferrets, and birds. Therefore, NeuGc binding could be a determinant of an Influenza A virus species barrier. Here, we investigated the molecular determinants of NeuGc specificity and the origin of viruses that bind NeuGc.
Disintegration promotes proto-spacer integration by the Cas1-Cas2 complex
Authors: Ma Chien-Hui , Javanmardi Kamyab , Finkelstein Ilya J. , Jayaram Makkuni
Published: December 2020

‘Disintegration’—the reversal of transposon DNA integration at a target site—is regarded as an abortive off-pathway reaction. Here we challenge this view with a biochemical investigation of the mechanism of protospacer insertion by theStreptococcus pyogenesCas1-Cas2 complex, which is mechanistically analogous to DNA transposition. In supercoiled target sites, the predominant outcome is the disintegration of one-ended insertions that fail to complete the second integration event. In linear target sites, one-ended insertions far outnumber complete proto-spacer insertions. The second insertion event is most often accompanied by disintegration of the first, mediated either by the 3’-hydroxyl exposed during integration or by water. One-ended integration intermediates may mature into complete spacer insertions via DNA repair pathways that are also involved in transposon mobility. We propose that disintegration-promoted integration is functionally important in the adaptive phase of CRISPR-mediated bacterial immunity, and perhaps in other analogous transposition reactions.
Relationship between vestibular hair cell loss and deficits in two anti-gravity reflexes in the rat
Authors: Maroto Alberto F. , Barrallo-Gimeno Alejandro , Llorens Jordi
Published: December 2020

The tail-lift reflex and the air-righting reflex in rats are anti-gravity reflexes that depend on vestibular function. To begin identifying their cellular basis, this study examined the relationship between reflex loss and the graded lesions caused in the vestibular sensory epithelia by varying doses of an ototoxic compound. After ototoxic exposure, we recorded these reflexes using high speed video. The movies were used to obtain objective measures of the reflexes: the minimum angle formed by the nose, the back of the neck and the base of the tail during the tail-lift maneuver and the time to right in the air-righting test. The vestibular sensory epithelia were then collected from the rats and used to estimate the loss of type I (HCI), type II (HCII) and all hair cells (HC) in both central and peripheral parts of the crista, utricle, and saccule. As expected, tail-lift angles decreased, and air-righting times increased, while the numbers of HCs remaining in the epithelia decreased in a dose-dependent manner. The results demonstrated greater sensitivity of HCI compared to HCII to the IDPN ototoxicity, as well as a relative resiliency of the saccule compared to the crista and utricle. Comparing the functional measures with the cell counts, we observed that loss of the tail-lift reflex associates better with HCI than with HCII loss. In contrast, most HCI in the crista and utricle were lost before air-righting times increased. These data suggest that these reflexes depend on the function of non-identical populations of vestibular HCs.
Untangling structural factors and evolutionary drivers in nascent polyploids
Authors: de Carvalho Julie Ferreira , Stoeckel Solenn , Eber Frédérique , Lodé-Taburel Maryse , Gilet Marie-Madeleine , Trotoux Gwenn , Morice Jérôme , Falentin Cyril , Chèvre Anne-Marie , Rousseau-Gueutin Mathieu
Published: December 2020

Allopolyploids have globally higher fitness than their diploid progenitors however, by comparison, most resynthesized allopolyploids have poor fertility and highly unstable genome. Elucidating the evolutionary processes promoting genome stabilization and fertility is thus essential to comprehend allopolyploid success.

Using theBrassicamodel, we mimicked the speciation process of a nascent allopolyploid species by resynthesizing allotetraploidB. napusand systematically selecting for euploid individuals over eight generations in four independent allopolyploidization events with contrasted genetic backgrounds, cytoplasmic donors and polyploid formation type. We evaluated the evolution of meiotic behavior, fertility and identified rearrangements in S1 to S9 lineages, to explore the positive consequences of euploid selection onB. napusgenome stability.

Recurrent selection of euploid plants for eight generations drastically reduced the percentage of aneuploid progenies as early as the fourth generation, concomitantly with a quasi disappearance of newly fixed homoeologous rearrangements. The consequences of homoeologous rearrangements on meiotic behavior and seed number strongly depended on the genetic background and cytoplasm donor.

The combined use of both self-fertilisation and outcrossing as well as recurrent euploid selection, allowed identification of genomic regions associated with fertility and meiotic behavior, providing complementary evidence to explainB. napusspeciation success.
Pathogen effector recognition-dependent association of NRG1 with EDS1 and SAG101 in TNL receptor immunity
Authors: Sun Xinhua , Lapin Dmitry , Feehan Joanna M. , Stolze Sara C. , Kramer Katharina , Dongus Joram A. , Rzemieniewski Jakub , Blanvillain-Baufumé Servane , Harzen Anne , Bautor Jaqueline , Derbyshire Paul , Menke Frank L. H. , Finkemeier Iris , Nakagami Hirofumi , Jones Jonathan D.G. , Parker Jane E.
Published: December 2020

Plants utilise intracellular nucleotide-binding, leucine-rich repeat (NLR) immune receptors to detect pathogen effectors and activate local and systemic defence. NRG1 and ADR1 “helper” NLRs (RNLs), cooperate with enhanced disease susceptibility 1 (EDS1), senescence-associated gene 101 (SAG101) and phytoalexin-deficient 4 (PAD4) lipase-like proteins to mediate signalling from TIR domain NLR receptors (TNLs). However, the mechanism of RNL/EDS1-family protein cooperation is poorly understood. Here, we provide genetic and molecular evidence for exclusive EDS1/SAG101/NRG1 and EDS1/PAD4/ADR1 co-functions in TNL immunity. Using immunoprecipitation and mass spectrometry, we show effector recognition-dependent association of NRG1 with EDS1 and SAG101, but not PAD4. An EDS1-SAG101 complex associates with NRG1, and EDS1-PAD4 associates with ADR1, only in an immune-activated state. NRG1 requires an intact nucleotide-binding P-loop motif, and EDS1 a functional EP domain and its partner SAG101, for induced association and immunity. Thus, two distinct modules (NRG1/EDS1/SAG101 and ADR1/EDS1/PAD4) are required to execute TNL receptor defence signalling.
Arginine Methylation Regulates Ribosome CAR Function
Authors: Scopino Kristen , Dalgarno Carol , Nachmanoff Clara , Krizanc Daniel , Thayer Kelly M. , Weir Michael P.
Published: December 2020

The ribosome CAR interaction surface is hypothesized to provide a layer of translation regulation through hydrogen-bonding to the +1 mRNA codon that is next to enter the ribosome A site during translocation. The CAR surface consists of three residues, 16S/18S rRNA C1054, A1196 (E. coli16S numbering), and R146 of yeast ribosomal protein Rps3. R146 can be methylated by the Sfm1 methyltransferase which is downregulated in stressed cells. Through molecular dynamics analysis, we show here that methylation of R146 compromises the integrity of CAR by reducing the pi stacking of the R146 guanidinium group with A1196, leading to reduced CAR hydrogen-bonding with the +1 codon. We propose that ribosomes assembled under stressed conditions have unmethylated R146, resulting in elevated CAR/+1 codon interactions, which tunes translation levels in response to the altered cellular context.
Metastasis and cancer stem cell markers identify two colorectal cancer subtypes with different molecular and clinical features
Authors: Alsaihati Burair A. , Zhao Shaying
Published: December 2020

Colorectal cancer (CRC) is among the top prevalent cancer types with lethal outcome in the United States and worldwide. CRC inter-tumor heterogeneity highlights the importance of identifying molecular markers for meaningful classification and prognosis. The recently published Consensus Molecular Subtypes (CMS) represent a widely used molecular subtyping system of CRC. However, our analyses indicate that clear heterogeneity still exists in some CMSs. In this work, we demonstrate that both CMS2 and CMS4 are composed of two molecularly distinct subtypes. We named them S1 and S2, short for subtype 1 and subtype 2. Our results indicate that the two subtypes also differ clinically. Notably, S2 exhibits more frequent lymphatic invasion across CRCs and more frequent metastasis events within CMS2 patients.
Cadherin-11 dimerization multi-site kinetics: combined partial unfolding and strand-swapping
Authors: Koss Hans , Honig Barry , Shapiro Lawrence , Palmer Arthur G
Published: December 2020

Cadherin extracellular domain 1 (EC1) mediates homophilic dimerization in adherens junctions. Conserved Trp2 and Trp4 residues in type II cadherins anchor the EC1 A-strand intermolecularly in strand-swapped dimers. Herein, NMR spectroscopy is used to elucidate the roles of Trp2 and Trp4 in Cadherin-11 dimerization. The monomeric state, with the A-strand and Trp side chains packed intramolecularly, is in equilibrium with sparsely populated partially and fully A-strand-exposed states, in which Trp2 (and Trp4, respectively) side-chain packing is disrupted. Exchange kinetics between the major state and the partially (fully) A-strand-exposed state is slow-intermediate (intermediate-fast). A separate very fast process exchanges ordered and random-coil BC loop conformations with populations dependent on A-strand exposure and dimerization status. Additionally, very slow processes connect the folded A-strand-exposed conformation to partially unfolded states, which may represent additional domain-swapping intermediates. The dimerization mechanism of type II cadherins is revealed as coupled folding and strand-swapping.
Identification of Potential Antibody Epitopes in MMP-15
Authors: Gan Jessie , Eisen Cheryl , Smider Vaughn
Published: December 2020

Monoclonal antibody therapy is a well-established cancer treatment paradigm that often targets cancers-pecific cell surface proteins. Matrix Metalloproteinase 15 (MMP-15) is a surface protein implicated in metastasis and angiogenesis, however it is not well characterized. Here we use bioinformatics tools to identify epitopes for drug or diagnostic targeting and elucidate features of this potentially important protein in metastatic processes. We identified conserved regions in MMP-15 as well as unique, variable peptide regions compared to other Membrane Type MMPs (MT-MMP). Conservation of catalytic and hemopexin domains in MMP-15 imply functional importance, however, their similarity to other MT-MMPs discourage use as target epitopes. Our analyses also identified an MMP-15 peptide that was highly divergent from other MMPs, suggesting that it may serve as an appropriate specific epitope for a specific antibody drug. Thus, we were able to elucidate features and potential unique epitopes of MMP-15 for use in further antibody discovery and targeting.
A comparative analysis of COVID-19 mortality rate across the globe: An extensive analysis of the associated factors
Authors: Jain Vineet , Nabi Nusrat , Chandra Kailash , Irshad Sana , kashyap Varun , Kohli Sunil , Gupta Arun
Published: December 2020

Background

The vast variation in COVID 19 mortality across the globe draws attention to potential risk factors other than the patient characteristics that determine COVID-19 mortality.

Subjects and Methods

We have quantified and analyzed one of the broadest set of clinical factors associated with COVID-19-related death, ranging from disease related co-morbities, socioeconomic factors, healthcare capacity and government policy and interventions. Data for population, total cases, total COVID mortality, tests done, and GDP per capita were extracted from the worldometers database. Datasets for health expenditure by government, hospital beds, rural population, prevalence of smoking, prevalence of overweight population, deaths due to communicable disease and incidence of malaria were extracted from the World Bank website. Prevalence of diabetes was retrieved from the indexmundi rankings. The average population age, 60+ population, delay in lockdown, population density and BCG data were also included for analysis. The COVID-19 mortality per million and its associated factors were retrieved for 56 countries across the globe. Quantitative analysis was done at the global as well as continent level. All the countries included in the study were categorized continent and region wise for comparative analysis determining the correlation between COVID 19 mortality and the aforementioned factors.

Results

There was significant association found between mortality per million and 60+ population of country, average age, prevalence of diabetes mellitus, and case fatality rate with correlation and p value (p) of 0.422 (p 0.009), 0.386 (p 0.0186), −0.384 (p 0.019) and 0.753 (p 0.000) respectively at 95% CI.

Conclusion

The study observations will serve as a evidence based management strategy for generating predictive model for COVID-19 infection and mortality rate.
Content analysis and characterization of medical tweets during the early Covid-19 pandemic
Authors: Prager Ross , Pratte Michael , Unni Rudy R. , Bala Sudarshan , Fat Hing Nicholas Ng , Wu Kay , McGrath Trevor A. , Thomas Adam , Thompson Laura Hilary , Hajjar Julia , Thoma Brent , Rola Philippe , Karovitch Alan , McInnes Matthew DF , Kyeremanteng Kwadwo
Published: December 2020

Objective

The novel coronavirus disease 2019 (Covid-19) has infected millions worldwide and impacted the lives of many folds more. Many clinicians share new Covid-19 related resources, research, and ideas within the online Free Open Access to Medical Education (FOAM) community of practice. This study provides a detailed content and contributor analysis of Covid-19 related tweets among the FOAM community.

Design, Setting, Participants

Twitter was searched from November 1st, 2019 to March 21st, 2020 for English tweets discussing Covid-19 in the FOAM community. Tweets were classified into one of 13 pre-specified content categories: original research, editorials, FOAM resource, public health, podcast or video, learned experience, refuting false information, policy discussion, emotional impact, blatantly false information, other Covid-19, and non-Covid-19. Further analysis of linked original research and FOAM resources was performed. 1000 randomly selected contributor profiles and those deemed to have contributed false information were analyzed.

Results

The search yielded 8541 original tweets from 4104 contributors. The number of tweets in each content category were: 1557 other Covid-19 (18·2%), 1190 emotional impact (13·9%), 1122 FOAM resources (13·1%), 1111 policy discussion (13·0%), 928 advice (10·9%), 873 learned experience (10·2%), 424 non-Covid-19 (5·0%), 410 podcast or video (4·8%), 304 editorials (3·6%), 275 original research (3·2%), 245 public health (2·9%), 83 refuting false information (1·0%), and 19 blatantly false (0·2%).

Conclusions

Early in the Covid-19 pandemic, the FOAM community used Twitter to share Covid-19 learned experiences, online resources, crowd-sourced advice, research, and to discuss the emotional impact of Covid-19. Twitter also provided a forum for post-publication peer review of new research. Sharing blatantly false information within this community was infrequent. This study highlights several potential benefits from engaging with the FOAM community on Twitter.
AF10 (MLLT10) prevents somatic cell reprogramming through regulation of DOT1L-mediated H3K79 methylation
Authors: Uğurlu-Çimen Deniz , Odluyurt Deniz , Sevinç Kenan , Özkan-Küçük Nazlı Ezgi , Özçimen Burcu , Demirtaş Deniz , Enüstün Eray , Aztekin Can , Philpott Martin , Oppermann Udo , Özlü Nurhan , Önder Tamer T.
Published: December 2020

The histone H3 lysine 79 (H3K79) methyltransferase DOT1L is a key chromatin-based barrier to somatic cell reprogramming. However, the mechanisms by which DOT1L safeguards cell identity and somatic-specific transcriptional programs remain unknown. Here, we employed a proteomic approach using proximity-based labeling to identify DOT1L-interacting proteins and investigated their effects on reprogramming. Among DOT1L interactors, suppression of AF10 (MLLT10) via RNA interference or CRISPR/Cas9, significantly increases reprogramming efficiency. In somatic cells and induced pluripotent stem cells (iPSCs) higher order H3K79 methylation is dependent on AF10 expression. In AF10 knockout cells, re-expression wildtype AF10, but not a mutant defective in DOT1L binding, rescues overall H3K79 methylation and reduces reprogramming efficiency. Transcriptomic analyses during reprogramming show that AF10 suppression results in downregulation of fibroblast-specific genes and accelerates the activation of pluripotency-associated genes. Our findings establish AF10 as a novel barrier to reprogramming by regulating H3K79 methylation and thereby sheds light on the mechanism by which cell identity is maintained in somatic cells.
Visual recognition is heralded by shifts in local field potential oscillations and inhibitory networks in primary visual cortex
Authors: Hayden Dustin J. , Montgomery Daniel P. , Cooke Samuel F. , Bear Mark F.
Published: December 2020

Learning to recognize and filter familiar, irrelevant sensory stimuli eases the computational burden on the cerebral cortex. Inhibition is a candidate mechanism in this filtration process, and oscillations in the cortical local field potential (LFP) serve as markers of the engagement of different inhibitory neurons. We show here that LFP oscillatory activity in visual cortex is profoundly altered as male and female mice learn to recognize an oriented grating stimulus—low frequency (∼15 Hz peak) power sharply increases while high frequency (∼65 Hz peak) power decreases. These changes report recognition of the familiar pattern, as they disappear when the stimulus is rotated to a novel orientation. Two-photon imaging of neuronal activity reveals that parvalbumin-expressing inhibitory neurons disengage with familiar stimuli and reactivate to novelty, whereas somatostatin-expressing inhibitory neurons show opposing activity patterns. We propose a model in which the balance of two interacting interneuron circuits shifts as novel stimuli become familiar.

Significance Statement

Habituation, familiarity and novelty detection are fundamental cognitive processes that enable organisms to adaptively filter meaningless stimuli and focus attention on potentially important elements of their environment. We have shown that this process can be studied fruitfully in the mouse primary visual cortex by using simple grating stimuli for which novelty and familiarity are defined by orientation, and by measuring stimulus-evoked and continuous local field potentials. Altered event-related and spontaneous potentials, and deficient habituation, are well-documented features of several neurodevelopmental psychiatric disorders. The paradigm described here will be valuable to interrogate the origins of these signals and the meaning of their disruption more deeply.
Foreign direct investment and economic growth. Analysis of sectoral foreign direct investment in Tanzania
Authors: Taylor Rosemary Stanley
Published: December 2020

This paper assesses the role of foreign direct investment in economic growth by analyzing the contribution of sectoral external finance in Tanzania. Time series data from 1988 to 2017 and 1999 to 2017 for the general and sector‐specific foreign finance respectively is studied using time series econometrics techniques. More specifically, the autoregressive distributive lag bound test for cointegration and error correction model are employed to evaluate the impact of sector foreign direct investment on growth. The diagnostic tests suggest that our models are free from instability, nonnormality, misspecification, heteroscedasticity, and serial correlation. Estimated long‐ and short‐term coefficients show that the effect of the primary sector foreign direct investment is positive and statistically significant at the 10% and 5% significance levels, respectively. In contrast, that of the secondary and tertiary sectors is insignificant. The coefficient of the general foreign direct investment is found to be statistically insignificant. These results confirm that the type rather than the quantity of foreign direct investment may be more relevant in explaining economic growth. Other control variables exhibit their expected signs except that of openness to trade. Based on these findings, the study recommends more and strategic foreign direct investment incentives to the primary sector.