bluuebunny/crossref_metadata_2025 huggingface dataset:
0393 The Effect of Trazadone Use on Non-REM Sleep Instability in Community-Dwelling Older Men
Authors: Hartmann S , Baumert M
Published: May 2020

Introduction

With steadily growing numbers of patients with a depressive disorder, the effect of antidepressants on sleep architecture is of increasing concern. One major oral antidepressant medication is trazadone, which has also been prescribed in low doses for sleep insomnia treatment. Here, we investigate the effect of trazadone on NREM sleep instability also known as cyclic alternating pattern (CAP) in community-dwelling older men.

Methods

CAP was scored in overnight EEG recordings from 41 older men on trazadone (TRZ) and 50 age-matched men who did not use trazadone (NTRZ), participating in the Osteoporotic Fractures in Men Sleep Study. A high performance automated detection system determined the ratio between CAP time and NREM sleep time (CAP rate), the number of A1-phases per hour of NREM sleep (A1 index), and the number of A2+A3-phases per hour of NREM sleep (A2+A3 index). The effect of TRZ on CAP parameters was determined using the Mann-Whitney U test.

Results

CAP rate was significantly decreased in men using trazadone (NTRZ: 58.2±19.7%, TRZ: 47.9±15.9%) as compared to non-trazadone user (p < 0.01). Subtype indices did not show any significant difference between both groups but to some extent less frequent A2-A3 phases for TRZ user (A1-phases: NTRZ 13.0±18.7 no./h vs. TRZ 10.8±20.4 no./h, p = 0.35; A2+A3-phases: NTRZ 51.5±33.7 no./h vs. TRZ 44.7±23.3 no./h, p = 0.068).

Conclusion

CAP rate was significantly decreased in older men on trazadone as compared to older men who did not use trazadone, suggesting that trazadone usage has a stabilising effect on sleep micro-structure.

Support

The National Heart, Lung, and Blood Institute (NHLBI) provides funding for the MrOS Sleep ancillary study “Outcomes of Sleep Disorders in Older Men” under the following grant numbers: R01 HL071194, R01 HL070848, R01 HL070847, R01 HL070842, R01 HL070841, R01 HL070837, R01 HL070838, and R01 HL070839.
0834 Different Neural Circuits Were Associated With Different Parts of Relationships Among Sleep, Pain and Anxiety in Women with Primary Dysmenorrhoea
Authors: Chein K , Wei S , Hung C , Tu C , Hsieh J
Published: May 2020

Introduction

Although the relationships amongst sleep, pain and anxiety have been evidenced, the underlying neurological mechanisms remain elusive. Primary dysmenorrhea is a good model of spontaneous pain with clear painful (menstruation, state) and pain free (e.g., peri-ovulatory phase, trait) conditions. We sought to investigate the state- and trait-related neural signatures that link sleep and anxiety in primary dysmenorrhea.

Methods

Thirty female subjects with primary dysmenorrhea and 30 healthy female controls completed resting-state functional magnetic resonance imaging, the State-Trait Anxiety Inventory and sleep quality assessments during menstruation and peri-ovulatory phases. As we have reported that there was altered default mode network in the primary dysmenorrhea, posterior parietal cortex (PPC) was therefore chosen as the seed to elucidate the functional connectivity that may correlate with sleep and anxiety.

Results

The primary dysmenorrheic subjects exhibited sleep disturbances throughout the menstrual cycle with increased state anxiety. The primary dysmenorrheic subjects demonstrated significantly higher correlations between the sleep quality and the PPC-insula and -putamen functional connectivity during the peri-ovulatory phase. During menstruation, the primary dysmenorrheic subjects demonstrated significantly lower correlations between their state-anxiety scores and the PPC-occipital cortex functional connectivity.

Conclusion

After regressing out the effects of trait anxiety, the correlation between sleep quality and the PPC-putamen functional connectivity was not significant, indicating anxiety-mediated sleep-pain relationship. The PPC-insula functional connectivity, by contrast, was remained significant. Furthermore, state anxiety was associated with the PPC-occipital cortex functional connectivity that was significantly impaired in primary dysmenorrheic subjects. These findings hinted pain and anxiety mediating sleep quality in different neurological circuits.

Support

Taipei City Goverment(10401-62-046 and 10501-62-046)
Predicting left ventricular contractile function via Gaussian process emulation in aortic-banded rats
Authors: Longobardi S. , Lewalle A. , Coveney S. , Sjaastad I. , Espe E. K. S. , Louch W. E. , Musante C. J. , Sher A. , Niederer S. A.
Published: May 2020

Cardiac contraction is the result of integrated cellular, tissue and organ function. Biophysical
in silico
cardiac models offer a systematic approach for studying these multi-scale interactions. The computational cost of such models is high, due to their multi-parametric and nonlinear nature. This has so far made it difficult to perform model fitting and prevented global sensitivity analysis (GSA) studies. We propose a machine learning approach based on Gaussian process emulation of model simulations using probabilistic surrogate models, which enables model parameter inference via a Bayesian history matching (HM) technique and GSA on whole-organ mechanics. This framework is applied to model healthy and aortic-banded hypertensive rats, a commonly used animal model of heart failure disease. The obtained probabilistic surrogate models accurately predicted the left ventricular pump function (
R
2
 = 0.92 for ejection fraction). The HM technique allowed us to fit both the control and diseased virtual bi-ventricular rat heart models to magnetic resonance imaging and literature data, with model outputs from the constrained parameter space falling within 2 SD of the respective experimental values. The GSA identified Troponin C and cross-bridge kinetics as key parameters in determining both systolic and diastolic ventricular function.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Quantification of model and data uncertainty in a network analysis of cardiac myocyte mechanosignalling
Authors: Cao Shulin , Aboelkassem Yasser , Wang Ariel , Valdez-Jasso Daniela , Saucerman Jeffrey J. , Omens Jeffrey H. , McCulloch Andrew D.
Published: May 2020

Cardiac myocytes transduce changes in mechanical loading into cellular responses via interacting cell signalling pathways. We previously reported a logic-based ordinary differential equation model of the myocyte mechanosignalling network that correctly predicts 78% of independent experimental results not used to formulate the original model. Here, we use Monte Carlo and polynomial chaos expansion simulations to examine the effects of uncertainty in parameter values, model logic and experimental validation data on the assessed accuracy of that model. The prediction accuracy of the model was robust to parameter changes over a wide range being least sensitive to uncertainty in time constants and most affected by uncertainty in reaction weights. Quantifying epistemic uncertainty in the reaction logic of the model showed that while replacing ‘OR’ with ‘AND’ reactions greatly reduced model accuracy, replacing ‘AND’ with ‘OR’ reactions was more likely to maintain or even improve accuracy. Finally, data uncertainty had a modest effect on assessment of model accuracy.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Quantification of uncertainty in a new network model of pulmonary arterial adventitial fibroblast pro-fibrotic signalling
Authors: Wang Ariel , Cao Shulin , Aboelkassem Yasser , Valdez-Jasso Daniela
Published: May 2020

Here, we present a novel network model of the pulmonary arterial adventitial fibroblast (PAAF) that represents seven signalling pathways, confirmed to be important in pulmonary arterial fibrosis, as 92 reactions and 64 state variables. Without optimizing parameters, the model correctly predicted 80% of 39 results of input–output and inhibition experiments reported in 20 independent papers not used to formulate the original network. Parameter uncertainty quantification (UQ) showed that this measure of model accuracy is robust to changes in input weights and half-maximal activation levels (EC
50
), but is more affected by uncertainty in the Hill coefficient (
n
), which governs the biochemical cooperativity or steepness of the sigmoidal activation function of each state variable. Epistemic uncertainty in model structure, due to the reliance of some network components and interactions on experiments using non-PAAF cell types, suggested that this source of uncertainty had a smaller impact on model accuracy than the alternative of reducing the network to only those interactions reported in PAAFs. UQ highlighted model parameters that can be optimized to improve prediction accuracy and network modules where there is the greatest need for new experiments.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Reducing complexity and unidentifiability when modelling human atrial cells
Authors: Houston C. , Marchand B. , Engelbert L. , Cantwell C. D.
Published: May 2020

Mathematical models of a cellular action potential (AP) in cardiac modelling have become increasingly complex, particularly in gating kinetics, which control the opening and closing of individual ion channel currents. As cardiac models advance towards use in personalized medicine to inform clinical decision-making, it is critical to understand the uncertainty hidden in parameter estimates from their calibration to experimental data. This study applies approximate Bayesian computation to re-calibrate the gating kinetics of four ion channels in two existing human atrial cell models to their original datasets, providing a measure of uncertainty and indication of potential issues with selecting a single unique value given the available experimental data. Two approaches are investigated to reduce the uncertainty present: re-calibrating the models to a more complete dataset and using a less complex formulation with fewer parameters to constrain. The re-calibrated models are inserted back into the full cell model to study the overall effect on the AP. The use of more complete datasets does not eliminate uncertainty present in parameter estimates. The less complex model, particularly for the fast sodium current, gave a better fit to experimental data alongside lower parameter uncertainty and improved computational speed.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Variability in electrophysiological properties and conducting obstacles controls re-entry risk in heterogeneous ischaemic tissue
Authors: Lawson Brodie A. J. , Oliveira Rafael S. , Berg Lucas A. , Silva Pedro A. A. , Burrage Kevin , dos Santos Rodrigo Weber
Published: May 2020

Ischaemia, in which inadequate blood supply compromises and eventually kills regions of cardiac tissue, can cause many types of arrhythmia, some life-threatening. A significant component of this is the effects of the resulting hypoxia, and concomitant hyperklaemia and acidosis, on the electrophysiological properties of myocytes. Clinical and experimental data have also shown that regions of structural heterogeneity (fibrosis, necrosis, fibro-fatty infiltration) can act as triggers for arrhythmias under acute ischaemic conditions. Mechanistic models have successfully captured these effects
in silico
. However, the relative significance of these separate facets of the condition, and how sensitive arrhythmic risk is to the extents of each, is far less explored. In this work, we use partitioned Gaussian process emulation and new metrics for source-sink mismatch that rely on simulations of bifurcating cardiac fibres to interrogate a model of heterogeneous ischaemic tissue. Re-entries were most sensitive to the level of hypoxia and the fraction of non-excitable tissue. In addition, our results reveal both protective and pro-arrhythmic effects of hyperklaemia, and present the levels of hyperklaemia, hypoxia and percentage of non-excitable tissue that pose the highest arrhythmic risks.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Gaussian process manifold interpolation for probabilistic atrial activation maps and uncertain conduction velocity
Authors: Coveney Sam , Corrado Cesare , Roney Caroline H. , O’Hare Daniel , Williams Steven E. , O’Neill Mark D. , Niederer Steven A. , Clayton Richard H. , Oakley Jeremy E. , Wilkinson Richard D.
Published: May 2020

In patients with atrial fibrillation, local activation time (LAT) maps are routinely used for characterizing patient pathophysiology. The gradient of LAT maps can be used to calculate conduction velocity (CV), which directly relates to material conductivity and may provide an important measure of atrial substrate properties. Including uncertainty in CV calculations would help with interpreting the reliability of these measurements. Here, we build upon a recent insight into reduced-rank Gaussian processes (GPs) to perform probabilistic interpolation of uncertain LAT directly on human atrial manifolds. Our Gaussian process manifold interpolation (GPMI) method accounts for the topology of the atrium, and allows for calculation of statistics for predicted CV. We demonstrate our method on two clinical cases, and perform validation against a simulated ground truth. CV uncertainty depends on data density, wave propagation direction and CV magnitude. GPMI is suitable for probabilistic interpolation of other uncertain quantities on non-Euclidean manifolds.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Parameter subset reduction for patient-specific modelling of arrhythmogenic cardiomyopathy-related mutation carriers in the CircAdapt model
Authors: van Osta Nick , Lyon Aurore , Kirkels Feddo , Koopsen Tijmen , van Loon Tim , Cramer Maarten J. , Teske Arco J. , Delhaas Tammo , Huberts Wouter , Lumens Joost
Published: May 2020

Arrhythmogenic cardiomyopathy (AC) is an inherited cardiac disease, clinically characterized by life-threatening ventricular arrhythmias and progressive cardiac dysfunction. Patient-specific computational models could help understand the disease progression and may help in clinical decision-making. We propose an inverse modelling approach using the CircAdapt model to estimate patient-specific regional abnormalities in tissue properties in AC subjects. However, the number of parameters (n = 110) and their complex interactions make personalized parameter estimation challenging. The goal of this study is to develop a framework for parameter reduction and estimation combining Morris screening, quasi-Monte Carlo (qMC) simulations and particle swarm optimization (PSO). This framework identifies the best subset of tissue properties based on clinical measurements allowing patient-specific identification of right ventricular tissue abnormalities. We applied this framework on 15 AC genotype-positive subjects with varying degrees of myocardial disease. Cohort studies have shown that atypical regional right ventricular (RV) deformation patterns reveal an early-stage AC disease. The CircAdapt model of cardiovascular mechanics and haemodynamics has already demonstrated its ability to capture typical deformation patterns of AC subjects. We, therefore, use clinically measured cardiac deformation patterns to estimate model parameters describing myocardial disease substrates underlying these AC-related RV deformation abnormalities. Morris screening reduced the subset to 48 parameters. qMC and PSO further reduced the subset to a final selection of 16 parameters, including regional tissue contractility, passive stiffness, activation delay and wall reference area.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Considering discrepancy when calibrating a mechanistic electrophysiology model
Authors: Lei Chon Lok , Ghosh Sanmitra , Whittaker Dominic G. , Aboelkassem Yasser , Beattie Kylie A. , Cantwell Chris D. , Delhaas Tammo , Houston Charles , Novaes Gustavo Montes , Panfilov Alexander V. , Pathmanathan Pras , Riabiz Marina , dos Santos Rodrigo Weber , Walmsley John , Worden Keith , Mirams Gary R. , Wilkinson Richard D.
Published: May 2020

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterize uncertainty in model inputs and how that propagates through to outputs or predictions; examples of this can be seen in the papers of this issue. In this review and perspective piece, we draw attention to an important and under-addressed source of uncertainty in our predictions—that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed
model discrepancy
, and we are often uncertain as to the size and consequences of this discrepancy. Here, we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes and autoregressive-moving-average models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Sensitivity of a data-assimilation system for reconstructing three-dimensional cardiac electrical dynamics
Authors: Hoffman Matthew J. , Cherry Elizabeth M.
Published: May 2020

Modelling of cardiac electrical behaviour has led to important mechanistic insights, but important challenges, including uncertainty in model formulations and parameter values, make it difficult to obtain quantitatively accurate results. An alternative approach is combining models with observations from experiments to produce a data-informed reconstruction of system states over time. Here, we extend our earlier data-assimilation studies using an ensemble Kalman filter to reconstruct a three-dimensional time series of states with complex spatio-temporal dynamics using only surface observations of voltage. We consider the effects of several algorithmic and model parameters on the accuracy of reconstructions of known scroll-wave truth states using synthetic observations. In particular, we study the algorithm’s sensitivity to parameters governing different parts of the process and its robustness to several model-error conditions. We find that the algorithm can achieve an acceptable level of error in many cases, with the weakest performance occurring for model-error cases and more extreme parameter regimes with more complex dynamics. Analysis of the poorest-performing cases indicates an initial decrease in error followed by an increase when the ensemble spread is reduced. Our results suggest avenues for further improvement through increasing ensemble spread by incorporating additive inflation or using a parameter or multi-model ensemble.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Afterdepolarizations and abnormal calcium handling in atrial myocytes with modulated SERCA uptake: a sensitivity analysis of calcium handling channels
Authors: Lo Andy C. Y. , Bai Jieyun , Gladding Patrick A. , Fedorov Vadim V. , Zhao Jichao
Published: May 2020

Delayed afterdepolarizations (DADs) and spontaneous depolarizations (SDs) are typically triggered by spontaneous diastolic Ca
2+
release from the sarcoplasmic reticulum (SR) which is caused by an elevated SR Ca
2+
-ATPase (SERCA) uptake and dysfunctional ryanodine receptors. However, recent studies on the T-box transcription factor gene (TBX5) demonstrated that abnormal depolarizations could occur despite a reduced SERCA uptake. Similar findings have also been reported in experimental or clinical studies of diabetes and heart failure. To investigate the sensitivity of SERCA in the genesis of DADs/SDs as well as its dependence on other Ca
2+
handling channels, we performed systematic analyses using the Maleckar
et al
. model. Results showed that the modulation of SERCA alone cannot trigger abnormal depolarizations, but can instead affect the interdependency of other Ca
2+
handling channels in triggering DADs/SDs. Furthermore, we discovered the existence of a threshold value for the intracellular concentration of Ca
2+
([Ca
2+
]
i
) for abnormal depolarizations, which is modulated by the maximum SERCA uptake and the concentration of Ca
2+
in the uptake and release compartments in the SR ([Ca
2+
]
up
and [Ca
2+
]
rel
). For the first time, our modelling study reconciles different mechanisms of abnormal depolarizations in the setting of ‘lone’ AF, reduced TBX5, diabetes and heart failure, and may lead to more targeted treatment for these patients.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Creation and application of virtual patient cohorts of heart models
Authors: Niederer S. A. , Aboelkassem Y. , Cantwell C. D. , Corrado C. , Coveney S. , Cherry E. M. , Delhaas T. , Fenton F. H. , Panfilov A. V. , Pathmanathan P. , Plank G. , Riabiz M. , Roney C. H. , dos Santos R. W. , Wang L.
Published: May 2020

Patient-specific cardiac models are now being used to guide therapies. The increased use of patient-specific cardiac simulations in clinical care will give rise to the development of virtual cohorts of cardiac models. These cohorts will allow cardiac simulations to capture and quantify inter-patient variability. However, the development of virtual cohorts of cardiac models will require the transformation of cardiac modelling from small numbers of bespoke models to robust and rapid workflows that can create large numbers of models. In this review, we describe the state of the art in virtual cohorts of cardiac models, the process of creating virtual cohorts of cardiac models, and how to generate the individual cohort member models, followed by a discussion of the potential and future applications of virtual cohorts of cardiac models.

This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Hard to catch: Experimental evidence supports evasive mimicry
Authors: Páez V Erika , Valkonen Janne K. , Willmott Keith R. , Matos-Maraví Pável , Elias Marianne , Mappes Johanna
Published: May 2020

Most research on aposematism has focused on chemically defended prey, but signalling difficulty of capture remains poorly explored. Similarly to classical Batesian and Müllerian mimicry related to distastefulness, such “evasive aposematism” may also lead to convergence in warning colours, known as evasive mimicry. A prime candidate group for evasive mimicry areAdelphabutterflies, which are agile insects and show remarkable colour pattern convergence. We tested the ability of naïve blue tits to learn to avoid and generaliseAdelphawing patterns associated with difficulty of capture, and compared their response to that of birds that learned to associate the same wing patterns with distastefulness. Birds learned to avoid all wing patterns tested, but learning was faster with evasive prey compared with distasteful prey. Birds generalised their learned avoidance from evasive models to imperfect mimics if the mimic shared colours with the model. Despite imperfect mimics gaining protection from bird’s generalisation, perfect mimics always had the best fitness, supporting selection for accurate mimicry. Faster avoidance learning and broader generalisation of evasive prey suggest that being hard to catch may deter predators at least as effectively as distastefulness. Our results provide empirical evidence for a potentially widespread alternative scenario, evasive mimicry, for the evolution of similar aposematic colour patterns.
Physical constrains and functional plasticity of cellulases: Linear scaling relationships for a heterogeneous enzyme reaction
Authors: Kari Jeppe , Molina Gustavo A. , Schaller Kay S. , Christensen Stefan J. , Schiano-di-Cola Corinna , Badino Silke F. , Sørensen Trine H. , Røjel Nanna , Keller Malene B. , Kolaczkowski Bartlomiej M. , Olsen Johan P. , Krogh Kristian B. R. M. , Jensen Kenneth , Cavaleiro Ana Mafalda , Peters Günther H. J. , Spodsberg Nikolaj , Borch Kim , Westh Peter
Published: May 2020

Enzyme reactions, both in Nature and technical applications, commonly occur at the interface of immiscible phases. Nevertheless, stringent descriptions of interfacial enzyme catalysis remain sparse, and this is partly due to a shortage of coherent experimental data to guide and assess such work. We have produced and kinetically characterized 83 cellulases, which revealed a conspicuous linear free energy relationship (LFER) between the strength of substrate binding and the activation barrier. This common scaling occurred despite the investigated enzymes were structurally and mechanistically diverse. We suggest that the scaling reflects basic physical restrictions of the hydrolytic process and that evolutionary selection have condensed cellulase phenotypes near the line. One consequence of the LFER is that the activity of a cellulase can be estimated from substrate binding strength, irrespectively of structural and mechanistic details, and this appears promising forin silicoselection and design within this industrially important group of enzymes. On a more general note, the LFER may identify a link to inorganic heterogeneous catalysis, and hence open for the implementation of approaches from this field within interfacial enzymology.
Probabilistic seasonal dengue forecasting in Vietnam using superensembles
Authors: Colon-Gonzalez Felipe J , Soares Bastos Leonardo , Hofmann Barbara , Hopkin Alison , Harpham Quillon , Crocker Thomas , Amato Rosanna , Ferrario Iacopo , Moschini Francesca , James Samuel , Malde Sajni , Ainscoe Eleanor , Nam Vu Sinh , Tan Dang Quang , Khoa Nguyen Duc , Harrison Mark , Tsarouchi Gina , Lumbroso Darren , Brady Oliver J , Lowe Rachel
Published: May 2020

Timely information is key for decision-making. The ability to predict dengue transmission ahead of time would significantly benefit planners and decision-makers. Dengue is climate-sensitive. Monitoring climate variability could provide advance warning about dengue risk. Multiple dengue early warning systems have been proposed. Often, these systems are based on deterministic models that have limitations for quantifying the probability that a public health event may occur. We introduce an operational seasonal dengue forecasting system where Earth observations and seasonal climate forecasts are used to drive a superensemble of probabilistic dengue models to predict dengue risk up to six months ahead. We demonstrate that the system has skill and relative economic value at multiple forecast horizons, seasons, and locations. The superensemble generated, on average, more accurate forecasts than those obtained from the models used to create it. We argue our system provides a useful tool for the development and
deployment of targeted vector control interventions, and a more efficient allocation of resources in Vietnam.
Demographic and Clinical Characteristics of the Severe Covid-19 Infections: First Report from Mashhad University of Medical Sciences, Iran
Authors: Goshayeshi Ladan , Rad Mina Akbari , Bergquist Robert , Allahyari Abolghasem ,   members of the MUMS Covid-19 Research Team, Hoseini Benyamin
Published: May 2020

Background

Coronavirus Disease 2019 (Covid-19) is expanding worldwide. The characteristics of this infection in patients varies from country to country. To move forward, clinical data on infected patients are needed. Here, we report a comparison between fatalities and recovery of patients with severe Covid-19, based on demographic and clinical characteristics.

Methods

Between 5 March and 12 May 2020 in Mashhad, Iran, 1,278 of 4,000 suspected Covid-19 patients were confirmed positive by real-time reverse-transcriptase–polymerase-chain-reaction assay of upper respiratory specimens. We compared the demographic, exposure history and clinical symptoms of 925 survivors and 353 fatal cases with confirmed disease.

Results

Mean (SD) age for all confirmed patients was 56.9 (18.7) years, 67.1 (15.9) years in fatal cases and 53.0 (18.3) years in survivors. Multivariable logistic regression analysis showed that the outcome of patients was associated with age (OR = 1.049, P = 0.0001, 95% CI = 1.040-1.057). Despite a high burden of Covid-19 infections in the 30-39 and 40-49 year age groups, most of these (89.6% and 87.2%, respectively) recovered. The median (IQR) duration of hospitalization was 9.0 (6.0-14.0) days. The most prevalent co-morbidities were cardiovascular disorders (21%) and diabetes (16.3%). Dyspnoea (72.7%), cough (68.1%) and fever (63.8%) were the most frequent clinical symptoms. Healthcare workers, of whom two (3%) died, comprised 5.2% of infected-cases. Combination antiviral and antibiotic therapy was used in 43.0% of cases.

Conclusions

The characteristics of severe Covid-19 varied substantially between fatal cases and survivors, with diabetes and cardiovascular disorders the most prevalent co-morbidities. In contrast to other studies, there were a higher number of fatalities in younger patients in our settings.
A Rapid Review and Meta-Analysis of the Asymptomatic Proportion of PCR-Confirmed SARS-CoV-2 Infections in Community Settings
Authors: Beale Sarah , Hayward Andrew , Shallcross Laura , Aldridge Robert W , Fragaszy Ellen
Published: May 2020

Background

Up to 80% of active SARS-CoV-2 infections are proposed to be asymptomatic based on cross-sectional studies. However, accurate estimates of the asymptomatic proportion require systematic detection and follow-up to differentiate between truly asymptomatic and pre-symptomatic cases. We conducted a rapid review and meta-analysis of the asymptomatic proportion of PCR-confirmed SARS-CoV-2 infections based on methodologically-appropriate studies in community settings.

Methods

We searched Medline and EMBASE for peer-reviewed articles, and BioRxiv and MedRxiv for pre-prints published before 25/08/2020. We included studies based in community settings that involved systematic PCR testing on participants and follow-up symptom monitoring regardless of symptom status. We extracted data on study characteristics, frequencies of PCR-confirmed infections by symptom status, and (if available) cycle threshold/genome copy number values and/or duration of viral shedding by symptom status, and age of asymptomatic versus (pre)symptomatic cases. We computed estimates of the asymptomatic proportion and 95% confidence intervals for each study and overall using random effect meta-analysis.

Findings

We screened 1138 studies and included 21. The pooled asymptomatic proportion of SARS-CoV-2 infections was 23% (95% CI 16%-30%). When stratified by testing context, the asymptomatic proportion ranged from 6% (95% CI 0-17%) for household contacts to 47% (95% CI 21-75%) for non-outbreak point prevalence surveys with follow-up symptom monitoring. Estimates of viral load and duration of viral shedding appeared to be similar for asymptomatic and symptomatic cases based on available data, though detailed reporting of viral load and natural history of viral shedding by symptom status were limited. Evidence into the relationship between age and symptom status was inconclusive.

Conclusion

Asymptomatic viral shedding comprises a substantial minority of SARS-CoV-2 infections when estimated using methodologically-appropriate studies. Further investigation into variation in the asymptomatic proportion by testing context, the degree and duration of infectiousness for asymptomatic infections, and demographic predictors of symptom status are warranted.
Underreporting of death by COVID-19 in Brazil's second most populous state
Authors: Alves Thiago Henrique Evangelista , Souza Tafarel Andrade de , Silva Samyla de Almeida , Ramos Nayani Alves , Oliveira Stefan Vilges de
Published: May 2020

The COVID-19 pandemic brings to light the reality of the Brazilian health system. The underreporting of COVID-19 deaths in the state of Minas Gerais (MG), where is concentrated the second largest population of the country, reveals government unpreparedness, as there is a low capacity of testing in the population, which prevents the real understanding of the general panorama of Sars-Cov-2 dissemination. The goals of this research are to analyze the causes of deaths in the different Brazilian government databases (ARPEN and SINAN) and to assess whether there are sub-records shown by the unexpected increase in the frequency of deaths from causes clinically similar to COVID-19. A descriptive and quantitative analysis of the number of COVID-19 deaths and similar causes was made in different databases. Ours results demonstrate that the different official sources had a discrepancy of 209.23% between these data referring to the same period. There was also a 648.61% increase in SARS deaths in 2020, when compared to the average of previous years. Finally, it was shown that there was an increase in the rate of pneumonia and respiratory insufficiency (RI) by 5.36% and 5.72%, respectively. In conclusion, there is an underreporting of COVID-19 deaths in MG due to the unexplained excess of SARS deaths, Respiratory insufficiency and pneumonia compared to previous years.
Developmental demands contribute to early neuromuscular degeneration in CMT2D mice
Authors: Sleigh James N. , Mech Aleksandra M. , Schiavo Giampietro
Published: May 2020

Dominantly inherited, missense mutations in the widely expressed housekeeping gene,GARS1, cause Charcot-Marie-Tooth type 2D (CMT2D), a peripheral neuropathy characterised by muscle weakness and wasting in limb extremities. Mice modelling CMT2D display early and selective neuromuscular junction (NMJ) pathology, epitomised by disturbed maturation and neurotransmission, leading to denervation. Indeed, the NMJ disruption has been reported in several different muscles; however, a systematic comparison of neuromuscular synapses from distinct body locations has yet to be performed. We therefore analysed NMJ development and degeneration across five different wholemount muscles to identify key synaptic features contributing to the distinct pattern of neurodegeneration in CMT2D mice. Denervation was found to occur along a distal-to-proximal gradient, providing a cellular explanation for the greater weakness observed in mutantGarshindlimbs compared to forelimbs. Nonetheless, muscles from similar locations and innervated by axons of equivalent length showed significant differences in neuropathology, suggestive of additional factors impacting on site-specific neuromuscular degeneration. Defective NMJ development preceded and associated with degeneration, but was not linked to a delay of wild-type NMJ maturation processes. Correlation analyses indicate that muscle fibre type nor synaptic architecture explain the differential denervation of CMT2D NMJs, rather it is the extent of post-natal synaptic growth that predisposes to neurodegeneration. Together, this work improves our understanding of the mechanisms driving synaptic vulnerability in CMT2D and hints at pertinent pathogenic pathways.
MitoWave: Spatio-temporal analysis of mitochondrial membrane potential fluctuations during ischemia-reperfusion
Authors: Ashok D. , O’Rourke B.
Published: May 2020

Mitochondria exhibit non-stationary unstable membrane potential (ΔΨm) when subjected to stress, such as during Ischemia/Reperfusion (I/R). Understanding the mechanism of ΔΨminstability involves characterizing and quantifying this phenomenon in response to I/R stress in an unbiased and reproducible manner. We designed a simple ImageJ-MATLAB-based workflow called ‘MitoWave’ to unravel dynamic mitochondrial ΔΨmchanges that occur during ischemia and reperfusion. MitoWave employs MATLAB’s wavelet transform toolbox.In-vitroIschemia was effected by placing a glass coverslip for 60 minutes on a monolayer of neonatal mouse ventricular myocytes (NMVMs). Removal of the coverslip allowed for reperfusion. ΔΨmresponse to I/R was recorded on a confocal microscope using TMRM as the indicator. As proof-of-principle, we used MitoWave analysis on ten invitro I/R experiments. Visual observations corroborated quantitative MitoWave analysis results in classifying the ten I/R experiments into five outcomes that were observed based on the oscillatory state of ΔΨmthroughout the reperfusion time period. Statistical analysis of the distribution of oscillating mitochondrial clusters during reperfusion shows significant differences between five different outcomes (p< 0.001). Features such as time-points of ΔΨmdepolarization during I/R, area of mitochondrial clusters and time-resolved frequency components during reperfusion were determined per cell and per mitochondrial cluster. We found that mitochondria from NMVMs subjected to I/R oscillate in the frequency range of 8.6-45mHz, with a mean of 8.73±4.35mHz. Oscillating clusters had smaller areas ranging from 49.78±40.64 μm2while non-oscillating clusters had larger areas 65.97±42.07μm2. A negative correlation between frequency and mitochondrial cluster area was seen. We also observed that late ΔΨmloss during ischemia correlated with early ΔΨmstabilization after oscillation on reperfusion. Thus, MitoWave analysis provides a way to quantify complex time-resolved mitochondrial behavior. It provides an easy to follow workflow to automate microscopy analysis and allows for unbiased, reproducible quantitation of complex nonstationary cellular phenomena.

Statement of Significance

Understanding mitochondrial instability in Ischemia Reperfusion injury is key to determining efficacy of interventions. The MitoWave analysis is a powerful yet simple tool that enables even beginner MATALAB-Image J users to automate analysis of time-series from microscopy data. While we used it to detect ΔΨmchanges during I/R, it can be adapted to detect any such spatio-temporal changes. It standardizes the quantitative analysis of complex biological signals, opens the door to in-depth screening of the genes, proteins and mechanisms underlying metabolic recovery after ischemia-reperfusion.
Democratising “Microscopi”: a 3D printed automated XYZT fluorescence imaging system for teaching, outreach and fieldwork
Authors: Wincott Matthew , Jefferson Andrew , Dobbie Ian M. , Booth Martin J. , Davis Ilan , Parton Richard M.
Published: May 2020

Commercial fluorescence microscope stands and fully automated XYZt fluorescence imaging systems are generally beyond the limited budgets available for teaching and outreach. We have addressed this problem by developing “Microscopi”, an accessible, affordable, DIY automated imaging system that is built from 3D printed and commodity off-the-shelf hardware, including electro-mechanical, computer and optical components. Our design features automated sample navigation and image capture with a simple web-based graphical user interface, accessible with a tablet or other mobile device. The light path can easily be switched between different imaging modalities. The open source Python-based control software allows the hardware to be driven as an integrated imaging system. Furthermore, the microscope is fully customisable, which also enhances its value as a learning tool. Here, we describe the basic design and demonstrate imaging performance for a range of easily sourced specimens.

Highlights

Portable, low cost, self-build from 3D printed and commodity components

Multimodal imaging: bright field, dark field, pseudo-phase and fluorescence

Automated XYZt imaging from a tablet or smartphone via a simple GUI

Wide ranging applications in teaching, outreach and fieldwork

Open source hardware and software design, allowing user modification
Intrinsic and extrinsic factors collaborate to activate pharyngeal satellite cells without muscle injury
Authors: Kim Eunhye , Zhang Yiming , Wu Fang , Allen James , Vest Katherine E. , Choo Hyojung J.
Published: May 2020

Satellite cells (SCs), adult muscle stem cells in craniofacial muscles proliferate and differentiate/fuse without injury, unlike quiescent SCs in uninjured limb muscle. However, whether intrinsic or extrinsic factors driving their increased basal activity are largely unknown. We compared SCs from the pharynx, which contains constrictor muscles critical for swallowing, to SCs from limb muscle. Pharyngeal SCs are intrinsically more proliferative and contain higher mitochondrial content relative to limb SCs. Pharyngeal SCs occupy less quiescent microenvironments containing collagen V and pharyngeal muscles provide a distinctive SC niche enriched with neighboring resident macrophages and fibroadipogenic progenitors. Loss of SCs impacts pharyngeal myofiber cross-sectional area and the number of neighboring cells, suggesting that SCs are required to maintain pharyngeal muscle homeostasis and its unique niche. Taken together, this study gives new insights to explain the distinctive SC activity of craniofacial muscles, which may explain their unique susceptibility to various muscular dystrophies.
XMAP215 and γ-tubulin additively promote microtubule nucleation in purified solutions
Authors: King Brianna R. , Moritz Michelle , Kim Haein , Agard David A. , Asbury Charles L. , Davis Trisha N.
Published: May 2020

Microtubule nucleation is spatiotemporally regulated in cells by several molecules, including the template γ-tubulin and the polymerase XMAP215. Recently, XMAP215 and the γ-tubulin ring complex were reported to function synergistically, and this synergy was hypothesized to be due to direct binding between XMAP215 and γ-tubulin. Here, we address this hypothesis by 1) probing domain requirements for XMAP215 to promote microtubule nucleation and 2) testing whether XMAP215 functions synergistically with γ-tubulin in the absence of the other ring complex proteins. We confirm that γ-tubulin and XMAP215 are classically defined nucleators that reduce the nucleation lag seen in bulk tubulin assembly. Then, using deletion constructs, we show that XMAP215’s ability to nucleate microtubules in purified solutions correlates with its ability to elongate existing microtubules and does not depend on the number of TOG domains. Finally, we show that XMAP215 and γ-tubulin promote αβ-tubulin assembly in an additive, not synergistic, manner. Thus, their modes of action during microtubule nucleation are distinct, and the synergy reported between XMAP215 and the γ-tubulin ring complex is not due to γ-tubulin alone.
Characterization of extracellular vesicles produced byAspergillus fumigatusprotoplasts
Authors: Rizzo Juliana , Chaze Thibault , Miranda Kildare , Roberson Robert W. , Gorgette Olivier , Nimrichter Leonardo , Matondo Mariette , Latgé Jean-Paul , Beauvais Anne , Rodrigues Marcio L.
Published: May 2020

Extracellular vesicles (EVs) are outer membranous compartments produced by yeast and mycelial forms of several fungal species. One of the difficulties to perceive the role of EVs during the fungal life is the fact that an active secretion of these EVs has not been clearly demonstrated in situ due to the presence of a thick cell wall. One alternative to have a better access to these vesicles is to use protoplasts. This approach has been investigated here withAspergillus fumigatus, one of the most common opportunistic fungal pathogens worldwide. Analysis of regenerating protoplasts by scanning electron microscopy and fluorescence microscopy indicated the occurrence of outer membrane projections in association with surface components and the release of particles with properties resembling those of fungal EVs. EVs in culture supernatants were characterized by transmission electron microscopy and nanoparticle tracking analysis. Proteomic and glycome analysis of EVs revealed the presence of a complex array of enzymes related to lipid / sugar metabolism, pathogenic processes, and cell wall biosynthesis. Our data indicate that i) EV production is a common feature of different morphological stages of this major fungal pathogen, and ii) protoplastic EVs are a promising tool to undertake studies of vesicle functions in fungal cells.

IMPORTANCE

Fungal cells use extracellular vesicles (EVs) to export biologically active molecules to the outer space. Since fungal cells are encaged in a thick cell wall, it is reasonable to expect that this structure might impact the vesicle-mediated molecular export. In this study, we used protoplasts ofAspergillus fumigatus, a major fungal pathogen, as a model to evaluate EV production in the absence of a cell wall. Our results demonstrated that wall-lessA. fumigatusexports plasma membrane-derived EVs containing a complex combination of proteins and glycans. Our study is the first to characterize fungal EVs in the absence of a cell wall. Our results suggest that protoplasts are a promising model for functional studies of fungal vesicles.
The connection of growth and medication of COVID-19 affected people after 30 days of lock down in India
Authors: Bhattacharyya Achintya , Bhattacharyya Debosmita , Mukherjee Joy
Published: May 2020

The COVID-19 pandemic has already consumed few months of indolence all over the world. Almost every part of the world from which the victim of COVID 19 are, have not yet been able to find out a strong way to combat corona virus. Therefore, the main aim is to minimize the spreading of the COVID-19 by detecting most of the affected people during lockdown. Hence, it is necessary to understand what the nature of growth is of spreading of this corona virus with time after almost one month (30 days) of lockdown. In this paper we have developed a very simple mathematical model to describe the growth of spreading of corona virus in human being. This model is based on realistic fact and the statistics we have so far. For controlling the spread of the COVID-19, minimization of the growth with minimum number of days of lockdown is necessary. We have established a relation between the long-term recovery coefficient and the long-term infected coefficient. The growth can be minimized if such condition satisfies. We have also discussed how the different age of the people can be cured by applying different types of medicine. We have presented the data of new cases, recovery and deaths per day to visualize the different coefficient for India and establish our theory. We have also explained how the medicine could be effective to sustain and improve such condition for country having large population like India.