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At least 595 records · Page 33Linked to original sources
arXiv2021

Open microscopy in the life sciences: Quo Vadis?

Light microscopy allows observing cellular features and objects with sub-micrometer resolution. As such, light microscopy has been playing a fundamental role in the life sciences for more than a hundred years. Fueled by the availability of mass-produced electronics and hardware, publicly shared documentation and building instructions, open-source software, wide access to rapid prototyping and 3D printing, and the enthusiasm of contributors and users involved, the concept of open microscopy has been gaining incredible momentum, bringing new sophisticated tools to an expanding user base. Here, we will first discuss the ideas behind open science and open microscopy before highlighting recent projects and developments in open microscopy. We argue that the availability of well-designed open hardware and software solutions targeting broad user groups or even non-experts, will increasingly be relevant to cope with the increasing complexity of cutting-edge imaging technologies. We will then extensively discuss the current and future challenges of open microscopy.

q-bio.OT↗
arXiv2021

Diachronic Text Mining Investigation of Therapeutic Candidates for COVID-19

Diachronic text mining has frequently been applied to long-term linguistic surveys of word meaning and usage shifts over time. In this paper we apply short-term diachronic text mining to a rapidly growing corpus of scientific publications on COVID-19 captured in the CORD-19 dataset in order to identify co-occurrences and analyze the behavior of potential candidate treatments. We used a data set associated with a COVID-19 drug re-purposing study from Oak Ridge National Laboratory. This study identified existing candidate coronavirus treatments, including drugs and approved compounds, which had been analyzed and ranked according to their potential for blocking the ability of the SARS-COV-2 virus to invade human cells. We investigated the occurrence of these candidates in temporal instances of the CORD-19 corpus. We found that at least 25% of the identified terms occurred in temporal instances of the corpus to the extent that their frequency and contextual dynamics could be evaluated. We identified three classes of behaviors: those where frequency and contextual shifts were small and positively correlated; those where there was no correlation between frequency and contextual changes; and those where there was a negative correlation between frequency and contextual shift. We speculate that the latter two patterns are indicative that a target candidate therapeutics is undergoing active evaluation. The patterns we detected demonstrate the potential benefits of using diachronic text mining techniques with a large dynamic text corpus to track drug-repurposing activities across international clinical and laboratory settings.

cs.CL↗
arXiv2021

Generational Frameshifts in Technology: Computer Science and Neurosurgery, The VR Use Case

We are at a unique moment in history where there is a confluence of technologies which will synergistically come together to transform the practice of neurosurgery. These technological transformations will be all-encompassing, including improved tools and methods for intraoperative performance of neurosurgery, scalable solutions for asynchronous neurosurgical training and simulation, as well as broad aggregation of operative data allowing fundamental changes in quality assessment, billing, outcome measures, and dissemination of surgical best practices. The ability to perform surgery more safely and more efficiently while capturing the operative details and parsing each component of the operation will open an entirely new epoch advancing our field and all surgical specialties. The digitization of all components within the operating room will allow us to leverage the various fields within computer and computational science to obtain new insights that will improve care and delivery of the highest quality neurosurgery regardless of location. The democratization of neurosurgery is at hand and will be driven by our development, extraction, and adoption of these tools of the modern world. Virtual reality provides a good example of how consumer-facing technologies are finding a clear role in industry and medicine and serves as a notable example of the confluence of various computer science technologies creating a novel paradigm for scaling human ability and interactions. The authors describe the technology ecosystem that has come and highlight a myriad of computational and data sciences that will be necessary to enable the operating room of the near future.

cs.HC↗
arXiv2022

An immunological autobiography: my year as a COVID-19 vaccine trial participant

I present here longitudinal evaluation of T and B cell immunity to SARS-CoV2 and variants of concern (VOC) from a single subject (me) over an entire year post vaccination. After enrolling in the Moderna phase III clinical trial, I collected my own biological samples pre- and post-immunization in the event of being a recipient of the experimental vaccine. The evidence strongly supports the conclusion that I did not receive the placebo. The analysis is admittedly limited to an n of 1, but the results fit well with data taken from published works and represent one of the more comprehensive longitudinal evaluations of vaccine-elicited immunity within a single individual yet to be undertaken. Though the data amount to a well-documented anecdote, given its granularity, it is not without its insights and may be of further use in directing future longitudinal studies that have actual statistical significance.

q-bio.OT↗
arXiv2021

Proteins Evolution Upon Point Mutations

The primary aim of this work is to explore how proteins point mutations impact their marginal stability and, hence, their evolvability. With this purpose, we show that the use of four classic notions, namely, those from Leibniz & Kant (1768), Maynard Smith (1970), Einstein & Infeld (1961), and Anfinsen (1973), is sufficient for a better understanding of the protein-evolution and, consequently, to determine the factors that could control it. The preliminary results -- without considering epistasis effects explicitly -- indicate that the protein marginal-stability change upon point mutations provides the necessary and sufficient information to describe, through a Boltzmann factor, the evolution of the amide hydrogen-exchange protection factors. This finding is of paramount importance because it illustrates the impact of point mutations on both the protein marginal-stability and the ensemble of folded conformations coexisting with the native state and, in the presence of metamorphism, on the propensity for the appearance of new folds and functions.

q-bio.OT↗
arXiv2021

Analysis of chronic diseases progression using stochastic modeling

This book handles the fatty liver disease from the bio-statistical point of view . It discusses the disease process in the simple general form of health-disease-death multi-states model . Continuous Time Markov Chains are used to estimate the rate transition matrix utilizing the MLE and Quasi-Newton formula , once obtained , the probability transition matrix can be estimated by exponentiation of the rate matrix . The probability transition matrix can also be obtained by solving the forward Kolmogorov differential equations , which yields more stable solution than exponentiation of rate matrix. The disease process is expanded in 9 states model to explain the transition among the detailed stages of the disease process , in more elaborate form. The probability transition matrix is used to estimate the number of patients in each stage , this matrix along with the rate transition matrix , both are used to estimate life expectancy of patients is each stage. These statistical indices are of great value as they can help the health policy makers and medical insurance managers to allocate the resources for investigating and treating patients in different stages of the disease . This method is of a high potential value to be used in longitudinal studies conducted by the pharmaceutical companies to evaluate the effect of anti-fibrotic drugs used to treat patients within the initial stages of fibrosis . Poisson regression model is also used to relate the high risk covariates such as type 2 diabetes, hypercholesterolemia , obesity and hypertension with the rate of progression and evolution of the stages of the disease over time. The general model , the expanded model and the model with covariates are illustrated by artificial hypothetical examples to demonstrate the mathematical statistical indices .

q-bio.OT↗
arXiv2021

Nachhaltige Strategien gegen die COVID-19-Pandemie in Deutschland im Winter 2021/2022

In this position paper, a large group of interdisciplinary experts outlines response strategies against the spread of SARS-CoV-2 in the winter of 2021/2022 in Germany. We review the current state of the COVID-19 pandemic, from incidence and vaccination efficacy to hospital capacity. Building on this situation assessment, we illustrate various possible scenarios for the winter, and detail the mechanisms and effectiveness of the non-pharmaceutical interventions, vaccination, and booster. With this assessment, we want to provide orientation for decision makers about the progress and mitigation of COVID-19.

q-bio.OT↗
arXiv2021

Attaining scalable storage-expansion dualism for bioartificial tissues

The untenable dependence of cryopreservation on cytotoxic cryoprotectants has motivated the mining of biochemical libraries to identify molecular features marking cryoprotectants that may prevent ice crystal growth. It is hypothesized that such molecules may be useful across all temperatures eliminating cellular destruction due to equilibration cytotoxicity before and after cryopreservation. By probing the biochemical space using solvation-associated molecular topology and partition-distribution measures we developed an analytic formalism for ice crystal inhibition. By probing the union between a heat-shock protein cluster and an anti-freeze glycoprotein cluster, the model development process generated distinct regions of interest for anti-freeze glycoprotein and proved robust across different classes of proteins. These results confirm that there is a chemical space within which efficacious Ice Crystal Inhibitor molecular libraries can be constructed. These spaces contain latent projections drawn from solvent accessibility, hydrogen bonding capacity and molecular geometry. They also showed that molecular design can be a useful tool in the development of new-age cryoactive matrices to enable the smooth transition across culture, preservation and expansion. These chemical spaces provide low cytotoxicity since such amphipathic molecules occupy a continuum between solubizing and membrane stabilizing regions as shown by the free energy of translocation calculations. These biochemical design spaces are fundamentally the solution to efficient scale-up and deployment of cell therapies. Consequently, this article proposes the use of a molecular knowledge-mining approach in the development of a class of non-cytotoxic cryoprotective agents in the class of Ice Crystal Inhibitor compatible with continuous cryothermic and normothermic cell storage and expansion.

q-bio.OT↗
arXiv2021

Global alignment for relation extraction in Microbiology

We investigate a method to extract relations from texts based on global alignment and syntactic information. Combined with SVM, this method is shown to have a performance comparable or even better than LSTM on two RE tasks.

q-bio.OT↗
arXiv2021

A New Rapid Test to End COVID

Despite 93.1% to 95.8% of the UK adult population having been vaccinated and currently 83.5% to 89.8% of adults having received at least two doses (1), and despite many households testing twice a week with lateral flow tests (2), R at the time of writing is 0.9 to 1.1, with a growth rate range for England of between -1% and +1% (3). Furthermore, up to 30% of infected individuals are going on to experience Long Covid (4). The crisis is far from over and as new variants of concern like Omicron spread, the situation is not under control, even in the highly vaccinated and tested UK and far less so in many countries. The problem is likely to be replicated in other countries with currently low infection levels as isolation is eased in future, even if these countries reach a high level of vaccination. Additionally, concerns have been raised about fall in immunity by 6 months after receiving the Pfizer and AstraZeneca vaccines (5), and the ability of Omicron to re-infect and cause illness in vaccinated people, with urgent booster jabs now being given to attempt to mitigate this. A solution to stop the spread of all variants of COVID-19 is needed now, and we present it here: CLDC, a rapid test that is 98%+ sensitive, low cost and scalable.

q-bio.OT↗
arXiv2021

What Omicron Does, and How It Does It

Improvement of protein function by evolution (natural selection) is expected on general grounds, but even with the modern database positive proof has remained a difficult problem for theory. Here we extend our recent analysis of the evolution of CoV-1 to much more contagious CoV-2, to Omicron, which appears to be qualitatively different from other recent strains like Delta. Overall the synchronized dynamics of Omicron is more elaborate than CoV-2 or its variants like Delta. The surprising result is that while Omicron could be more contagious than even Delta, it is probably much less dangerous

q-bio.OT↗
arXiv2021

Metabolic cascades of energy

Life has a special status, it even has its own science: biology. In many ways, the logic of life seems to differ from that of atoms, molecules, planets, or any other `inanimate object'. However, life is increasingly measured using quantities shared by all sciences, like mass, force, energy or power. An analysis of the dimensions of these quantities provides powerful ways to infer the relationships they might have with one another. Here we show that a dimensional analysis of the metabolic laws connecting the characteristic powers and masses of living organisms offers new ways to understand the deep connections between the chemistry of microscopic molecules and the physics of macroscopic objects bound by gravity. This analysis reveals a link between metabolism and the cascades of energy observed in turbulent flows, opening new perspectives for both fields.

q-bio.OT↗
arXiv2021

Concatenated Code Design for Constrained DNA Data Storage with Asymmetric Errors

DNA Data storage has recently attracted much attention due to its durable preservation and extremely high information density (bits per gram) properties. In this work, we propose a hybrid coding strategy comprising of generalized constrained codes to tackle homopolymer (run-length) limit and a protograph based low-density parity-check (LDPC) code to correct asymmetric nucleotide level (i.e., A/T/C/G) substitution errors that may occur in the process of DNA sequencing. Two sequencing techniques namely, Nanopore sequencer and Illumina sequencer with their equivalent channel models and capacities are analyzed. A coding architecture is proposed to potentially eliminate the catastrophic errors caused by the error-propagation in the constrained decoding while enabling high coding potential. We also show the log likelihood ratio (LLR) calculation method for the belief propagation decoding with this coding architecture. The simulation results and the theoretical analysis show that the proposed coding scheme exhibits good bit-error rate (BER) performance and high coding potential ($\sim1.98$ bits per nucleotide).

cs.IT↗
arXiv2021

Setting Boundaries for Statistical Mechanics

Statistical mechanics has grown without bounds in space. Statistical mechanics of point particles in an unbounded perfect gas is commonly accepted as a foundation for understanding many systems, including liquids like the concentrated salt solutions of life and electrochemical technology, from batteries to nanodevices. Liquids, however, are not gases. Liquids are filled with interacting molecules and so the model of a perfect gas is imperfect. Here we show that statistical mechanics without bounds (in space) is impossible as well as imperfect, if the molecules interact as charged particles, as nearly all atoms do. The behavior of charged particles is not defined until boundary structures and values are defined because charges are governed by the Maxwell partial differential equations. Partial differential equations require boundary conditions to be computable or well defined. The Maxwell equations require boundary conditions on finite sized spatial boundaries (i.e., structures). Boundary conditions cannot be defined 'at infinity' in a general (i.e., unique) way because the limiting process that defines infinity includes such a wide variety of behavior, from light waves that never decay, to fields from dipole and multipolar charges that decay steeply, to Coulomb fields that decay but not so steeply. Statistical mechanics involving charges thus involves spatial boundaries and boundary conditions of finite size. Nearly all matter involves charges, thus nearly all statistical mechanics requires structures and boundary conditions on those structures. Boundaries and boundary conditions are not prominent in classical statistical mechanics. Including boundaries is a challenge to mathematicians. Statistical mechanics must describe bounded systems if it is to provide a proper foundation for studying matter.

q-bio.OT↗
arXiv2021

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health

Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth-independence, rather than Earth-reliance. Promising developments in the fields of artificial intelligence and machine learning for biology and health can address these needs. We propose an appropriately autonomous and intelligent Precision Space Health system that will monitor, aggregate, and assess biomedical statuses; analyze and predict personalized adverse health outcomes; adapt and respond to newly accumulated data; and provide preventive, actionable, and timely insights to individual deep space crew members and iterative decision support to their crew medical officer. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration, on future applications of artificial intelligence in space biology and health. In the next decade, biomonitoring technology, biomarker science, spacecraft hardware, intelligent software, and streamlined data management must mature and be woven together into a Precision Space Health system to enable humanity to thrive in deep space.

q-bio.OT↗
arXiv2021

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space.

q-bio.OT↗
arXiv2021

Analysis of animal-related electric outages using species distribution models and community science data

Animal-related outages (AROs) are a prevalent form of outages in electrical distribution systems. Animal-infrastructure interactions vary across focal species and regions, underlining the need to study the animal-outage relationship in more species and diverse systems. Animal activity has been used as an indicator of reliability in the electrical grid system and to describe temporal patterns in AROs. However, these ARO models have been limited by a lack of available estimates of species activity, instead approximating activity based on seasonal and weather patterns in animal-related outage records and characteristics of broad taxonomic groups, e.g., squirrels. We highlight publicly available resources to fill the ecological data gap that is limiting joint analyses between ecology and energy sectors. Species distribution models (SDMs), a common technique to model the distribution of a species across geographic space and time, paired with data sourced from eBird, a community science database for bird observations, provided us with species-specific estimates of activity to model spatio-temporal patterns of AROs. These flexible, species-specific estimates can allow future animal-indicators of grid reliability to be investigated in more diverse regions and ecological communities, providing a better understanding of the variation that exists in animal-outage relationship. AROs were best modeled by accounting for multiple outage-prone species activity patterns and their unique relationships with seasonality and habitat availability. Different species were important for modeling outages in different landscapes and seasons depending on their distribution and migration behavior. We recommend that future models of AROs include species-specific activity data that account for the diverse spectrum of spatio-temporal activity patterns that outage-prone animals exhibit.

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