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arXiv2020

Software for Microscopy Workshop White Paper

Microscopes have morphed from purely optical instruments into motorized, robotic machines that form images on digital sensors rather than eyeballs. This continuing trend towards automation and digitization enables many new approaches to microscopy that would have been impossible or impractical without computer interfaces. Accordingly, todays development of new microscopes most often depends on concurrent software development to bring these custom-build systems to life. This dependence on software brings opportunities and challenges. Most importantly, a key challenge while developing new microscopes is to develop the appropriate software. Despite the fact that software is easily copied and distributed, remarkably few opportunities are available to share experiences creating microscope control software. In turn, this brings challenges in creating maintainable and flexible software code and writing User Interfaces (UIs) that are easily used by researchers, who are primarily life scientists. To start to address these challenges by identifying common problems and shared solutions, we assembled a small group of researchers that develop or use software to control their custom-build microscopes at the Janelia Research Campus for a two-day workshop in February 2020. The outcome of the workshop was the definition of clear milestones, as well as the recognition of an involved community, much larger than the one assembled at the workshop. This community encounters similar hurdles and shares a great desire to overcome these by stronger, community-wide collaborations on Open Source Software. This White Paper summarizes the major issues identified, proposes approaches to address these as a community, and outlines the next steps that can be taken to develop a framework facilitating shared microscope software development, significantly speeding up development of new microscopy systems.

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arXiv2020

In-silico nucleotide and protein analyses of S-gene region in selected zoonotic coronaviruses reveal conserved domains and evolutionary emergence with trajectory course of viral entry from SARS-CoV2 genomic data

The recent zoonotic coronavirus virus outbreak of a novel type [COVID 19] has necessitated the adequate understanding of the evolutionary pathway of zoonotic viruses which adversely affects human populations for therapeutic constructs to combat the pandemic now and in the future. We analyzed conserved domains of the severe acute respiratory coronavirus 2 [SARS-CoV2] for possible targets of viral entry inhibition in host cells, evolutionary relationship of human coronavirus [229E] and zoonotic coronaviruses with SAR-CoV2 as well as evolutionary relationship between selected SARS-CoV 2 genomic data. Conserved domains with antagonistic action on host innate antiviral cellular mechanisms in SARS-CoV 2 include nsp 11, nsp 13 etc. Also, multiple sequence alignments of the spike [S] gene protein of selected candidate zoonotic coronaviruses alongside the S gene protein of the SARs-CoV2 revealed closest evolutionary relationship [95.6%] with pangolin coronaviruses [S] gene. Clades formed between Wuhan SARS-CoV2 phylogeny data and five others suggests viral entry trajectory while revealing genomic and protein SARS CoV 2 data from Philippines as early ancestors. Therefore, phylogeny of SARS-CoV 2 genomic data suggests profiling in diverse populations with and without the outbreak alongside migration history and racial background for mutation tracking and dating of viral subtype divergence which is essential for effective management of present and future zoonotic coronavirus outbreaks.

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arXiv2020

Predation by Atractosteus tropicus on Bufo marinus and its possible affect on population in a lowland tropical wet rainforest

Fish predation can affect amphibian populations. Most examples report invasive fish species and their negative effect on specific amphibians. Here we provide an occurrence of natural fish predation by the tropical gar Atractosteus tropicus on the cane toad Bufo marinus. We observed physical damage caused by A. tropicus attacking B. marinus. When adult B. marinus were removed from the population subadult toads refilled the adults niche, resupplementing the population. Local observations of predation by fish on amphibians are important to differentiate natural population fluctuations from amphibian population declines.

q-bio.OT↗

arXiv2023

Life's mechanism

The multifarious internal workings of organisms are difficult to reconcile with a single feature defining a state of being alive. Indeed, definitions of life rely on emergent properties (growth, capacity to evolve, agency) only symptomatic of intrinsic functioning. Empirical studies demonstrate that biomolecules including ratcheting or rotating enzymes and ribozymes undergo repetitive conformation state changes driven either directly or indirectly by thermodynamic gradients. They exhibit disparate structures, but govern processes relying on directional physical motion (DNA transcription, translation, cytoskeleton transport) and share the principle of repetitive uniplanar conformation changes driven by thermodynamic gradients, producing dependable unidirectional motion: heat engines exploiting thermodynamic disequilibria to perform work. Recognition that disparate biological molecules demonstrate conformation state changes involving directional motion, working in self-regulating networks, allows a mechanistic definition: life is a self-regulating process whereby matter undergoes cyclic, uniplanar conformation state changes that convert thermodynamic disequilibria into directed motion, performing work that locally reduces entropy. Living things are structures including an autonomous network of units exploiting thermodynamic gradients to drive uniplanar conformation state changes that perform work. These principles are independent of any specific chemical environment, and can be applied to other biospheres.

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arXiv2020

Sewage Pooling Test for SARS-CoV-2

CoVID-19 is currently one of the biggest threats to mankind. To date, it is the reason for infections of over 35 lakhs and the death of over 2 lakh human beings. We propose a procedure to detect CoVID-19 affected localities using a sewage mass testing and pooling mechanism which has gained ground in recent times. The proposed method named Sewage Pooling Algorithm tests wastewater samples from sewage systems to pinpoint the regions which are affected by maximum chances of the virus spread. The algorithm also uses a priority-based backtracking procedure to perform testing in sewage links depending on the probability of infection in the sub-areas. For places with very rare CoVID cases, we present a gradient-based search method to prune those areas. The proposed method has less human intervention and increases the effective tests/million people over current in-place methods.

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arXiv2020

Hemogram Data as a Tool for Decision-making in COVID-19 Management: Applications to Resource Scarcity Scenarios

COVID-19 pandemics has challenged emergency response systems worldwide, with widespread reports of essential services breakdown and collapse of health care structure. A critical element involves essential workforce management since current protocols recommend release from duty for symptomatic individuals, including essential personnel. Testing capacity is also problematic in several countries, where diagnosis demand outnumbers available local testing capacity. This work describes a machine learning model derived from hemogram exam data performed in symptomatic patients and how they can be used to predict qRT-PCR test results. Methods: A Naive-Bayes model for machine learning is proposed for handling different scarcity scenarios, including managing symptomatic essential workforce and absence of diagnostic tests. Hemogram result data was used to predict qRT-PCR results in situations where the latter was not performed, or results are not yet available. Adjusts in assumed prior probabilities allow fine-tuning of the model, according to actual prediction context. Proposed models can predict COVID-19 qRT-PCR results in symptomatic individuals with high accuracy, sensitivity and specificity. Data assessment can be performed in an individual or simultaneous basis, according to desired outcome. Based on hemogram data and background scarcity context, resource distribution is significantly optimized when model-based patient selection is observed, compared to random choice. The model can help manage testing deficiency and other critical circumstances. Machine learning models can be derived from widely available, quick, and inexpensive exam data in order to predict qRT-PCR results used in COVID-19 diagnosis. These models can be used to assist strategic decision-making in resource scarcity scenarios, including personnel shortage, lack of medical resources, and testing insufficiency.

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arXiv2020

Statistical Issues and Recommendations for Clinical Trials Conducted During the COVID-19 Pandemic

The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.

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arXiv2020

Fomite transmission and disinfection strategies for SARS-CoV-2 and related viruses

Contaminated objects or surfaces, referred to as fomites, play a critical role in the spread of viruses, including SARS-CoV-2, the virus responsible for the COVID-19 pandemic. The long persistence of viruses (hours to days) on surfaces calls for an urgent need for surface disinfection strategies to intercept virus transmission and the spread of the disease. Elucidating the physicochemical processes and surface science underlying the adsorption and transfer of virus between surfaces, as well as their inactivation, are important in understanding how the disease is transmitted, and in developing effective interception strategies. This review aims to summarize the current knowledge and underlying physicochemical processes of virus transmission, in particular via fomites, and common disinfection approaches. Gaps in knowledge and needs for further research are also identified. The review focuses on SARS-CoV-2, but will supplement the discussions with related viruses.

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arXiv2020

3D CA model of tumor-induced angiogenesis

Tumor-induced angiogenesis is the formation of new sprouts from preexisting nearby parent blood vessels. Computationally, tumor-induced angiogenesis can be modeled using cellular automata (CA), partial differential equations, etc. In this present study, a realistic physiological approach has been made to model the process of angiogenesis by using 3D CA model. CA technique uses various neighborhoods like Von-Neumann neighborhood, Moore neighborhood, and Margolus neighborhood. In our model Von-Neumann neighborhood has used for distribution of some significant chemical and non-chemical tumor angiogenic factors like vascular endothelial growth factor, endothelial cells, O2, extracellular matrix, fibronectin, etc., and Moore neighborhood is used for distribution of matrix metalloproteinase. In vivo tumor environment all the factors are not distributed equally in the extracellular matrix. Distributions of those chemical and nonchemical factors depend on their source, nature and function. To keep similarity with the biological tumor environment, we have formulated initial distributions of the chemical and non-chemical factors accordingly. We have started the simulation in MATLAB with this initial distribution. Number of sprouts randomly varies from one run to another. We observed that sprouts are not originating from the same locations in each simulation. A sprout has high sensitivity of VEGF and fibronectin concentrations. sVEGFR-1 always tries to regress the sprout. When two or more sprouts come closer, they merge with each other leading to anastomosis. Sufficient number of tip cells may cause sprout towards tumor.

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arXiv2020

Automated Measurements of Key Morphological Features of Human Embryos for IVF

A major challenge in clinical In-Vitro Fertilization (IVF) is selecting the highest quality embryo to transfer to the patient in the hopes of achieving a pregnancy. Time-lapse microscopy provides clinicians with a wealth of information for selecting embryos. However, the resulting movies of embryos are currently analyzed manually, which is time consuming and subjective. Here, we automate feature extraction of time-lapse microscopy of human embryos with a machine-learning pipeline of five convolutional neural networks (CNNs). Our pipeline consists of (1) semantic segmentation of the regions of the embryo, (2) regression predictions of fragment severity, (3) classification of the developmental stage, and object instance segmentation of (4) cells and (5) pronuclei. Our approach greatly speeds up the measurement of quantitative, biologically relevant features that may aid in embryo selection.

cs.CV↗

arXiv2020

A decade of movement ecology

Movement is fundamental to life, shaping population dynamics, biodiversity patterns, and ecosystem structure. Recent advances in tracking technology have enabled fundamental questions about movement to be tackled, leading to the development of the movement ecology framework (MEF), considered a milestone in the field [1]. The MEF introduced an integrative theory of organismal movement, linking internal state, motion capacity and navigation capacity to external factors. Here, a decade later, we investigated the current state of research in the field. Using a text mining approach on >8000 peer-reviewed papers in movement ecology, we explored the main research topics, evaluated the impact of the MEF, and assessed changes in the use of technological devices, software and statistical methods. The number of publications has increased considerably and there have been major technological changes in the past decade (i.e.~increased use of GPS devices, accelerometers and video cameras, and a convergence towards R), yet we found that research focuses on the same questions, specifically, on the effect of environmental factors on movement and behavior. In practice, it appears that movement ecology research does not reflect the MEF. We call on researchers to transform the field from technology-driven to embrace interdisciplinary collaboration, in order to reveal key processes underlying movement (e.g.~navigation), as well as evolutionary, physiological and life-history consequences of particular strategies.

q-bio.PE↗

arXiv2020

Ontology-based systematic classification and analysis of coronaviruses, hosts, and host-coronavirus interactions towards deep understanding of COVID-19

Given the existing COVID-19 pandemic worldwide, it is critical to systematically study the interactions between hosts and coronaviruses including SARS-Cov, MERS-Cov, and SARS-CoV-2 (cause of COVID-19). We first created four host-pathogen interaction (HPI)-Outcome postulates, and generated a HPI-Outcome model as the basis for understanding host-coronavirus interactions (HCI) and their relations with the disease outcomes. We hypothesized that ontology can be used as an integrative platform to classify and analyze HCI and disease outcomes. Accordingly, we annotated and categorized different coronaviruses, hosts, and phenotypes using ontologies and identified their relations. Various COVID-19 phenotypes are hypothesized to be caused by the backend HCI mechanisms. To further identify the causal HCI-outcome relations, we collected 35 experimentally-verified HCI protein-protein interactions (PPIs), and applied literature mining to identify additional host PPIs in response to coronavirus infections. The results were formulated in a logical ontology representation for integrative HCI-outcome understanding. Using known PPIs as baits, we also developed and applied a domain-inferred prediction method to predict new PPIs and identified their pathological targets on multiple organs. Overall, our proposed ontology-based integrative framework combined with computational predictions can be used to support fundamental understanding of the intricate interactions between human patients and coronaviruses (including SARS-CoV-2) and their association with various disease outcomes.

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arXiv2020

A quantitative compendium of COVID-19 epidemiology

Accurate numbers are needed to understand and predict viral dynamics. Curation of high-quality literature values for the infectious period duration or household secondary attack rate, for example, is especially pressing currently because these numbers inform decisions about how and when to lockdown or reopen societies. We aim to provide a curated source for the key numbers that help us understand the virus driving our current global crisis. This compendium focuses solely on COVID-19 epidemiology. The numbers reported in summary format are substantiated by annotated references. For each property, we provide a concise definition, description of measurement and inference methods, and associated caveats. We hope this compendium will make essential numbers more accessible and avoid common sources of confusion for the many newcomers to the field such as using the incubation period to denote and quantify the latent period or using the hospitalization duration for the infectiousness period duration. This document will be repeatedly updated and the community is invited to participate in improving it.

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arXiv2020

Clinical Trial Drug Safety Assessment for Studies and Submissions Impacted by COVID-19

In this paper, we provide guidance on how standard safety analyses and reporting of clinical trial safety data may need to be modified, given the potential impact of the COVID-19 pandemic. The impact could include missed visits, alternative methods for assessments (such as virtual visits), alternative locations for assessments (such as local labs), and study drug interruptions. We focus on safety planning for Phase 2-4 clinical trials and integrated summaries for submissions. Starting from the recommended safety analyses proposed in white papers and a workshop, created as part of an FDA/PHUSE collaboration (PHUSE 2013, 2015, 2017, 2019), we assess what modifications might be needed. Impact from COVID-19 will likely affect treatment arms equally, so analyses of adverse events from controlled data can, to a large extent, remain unchanged. However, interpretation of summaries from uncontrolled data (summaries that include open-label extension data) will require even more caution than usual. Special consideration will be needed for safety topics of interest, especially events expected to have a higher incidence due to a COVID-19 infection or due to quarantine or travel restrictions (e.g., depression). Analyses of laboratory measurements may need to be modified to account for the combination of measurements from local and central laboratories.

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arXiv2020

Intermolecular Enzymatic Encoding of Nucleic Acid, Steroid Complexes: A New Theory on the Chemical Origin of Life Based on Evidence of Structural Symmetry

The origin of life is one of the greatest mysteries. The mechanism for the synthesis of DNA is synonymous with the chemical origin of life, and theories have been developed along many lines of reasoning, but resolving all requirements remains a challenge, such as defining an objective path to produce sequences of encoded nucleotides paired as adenine to thymine and guanine to cytosine. Here, a new theory for the origin of DNA is presented. The theory is based upon three lines of experimental evidence and agreement of structural symmetry between DNA nucleotides and steroid hormones, and introduces a new concept of synthesizing both structural and functional characteristics of DNA at the same time within a single unified complex of interleaved tetra-ringed structures, steroid molecules which form reaction vessels that serve as co-enzymatic building blocks. The new theory indicates that the establishment of the DNA nucleotide code is among the very first synthesis steps. Moreover, as a consequence of the intermolecular synthesis of both structural and functional characteristics within a unified complex, there is a culminating process step that sets forth in motion both DNA and the steroid structures that subsequently trigger replication and transcription, as well as protein translation, thereby resulting in the instantaneous release of life function.

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arXiv2020

Comparative study of the biological activities of the aqueous extracts of two spontaneous plants harvested in the Algerian Sahara

The present study investigates the insecticidal and herbicidal effects of leaf extracts from two plants were harvested in the Northern Algerian Sahara. These are Cleome arabica (Capparaceae) and Pergularia tomentosa (Asclepiadaceae). The efficacy of the extracts from the plants was evaluated by the reflux extraction method. The phytochemical screening of the aqueous extracts of C. arabica shows a remarkable richness in active principles in comparison with the extract of P. tomentosa; including flavonoids, saponosides, glycosides, terpenes, sterols, deoxyose, polyphenols and total alkaloids. The imago of Tribolium confusum treated with aqueous extracts of C. arabica and P. tomentosa at doses of 80% to 100% respectively have mortality rates of 73.33% to 96.67%, and 36.67% to 86.67%. The lethal time 50 (TL50%) of the aqueous extract of C. arabica was estimated about 6.41 days, and 6.94 days for the extract P. tomentosa for the imago of T. confusum. The extracts of P. tomentosa is less toxic than the extracts of C. arabica. The allelopathic potentials of C. arabica and P. tomentosa tested on germination of the seeds of a weed Dactyloctenium aegyptium (Poaceae) and two cultivated species, including Hordeumvulgare and Triticumdurum (Poaceae), show that the inhibitory effect of extracts of C. arabica is very highly significant. It manifests itself in the growth of the aerial and underground part of the H. vulgar and T. durum. The inhibition rate is more than 84.44% for D. aegyptium seeds treated with the different concentrations. The inhibition rates range from 75.56% to 91.11% for T. durum wheat irrigate at 80% to 100%, but are only 55.56% to 77.78% for barley seeds treated with the same concentrations (80% to 100%).

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arXiv2020

Universal Relation for Life-span Energy Consumption in Living Organisms: Insights for the origin of ageing

Metabolic energy consumption has long been thought to play a major role in the aging process ({\it 1}). Across species, a gram of tissue on average expends about the same amount of energy during life-span ({\it 2}). Energy restriction has also been shown that increases maximum life-span ({\it 3}) and retards age-associated changes ({\it 4}). However, there are significant exceptions to a universal energy consumption during life-span, mainly coming from the inter-class comparison ({\it 5, 6}). Here we present a unique relation for life-span energy consumption, valid for $\sim$300 species representing all classes of living organisms, from unicellular ones to the largest mammals. The relation has an average scatter of only 0.3 dex, with 95\% ($\rm 2-σ$) of the organisms having departures less than a factor of $π$ from the relation, despite the $\sim$20 orders of magnitude difference in body mass, reducing any possible inter-class variation in the relation to only a geometrical factor. This result can be interpreted as supporting evidence for the existence of an approximately constant total number $\rm N_r \sim 10^8$ of respiration cycles per lifetime for all organisms, effectively predetermining the extension of life by the basic energetics of respiration, being an incentive for future studies that investigate the relation of such constant $\rm N_r$ cycles per lifetime with the production rates of free radicals and oxidants, which may give definite constraints on the origin of ageing.

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arXiv2020

Not even the air of empty spaces is coronavirus free (Two meters is not a safe distance)

A key safety measure encouraged by health authorities to avoid the SARS-CoV-2 spreading is the distance of one to two meters between people. This recommended two-meters distance is mainly based on short-distance contagion, when infected drops are expelled during a speech, coughing, or sneezing and directly hit another person. The dangerous form of airway contamination caused by droplets that remain suspended in the air for several hours has been almost ignored. However, the theoretical calculations performed in this work, recent experiments, and the accumulated knowledge in this and other epidemics indicate that, because of the airborne transmission, there is no safe distance to the coronavirus, either indoors or in open places. Recent investigations have confirmed not only the presence of the coronavirus in droplets suspended in the air but that these viruses remain active for several hours. Furthermore, significant indirect evidence of this means of transmission is the great difference in contagion between Brazilian regions in the current outbreak. While the Amazonian states have a contamination rate greater than 20%, in the southern states of the country this rate is less than 1%, despite high temperatures in the Northern region. Notwithstanding the social and economic differences between these regions, it seems that the extremely high humidity of the forest air prolongs the survival of the viruses in the drops in the external environment. Our theoretical calculations explain empirical observations from recent epidemiological studies and strengthen the need to use, not only a mask but also protective glasses throughout the population in the same way that they are mandatory for health professionals. Besides, our calculations show how air conditioning and heating systems can increase contagion. Finally, we suggest measures that could reduce the spread of the pandemic.

physics.soc-ph↗