bluuebunny/crossref_metadata_2025 huggingface dataset:
A Stochastic Compartmental Model for COVID-19
Authors: Sonnino Giorgio , Mora Fernando , Nardone Pasquale
Published: December 2020

We propose two stochastic models for the Coronavirus pandemic. The statistical properties of the models, in particular the correlation functions and the probability density function, have duly been computed. Our models, which generalises a model previously proposed and published in a specialised journal, take into account the adoption of the lockdown measures as well as the crucial role of the hospitals and Health Care Institutes. To accomplish this work we have analysed two scenarios: theSIS-model (Susceptible ⇒ Infectious ⇒ Susceptible) in presence of the lockdown measures and theSIS-model integrated with the action of the hospitals (always in presence of the lockdown measures). We show that in the case of the pureSIS-model, once the lockdown measures are removed, the Coronavirus will start growing again. However, in the second scenario, beyond a certain threshold of the hospital capacities, the Coronavirus is not only kept under control, but its capacity to spread tends to diminish in time. Therefore, the combined effect of the lockdown measures with the action of the hospitals and health Institutes is able to contain and dampen the spread of the SARS-CoV-2 epidemic. This result can be used during a period of time when the massive distribution of delivery of a limited number of vaccines in a given population is not yet feasible. By way of example, we analysed the data for USA and France where the intensities of the noise have been estimated by Statistical Mechanics. In particular, for USA we have analysed two possible hypotheses: USA is still subject to the first wave of infection by and USA is in the second (or third) wave of SARS-CoV-2 infection.The agreement between theoretical predictions and real data confirms the validity of our approach.
Household factors and the risk of severe COVID-like illness early in the US pandemic
Authors: Nash Denis , Qasmieh Saba , Robertson McKaylee , Rane Madhura , Zimba Rebecca , Kulkarni Sarah , Berry Amanda , You William , Mirzayi Chloe , Westmoreland Drew , Parcesepe Angela , Waldron Levi , Kochhar Shivani , Maroko Andrew R , Grov Christian ,   for the CHASING COVID Cohort Study Team
Published: December 2020

Objective

To investigate the role of children in the home and household crowding as risk factors for severe COVID-19 disease.

Methods

We used interview data from 6,831 U.S. adults screened for the Communities, Households and SARS/CoV-2 Epidemiology (CHASING) COVID Cohort Study in April 2020.

Results

In logistic regression models, the adjusted odds ratio [aOR] of hospitalization due to COVID-19 for having (versus not having) children in the home was 10.5 (95% CI:5.7-19.1) among study participants living in multi-unit dwellings and 2.2 (95% CI:1.2-6.5) among those living in single unit dwellings. Among participants living in multi-unit dwellings, the aOR for COVID-19 hospitalization among participants with more than 4 persons in their household (versus 1 person) was 2.5 (95% CI:1.0-6.1), and 0.8 (95% CI:0.15-4.1) among those living in single unit dwellings.

Conclusion

Early in the US SARS-CoV-2 pandemic, certain household exposures likely increased the risk of both SARS-CoV-2 acquisition and the risk of severe COVID-19 disease.
Circulating ACE2-expressing Exosomes Block SARS-CoV-2 Infection as an Innate Antiviral Mechanism
Authors: El-Shennawy Lamiaa , Hoffmann Andrew D. , Dashzeveg Nurmaa K. , Mehl Paul J. , Yu Zihao , Tokars Valerie L. , Nicolaescu Vlad , Ostiguin Carolina , Jia Yuzhi , Li Lin , Furlong Kevin , Mao Chengsheng , Wysocki Jan , Batlle Daniel , Hope Thomas J. , Shen Yang , Luo Yuan , Chae Young , Zhang Hui , Swaminathan Suchitra , Randall Glenn C. , Demonbreun Alexis R , Ison Michael G , Fang Deyu , Liu Huiping
Published: December 2020

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the coronavirus disease 2019 (COVID-19) with innate and adaptive immune response triggered in such patients by viral antigens. Both convalescent plasma and engineered high affinity human monoclonal antibodies have shown therapeutic potential to treat COVID-19. Whether additional antiviral soluble factors exist in peripheral blood remain understudied. Herein, we detected circulating exosomes that express the SARS-CoV-2 viral entry receptor angiotensin-converting enzyme 2 (ACE2) in plasma of both healthy donors and convalescent COVID-19 patients. We demonstrated that exosomal ACE2 competes with cellular ACE2 for neutralization of SARS-CoV-2 infection. ACE2-expressing (ACE2+) exosomes blocked the binding of the viral spike (S) protein RBD to ACE2+cells in a dose dependent manner, which was 400- to 700-fold more potent than that of vesicle-free recombinant human ACE2 extracellular domain protein (rhACE2). As a consequence, exosomal ACE2 prevented SARS-CoV-2 pseudotype virus tethering and infection of human host cells at a 50-150 fold higher efficacy than rhACE2. A similar antiviral activity of exosomal ACE2 was further demonstrated to block wild-type live SARS-CoV-2 infection. Of note, depletion of ACE2+exosomes from COVID-19 patient plasma impaired the ability to block SARS-CoV-2 RBD binding to host cells. Our data demonstrate that ACE2+exosomes can serve as a decoy therapeutic and a possible innate antiviral mechanism to block SARS-CoV-2 infection.
Quadratic Mutual Information estimation of mouse dLGN receptive fields reveals asymmetry between ON and OFF visual pathways
Authors: Mu Zhiguang , Nikolic Konstantin , Schultz Simon R.
Published: December 2020

The longstanding theory of “parallel processing” predicts that, except for a sign reversal, ON and OFF cells are driven by a similar pre-synaptic circuit and have similar visual field coverage, direction/orientation selectivity, visual acuity and other functional properties. However, recent experimental data challenges this view. Here we present an information theory based receptive field (RF) estimation method - quadratic mutual information (QMI) - applied to multi-electrode array electrophysiological recordings from the mouse dorsal lateral geniculate nucleus (dLGN). This estimation method provides more accurate RF estimates than the commonly used Spike-Triggered Average (STA) method, particularly in the presence of spatially correlated inputs. This improved efficiency allowed a larger number of RFs (285 vs 189 cells) to be extracted from a previously published dataset. Fitting a spatial-temporal Difference-of-Gaussians (ST-DoG) model to the RFs revealed that while the structural RF properties of ON and OFF cells are largely symmetric, there were some asymmetries apparent in the functional properties of ON and OFF visual processing streams - with OFF cells preferring higher spatial and temporal frequencies on average, and showing a greater degree of orientation selectivity.
Multi-Level Attention Graph Neural Network for Clinically Interpretable Pathway-Level Biomarkers Discovery
Authors: Xing Xiaohan , Yang Fan , Li Hang , Zhang Jun , Zhao Yu , Huang Junzhou , Meng Max Q.-H. , Yao Jianhua
Published: December 2020

Precision medicine, regarded as the future of healthcare, is gaining increasing attention these years. As an essential part of precision medicine, clinical omics have been successfully applied in disease diagnosis and prognosis using machine learning techniques. However, existing methods mainly make predictions based on gene-level individual features or their random combinations, none of the previous work has considered the activation of signaling pathways. Therefore, the model interpretability and accuracy are limited, and reasonable signaling pathways are yet to be discovered. In this paper, we propose a novel multi-level attention graph neural network (MLA-GNN), which applies weighted correlation network analysis (WGCNA) to format the omic data of each patient into graph-structured data, and then constructs multi-level graph features, and fuses them through a well-designed multi-level graph feature fully fusion (MGFFF) module to conduct multi-task prediction. Moreover, a novel full-gradient graph saliency mechanism is developed to make the MLA-GNN interpretable. MLA-GNN achieves state-of-the-art performance on transcriptomic data from TCGA-LGG/TCGA-GBM and proteomic data from COVID-19/non-COVID-19 patient sera. More importantly, the proposed model's decision can be interpreted in the signaling pathway level and is consistent with the clinical understanding.
Easy to interpret Coordinate Based Meta-Analysis of neuroimaging studies: Analysis of Brain Coordinates (ABC)
Authors: Tench CR , Tanasescu R , Constantinescu CS , Auer DP , Cottam WJ
Published: December 2020

Functional MRI and voxel-based morphometry (VBM) are important approaches to testing hypotheses in neuroscience, helping us to understand neurological disease, and brain function and development. However, they are technically challenging with no one optimal generalisable method, and the multiple popular techniques have been shown to produce different results. Furthermore, results may be sensitive to settings, such as smoothing or statistical thresholding, that can be difficult to optimise per hypothesis. It is useful, therefore, to be able to meta-analyse published results from such studies that tested a similar hypothesis potentially using different analysis methods, scanners, and protocols as well as different subjects. Coordinate based meta-analysis (CBMA) offers this using only commonly reported summary results. It is the aim of CBMA to find those results that indicate replicable effects across studies. However, just like the multiple analysis methods offered for neuroimaging, there are now multiple CBMA algorithms each with specific features and empirical parameters/assumptions. Results derived from CBMA are inevitably conditional on the algorithm used, so conclusions are clearer when the analysis approach is easy to understand. With this in mind a new CBMA method (Analysis of Brain Coordinates; ABC) is presented, with the aim of being easy to interpret by eliminating empirical assumptions where possible and by relating statistical thresholding directly to replication of effect.
A Method to Adjust a Prior Distribution in Bayesian Second-level fMRI Analysis
Authors: Han Hyemin
Published: December 2020

Previous research has shown the potential value of Bayesian methods in fMRI (functional magnetic resonance imaging) analysis. For instance, the results from Bayes factor-applied second-level fMRI analysis showed a higher hit rate compared with frequentist second-level fMRI analysis, suggesting greater sensitivity. Although the method reported more positives as a result of the higher sensitivity, it was able to maintain a reasonable level of selectivity in term of the false positive rate. Moreover, employment of the multiple comparison correction method to update the default prior distribution significantly improved the performance of Bayesian second-level fMRI analysis. However, previous studies have utilized the default prior distribution and did not consider the nature of each individual study. Thus, in the present study, a method to adjust the Cauchy prior distribution based on a priori information, which can be acquired from the results of relevant previous studies, was proposed and tested. A Cauchy prior distribution was adjusted based on the contrast, noise strength, and proportion of true positives that were estimated from a meta-analysis of relevant previous studies. In the present study, both the simulated images and real contrast images from two previous studies were used to evaluate the performance of the proposed method. The results showed that the employment of the prior adjustment method resulted in improved performance of Bayesian second-level fMRI analysis.
A functional-structural connectivity metric detects ipsilateral connections with distinct functional specialisation in each hemisphere
Authors: Civier Oren , Sourty Marion , Calamante Fernando
Published: December 2020

We introduce a connectomics metric that integrates information on structural connectivity (SC) from diffusion MRI tractography and functional connectivity (FC) from resting-state functional MRI, at individual subject level. The metric is based on the ability of SC to broadly predict FC using a simple linear predictive model; for each connection in the brain, the metric quantifies the deviation from that model. For the metric to capture underlying physiological properties, we minimise systematic measurement errors and processing biases in both SC and FC, and address several challenges with the joint analysis. This also includes a data-driven normalisation approach. The combined metric may provide new information by indirectly assessing white matter structural properties that cannot be inferred from diffusion MRI alone, and/or complex interregional neural interactions that cannot be inferred from functional MRI alone. To demonstrate the utility of the metric, we used young adult data from the Human Connectome Project to examine all bilateral pairs of ipsilateral connections, i.e. each left-hemisphere connection in the brain was paired with its right-hemisphere homologue. We detected a minority of bilateral pairs where the metric value is significantly different across hemispheres, which we suggest reflects cases of ipsilateral connections that have distinct functional specialisation in each hemisphere. The pairs with significant effects spanned all cortical lobes, and also included several cortico-subcortical connections. Our findings highlight the potential in a joint analysis of structural and functional measures of connectivity, both for clinical applications and to help in the interpretation of results from standard functional connectivity analysis.

Significance Statement

Based on the notion that structure predicts function, the scientific community sought to demonstrate that structural information on fibre bundles that connect brain regions is sufficient to estimate the strength of interregional interactions. However, an accurate prediction using MRI has proved elusive. This paper posits that the failure to predict function from structure originates from limitations in measurement or interpretation of either diffusion MRI (to assess fibre bundles), fMRI (to assess functional interactions), or both. We show that these limitations can be nevertheless beneficial, as the extent of divergence between the two modalities may reflect hard-to-measure properties of interregional connections, such as their functional role in the brain. This provides many insights, including into the division of labour between hemispheres.
Deep-Learning-Based Multivariate Pattern Analysis (dMVPA): A Tutorial and a Toolbox
Authors: Kuntzelman Karl M. , Williams Jacob M. , Lim Phui Cheng , Samal Ashok , Rao Prahalada K. , Johnson Matthew R.
Published: December 2020

In recent years, multivariate pattern analysis (MVPA) has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and other neuroimaging methodologies. In a similar time frame, “deep learning” (a term for the use of artificial neural networks with convolutional, recurrent, or similarly sophisticated architectures) has produced a parallel revolution in the field of machine learning and has been employed across a wide variety of applications. Traditional MVPA also uses a form of machine learning, but most commonly with much simpler techniques based on linear calculations; a number of studies have applied deep learning techniques to neuroimaging data, but we believe that those have barely scratched the surface of the potential deep learning holds for the field. In this paper, we provide a brief introduction to deep learning for those new to the technique, explore the logistical pros and cons of using deep learning to analyze neuroimaging data – which we term “deep MVPA,” or dMVPA – and introduce a new software toolbox (the “Deep Learning In Neuroimaging: Exploration, Analysis, Tools, and Education” package, DeLINEATE for short) intended to facilitate dMVPA for neuroscientists (and indeed, scientists more broadly) everywhere.
Accessible Analysis of Longitudinal Data with Linear Mixed Effects Models
Authors: Murphy Jessica I. , Weaver Nicholas E. , Hendricks Audrey E.
Published: December 2020

Longitudinal mouse models are commonly used to study possible causal factors associated with human health and disease. However, the statistical models, such as two-way ANOVA, often applied in these studies do not appropriately model the experimental design, resulting in biased and imprecise results. Here, we describe the linear mixed effects (LME) model and how to use it for longitudinal mice studies. We re-analyze a dataset published by Blanton et al (Science 2016) that modeled mice growth trajectories after microbiome implantation from nourished or malnourished children. We compare the fit and stability of different parameterizations of ANOVA and LME models; most models found the nourished vs. malnourished growth trajectories differed significantly. We show through simulation that the results from the two-way ANOVA and LME models are not always consistent. Incorrectly modeling correlated data can result in increased rates of false positives or false negatives, supporting the need to model correlated data correctly. We provide an interactive Shiny App to enable accessible and appropriate analysis of longitudinal data using LME models.
In vivo Evaluation and in silico Prediction of the Toxicity of Drepanoalpha Hard capsules
Authors: Gbolo Zoawe Benjamin , Ngbolua Koto-te-Nyiwa Jean-Paul , Tshibangu Sha-Tshibey Damien , Memvanga Bondo Patrick , Tshilanda Dinangayi Dorothee , Matondo Aristote , Kilembe Thambwe Jason , Lebwaze Masamba Bienvenu , Nachtergael Amandine , Mpiana Tshimankinda Pius , Duez Pierre
Published: December 2020

Drepanoalpha® hard capsules, a dry ethanolic extract (drug-extract ratio, 100/11) of a mixture of Justicia secunda Vahl and Moringa oleifera Lam dried leaves (1: 1, w/w) are used for the management of sickle cell disease in the Democratic Republic of Congo. Aim of the study: This phytomedicine safety was investigated by acute and sub-acute administration in Guinea pigs. Materials and methods: Healthy, male and nulliparous and non-pregnant female Guinea pigs were obtained from Laboratory of Animal Experimentation and Toxicology of the Department of Biology, Faculty of Sciences, University of Kinshasa. The animals were randomly selected, marked and divided into 2 groups of 5 animals each (3 males and 2 females) and 4 groups of 3 animals each for acute and sub-acute toxicity studies, respectively. The contents of hard capsules were dissolved in normal saline solution (NaCl 0.9 %). Animals received by gavage a single dose of 5000 mg/ kg of body weight (B.W.) of Drepanoalpha® hard capsules (acute toxicity) and 125 mg/ kg, 250 mg/ kg and 500 mg/ kg of B.W. twice daily for 28 days (sub-acute toxicity). Normal saline solution was used as control. Hematological, biochemical and histopathological analyses were performed and the behavior of the animals was observed after treatment. Results: The median lethal dose (LD50) is higher than 5000 mg/ kg of B.W., and the relative weights of vital organs (kidneys, liver and heart) collected from Guinea pigs at the end of treatment on D14 (acute toxicity) and D28 (sub-acute toxicity) has not undergone significant changes (p > 0.05). The results of haematological (red and white blood cells counts, haemoglobin, haematocrit) and biochemical (ALT, AST, albumin, total protein) tests did not show significant differences between control and test groups (α=0.05 for acute toxicity), while the histopathological study revealed no damage to the various organs excised. Conclusion: The results indicate the safety of Drepanoalpha® hard capsules, confirming previous studies, in rats and Guinea pigs, based on aqueous decoction of its raw herbs mixtures and the corresponding lyophilizate. Keywords: Acute toxicity, Sub-acute toxicity, Drepanoalpha® hard capsules
AStreptococcusquorum sensing system enables suppression of innate immunity
Authors: Rahbari Kate , Chang Jennifer , Federle Michael
Published: December 2020

Some bacterial pathogens utilize cell-cell communication systems, such as quorum sensing (QS), to coordinate genetic programs during host colonization and infection. The human-restricted pathosymbiontStreptococcus pyogenes(Group A Streptococcus, GAS) uses the Rgg2/Rgg3 QS system to modify the bacterial surface, enabling biofilm formation and lysozyme resistance. Here, we demonstrate that innate immune cell responses to GAS are substantially altered by the QS status of the bacteria. We found that macrophage activation, stimulated by multiple agonists and assessed by cytokine production and NFκB activity, was substantially suppressed upon interaction with QS-active GAS but not QS-inactive bacteria. Neither macrophage viability nor bacterial adherence were seen as different between QS activity states, yet TNFα, IL-6, and IFNβ levels and NFκB reporter activity were drastically lower following infection with QS-active GAS. Suppression required contact between viable bacteria and macrophages. A QS-regulated biosynthetic gene cluster (BGC) in the GAS genome, encoding several putative enzymes, was also required for macrophage modulation. Our findings suggest a model wherein upon contact with macrophages, QS-active GAS produce a BGC-derived factor capable of suppressing inflammatory responses. The suppressive capability of QS-active GAS is abolished after treatment with a specific QS inhibitor. These observations suggest that interfering with the ability of bacteria to collaborate via QS can serve as a strategy to counteract microbial efforts to manipulate host defenses.

Importance

Streptococcus pyogenesis restricted to human hosts and commonly causes superficial diseases such as pharyngitis; it can also cause severe and deadly manifestations including necrotizing skin disease or severe post-infectious sequelae like rheumatic heart disease. Understanding the complex mechanisms used by this pathogen to manipulate host defenses could aid in developing new therapeutics to treat infections. Here, we examine the impact of a bacterial cell-cell communication system, which is highly conserved acrossS. pyogenes, on host innate immune responses. We find thatS. pyogenesuses this system to suppress macrophage pro-inflammatory cytokine responses. Interference with this communication system could serve as a strategy to disarm bacteria and maintain an effective immune response.
Insulinase like protease 1 contributes to macrogamont formation inCryptosporidium parvum
Authors: Xu Rui , Feng Yaoyu , Xiao Lihua , Sibley L. David
Published: December 2020

The apicomplexan parasiteCryptosporidium parvumcontains an expanded family of 22 insulinase like proteases (INS), a feature that contrasts with their otherwise streamlined genome. Here we examined the function of INS1, which is most similar to the human insulinase protease that cleaves a variety of small peptide substrates. INS1 is a M16A clan member and contains a signal peptide, an N-terminal domain with the HxxEH active site, followed by three inactive domains. Unlike previously studiedC. parvumINS proteins that are expressed in sporozoites and during merogony, INS1 was expressed exclusively in macrogamonts, where it was localized in small cytoplasmic vesicles. Although INS1 did not colocalize with the oocyst wall protein recognized by the antibody OW50, immune-electron microscopy indicated that INS1 resides in small vesicles in the secretory system. Notably, these small INS1 positive vesicles often subtend large vacuoles resembling wall forming bodies, which contain precursors for oocyst wall formation. Genetic deletion of INS1, or replacement with an active site mutant, resulted in lower formation of macrogamontsin vitroand reduced oocyst sheddingin vivo. Our findings reveal that INS1 functions in formation or maturation of macrogamonts and that its loss results in attenuated virulence in immunocompromised mice.

Importance

Cryptosporidiosis is a debilitating diarrheal disease in young children in developing countries. Absence of effective treatments or vaccines makes this infection very difficult to manage in susceptible populations. Although the oral dose of oocysts needed to cause infection is low, infected individuals shed very high numbers of oocysts, hence readily contaminating the environment. Our studies demonstrate that the protease INS1 is important for formation of female sexual stages and that in its absence, parasites produce fewer oocysts and are attenuated in immunocompromised mice. These findings suggest that mutants lacking INS1, or related proteases, may be useful for producing attenuated vaccines to induce immunity without causing disease.
Development and optimization of a new method for direct extraction of SARS-CoV-2 RNA from municipal wastewater using magnetic beads
Authors: Parra Guardado Ana L. , Sweeney Crystal L. , Hayes Emalie , Trueman Benjamin F. , Huang Yannan , Jamieson Rob C. , Rand Jennie L. , Gagnon Graham A. , Stoddart Amina K.
Published: December 2020

The use of magnetic beads in the extraction of nucleic acids from wastewater is presented as an approach to simplify extraction techniques for the detection of SARS-CoV-2 viral fragments in wastewater. In particular, this paper describes the development and optimization of a direct method for extracting SARS-CoV-2 RNA from municipal wastewater using magnetic beads. The recovery efficiency of the method using Accuplex SARS-CoV-2 Positive Reference Material (ASCV-2) was examined. Method factors assessed were sample volume, concentration of magnetic bead mix, elution temperature, and water matrix (deionized (DI) water and wastewater). The combination of optimized method parameters that resulted in the highest RNA recovery in both DI water (26.0 ± 0.8%) and wastewater (11.8 ± 1.4%) was a sample volume of 1.0 mL, a magnetic beads concentration of 100 µL mL-1 sample, and an elution temperature of 60 °C. The performance of this optimized method was further assessed in recovery experiments using wastewater samples spiked at 1.8×106 and 1.8×104 gene copies L-1 (GU L-1) with Gamma Inactivated SARS-COV-2 (GI-SCV-2) and 1.0×106 and 1.0×104 infectious units L-1 of Human Coronavirus 229E (HCV 229E) as viral surrogates. Recoveries of 86.1 and 4.6% were achieved for wastewater samples spiked with GI-SCV-2 at low and high concentrations, respectively. In assessing the effects of wastewater pre-filtration and addition of DL-Dithiothreitol (DTT, used to inactivate RNases that may degrade RNA) on recovery efficiency of ASCV-2, the magnetic bead-based extraction protocol performed optimally with unfiltered wastewater without DTT (recovery = 17.4 ± 0.4%). The method limit of detection (MLOD) for ASCV-2 recovered from pre-filtered wastewater was determined to be 4.6×104 GU L-1 (95% degree of confidence). Using this optimized magnetic bead-based extraction protocol, the presence of SARS-CoV-2 RNA was verified in wastewater collected from sewershed locations in Atlantic Canada. This emerging RNA extraction method is direct, rapid, and does not require the use of specialized equipment, thus offering advantageous application for laboratories with limited resources. As such, this method is an indispensable tool in the monitoring of wastewater for SARS-CoV-2 to potentially understand COVID-19 infection occurrence within communities and inform public health leaders.

Graphical Abstract
Initial vancomycin versus metronidazole for the treatment of first-episode non-severe Clostridioides difficile infection
Authors: Zhang Kevin , Beckett Patricia , Abouanaser Salaheddin , Smieja Marek
Published: December 2020

Objective

Clostridioides difficile infection (CDI) is the leading cause of infectious nosocomial diarrhea. Although initial fidaxomicin or vancomycin treatment is recommended by most major guidelines to treat severe CDI, there exists varied recommendations for first-episode non-severe CDI. Given the discrepancy in current treatment guidelines, we sought to evaluate the use of initial vancomycin versus metronidazole for first-episode non-severe CDI.

Methods

We conducted a retrospective cohort study of all adult inpatients with first-episode CDI at our institution from January 2013 to May 2018. The initial vancomycin versus initial metronidazole cohorts were examined using a multivariate logistic regression model.

Results

Patients (n = 737) had a median age of 72.3 years and 357 (48.4%) had hospital-acquired infection. Among patients with non-severe CDI (n = 326), recurrence, new incident infection, and 30-day mortality rates were 16.2%, 10.9%, and 5.3%, respectively, when treated with initial metronidazole, compared to 20.0%, 1.4%, and 10.0%, respectively, when treated with initial vancomycin. In an adjusted multivariable analysis, the use of initial vancomycin for the treatment of non-severe CDI was associated with a reduction in new incident infection (ORadj: 0.11; 95% CI: 0.02–0.86; P=0.035), compared to initial metronidazole.

Conclusions

Initial vancomycin was associated with a reduced rate of new incident infection in the treatment of adult inpatients with first-episode non-severe CDI. These findings support the use of initial vancomycin for all inpatients with CDI, when fidaxomicin is unavailable.
Correction of human forehead temperature variations measured by non-contact infrared thermometer
Authors: Shajkofci Adrian
Published: December 2020

Elevated body temperature (fever) can be a common symptom of a medical condition, such as a viral or bacterial infection, including SARS-CoV-2 or influenza. Non-contact infrared thermometers are able to measure forehead temperature in a timely manner and were used to perform a fast fever screening in a population. However, forehead temperature measurements differ greatly from basal body temperatures, and are the target of massive perturbations from the environment. Here we gathered a dataset of N=18024 measurements using the same precision infrared sensor in different locations while tracking both outside temperature, room temperature, time of measurement, and identity. Herein, we propose a method able to extract and remove the influence of external perturbations and set the threshold for fever based on local statistics to 37.38 °C, after calibration and temperature correction. This method can help manufacturers and decision-makers to build and use more accurate tools so as to maximize both sensitivity and specificity of the screening protocol.

Abstract Figure
The influence of body side and sex on neck muscle responses to left-frontal-oblique impacts
Authors: Mühlbeier Andreas , Boström Kim Joris , de Lussanet Marc H. E. , Kalthoff Wolfram , Kraaijenbrink Cassandra , Hagenfeld Lena , Natrup Jens , Castro William H. M. , Wagner Heiko
Published: December 2020

Low-velocity motor vehicle crashes frequently induce chronic neck disorders also referred to as whiplash-associated disorders (WAD). The etiology of WAD is still not fully understood. Women are affected more often and more severely than men. A frontal-oblique collision direction leads to WAD relatively frequently, but is poorly investigated as compared to rear-end or frontal collision directions. An oblique impact direction is assumed to strain the contralateral neck side more than the ipsilateral side, provoking an asymmetrical response pattern of the left and right cervical muscles. In this study, we examined the muscle reflex responses of the sternocleidomastoid, the paraspinal, and the trapezius muscles as well as the kinematic responses of 60 subjects during left-frontal-oblique collisions. Neither the reflex delay nor the peak head acceleration revealed significant sex differences. Thus, the elsewhere reported higher injury risk of females as compared to males cannot be explained by the electromyographic and kinematic results of this study. In females as well as in males the right muscle responses revealed shorter onset times than the left muscle responses. Thus, cervical muscles seem to be activated depending on the specific direction of the impact. Moreover, the difference between right and left muscle responses cannot be explained by a startle reflex. The movement of the head in relation to the torso (female mean ± SD: 92 ± 16 ms; male: 87 ± 16 ms) started almost simultaneously to the onset of the first muscle activation (right paraspinal muscles: female mean: 95 ms and 95%-CI 82 − 109; male mean: 95 ms and 95%-CI 84 − 108) indicating that the initial muscle activity seems not to be triggered by a stretch reflex in the PARA muscles.
Nectar non-protein amino acids (NPAAs) do not change nectar palatability but enhance learning and memory in honey bees
Authors: Carlesso Daniele , Smargiassi Stefania , Pasquini Elisa , Bertelli Giacomo , Baracchi David
Published: December 2020

Floral nectar is a pivotal element of the intimate relationship between plants and pollinators and its chemical composition is likely to have been shaped by strong selective pressures. Nectars are composed of a plethora of nutritionally valuable compounds but also hundreds of secondary metabolites (SMs) whose ecological role is still not completely understood. Here we performed a set of behavioural experiments to study whether five ubiquitous nectar non-protein amino acids (NPAAs: β-alanine, GABA, citrulline, ornithine and taurine) interact with gustation, feeding preference, and learning and memory in the pollinatorApis mellifera. We showed that harnessed foragers were unable to discriminate NPAAs from water when only accessing antennal chemo-tactile information and that freely moving bees did not exhibit innate feeding preferences for NPAA-laced sucrose solutions. Also, dietary consumption of NPAAs did not alter food consumption or longevity in caged bees over 10 days. Taken together our data suggest that ecologically relevant concentrations of NPAAs did not alter nectar palatability to bees. Olfactory conditioning assays showed that honey bees were more likely to learn a scent when it signalled a sucrose reward containing either β-alanine or GABA, and that GABA also enhanced specific memory retention. Conversely, when ingested two hours prior to conditioning, GABA, β-alanine, and taurine weakened bees’ acquisition performances but not specific memory retention, which was enhanced in the case of β-alanine and taurine. Neither citrulline nor ornithine affected learning and memory. Our study suggests that NPAAs in nectars may represent a cooperative strategy adopted by plants to attract beneficial pollinators, while simultaneously enhancing pollen transfer among conspecific flowers. Future work should validate these results in more ecological scenarios and extend the study to as many nectar SMs as possible, alone and in combination, as well as to other species of pollinators.
Machine Learning-Assisted Directed Evolution Navigates a Combinatorial Epistatic Fitness Landscape with Minimal Screening Burden
Authors: Wittmann Bruce J. , Yue Yisong , Arnold Frances H.
Published: December 2020

Due to screening limitations, in directed evolution (DE) of proteins it is rarely feasible to fully evaluate combinatorial mutant libraries made by mutagenesis at multiple sites. Instead, DE often involves a single-step greedy optimization in which the mutation in the highest-fitness variant identified in each round of single-site mutagenesis is fixed. However, because the effects of a mutation can depend on the presence or absence of other mutations, the efficiency and effectiveness of a single-step greedy walk is influenced by both the starting variant and the order in which beneficial mutations are identified—the process is path-dependent. We recently demonstrated a path-independent machine learning-assisted approach to directed evolution (MLDE) that allowsin silicoscreening of full combinatorial libraries made by simultaneous saturation mutagenesis, thus explicitly capturing the effects of cooperative mutations and bypassing the path-dependence that can limit greedy optimization. Here, we thoroughly investigate and optimize an MLDE workflow by testing a number of design considerations of the MLDE pipeline. Specifically, we (1) test the effects of different encoding strategies on MLDE efficiency, (2) integrate new models and a training procedure more amenable to protein engineering tasks, and (3) incorporate training set design strategies to avoid information-poor low-fitness protein variants (“holes”) in the training data. When applied to an epistatic, hole-filled, four-site combinatorial fitness landscape of protein G domain B1 (GB1), the resulting focused training MLDE (ftMLDE) protocol achieved the global fitness maximum up to 92% of the time at a total screening burden of 470 variants. In contrast, minimal-screening-burden single-step greedy optimization over the GB1 fitness landscape reached the global maximum just 1.2% of the time; ftMLDE matching this minimal screening burden (80 total variants) achieved the global optimum up to 9.6% of the time with a 49% higher expected maximum fitness achieved. To facilitate further development of MLDE, we present the MLDE software package (https://github.com/fhalab/MLDE), which is designed for use by protein engineers without computational or machine learning expertise.
Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin
Authors: Kaplow Irene M. , Schäffer Daniel E. , Wirthlin Morgan E. , Lawler Alyssa J. , Brown Ashley R. , Kleyman Michael , Pfenning Andreas R.
Published: December 2020

Background

Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation at many enhancers, distal regulatory elements that control spatio-temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific, code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.

Results

We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that is able to predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Then, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity and liver enhancers associated with liver regeneration have a stronger tendency than the general population to have predicted lineage-specific open chromatin.

Conclusion

The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.
Non-canonical H3K79me2-dependent pathways promote the survival of MLL-rearranged leukemia
Authors: Richter William F. , Shah Rohan N. , Ruthenburg Alexander J.
Published: December 2020

MLL-rearranged leukemia depends on H3K79 methylation. Depletion of this transcriptionally-activating mark by DOT1L deletion or high concentrations of the inhibitor pinometostat downregulatesHOXA9andMEIS1, and consequently reduces leukemia survival. Yet some MLL-rearranged leukemias are inexplicably susceptible to low-dose pinometostat, far below concentrations that downregulate this canonical proliferation pathway. In this context, we define alternative proliferation pathways that more directly derive from H3K79me2 loss. By ICeChIP-seq, H3K79me2 is markedly depleted at pinometostat-downregulated and MLL-fusion targets, with paradoxical increases of H3K4me3 and loss of H3K27me3. Although downregulation of polycomb components accounts for some of the proliferation defect, transcriptional downregulation of FLT3 is the major pathway. Loss-of-FLT3-function recapitulates the cytotoxicity and gene expression consequences of low-dose pinometostat, whereas overexpression of constitutively activeSTAT5A, a target of FLT3-ITD-signalling, largely rescues these defects. This pathway also depends on MLL1, indicating combinations of DOT1L, MLL1 and FLT3 inhibitors should be explored for treatingFLT3-mutant leukemia.
Quality of life and depressive symptoms among Peruvian university students during the COVID-19 pandemic
Authors: Figueroa-Quiñones Joel , Ipanaqué-Zapata Miguel , Machay-Pak Daniel , Rodríguez-Ruiz Juan
Published: December 2020

Objectives

Characterize the quality of life and depressive symptoms of university students in Peru during the COVID-19 pandemic and to determine the associated factors.

Methods

Multi-centre study in 1634 university students recruited by convenience sampling. Quality of life (QoL) was assessed with the European Quality of Life-5 Dimensions at three levels (EQ-5D-3L) and depressive symptoms with the Patient Health Questionarie-9 (PHQ-9). To evaluate factors associated with QoL and depressive symptoms, linear and adjusted regressions were used, with robust variance reporting coefficients (β).

Results

The percentage of participants most affected by QoL dimension was: anxiety/depression (47.2%) and pain/discomfort (35.6%). Regarding the Visual Analog Scale (EQ-VAS) of QoL, the score was 76.0 + 25.6. Those who had family economic decline during quarantine (β=-3.4, IC95%=-6.5 to −0.3) or family with chronic diseases (β=-3.7, IC95%=-6.1 to −1.4) presented significantly lower scores in their QoL. Regarding depressive symptomatology, the university students reported a moderate to severe level (28.9%). A higher risk of depressive symptoms was found in residents of Ayacucho (β=0.8, IC95%=0.1 to 1.5), those who were released from quarantine (β=0.7, IC95%=0.2 to 1.2) and those who had a family member with chronic disease (β=1.5, IC95%=1.0 to 2.1).

Conclusions

Almost half and one third of participants reported anxiety/depression, and pain/discomfort in their QoL respectively. Nearly a third presented moderate and severe depressive symptoms. The deterioration of QoL was worse in those who had a decrease in income and a family member with chronic illness. The presence of depressive symptoms was found in students in Ayacucho, those who left home during quarantine and those who had a family member with chronic diseases.
Effect of belt electrode-skeletal muscle electrical stimulation on immobilization-induced muscle fibrosis
Authors: Honda Yuichiro , Tanaka Natsumi , Kajiwara Yasuhiro , Kondo Yasutaka , Kataoka Hideki , Sakamoto Junya , Akimoto Ryuji , Nawata Atsushi , Okita Minoru
Published: December 2020

Purpose

Macrophage accumulation in response to decreasing myonuclei may be the major mechanism underlying immobilization-induced muscle fibrosis in muscle contracture, an intervention strategy suppressing these lesions is necessary. Therefore, this research investigated the effect of belt electrode-skeletal muscle electrical stimulation (B-SES), a new electrical stimulation device, to the macrophage accumulation via myonuclei decrease in immobilization-induced muscle fibrosis.

Materials and Methods

18 Wistar male rats were divided into the control group, immobilization group (with plaster cast fixation to immobilize the soleus muscles in a shortened position for 2 weeks), and B-SES group (with muscle contractile exercise through B-SES during the immobilization period). B-SES stimulation was performed at a frequency of 50 Hz and an intensity of 4.7 mA, muscle contractile exercise by B-SES was applied to the lower limb muscles for 20 minutes/session (twice a day) for 2 weeks (6 times/week). The bilateral soleus muscles were used for histological, immunohistochemical, biochemical, and molecular biological analyses.

Results

The number of myonuclei was significantly higher in the B-SES group than in the immobilization group, and there was no significant difference between the B-SES and control groups. The cross-sectional area of type I and II myofibers in the immobilization and B-SES groups was significantly lower than that in the control group, and the cross-sectional area of type I myofibers in the B-SES group was higher than that in the immobilization group. However, Atrogin-1 and MuRF-1 mRNA expression in the immobilization and B-SES groups was significantly higher than those in the control group. Additionally, the number of macrophages, IL-1β, TGF-β1, and α-SMA mRNA expression, and hydroxyproline expression was significantly lower in the control and B-SES groups than those in the immobilization group.

Conclusion

This research surmised that muscle contractile exercise through B-SES prevented immobilization-induced muscle fibrosis, and this alteration suppressed the development of muscle contracture.
CFPU: a cell-free processing unit for high-throughput, automated in vitro circuit characterization
Authors: Swank Zoe , Maerkl Sebastian J.
Published: December 2020

Forward engineering synthetic circuits is at the core of synthetic biology. Automated solutions will be required to facilitate circuit design and implementation. Circuit design is increasingly being automated with design software, but innovations in experimental automation are lagging behind. Microfluidic technologies made it possible to performin vitrotranscription-translation (tx-tl) reactions with increasing throughput and sophistication, enabling screening and characterization of individual circuit elements and complete circuit designs. Here we developed an automated microfluidic cell-free processing unit (CFPU) that extends high-throughput screening capabilities to a continuous reaction environment, which is essential for the implementation and analysis of more complex and dynamic circuits. The CFPU contains 280 chemostats that can be individually programmed with DNA circuits. Each chemostat is periodically supplied with tx-tl reagents, giving rise to sustained, long-term steady state conditions. Using microfluidic pulse width modulation (PWM) the device is able to generate tx-tl reagent compositions in real-time. The device has higher throughput, lower reagent consumption, and overall higher functionality than current chemostat devices. We applied this technology to map transcription factor based repression under equilibrium conditions and implemented dynamic gene circuits switchable by small molecules. We expect the CFPU to help bridge the gap between circuit design and experimental automation forin vitrodevelopment of synthetic gene circuits.