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arXiv2020

A stable method for 4D CT-based CFD simulation in the right ventricle of a TGA patient

The paper discusses a stabilization of a finite element method for the equations of fluid motion in a time-dependent domain. After experimental convergence analysis, the method is applied to simulate a blood flow in the right ventricle of a post-surgery patient with the transposition of the great arteries disorder. The flow domain is reconstructed from a sequence of 4D CT images. The corresponding segmentation and triangulation algorithms are also addressed in brief.

physics.med-ph↗

arXiv2022

Convalescent Blood Treatment for COVID-19: Are Local Donors Enough?

COVID-19 is now a global pandemic, and an effective vaccine may be many months away. Over 100 years ago, Spanish flu fatalities were attenuated when doctors began treating patients with blood plasma donated by recovered (or convalesced) survivors. Passive immunity transfer via administration of convalesced blood product (CBP) appears to represent a readily available and promising avenue for mitigating mortalities, expediting recovery time, and even prophylaxis against the SARS-CoV-2 virus. Here, we review challenges to CBP efficacy, and present a graph theoretical model of transmission dynamics that identifies evolving hubs of COVID-19 cases. Importantly, this model suggests that CBP efficacy may rest on an efficient and distributed global sampling scheme as opposed to CBP pooled from local donors alone.

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arXiv2020

Unboxing mutations: Connecting mutation types with evolutionary consequences

Mutations are typically classified by their effects on the nucleotide sequence and by their size. Here, we argue that if our main aim is to understand the effect of mutations on evolutionary outcomes (such as adaptation or speciation), we need to instead consider their population genetic and genomic effects, from altering recombination rate to modifying chromatin. We start by reviewing known population genetic and genomic effects of different mutation types and connect these to the major evolutionary processes of drift and selection. We illustrate how mutation type can thus be linked with evolutionary outcomes and provide suggestions for further exploring and quantifying these relationships. This reframing lays a foundation for determining the evolutionary significance of different mutation types.

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arXiv2020

A Global View of Standards for Open Image Data Formats and Repositories

Biological and biomedical imaging datasets record the constitution, architecture and dynamics of living organisms across several orders of magnitude of space and time. Imaging technologies are now used throughout the life and biomedical sciences to achieve discovery and understanding of biological mechanisms in the basic sciences as well as assessment, diagnosis and therapeutic intervention in clinical trials and animal and human medicine. The universal application and use of imaging raises an important question and opportunity: what is the value and ultimate destination of biological and medical imaging data? In the last few years, several informatics and data science technologies have matured sufficiently so that routine publication of these datasets is now possible. Participants in Global BioImaging from 15 countries and all populated continents have agreed on the need for recommendations and guidelines for the establishment of image data repositories and the formats they use for delivering data to the global scientific community. This white paper presents a shared, global view of criteria for these common, globally applicable guidelines and provisional proposals for open tools and resources that are available now and can provide a foundation for future development.

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arXiv2020

Molecular Communications in Viral Infections Research: Modelling, Experimental Data and Future Directions

Hundreds of millions of people worldwide are affected by viral infections each year, and yet, several of them neither have vaccines nor effective treatment during and post-infection. This challenge has been highlighted by the COVID-19 pandemic, showing how viruses can quickly spread and how they can impact society as a whole. Novel techniques that bring in different disciplines must emerge to provide forward-looking strategies to combat viral infections, as well as possible future pandemics. In the past decade, an interdisciplinary area involving bioengineering, nanotechnology and information and communication technology (ICT) has been developing, known as Molecular Communications. This new emerging area uses elements of classical communication systems and maps it to molecular signalling and communication found inside and outside the body, where the aim is to develop new tools that can serve future medicine. In this paper, we provide an extensive and detailed discussion on how Molecular Communications can be integrated into the research on viral infectious diseases modelling, and how possible treatment and vaccines can be developed considering molecules as information carriers. We provide a literature review on the existing models of Molecular Communications for viral infection (in-body and out-body), a deep analysis on their effects on the host and subsequent communication process for other systems within the body (e.g., immune response), sources of experimental data on known viral infections and how it can be used by the Molecular Communications community, as well as open issues and future directions. Since the development of therapeutics/vaccines needs an interdisciplinary approach centred around ICT, we are confident that Molecular Communications can play a central role here by providing a detail characterisation and manipulation of the propagation of molecules in different media.

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arXiv2020

Comparing Machine Learning Algorithms with or without Feature Extraction for DNA Classification

The classification of DNA sequences is a key research area in bioinformatics as it enables researchers to conduct genomic analysis and detect possible diseases. In this paper, three state-of-the-art algorithms, namely Convolutional Neural Networks, Deep Neural Networks, and N-gram Probabilistic Models, are used for the task of DNA classification. Furthermore, we introduce a novel feature extraction method based on the Levenshtein distance and randomly generated DNA sub-sequences to compute information-rich features from the DNA sequences. We also use an existing feature extraction method based on 3-grams to represent amino acids and combine both feature extraction methods with a multitude of machine learning algorithms. Four different data sets, each concerning viral diseases such as Covid-19, AIDS, Influenza, and Hepatitis C, are used for evaluating the different approaches. The results of the experiments show that all methods obtain high accuracies on the different DNA datasets. Furthermore, the domain-specific 3-gram feature extraction method leads in general to the best results in the experiments, while the newly proposed technique outperforms all other methods on the smallest Covid-19 dataset

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arXiv2020

Self-Organized Networks: Darwinian Evolution of Myosin-1

Cytoskeletons are self-organized networks based on polymerized proteins: actin, tubulin, and driven by motor proteins, such as myosin, kinesin and dynein. Their positive Darwinian evolution enables them to approach optimized functionality (self-organized criticality). The principal features of the eukaryotic evolution of the cytoskeleton motor protein myosin-1 parallel those of actin and tubulin, but also show striking differences connected to its dynamical function. Optimized (long) hydropathic waves characterize the molecular level Darwinian evolution towards optimized functionality (self-organized criticality). The N-terminal and central domains of myosin-1 have evolved in eukaryotes at different rates, with the central domain hydropathic extrema being optimally active in humans. A test shows that hydropathic scaling can yield accuracies of better than 1% near optimized functionality. Evolution towards synchronized level extrema is connected to a special function of Mys-1 in humans involving Golgi complexes.

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arXiv2020

Exploring the Synchrony Between Body Temperature and HR, RR, and Aortic Blood Pressure in Viral/Bacterial Disease Onsets with Signal Dynamics

Signal-based early detection of illnesses has been a key topic in research and hospital settings; it reduces technological costs and paves the way for quick and effective patient-care operations. Elementary machine learning and signal processing algorithms have proven to be sufficient in classifying the onset of viral and bacterial conditions before clinical symptoms are shown. Inspired by these recent developments, this project employs signal dynamics analysis to infer changes in vital signs (temperature, respiration, and heart rate). The results demonstrate that the trends of one vital function can be predicted from that of another. In particular, it is shown that heart rate and respiration typically change shortly after body temperature, and aortic blood pressure follows. This is not an etiologically specific approach, but if advanced further, it can enable patients and wearable system users to tame these changes and prevent immediate symptoms.

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arXiv2020

Clinical Landscape of COVID-19 Testing: Difficult Choices

The coronavirus disease 2019 (COVID-19) pandemic has spread rapidly across the world, leading to enormous amounts of human death and economic loss. Until definitive preventive or curative measures are developed, policies regarding testing, contact tracing, and quarantine remain the best public health tools for curbing viral spread. Testing is a crucial component of these efforts, enabling the identification and isolation of infected individuals. Differences in testing methodologies, time frames, and outcomes can have an impact on their overall efficiency, usability and efficacy. In this early draft, we draw a comparison between the various types of diagnostic tests including PCR, antigen, and home tests in relation to their relative advantages, disadvantages, and use cases. We also look into alternative and unconventional methods. Further, we analyze the short-term and long-term impacts of the virus and its testing on various verticals such as business, government laws, policies, and healthcare.

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arXiv2020

Interpretation of Confocal ISO 21073: 2019 confocal microscopes: Optical data of fluorescence confocal microscopes for biological imaging- Recommended Methodology for Quality Control

The performance of a confocal imaging system may be no better than a general-purpose widefield system if it is not properly maintained or quality controlled. The publication of ISO 21073, 'Confocal microscopes- Optical data of fluorescence confocal microscopes for biological imaging', set a standard for the minimal Quality Control (QC) that should be performed for Confocal Microscopes. Here we describe methodology for performing the QC requirements to satisfy ISO 21073, as well as suggesting other QC methods that should be performed to obtain a minimum level of information about the microscope system.

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arXiv2020

"Discrimination of virgin olive oils with different geographical origin: a rapid untargeted chromatographic approach based on volatile compounds"

Many studies have shown that the geographic origin is one of the most influencing factors in the choice of olive oil. To avoid misleading, European regulation has established specific rules to report the geographical origin of extra virgin and virgin olive oils on the product label, but an official analytical procedure to verify this information has not been yet defined. In this work, a flash gas chromatography untargeted approach for determination of volatile compounds, followed by a chemometric data elaboration, is proposed for discrimination of EVOOs and VOOs according to their geographical origin (EU and Extra-EU). A set of 210 samples was analyzed and two different classification techniques were used, one linear and one non-linear. The two models were also validated using an external data set. Satisfactory results were obtained for both chemometric approaches: considering the PLS-DA, 89% and 81% of EU and Extra-EU samples, respectively, were correctly classified; for ANN the percentages were 93% and 89%, respectively. These results confirm the reliability of the method as a rapid approach to discriminate EVOOs and VOOs according to their geographical provenance.

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arXiv2020

Paradox resolved: The allometric scaling of cancer risk across species

Understanding the cross-species behavior of cancer is important for uncovering fundamental mechanisms of carcinogenesis, and for translating results of model systems between species. One of the most famous interspecific considerations of cancer is Peto's paradox, which asserts that organisms with vastly different body mass are expected to have a vastly different degree of cancer risk, a pattern that is not observed empirically. Here we show that this observation is not a paradox at all but follows naturally from the interspecific scaling of metabolic rates across mammalian body size. We connect metabolic allometry to evolutionary models of cancer development in tissues to show that waiting time to cancer scales with body mass in a similar way as normal organism lifespan does. Thus, the expectation across mammals is that lifetime cancer risk is invariant with body mass. Peto's observation is therefore not a paradox, but the natural expectation from interspecific scaling of metabolism and physiology. These allometric patterns have theoretical implications for understanding life span evolution, and practical implications for using smaller animals as model systems for human cancer.

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arXiv2020

Inverted repeats in coronavirus SARS-CoV-2 genome and implications in evolution

The coronavirus disease (COVID-19) pandemic, caused by the coronavirus SARS-CoV-2, has caused 60 millions of infections and 1.38 millions of fatalities. Genomic analysis of SARS-CoV-2 can provide insights on drug design and vaccine development for controlling the pandemic. Inverted repeats in a genome greatly impact the stability of the genome structure and regulate gene expression. Inverted repeats involve cellular evolution and genetic diversity, genome arrangements, and diseases. Here, we investigate the inverted repeats in the coronavirus SARS-CoV-2 genome. We found that SARS-CoV-2 genome has an abundance of inverted repeats. The inverted repeats are mainly located in the gene of the Spike protein. This result suggests the Spike protein gene undergoes recombination events, therefore, is essential for fast evolution. Comparison of the inverted repeat signatures in human and bat coronaviruses suggest that SARS-CoV-2 is mostly related SARS-related coronavirus, SARSr-CoV/RaTG13. The study also reveals that the recent SARS-related coronavirus, SARSr-CoV/RmYN02, has a high amount of inverted repeats in the spike protein gene. Besides, this study demonstrates that the inverted repeat distribution in a genome can be considered as the genomic signature. This study highlights the significance of inverted repeats in the evolution of SARS-CoV-2 and presents the inverted repeats as the genomic signature in genome analysis.

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arXiv2020

Repurposing the Combination Drug of Favipiravir, Hydroxychloroquine and Oseltamivir as a Potential Inhibitor against SARS-CoV-2: A Computational Study

The virus SARS-CoV-2 has created a situation of global emergency all over the world from the last few months. We are witnessing a helpless situation due to COVID-19 as no vaccine or drug is effective against the disease. In the present study, we have tested the applicability of some combination drugs against COVID-19. We have tried to understand the mechanism of action of some repurposed drugs: Favipiravir (F), Hydroxychloroquine (H) and Oseltamivir (O). The ADME analysis have suggested strong inhibitory possibility of F, H, O combination towards receptor protein of $3CL^{pro}$ of SARS-CoV-2 virus. The strong binding affinity, number of hydrogen bond interaction between inhibitor, receptor and lower inhibition constant computed from molecular docking validated the better complexation possibility of F+H+O: $3CL^{pro}$ combination. Various thermodynamical output from Molecular dynamics (MD) simulations like potential energy ($E_g$), temperature (T), density, pressure, SASA energy, interaction energies, Gibbs free energy ($ΔG_{bind}$) etc., also favored the complexation between F+H+O and CoV-2 protease. Our In-Silico results have recommended the strong candidature of combination drugs Favipiravir, Hydroxychloroquine and Oseltamivir as a potential lead inhibitor for targeting SARS-CoV-2 infections.

physics.bio-ph↗

arXiv2020

A Mitigation Score for COVID-19

This note describes a simple score to indicate the effectiveness of mitigation against infections of COVID-19 as observed by new case counts. The score includes normalization, making comparisons across jurisdictions possible. The smoothing employed provides robustness in the face of reporting vagaries while retaining salient features of evolution, enabling a clearer picture for decision makers and the public.

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arXiv2020

WI Fast Stats: a collection of web apps for the visualization and analysis of WI Fast Plants data

WI Fast Stats is the first and only dedicated tool tailored to the WI Fast Plants educational objectives. WI Fast Stats is an integrated animated web page with a collection of R-developed web apps that provide Data Visualization and Data Analysis tools for WI Fast Plants data. WI Fast Stats is a user-friendly easy-to-use interface that will render Data Science accessible to K-16 teachers and students currently using WI Fast Plants lesson plans. Users do not need to have strong programming or mathematical background to use WI Fast Stats as the web apps are simple to use, well documented, and freely available.

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arXiv2020

Effect of administration gamma-amino butyric acid on physiological performance of broiler chicks

This experiment was conducted to study the effect of administration γ-amino butyric acid (GABA) on physiology performance of broiler chicks. The following treatments were used: T1:control treatment, T2: the birds were administration 0.2ml 0.4% GABA solution daily, T3: the birds were administration 0.2ml 0.5% GABA solution daily and T4: the birds were administration 0.2ml 0.6% GABA solution daily. The results of the experiment indicated that there were significant differences for the calculating blood lipids .When calculating blood enzymes, there are significant differences between the treatments

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arXiv2020

Neuromatch Academy: Teaching Computational Neuroscience with global accessibility

Neuromatch Academy designed and ran a fully online 3-week Computational Neuroscience summer school for 1757 students with 191 teaching assistants working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility.

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