Mapping international research output within ethical, legal, and social implications (ELSI) of assisted reproductive technologies.

Purpose: Research about ethical, legal, and social implications (ELSI) of assisted reproductive technologies (ART) is influenced by cultural and value-based perspectives. It impacts regulations, funding, and clinical practice, and shapes the perception of ART in society. We analyze trends in the global literature on ELSI of ART between 1999 and 2019.

Mapping ethical, legal, & social implications (ELSI) of assisted reproductive technologies.

Purpose: A significant portion of the research on assisted reproductive technologies explores ethical, legal, and social implications. It has an impact on social perceptions, the evolution of norms of clinical practices, regulations and public funding. This paper reviews and maps the geographical distribution to test the hypothesis of geographical concentration and classifies the output by fields and topics.

A Bayesian machine scientist to aid in the solution of challenging scientific problems.

Closed-form, interpretable mathematical models have been instrumental for advancing our understanding of the world; with the data revolution, we may now be in a position to uncover new such models for many systems from physics to the social sciences. However, to deal with increasing amounts of data, we need "machine scientists" that are able to extract these models automatically from data. Here, we introduce a Bayesian machine scientist, which establishes the plausibility of models using explicit approximations to the exact marginal posterior over models and establishes its prior expectations about models by learning from a large empirical corpus of mathematical expressions.

Mapping research in assisted reproduction worldwide.

Research Question: What are the current research trends in human assisted reproduction around the world?

Design: An analysis of 26,000+ scientific publications (articles, letters and reviews) produced worldwide between 2005 and 2016. The corpus of publications indexed in PubMed was obtained by combining the Medical Subject Heading (MeSH) terms: 'Reproductive techniques', 'Reproductive medicine', 'Reproductive health', 'Fertility', 'Infertility' and 'Germ cells'. An analysis was then carried out using text mining algorithms to obtain the main topics of interest.

Metabolic plasticity in synthetic lethal mutants: Viability at higher cost.

The most frequent form of pairwise synthetic lethality (SL) in metabolic networks is known as plasticity synthetic lethality. It occurs when the simultaneous inhibition of paired functional and silent metabolic reactions or genes is lethal, while the default of the functional partner is backed up by the activation of the silent one. Using computational techniques on bacterial genome-scale metabolic reconstructions, we found that the failure of the functional partner triggers a critical reorganization of fluxes to ensure viability in the mutant which not only affects the SL pair but a significant fraction of other interconnected reactions, forming what we call a SL cluster.

Inferring propagation paths for sparsely observed perturbations on complex networks.

In a complex system, perturbations propagate by following paths on the network of interactions among the system's units. In contrast to what happens with the spreading of epidemics, observations of general perturbations are often very sparse in time (there is a single observation of the perturbed system) and in "space" (only a few perturbed and unperturbed units are observed). A major challenge in many areas, from biology to the social sciences, is to infer the propagation paths from observations of the effects of perturbation under these sparsity conditions.

V-ATPase: a master effector of E2F1-mediated lysosomal trafficking, mTORC1 activation and autophagy.

In addition to being a master regulator of cell cycle progression, E2F1 regulates other associated biological processes, including growth and malignancy. Here, we uncover a regulatory network linking E2F1 to lysosomal trafficking and mTORC1 signaling that involves v-ATPase regulation. By immunofluorescence and time-lapse microscopy we found that E2F1 induces the movement of lysosomes to the cell periphery, and that this process is essential for E2F1-induced mTORC1 activation and repression of autophagy.

Mapping high-growth phenotypes in the flux space of microbial metabolism.

Experimental and empirical observations on cell metabolism cannot be understood as a whole without their integration into a consistent systematic framework. However, the characterization of metabolic flux phenotypes is typically reduced to the study of a single optimal state, such as maximum biomass yield that is by far the most common assumption. Here, we confront optimal growth solutions to the whole set of feasible flux phenotypes (FFPs), which provides a benchmark to assess the likelihood of optimal and high-growth states and their agreement with experimental results.

The acute impact of polyphenols from Hibiscus sabdariffa in metabolic homeostasis: an approach combining metabolomics and gene-expression analyses.

We explored the acute multifunctional effects of polyphenols from Hibiscus sabdariffa in humans to assess possible consequences on the host's health. The expected dynamic response was studied using a combination of transcriptomics and metabolomics to integrate specific functional pathways through network-based methods and to generate hypotheses established by acute metabolic effects and/or modifications in the expression of relevant genes. Data were obtained from healthy male volunteers after 3 hours of ingestion of an aqueous Hibiscus sabdariffa extract.

Scaling and optimal synergy: Two principles determining microbial growth in complex media.

High-throughput experimental techniques and bioinformatics tools make it possible to obtain reconstructions of the metabolism of microbial species. Combined with mathematical frameworks such as flux balance analysis, which assumes that nutrients are used so as to maximize growth, these reconstructions enable us to predict microbial growth. Although such predictions are generally accurate, these approaches do not give insights on how different nutrients are used to produce growth, and thus are difficult to generalize to new media or to different organisms.

Cavity approach for modeling and fitting polymer stretching.

The mechanical properties of molecules are today captured by single molecule manipulation experiments, so that polymer features are tested at a nanometric scale. Yet devising mathematical models to get further insight beyond the commonly studied force-elongation relation is typically hard. Here we draw from techniques developed in the context of disordered systems to solve models for single and double-stranded DNA stretching in the limit of a long polymeric chain.

Energy metabolism and glutamate-glutamine cycle in the brain: a stoichiometric modeling perspective.

Background: The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity.

Results: We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system.

A novel methodology to estimate metabolic flux distributions in constraint-based models.

Quite generally, constraint-based metabolic flux analysis describes the space of viable flux configurations for a metabolic network as a high-dimensional polytope defined by the linear constraints that enforce the balancing of production and consumption fluxes for each chemical species in the system. In some cases, the complexity of the solution space can be reduced by performing an additional optimization, while in other cases, knowing the range of variability of fluxes over the polytope provides a sufficient characterization of the allowed configurations. There are cases, however, in which the thorough information encoded in the individual distributions of viable fluxes over the polytope is required.