A computational exploration of resilience and evolvability of protein–protein interaction networks

Protein–protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype’s PPI network’s resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks’ resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms—random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits.

Relationship between financial innovation, financial depth, and economic growth

The intrinsic property of modern economic development is financial deepening in the light of incremental spearheading financial innovation opportunities. The paper deals with the relationship between financial depth, financial innovation, and economic growth among 22 OECD economies over 2007–2018 by applying pooled OLS and fixed effect panel data regression analysis. The purpose of the paper is to empirically test whether the economic growth depends on financial depth, financial innovation, and institutional environment (Worldwide Governance Indicators). The findings shed light on the recent discussion on the pros and cons of financial innovation. The estimation results show that while financial depth is a strong predictor of economic growth across high- and upper-middle-income economies, financial innovation is a slightly weaker predictor. Despite the identified positive impact of financial innovation on economic growth, it is asserted that the negative effect of financial depth may indicate oversaturated financial market in developed countries. Сonsistent with the general notion that the institutional framework promotes the capacity of the financial sector for financial innovations implementation, this paper states that financial depth and financial innovations are better prerequisites of economic growth than institutional development. AcknowledgmentThe paper was funded as a part of the “Relationship between financial depth and economic growth in Ukraine” research project (No. 0121U110766), conducted in the State Institution “Institute for Economics and Forecasting of the NAS of Ukraine”.

Atrial fibrillation detection in outpatient electrocardiogram monitoring: An algorithmic crowdsourcing approach

Background Atrial fibrillation (AFib) is the most common cardiac arrhythmia associated with stroke, blood clots, heart failure, coronary artery disease, and/or death. Multiple methods have been proposed for AFib detection, with varying performances, but no single approach appears to be optimal. We hypothesized that each state-of-the-art algorithm is appropriate for different subsets of patients and provides some independent information. Therefore, a set of suitably chosen algorithms, combined in a weighted voting framework, will provide a superior performance to any single algorithm. Methods We investigate and modify 38 state-of-the-art AFib classification algorithms for a single-lead ambulatory electrocardiogram (ECG) monitoring device. All algorithms are ranked using a random forest classifier and an expert-labeled training dataset of 2,532 recordings. The seven top-ranked algorithms are combined by using an optimized weighting approach. Results The proposed fusion algorithm, when validated on a separate test dataset consisting of 4,644 recordings, resulted in an area under the receiver operating characteristic (ROC) curve of 0.99. The sensitivity, specificity, positive-predictive-value (PPV), negative-predictive-value (NPV), and F1-score of the proposed algorithm were 0.93, 0.97, 0.87, 0.99, and 0.90, respectively, which were all superior to any single algorithm or any previously published. Conclusion This study demonstrates how a set of well-chosen independent algorithms and a voting mechanism to fuse the outputs of the algorithms, outperforms any single state-of-the-art algorithm for AFib detection. The proposed framework is a case study for the general notion of crowdsourcing between open-source algorithms in healthcare applications. The extension of this framework to similar applications may significantly save time, effort, and resources, by combining readily existing algorithms. It is also a step toward the democratization of artificial intelligence and its application in healthcare.

Set in Perception

<p>When a person is set, he is said to be prepared for narrowed range of possible events. Instead of being equally prepared for all possible contingencies, he expects only a few. The general notion has been variously expressed as selective attention, specific expectancies or hypotheses, relative sensitisation, abstraction, perceptual bias, and in many other ways. Set, as a result of such preparation, is said to lead to greater efficiency of perception, and to greater efficiency of any later behaviour dependent upon the perception.</p>

Set in Perception

<p>When a person is set, he is said to be prepared for narrowed range of possible events. Instead of being equally prepared for all possible contingencies, he expects only a few. The general notion has been variously expressed as selective attention, specific expectancies or hypotheses, relative sensitisation, abstraction, perceptual bias, and in many other ways. Set, as a result of such preparation, is said to lead to greater efficiency of perception, and to greater efficiency of any later behaviour dependent upon the perception.</p>

Counterexamples to the Maximum Force Conjecture

Dimensional analysis shows that the speed of light and Newton’s constant of gravitation can be combined to define a quantity F*=c4/GN with the dimensions of force (equivalently, tension). Then in any physical situation we must have Fphysical=fF*, where the quantity f is some dimensionless function of dimensionless parameters. In many physical situations explicit calculation yields f=O(1), and quite often f≤1/4. This has led multiple authors to suggest a (weak or strong) maximum force/maximum tension conjecture. Working within the framework of standard general relativity, we will instead focus on idealized counter-examples to this conjecture, paying particular attention to the extent to which the counter-examples are physically reasonable. The various idealized counter-examples we shall explore strongly suggest that one should not put too much credence into any truly universal maximum force/maximum tension conjecture. Specifically, idealized fluid spheres on the verge of gravitational collapse will generically violate the weak (and strong) maximum force conjectures. If one wishes to retain any truly general notion of “maximum force” then one will have to very carefully specify precisely which forces are to be allowed within the domain of discourse.

Genome-wide estimation of recombination, mutation and positive selection enlightens diversification drivers of Mycobacterium bovis

Genome sequencing has reinvigorated the infectious disease research field, shedding light on disease epidemiology, pathogenesis, host–pathogen interactions and also evolutionary processes exerted upon pathogens. Mycobacterium tuberculosis complex (MTBC), enclosing M. bovis as one of its animal-adapted members causing tuberculosis (TB) in terrestrial mammals, is a paradigmatic model of bacterial evolution. As other MTBC members, M. bovis is postulated as a strictly clonal, slowly evolving pathogen, with apparently no signs of recombination or horizontal gene transfer. In this work, we applied comparative genomics to a whole genome sequence (WGS) dataset composed by 70 M. bovis from different lineages (European and African) to gain insights into the evolutionary forces that shape genetic diversification in M. bovis. Three distinct approaches were used to estimate signs of recombination. Globally, a small number of recombinant events was identified and confirmed by two independent methods with solid support. Still, recombination reveals a weaker effect on M. bovis diversity compared with mutation (overall r/m = 0.037). The differential r/m average values obtained across the clonal complexes of M. bovis in our dataset are consistent with the general notion that the extent of recombination may vary widely among lineages assigned to the same taxonomical species. Based on this work, recombination in M. bovis cannot be excluded and should thus be a topic of further effort in future comparative genomics studies for which WGS of large datasets from different epidemiological scenarios across the world is crucial. A smaller M. bovis dataset (n = 42) from a multi-host TB endemic scenario was then subjected to additional analyses, with the identification of more than 1,800 sites wherein at least one strain showed a single nucleotide polymorphism (SNP). The majority (87.1%) was located in coding regions, with the global ratio of non-synonymous upon synonymous alterations (dN/dS) exceeding 1.5, suggesting that positive selection is an important evolutionary force exerted upon M. bovis. A higher percentage of SNPs was detected in genes enriched into “lipid metabolism”, “cell wall and cell processes” and “intermediary metabolism and respiration” functional categories, revealing their underlying importance in M. bovis biology and evolution. A closer look on genes prone to horizontal gene transfer in the MTBC ancestor and included in the 3R (DNA repair, replication and recombination) system revealed a global average negative value for Taijima’s D neutrality test, suggesting that past selective sweeps and population expansion after a recent bottleneck remain as major evolutionary drivers of the obligatory pathogen M. bovis in its struggle with the host.

Categorical Nonstandard Analysis

In the present paper, we propose a new axiomatic approach to nonstandard analysis and its application to the general theory of spatial structures in terms of category theory. Our framework is based on the idea of internal set theory, while we make use of an endofunctor U on a topos of sets S together with a natural transformation υ, instead of the terms as “standard”, “internal”, or “external”. Moreover, we propose a general notion of a space called U-space, and the category USpace whose objects are U-spaces and morphisms are functions called U-spatial morphisms. The category USpace, which is shown to be Cartesian closed, gives a unified viewpoint toward topological and coarse geometric structure. It will also be useful to further study symmetries/asymmetries of the systems with infinite degrees of freedom, such as quantum fields.

Higher-order probabilistic adversarial computations: categorical semantics and program logics

Adversarial computations are a widely studied class of computations where resource-bounded probabilistic adversaries have access to oracles, i.e., probabilistic procedures with private state. These computations arise routinely in several domains, including security, privacy and machine learning. In this paper, we develop program logics for reasoning about adversarial computations in a higher-order setting. Our logics are built on top of a simply typed λ-calculus extended with a graded monad for probabilities and state. The grading is used to model and restrict the memory footprint and the cost (in terms of oracle calls) of computations. Under this view, an adversary is a higher-order expression that expects as arguments the code of its oracles. We develop unary program logics for reasoning about error probabilities and expected values, and a relational logic for reasoning about coupling-based properties. All logics feature rules for adversarial computations, and yield guarantees that are valid for all adversaries that satisfy a fixed resource policy. We prove the soundness of the logics in the category of quasi-Borel spaces, using a general notion of graded predicate liftings, and we use logical relations over graded predicate liftings to establish the soundness of proof rules for adversaries. We illustrate the working of our logics with simple but illustrative examples.

How the Extended Theory of Planned Behavior Can be Applied in the Research of the Influencing Factors of Food Waste in Restaurants: Learning from Serbian Urban Centers

This study is based on the general notion that restaurants should find more responsible solutions to dispose of the large amount of food that is not consumed. Moreover, the food wasted has great environmental, social and financial impacts, and yet this issue is still insufficiently presented in contemporary studies on food waste management. This paper applied the extended theory of planned behavior as a theoretical framework to elicit consumers’ behavior concerning food waste. A standard paper and pen survey recorded quantitative data provided by 221 respondents. The findings reported the following: (1) personal attitudes toward food waste positively affect an individual’s intention not to waste food; (2) perceived behavioral control positively affects an individual’s intention not to waste food; (3) the intention not to waste food negatively affects self-reported food waste behavior; (4) negative environmental attitudes negatively affect intention not to waste food; (5) hygiene-based food waste negatively affects perceived behavioral control. This study contributes to understanding consumers’ food waste behavior in restaurants and might have practical implications in the hospitality sector.