The Advent of Generative Chemistry.
Ontology highlight
ABSTRACT:
SUBMITTER: Vanhaelen Q
PROVIDER: S-EPMC7429972 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The straightforward but unexpected relationship presented here relates crustal thickness to magma type in the Izu-Ogasawara (Bonin) and Aleutian oceanic arcs. Volcanoes along the southern segment of the Izu-Ogasawara arc and the western Aleutian arc (west of Adak) are underlain by thin crust (10-20?km). In contrast those along the northern segment of the Izu-Ogasawara arc and eastern Aleutian arc are underlain by crust ~35?km thick. Interestingly, andesite magmas dominate eruptive products from the former volcanoes and mostly basaltic lavas erupt from the latter. According to the hypothesis presented here, rising mantle diapirs stall near the base of the oceanic crust at depths controlled by the thickness of the overlying crust. Where the crust is thin, melting occurs at relatively low pressures in the mantle wedge producing andesitic magmas. Where the crust is thick, melting pressures are higher and only basaltic magmas tend to be produced. The implications of this hypothesis are: (1) the rate of continental crust accumulation, which is andesitic in composition, would have been greatest soon after subduction initiated on Earth, when most crust was thin; and (2) most andesite magmas erupted on continental crust could be recycled from "primary" andesite originally produced in oceanic arcs.
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Project description:Molecular biology owes its prominent role in the biological sciences to the tools of recombinant DNA. While the foundations of recombinant DNA were laid in the 1970s with the discovery of type II restriction endonucleases,1,2 development of robust sequencing technology3 and pioneering work on gene synthesis,4,5 it was not until the turn of the new millennium before the first complete synthetic viral genomes saw the light of day including that of hepatitis C,6 poliovirus,7 and bacteriophage PhiX174.8 Recombinant DNA has come of age as entire cellular genomes are sequenced and stored as digitized information. So what's next? One novel branch of recombinant DNA, referred to as synthetic genomics,9 is occupied with (re)construction of entire cellular genomes from virtual sequence information and using chemical components. Here we look at the most recent developments in such de novo construction. For a broader and more extensive review on genome engineering, the reader is referred to the excellent paper by Carr and Church.10.
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Project description:Chemical and mechanical pattern formation is fundamental during embryogenesis and tissue development. Yet, the underlying molecular and cellular mechanisms are still elusive in many cases. Most current theories assume that tissue development is driven by chemical processes: either as a sequence of chemical patterns each depending on the previous one, or by patterns spontaneously arising from specific chemical interactions (such as "Turing-patterns"). Within both theories, mechanical patterns are usually regarded as passive by-products of chemical pre-patters. However, several experiments question these theories, and an increasing number of studies shows that tissue mechanics can actively influence chemical patterns during development. In this study, we thus focus on the interplay between chemical and mechanical processes during tissue development. On one hand, based on recent experimental data, we develop new mechanochemical simulation models of evolving tissues, in which the full 3D representation of the tissue appears to be critical for obtaining a realistic mechanochemical behaviour. The presented modelling approach is flexible and numerically studied using state of the art finite element methods. Thus, it may serve as a basis to combine simulations with new experimental methods in tissue development. On the other hand, we apply the developed approach and demonstrate that even simple interactions between tissue mechanics and chemistry spontaneously lead to robust and complex mechanochemical patterns. Especially, we demonstrate that the main contradictions arising in the framework of purely chemical theories are naturally and automatically resolved using the mechanochemical patterning theory.
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Project description:Patterns of origination and evolution of early complex life on this planet are largely interpreted from the fossils of the Precambrian soft-bodied Ediacara Biota. These fossils occur globally and represent a diverse suite of organisms living in marine environments. Although these exceptionally preserved fossil assemblages are typically difficult to reconcile with modern phyla, examination of the morphology, ecology, and taphonomy of these taxa provides keys to their relationships with modern taxa. Within the more than 30 million y range of the Ediacara Biota, fossils of these multicellular organisms demonstrate the advent of mobility, heterotrophy by multicellular animals, skeletonization, sexual reproduction, and the assembly of complex ecosystems, all of which are attributes of modern animals. This approach to these fossils, without the constraint of attempting phylogenetic reconstructions, provides a mechanism for comparing these taxa with both living and extinct animals.
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Project description:BackgroundThe discovery of antibiotics in the mid-twentieth century marked a major transition in tuberculosis (TB) treatment and control. There are few studies describing the duration of TB disease and its treatment from the pre-chemotherapy era and little data on how these treatments changed in response to the development of effective antibiotics. The goal of this research is to understand how inpatient treatment for high incidence populations, the First Nations peoples of Saskatchewan, Canada, changed in response to increasing availability of antibiotics effective against TB. We expected that as treatment regimens transitioned from convalescence-only to triple antibiotic therapy, the length of inpatient treatment would shorten.MethodsAnalyses were performed on records of sanatoria admissions and discharges occurring between 1933 and 1959 in Saskatchewan, Canada. Year of antibiotic discovery was taken as a proxy for treatment regimen: no chemotherapy (pre-1944), mono-therapy (Streptomycin, 1944-1946), dual-therapy (Streptomycin and PAS, 1946-1952), and triple-therapy (Streptomycin, PAS, and INH 1952-). A pooled linear regression of log-transformed length of first admission as predicted by year of admission was modeled to assess the relationship between admission length and year of admission, corrected for clinical and demographic variables.ResultsFirst admission length increased 19% in the triple-therapy era as compared to the pre-chemotherapy era, from 316 days (10.4 months) to 377 days (12.4 months). After the discovery of INH (1952), we find statistically significant increases in the proportion of successfully completed therapies (0.55 versus 0.60, p = 0.035), but also in patients who left hospital against medical advice (0.19 versus 0.29, p < 0.0001), indicating that as hospitalizations lengthened, more patients chose to discharge without the sanction of their physician. The readmission rate increased from 10 to 50% of all admissions while the province-level TB-specific death rate fell from 63.1 per 10,000 in 1933 to 4.7 per 10,000 in 1958.ConclusionCounterintuitively, we find that the length of first admissions increased with the discovery of TB-treating antibiotics. Increasing admission volume and readmission rate indicate an intensification of inpatient TB treatment during this era. These analyses provide a novel estimate of the effect of changing treatment policy on sanatorium admissions in this population.
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Project description: Not available
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Project description:The majority of state-of-the-art deep learning methods are discriminative approaches, which model the conditional distribution of labels given inputs features. The success of such approaches heavily depends on high-quality labeled instances, which are not easy to obtain, especially as the number of candidate classes increases. In this paper, we study the complementary learning problem. Unlike ordinary labels, complementary labels are easy to obtain because an annotator only needs to provide a yes/no answer to a randomly chosen candidate class for each instance. We propose a generative-discriminative complementary learning method that estimates the ordinary labels by modeling both the conditional (discriminative) and instance (generative) distributions. Our method, we call Complementary Conditional GAN (CCGAN), improves the accuracy of predicting ordinary labels and is able to generate high-quality instances in spite of weak supervision. In addition to the extensive empirical studies, we also theoretically show that our model can retrieve the true conditional distribution from the complementarily-labeled data.
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Project description:There are several plausible abiotic synthetic routes from prebiotic chemical materials to ribonucleotides and even short RNA oligomers. However, for refinement of the RNA World hypothesis to help explain the origins of life on the Earth, there needs to be a manner by which such oligomers can increase their length and expand their sequence diversity. Oligomers longer than at least 10-20 nucleotides would be needed for raw material for subsequent natural selection. Here, we explore spontaneous RNA-RNA recombination as a facile means by which such length and diversity enhancement could have been realized. Motivated by the discovery that RNA oligomers stored for long periods of time in the freezer expand their lengths, we systematically investigated RNA-RNA recombination processes. In addition to one known mechanism, we discovered at least three new mechanisms. In these, one RNA oligomer acts as a splint to catalyze the hybridization of two other oligomers and facilitates the attack of a 5'-OH, a 3'-OH, or a 2'-OH nucleophile of one oligomer onto a target atom of another. This leads to the displacement of one RNA fragment and the production of new recombinant oligomers. We show that this process can explain the spontaneous emergence of sequence complexity, both in vitro and in silico.
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