Pace Of Discovery Research Articles

PERSPECTIVES FOR THE DEVELOPMENT OF SCIENCE IN THE SOCIETY

The world has never been so open to scientific research and technological development as it is today, nor has human competence evolved so rapidly in directions not previously appreciated. The pace of discoveries is faster, although there are scientific fields in which goals are achieved more slowly and with considerable collective effort. However, we find that the successes achieved in the field of science have had an enormous impact on people's mentality and as a consequence have formed the belief that reflects science as a dominant factor in contemporary society. A philosophical reflection on the process of scientific development reveals that for a long time, the physical sciences have been dominant, and in recent years we are witnessing a fulminating development of biology (genetics), which has not only economic implications but also the ethical implications of a major importance. At the same time, the contemporary society of information and knowledge attests to obvious factors of a unique phenomenon called integrative science. It is projected at the integrative frontier of the astrophysics field that combines the processes of the universe constitution as a quantum system (processes that go beyond the theory of quantum mechanics, but also the theory of super lathes) and the processes of life, mind and consciousness. Integrative science proposes a new understanding of reality, even the one considered today purely structural. We hope that integrative science theories will reflect the reality that includes Consciousness as a fundamental factor of Existence.

Efficient storage and regression computation for population-scale genome sequencing studies.

In the era of big data in human genetics, large-scale biobanks aggregating genetic data from diverse populations have emerged as important for advancing our understanding of human health and disease. However, the computational and storage demands of whole genome sequencing (WGS) studies pose significant challenges, especially for researchers from underfunded institutions or developing countries, creating a disparity in research capabilities. We introduce new approaches that significantly enhance computational efficiency and reduce data storage requirements for WGS studies. By developing algorithms for compressed storage of genetic data, focusing particularly on optimising the representation of rare variants, and designing regression methods tailored for the scale and complexity of WGS data, we significantly lower computational and storage costs. We integrate our approach into PLINK 2.0. The implementation demonstrates considerable reductions in storage space and computational time without compromising analytical accuracy, as evidenced by the application to the AllofUs project data. We optimized the runtime of an exome-wide association analysis involving 19.4 million variants and the body mass index phenotype of 125,077 individuals, reducing it from 695.35 minutes (approximately 11.5 hours) on a single machine to just 1.57 minutes using 30 GB of memory and 50 threads (or 8.67 minutes with 4 threads). Additionally, we extended this approach to support multi-phenotype analyses. We anticipate that our approach will enable researchers across the globe to unlock the potential of population biobanks, accelerating the pace of discoveries that can improve our understanding of human health and disease.

Natural volatiles preventing mosquito biting: an integrated screening platform for accelerated discovery of ORco antagonists

Insect olfactory receptors are heteromeric ligand-gated cation channels composed of an obligatory receptor subunit, ORco, and one of many variable subunits, ORx, in as yet undefined molar ratios. When expressed alone ex vivo, ORco forms homotetrameric channels gated by ORco-specific ligands acting as channel agonists. Using an insect cell-based system as a functional platform for expressing mosquito odorant receptors ex vivo, we identified small molecules of natural origin acting as specific ORco channel antagonists, orthosteric or allosteric relative to a postulated ORco agonist binding site, which cause severe inhibition of olfactory function in mosquitoes. In the present communication, we have compiled common structural features of such orthosteric antagonists and developed a ligand-based pharmacophore whose properties are deemed necessary for binding to the agonist binding site and causing inhibition of ORco's biological function. In silico screening of an available collection of natural volatile compounds with the pharmacophore resulted in identification of several ORco antagonist hits. Cell-based functional screening of the same compound collection resulted in the identification of several compounds acting as orthosteric and allosteric antagonists of ORco channel function ex vivo and inducing anosmic behaviors to Aedes albopictus mosquitoes in vivo. Comparison of the in silico screening results with those of the functional assays revealed that the pharmacophore predicted correctly 7 out of the 8 confirmed orthosteric antagonists and none of the allosteric ones. Because the pharmacophore screen produced additional hits that did not cause inhibition of the ORco channel function, we also generated a Support Vector Machine (SVM) model based on two descriptors of all pharmacophore hits. Training of the SVM on the ex vivo validated compound collection resulted in the selection of the confirmed orthosteric antagonists with a very low cross-validation out-of-sample misclassification rate. Employment of the combined pharmacophore-SVM platform for in silico screening of a larger collection of olfaction-relevant volatiles produced several new hits. Functional validation of randomly selected hits and rejected compounds from this screen confirmed the power of this virtual screening platform as a convenient tool for accelerating the pace of discovery of novel vector control agents. To the best of our knowledge, this study is the first one that combines a pharmacophore with a SVM model for identification of AgamORco antagonists and specifically orthosteric ones.

Endogenous bufadienolides, mineralocorticoid receptor antagonists and fibrosis in chronic kidney disease.

Every year millions die prematurely of complications related to chronic kidney disease (CKD). Main causes of death are connected with cardiovascular (CV) complications. There is no cure for CKD although current treatment can slow the progression of the disease if diagnosed early. Fortunately, last decades have witnessed an accelerating pace of discovery regarding the cellular and molecular basis for CKD and CV disease. Novel biomarkers, including amino-terminal type III procollagen peptide (PIIINP), carboxy-terminal type I procollagen peptide (PICP), FGF23, marinobufagenin, and several miRNAs, show promise for early detection and risk stratification. In this review, we provide an overview of recent advances in the "fibrotic concept" of the etiology and pathogenesis of CKD which involves system consisting of Na/K-ATPase and its endogenous ligands including marinobufagenin which inhibits Fli1 and stimulates synthesis of collagen-1 in the vasculature. A novel treatment of CKD already involves the use of mineralocorticoid receptor antagonists capable of impairing marinobufagenin-Na/K-ATPase interactions.

Accuracy of renovo predictions on variants reclassified over time

BackgroundInterpreting the clinical consequences of genetic variants is the central problem in modern clinical genomics, for both hereditary diseases and oncology. However, clinical validation lags behind the pace of discovery, leading to distressing uncertainty for patients, physicians and researchers. This “interpretation gap” changes over time as evidence accumulates, and variants initially deemed of uncertain (VUS) significance may be subsequently reclassified in pathogenic/benign. We previously developed RENOVO, a random forest-based tool able to predict variant pathogenicity based on publicly available information from GnomAD and dbNFSP, and tested on variants that have changed their classification status over time. Here, we comprehensively evaluated the accuracy of RENOVO predictions on variants that have been reclassified over the last four years.Methodswe retrieved 16 retrospective instances of the ClinVar database, every 3 months since March 2020 to March 2024, and analyzed time trends of variant classifications. We identified variants that changed their status over time and compared RENOVO predictions generated in 2020 with the actual reclassifications.ResultsVUS have become the most represented class in ClinVar (44.97% vs. 9.75% (likely) pathogenic and 40,33% (likely) benign). The rate of VUS reclassification is linear and slow compared to the rate of VUS reporting, exponential and currently ~ 30x faster, creating a growing divide between what can be sequenced vs. what can be interpreted. Out of 10,196 VUS variants in January 2020 that have undergone a clinically meaningful reclassification to march 2024, RENOVO correctly classified 82.6% in 2020. In addition, RENOVO correctly identified the majority of the few variants that switched clinically meaningful classes (e.g., from benign to pathogenic and vice versa). We highlight variant classes and clinically relevant genes for which RENOVO provides particularly accurate estimates. In particularly, genes characterized by large prevalence of high- or low-impact variants (e.g., POLE, NOTCH1, FANCM etc.). Suboptimal RENOVO predictions mostly concern genes validated through dedicated consortia (e.g., BRCA1/2), in which RENOVO would anyway have a limited impact.ConclusionsTime trend analysis demonstrates that the current model of variant interpretation cannot keep up with variant discovery. Machine learning-based tools like RENOVO confirm high accuracy that can aid in clinical practice and research.

Next-generation multicomponent SMAs: leveraging HEA empirical parameters

Empirical rule calculation, commonly used for phase selection of high entropy alloys (HEAs), provides valuable guidelines for designing multicomponent solid solutions. It is unknown whether the technique can offer a similar design strategy for multicomponent intermetallics that undergo B2−B19′ transformation. Establishing such guidelines can significantly accelerate the pace of discovery for new shape memory alloys (SMAs) by narrowing down the search area within the vast compositional design space of multicomponent alloys. In this study, we compiled hundreds of data on medium and high-entropy NiTi-based alloys exhibiting B2−B19′ transformation. Our objective was to construct a more comprehensive Ω−δ map and locate multicomponent SMAs on it. Additionally, we conducted a thorough analysis to establish a correlation between transformation temperatures and compositional features in medium and high-entropy SMAs (ME and HE-SMAs). This correlation can be leveraged to design SMAs with targeted transformation temperatures.

Thrombotic thrombocytopenic purpura: 100 years of research on Moschcowitz syndrome

AbstractIn the 100 years since Eli Moschcowitz reported the first case of thrombotic thrombocytopenic purpura (TTP), there has been remarkable awareness and progress in the diagnosis and management of this rare blood disorder. This progress initially was the result of careful clinical observations followed by well thought-out therapeutic interventions, with dual goals of both improving outcomes and discerning the pathophysiology of TTP. The discovery of the ADAMTS13 protease set in motion the efforts to more accurately define the specific etiologies of thrombotic microangiopathies (TMAs) based on objective, scientific data rather than clinical characterizations alone. This accurate differentiation led to better and more revealing clinical trials and advancements in the treatment of TTP and other TMAs. Further advances followed and included improvements in immune-suppressive therapy and targeted therapies of immune-mediated TTP (iTTP; caplacizumab) and congenital TTP (cTTP; recombinant ADAMTS13). The longitudinal study of patients with TTP revealed the unexpected risk for long-term complications in both patients with iTTP and those with cTTP in remission. Ongoing studies aim to further understand the prevalence, mechanisms, and appropriate screening for these mood disorders, neurocognitive deficits, and cardiovascular complications that develop at remarkably high rates and are associated with a decreased life expectancy. These discoveries are a result of the collaborative efforts of investigators worldwide that have been fostered by the frequent interactions of investigators via the International TTP Working Group meetings and TMA workshops held regularly at international meetings. These efforts will support the rapid pace of discovery and improved understanding of this rare disease.

Long COVID in Brain Health Research: A Call to Action.

The COVID-19 pandemic has brought attention to the long-term consequences of the virus, particularly the persistent symptoms that characterize long COVID. This syndrome, which can last for months after the initial infection, includes a range of neurological and neuropsychiatric manifestations that have significant implications for brain health and dementia research. This review explores the current understanding of long COVID's cognitive, neurological, and psychiatric symptoms and their potential impact on brain stimulation and neuroimaging studies. It argues that researchers must adapt their study designs and screening processes to account for the confounding effects of long COVID and ensure the accuracy and reliability of their findings. To advance the understanding of this condition and its long-term effects on brain health, the review proposes a series of strategies, including the development of standardized screening tools, the investigation of underlying mechanisms, and the identification of risk factors and protective factors. It also emphasizes the importance of collaborative research efforts and international data sharing platforms in accelerating the pace of discovery and developing targeted interventions for individuals with long COVID. As the prevalence of this condition continues to grow, it is imperative that the neuroscience community comes together to address this challenge and support those affected by long COVID.

High-throughput nanopore DNA sequencing of large insert fosmid clones directly from bacterial colonies.

Fosmids and cosmids are vectors frequently used in functional metagenomic studies. With a large insert capacity (around 30 kb) they can encode dozens of cloned genes or in some cases, entire biochemical pathways. Fosmids with cloned inserts can be transferred to heterologous hosts and propagated to enable screening for new enzymes and metabolites. After screening, fosmids from clones with an activity of interest must be de novo sequenced, a critical step toward the identification of the gene(s) of interest. In this work, we present a new approach for rapid and high-throughput fosmid sequencing directly from Escherichia coli colonies without liquid culturing or fosmid purification. Our sample preparation involves fosmid amplification with phi29 polymerase and then direct nanopore sequencing using the Oxford Nanopore Technologies system. We also present a bioinformatics pipeline termed "phiXXer" that facilitates both de novo read assembly and vector trimming to generate a linear sequence of the fosmid insert. Finally, we demonstrate the accurate sequencing of 96 fosmids in a single run and validate the method using two fosmid libraries that contain cloned large insert (~30-40 kb) genomic or metagenomic DNA.IMPORTANCELarge-insert clone (fosmids or cosmids) sequencing is challenging and arguably the most limiting step of functional metagenomic screening workflows. Our study establishes a new method for high-throughput nanopore sequencing of fosmid clones directly from lysed Escherichia coli cells. It also describes a companion bioinformatic pipeline that enables de novo assembly of fosmid DNA insert sequences. The devised method widens the potential of functional metagenomic screening by providing a simple, high-throughput approach to fosmid clone sequencing that dramatically speeds the pace of discovery.

Spatial transcriptomics in health and disease.

The ability to localize hundreds of macromolecules to discrete locations, structures and cell types in a tissue is a powerful approach to understand the cellular and spatial organization of an organ. Spatially resolved transcriptomic technologies enable mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner. The rapid development of spatial transcriptomic technologies has accelerated the pace of discovery in several fields, including nephrology. Its application to preclinical models and human samples has provided spatial information about new cell types discovered by single-cell sequencing and new insights into the cell-cell interactions within neighbourhoods, and has improved our understanding of the changes that occur in response to injury. Integration of spatial transcriptomic technologies with other omics methods, such as proteomics and spatial epigenetics, will further facilitate the generation of comprehensive molecular atlases, and provide insights into the dynamic relationships of molecular components in homeostasis and disease. This Review provides an overview of current and emerging spatial transcriptomic methods, their applications and remaining challenges for the field.

Protein function prediction through multi-view multi-label latent tensor reconstruction

BackgroundIn last two decades, the use of high-throughput sequencing technologies has accelerated the pace of discovery of proteins. However, due to the time and resource limitations of rigorous experimental functional characterization, the functions of a vast majority of them remain unknown. As a result, computational methods offering accurate, fast and large-scale assignment of functions to new and previously unannotated proteins are sought after. Leveraging the underlying associations between the multiplicity of features that describe proteins could reveal functional insights into the diverse roles of proteins and improve performance on the automatic function prediction task.ResultsWe present GO-LTR, a multi-view multi-label prediction model that relies on a high-order tensor approximation of model weights combined with non-linear activation functions. The model is capable of learning high-order relationships between multiple input views representing the proteins and predicting high-dimensional multi-label output consisting of protein functional categories. We demonstrate the competitiveness of our method on various performance measures. Experiments show that GO-LTR learns polynomial combinations between different protein features, resulting in improved performance. Additional investigations establish GO-LTR’s practical potential in assigning functions to proteins under diverse challenging scenarios: very low sequence similarity to previously observed sequences, rarely observed and highly specific terms in the gene ontology.ImplementationThe code and data used for training GO-LTR is available at https://github.com/aalto-ics-kepaco/GO-LTR-prediction.

Glia Development and Function in the Nematode Caenorhabditis elegans.

The nematode Caenorhabditis elegans is a powerful experimental setting for uncovering fundamental tenets of nervous system organization and function. Its nearly invariant and simple anatomy, coupled with a plethora of methodologies for interrogating single-gene functions at single-cell resolution in vivo, have led to exciting discoveries in glial cell biology and mechanisms of glia-neuron interactions. Findings over the last two decades reinforce the idea that insights from C. elegans can inform our understanding of glial operating principles in other species. Here, we summarize the current state-of-the-art, and describe mechanistic insights that have emerged from a concerted effort to understand C. elegans glia. The remarkable acceleration in the pace of discovery in recent years paints a portrait of striking molecular complexity, exquisite specificity, and functional heterogeneity among glia. Glial cells affect nearly every aspect of nervous system development and function, from generating neurons, to promoting neurite formation, to animal behavior, and to whole-animal traits, including longevity. We discuss emerging questions where C. elegans is poised to fill critical knowledge gaps in our understanding of glia biology.

Particle separation mechanisms in suspension-feeding fishes: key questions and future directions

Key unresolved questions about particle separation mechanisms in suspension-feeding fishes are identified and discussed, focusing on areas with the potential for substantial future discovery. The published hypotheses that are explored have broad applicability to biological filtration and bioinspired improvements in commercial and industrial crossflow microfiltration processes and microfluidics. As the first synthesis of the primary literature on the particle separation mechanisms of marine, estuarine, and freshwater suspension-feeding fishes, the goals are to enable comparisons with invertebrate suspension-feeding processes, stimulate future theoretical and empirical studies, and further the development of biomimetic physical and computational fluid dynamics models. Of the eight particle separation mechanisms in suspension-feeding fishes, six have been proposed within the past twenty years (inertial lift and shear-induced migration, reduction of effective gap size by vortices, cross-step filtration, vortical flow along outer faces of gill raker plates, ricochet filtration, and lateral displacement). The pace of discovery is anticipated to continue accelerating. Multidisciplinary collaboration and integration among biologists and engineers (including chemical, mechanical, biomedical, and filtration engineering) will result in new perspectives to identify patterns and potential unifying mechanisms across the breadth of suspension-feeding fish taxa, morphology, and function.

Development of innovative activity of universities: domestic and international experience

The Republic of Kazakhstan has adopted the State Program of Industrial and Innovative Development for 2020-2025, the purpose of which is to achieve the competitiveness of the manufacturing industry in the domestic and foreign markets. The success of the implementation of this program largely depends on the combined efforts of university science, the potential of research institutes, business, with state support in the field of budget financing and in other areas. The purpose of the study is to identify the challenges facing the modern Kazakh higher education system in the context of economic modernization to increase its sustainability and competitiveness. In this regard, special attention is paid to the innovative component of any field of activity. The article, based on the study of world experience, identifies the main problems that hinder innovation activity at universities in Kazakhstan and provides recommendations on how to overcome them. As the pace of discovery and competition accelerates at the global level, universities are creating a culture in which entrepreneurship and innovative thinking are encouraged. Students under the guidance of teachers actively develop startups, striving to change society for the better by participating in social entrepreneurship. Innovative activities of universities are accompanied by the establishment of partnerships with leading companies and research institutes. The article presents the experience of leading universities in the USA, as well as universities in Central and Eastern Europe, Tokyo University (Japan) to increase the innovation activity of Kazakhstani universities. Traditional methods of analysis and synthesis, logical thinking, systematization and generalization of accumulated material were used to uncover the issues under study.

Demonstration of Two Multi‐Component Target Ablation Approaches and Their Application in Combinatorial Pulsed Laser Deposition

AbstractCombinatorial pulsed laser deposition (C‐PLD) based on segmented targets has led to new possibilities in the pace of discovery of novel advanced materials with significantly reduced deposition time and material consumption. However, fabrication of established segmented targets may be complex or not even possible for certain material combinations. In this article, two alternative C‐PLD techniques based on easy‐to‐fabricate segmented targets are presented. One approach uses two semi‐circular segments A and B with a systematic adjustable lateral shift of the target rotation axis from the target center. The other approach is based on a new target design defined by an ABA‐segmentation where B is a horizontal bar between two semi‐circular segments of A. Both approaches enable growth of discrete composition libraries. The concepts and important parameters are introduced and computer simulations as function of the geometric parameters are made to yield the expected thin film compositions. As proof‐of‐concept, the techniques are employed on the transparent, semiconducting ternary alloy zinc‐tin‐oxide. The simulations are in very good agreement with the experimental data. Physical properties of films grown by the demonstrated approaches are compared with those obtained by established PLD processes.

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The Aakashganga platform is an Open Access Platform centred on advancing and benefiting society by offering unrestricted access to the most recent research Our mission is to help expedite the pace of discovery and establish a more equitable knowledge system accessible to all

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The Aakashganga platform is an Open Access Platform centred on advancing and benefiting society by offering unrestricted access to the most recent research Our mission is to help expedite the pace of discovery and establish a more equitable knowledge system accessible to all

Temporal genome-wide fitness analysis of Mycobacterium marinum during infection reveals the genetic requirement for virulence and survival in amoebae and microglial cells.

Tuberculosis remains the most pervasive infectious disease and the recent emergence of drug-resistant strains emphasizes the need for more efficient drug treatments. A key feature of pathogenesis, conserved between the human pathogen Mycobacterium tuberculosis and the model pathogen Mycobacterium marinum, is the metabolic switch to lipid catabolism and altered expression of virulence genes at different stages of infection. This study aims to identify genes involved in sustaining viable intracellular infection. We applied transposon sequencing (Tn-Seq) to M. marinum, an unbiased genome-wide strategy combining saturation insertional mutagenesis and high-throughput sequencing. This approach allowed us to identify the localization and relative abundance of insertions in pools of transposon mutants. Gene essentiality and fitness cost of mutations were quantitatively compared between in vitro growth and different stages of infection in two evolutionary distinct phagocytes, the amoeba Dictyostelium discoideum and the murine BV2 microglial cells. In the M. marinum genome, 57% of TA sites were disrupted and 568 genes (10.2%) were essential, which is comparable to previous Tn-Seq studies on M. tuberculosis and M. bovis. Major pathways involved in the survival of M. marinum during infection of D. discoideum are related to DNA damage repair, lipid and vitamin metabolism, the type VII secretion system (T7SS) ESX-1, and the Mce1 lipid transport system. These pathways, except Mce1 and some glycolytic enzymes, were similarly affected in BV2 cells. These differences suggest subtly distinct nutrient availability or requirement in different host cells despite the known predominant use of lipids in both amoeba and microglial cells.IMPORTANCEThe emergence of biochemically and genetically tractable host model organisms for infection studies holds the promise to accelerate the pace of discoveries related to the evolution of innate immunity and the dissection of conserved mechanisms of cell-autonomous defenses. Here, we have used the genetically and biochemically tractable infection model system Dictyostelium discoideum/Mycobacterium marinum to apply a genome-wide transposon-sequencing experimental strategy to reveal comprehensively which mutations confer a fitness advantage or disadvantage during infection and compare these to a similar experiment performed using the murine microglial BV2 cells as host for M. marinum to identify conservation of virulence pathways between hosts.

Photo-induced electron paramagnetic resonance: A means to identify defects and the defect level throughout the bandgap of ultrawide bandgap semiconductors

Ultrawide bandgap semiconductors (UWBGs) provide great promise for optical devices operating in the near to deep ultraviolet, and recently they have become a viable semiconducting material for high power electronics. From the power grid to electronic vehicles, the intention is to replace massively awkward components with the convenience of a solid state electronic “chip.” Unfortunately, the challenges faced by wide bandgap electronic materials, such as GaN and SiC, increase as the bandgap increases. A point defect, for example, can take on more charge states and energy configurations. This perspective describes a method to investigate the many charge states and their associated transitions—photo-induced electron paramagnetic resonance (photo-EPR) spectroscopy. Although not new to the study of defects in semiconductors, photo-EPR studies can probe the entire ultrawide bandgap given the appropriate light source for excitation. Examples provided here cover specific defects in UWBGs, AlN, and Ga2O3. The discussion also reminds us how the rapid pace of discovery surrounding this newest class of semiconductors is due, in part, to fundamental research studies of the past, some as far back as a century ago and some based on very different materials systems.

A survey of researchers' methods sharing practices and priorities.

Missing or inaccessible information about the methods used in scientific research slows the pace of discovery and hampers reproducibility. Yet little is known about how, why, and under what conditions researchers share detailed methods information, or about how such practices vary across social categories like career stage, field, and region. In this exploratory study, we surveyed 997 active researchers about their attitudes and behaviors with respect to methods sharing. The most common approach reported by respondents was private sharing upon request, but a substantial minority (33%) had publicly shared detailed methods information independently of their research findings. The most widely used channels for public sharing were connected to peer-reviewed publications, while the most significant barriers to public sharing were found to be lack of time and lack of awareness about how or where to share. Insofar as respondents were moderately satisfied with their ability to accomplish various goals associated with methods sharing, we conclude that efforts to increase public sharing may wish to focus on enhancing and building awareness of existing solutions-even as future research should seek to understand the needs of methods users and the extent to which they align with prevailing practices of sharing.