Feedbacks between size and density determine rapid eco-phenotypic dynamics
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Environmental Sciences & Ecology↗
SEARCH · Engineering Papers
Results for “causality”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Inhibition of USP7 activity selectively eliminates senescent cells in part via restoration of p53 activity
The accumulation of senescent cells (SnCs) is a causal factor of various age-related diseases as well as some of the side effects of chemotherapy. Pharmacological elimination of SnCs (senolysis) has the potential to be developed into novel therapeutic strategies to treat these diseases and pathological conditions. Here we show that ubiquitin-specific peptidase 7 (USP7) is a novel target for senolysis because inhibition of USP7 with an inhibitor or genetic depletion of USP7 by RNA interference induces apoptosis selectively in SnCs. The senolytic activity of USP7 inhibitors is likely attributable in part to the promotion of the human homolog of mouse double minute 2 (MDM2) ubiquitination and degradation by the ubiquitin–proteasome system. This degradation increases the levels of p53, which in turn induces the pro-apoptotic proteins PUMA, NOXA, and FAS and inhibits the interaction of BCL-XL and BAK to selectively induce apoptosis in SnCs. Further, we show that treatment with a USP7 inhibitor can effectively eliminate SnCs and suppress the senescence-associated secretory phenotype (SASP) induced by doxorubicin in mice. These findings suggest that small molecule USP7 inhibitors are novel senolytics that can be exploited to reduce chemotherapy-induced toxicities and treat age-related diseases.
59 BASIC BIOLOGICAL SCIENCES↗
Age-related telomere attrition causes aberrant gene expression in sub-telomeric regions
Telomere attrition has been proposed as a biomarker and causal factor in aging. In addition to causing cellular senescence and apoptosis, telomere shortening has been found to affect gene expression in subtelomeric regions. Here, we analyzed the distribution of age-related differentially expressed genes from the GTEx RNA sequencing database of 54 tissue types from 979 human subjects and found significantly more upregulated than downregulated genes in subtelomeric regions as compared to the genome-wide average. Our data demonstrate spatial relationships between telomeres and gene expression in aging.
59 BASIC BIOLOGICAL SCIENCES↗
Rapid assessment of beech leaf disease in Fagus sylvatica buds
Abstract The European beech (Fagus sylvatica) is threatened by the foliar nematodeLitylenchus crenataesubsp.mccannii(Lcm), the causal agent of beech leaf disease (BLD). Thus far, the majority of studies regarding BLD have focused on American beech (F. grandifolia). To better determine the impact of Lcm in buds of European beech, a total of 54 buds were collected from naturally symptomatic trees. Here, we characterized for the first time the bud scale morphology of two different cultivars ofF. sylvaticainfected with Lcm. Detailed observations of asymptomatic and symptomatic bud scales provided insight into the physical changes and arrangements of cells in the bud scale, shedding light on the dynamic processes occurring during Lcm infection. In addition, we evaluated the suitability of using the bud scale morphology for the early detection of BLD and Lcm in naturally infected buds. The distinct cellular arrangement of symptomatic bud scales cells (i.e., asymmetric pattern of enlarged cells) provides a rapid and visual, user‐friendly methodology to prematurely diagnose BLD symptoms within the buds, as well as the detection of associated nematodes.
Forestry↗
Genetic variation associated with adult migration timing in lineages of Steelhead and Chinook Salmon in the Columbia River
Abstract With the discovery of a major effect region (GREB1L, ROCK1) for adult migration timing in genomes of both Chinook Salmon and Steelhead, several subsequent studies have investigated the effect size and distribution of early and late migration alleles among populations in the Columbia River. Here, we synthesize the results of these studies for the major lineages of Chinook Salmon and Steelhead that include highly distinct groups in the interior Columbia River that exhibit atypical life histories from most coastal lineage populations of these two species. Whole‐genome studies with high marker density have provided extensive insight into SNPs most associated with adult migration timing, and suites of markers for each species have been genotyped in large numbers of individuals to further validate phenotypic effects. For Steelhead, the largest phenotypic effect sizes have been observed in the coastal lineage (36% of variation for passage timing at Bonneville Dam; 43% of variation for tributary arrival timing) compared to the inland lineage (7.5% of variation for passage timing at Bonneville Dam; 8.4% of variation for tributary arrival timing) that overwinter in freshwater prior to spawning. For Chinook Salmon, large effect sizes have been observed in all three lineages for multiple adult migration phenotypes (Coastal lineage: percentage of variation of 27.9% for passage timing at Bonneville Dam, 28.7% for arrival timing for spawning; Interior ocean type: percentage of variation of 47.6% for passage timing at Bonneville Dam, 39.6% for tributary arrival timing, 77.9% for arrival timing for spawning; Interior stream type: percentage of variation of 35.3% for passage at Bonneville Dam, 9.8% for tributary arrival timing, 4.7% for arrival timing for spawning). Together, these results have extended our understanding of genetic variation associated with life history diversity in distinct populations of the Columbia River, however, much research remains necessary to determine the causal mechanism for this major effect region on migration timing in these species.
Narum, Shawn R.↗
Plant defensin MtDef4–derived antifungal peptide with multiple modes of action and potential as a bio–inspired fungicide
Chemical fungicides have been instrumental in protecting crops from fungal diseases. However, increasing fungal resistance to many of the single-site chemical fungicides calls for the development of new antifungal agents with novel modes of action (MoA). The sequence-divergent cysteine-rich antifungal defensins with multisite MoA are promising starting templates for design of novel peptide-based fungicides. Here, we experimentally tested such a set of 17-amino-acid peptides containing the γ-core motif of the antifungal plant defensin MtDef4. These designed peptides exhibited antifungal properties different from those of MtDef4. Focused analysis of a lead peptide, GMA4CG_V6, showed that it was a random coil in solution with little or no secondary structure elements. Additionally, it exhibited potent cation-tolerant antifungal activity against the plant fungal pathogen Botrytis cinerea, the causal agent of grey mould disease in fruits and vegetables. Its multisite MoA involved localization predominantly to the plasma membrane, permeabilization of the plasma membrane, rapid internalization into the vacuole and cytoplasm, and affinity for the bioactive phosphoinositides phosphatidylinositol 3-phosphate (PI3P), PI4P, and PI5P. The sequence motif RRRW was identified as a major determinant of the antifungal activity of this peptide. While topical spray application of GMA4CG_V6 on Nicotiana benthamiana and tomato plants provided preventive and curative suppression of grey mould disease symptoms, the peptide was not internalized into plant cells. Our findings open the possibility that truncated and modified defensin-derived peptides containing the γ-core sequence could serve as promising candidates for further development of bio-inspired fungicides.
54 ENVIRONMENTAL SCIENCES↗
Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach
Summary Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO 2 . We developed a 3D reaction‐diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO 2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf‐level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO 2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.
59 BASIC BIOLOGICAL SCIENCES↗
BUZZ : an essential gene for postinitiation root hair growth and a mediator of root architecture in Brachypodium distachyon
Here, we discover a player in root development. Recovered from a forward-genetic screen in Brachypodium distachyon, the buzz mutant initiates root hairs but they fail to elongate. In addition, buzz roots grow twice as fast as wild-type roots. Also, lateral roots show increased sensitivity to nitrate, whereas primary roots are less sensitive to nitrate. Using whole-genome resequencing, we identified the causal single nucleotide polymorphism as occurring in a conserved but previously uncharacterized cyclin-dependent kinase (CDK)-like gene. The buzz mutant phenotypes are rescued by the wild-type B. distachyon BUZZ coding sequence and by an apparent homolog in Arabidopsis thaliana. Moreover, T-DNA mutants in A. thaliana BUZZ have shorter root hairs. BUZZ mRNA localizes to epidermal cells and develops root hairs and, in the latter, partially colocalizes with the NRT1.1A nitrate transporter. Based on qPCR and RNA-Seq, buzz overexpresses ROOT HAIRLESS LIKE SIX-1 and -2 and misregulates genes related to hormone signaling, RNA processing, cytoskeletal, and cell wall organization, and to the assimilation of nitrate. Overall, these data demonstrate that BUZZ is required for tip growth after root hair initiation and root architectural responses to nitrate.
59 BASIC BIOLOGICAL SCIENCES↗
Soybean ( Glycine max ) Haplotype Map (GmHapMap): a universal resource for soybean translational and functional genomics
Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole-genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single-nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1-Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene-centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss-of-function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.
54 ENVIRONMENTAL SCIENCES↗
A common resequencing‐based genetic marker data set for global maize diversity
SUMMARY Maize ( Zea mays ssp. mays ) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole‐genome resequencing strategies, identifying millions of segregating single‐nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high‐confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering‐time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.
59 BASIC BIOLOGICAL SCIENCES↗
Understanding Laser Powder Bed Fusion Surface Roughness
Abstract Surface roughness is a well-known consequence of additive manufacturing methods, particularly powder bed fusion processes. To properly design parts for additive manufacturing, a comprehensive understanding of the inherent roughness is necessary. While many researchers have measured different surface roughness resultant from a variety of parameters in the laser powder bed fusion process, few have succeeded in determining causal relationships due to the large number of variables at play. To assist the community in understanding the roughness in laser powder bed fusion processes, this study explored several studies from the literature to identify common trends and discrepancies amongst roughness data. Then, an experimental study was carried out to explore the influence of certain process parameters on surface roughness. Through these comparisons, certain local and global roughness trends have been identified and discussed, as well as a new framework for considering the effect of process parameters on surface roughness.
Engineering↗
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics
Abstract Advancements in computing power have recently made it possible to utilize machine learning and deep learning to push scientific computing forward in a range of disciplines, such as fluid mechanics, solid mechanics, materials science, etc. The incorporation of neural networks is particularly crucial in this hybridization process. Due to their intrinsic architecture, conventional neural networks cannot be successfully trained and scoped when data are sparse, which is the case in many scientific and engineering domains. Nonetheless, neural networks provide a solid foundation to respect physics-driven or knowledge-based constraints during training. Generally speaking, there are three distinct neural network frameworks to enforce the underlying physics: (i) physics-guided neural networks (PgNNs), (ii) physics-informed neural networks (PiNNs), and (iii) physics-encoded neural networks (PeNNs). These methods provide distinct advantages for accelerating the numerical modeling of complex multiscale multiphysics phenomena. In addition, the recent developments in neural operators (NOs) add another dimension to these new simulation paradigms, especially when the real-time prediction of complex multiphysics systems is required. All these models also come with their own unique drawbacks and limitations that call for further fundamental research. This study aims to present a review of the four neural network frameworks (i.e., PgNNs, PiNNs, PeNNs, and NOs) used in scientific computing research. The state-of-the-art architectures and their applications are reviewed, limitations are discussed, and future research opportunities are presented in terms of improving algorithms, considering causalities, expanding applications, and coupling scientific and deep learning solvers.
Computer Science↗
Atomic step disorder on polycrystalline surfaces leads to spatially inhomogeneous work functions
Structural disorder causes materials’ surface electronic properties, e.g., work function (ϕ), to vary spatially, yet it is challenging to prove exact causal relationships to underlying ensemble disorder, e.g., roughness or granularity. For polycrystalline Pt, nanoscale resolution photoemission threshold mapping reveals a spatially varying ϕ=5.70±0.03 eV over a distribution of (111) vicinal grain surfaces prepared by sputter deposition and annealing. With regard to field emission and related phenomena, e.g., vacuum arc initiation, a salient feature of the ϕ distribution is that it is skewed with a long tail to values down to 5.4 eV, i.e., far below the mean, which is exponentially impactful to field emission via the Fowler–Nordheim relation. We show that the ϕ spatial variation and distribution can be explained by ensemble variations of granular tilts and surface slopes via a Smoluchowski smoothing model wherein local ϕ variations result from spatially varying densities of electric dipole moments, intrinsic to atomic steps, that locally modify ϕ. Atomic step-terrace structure is confirmed with scanning tunneling microscopy (STM) at several locations on our surfaces, and prior works showed STM evidence for atomic step dipoles at various metal surfaces. From our model, we find an atomic step edge dipole μ=0.12 D/edge atom, which is comparable to values reported in studies that utilized other methods and materials. Our results elucidate a connection between macroscopic ϕ and the nanostructure that may contribute to the spread of reported ϕ for Pt and other surfaces and may be useful toward more complete descriptions of polycrystalline metals in the models of field emission and other related vacuum electronics phenomena, e.g., arc initiation.
36 MATERIALS SCIENCE↗
Identification of driver genes for critical forms of COVID-19 in a deeply phenotyped young patient cohort
The drivers of critical coronavirus disease 2019 (COVID-19) remain unknown. Given major confounding factors such as age and comorbidities, true mediators of this condition have remained elusive. We used a multi-omics analysis combined with artificial intelligence in a young patient cohort where major comorbidities were excluded at the onset. The cohort included 47 “critical” (in the intensive care unit under mechanical ventilation) and 25 “non-critical” (in a non-critical care ward) patients with COVID-19 and 22 healthy individuals. The analyses included whole-genome sequencing, whole-blood RNA sequencing, plasma and blood mononuclear cell proteomics, cytokine profiling, and high-throughput immunophenotyping. An ensemble of machine learning, deep learning, quantum annealing, and structural causal modeling were used. Patients with critical COVID-19 were characterized by exacerbated inflammation, perturbed lymphoid and myeloid compartments, increased coagulation, and viral cell biology. Among differentially expressed genes, we observed up-regulation of the metalloprotease ADAM9. This gene signature was validated in a second independent cohort of 81 critical and 73 recovered patients with COVID-19 and was further confirmed at the transcriptional and protein level and by proteolytic activity. Ex vivo ADAM9 inhibition decreased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake and replication in human lung epithelial cells. In conclusion, within a young, otherwise healthy, cohort of individuals with COVID-19, we provide the landscape of biological perturbations in vivo where a unique gene signature differentiated critical from non-critical patients. We further identified ADAM9 as a driver of disease severity and a candidate therapeutic target.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Laboratory evolution in Novosphingobium aromaticivorans enables rapid catabolism of a model lignin-derived aromatic dimer
Lignin contains a variety of interunit linkages, leading to a range of potential decomposition products that can be used as carbon and energy sources by microbes. β-O-4 linkages are the most common in native lignin, and associated catabolic pathways have been well characterized. However, the fate of the mono-aromatic intermediates that result from β-O-4 dimer cleavage has not been fully elucidated. Here, we used experimental evolution to identify mutant strains of Novosphingobium aromaticivorans with improved catabolism of a model aromatic dimer containing a β-O-4 linkage, guaiacylglycerol-β-guaiacyl ether (GGE). We identified several parallel causal mutations, including a single nucleotide polymorphism in the promoter of an uncharacterized gene that roughly doubled the growth yield with GGE. We characterized the associated enzyme and demonstrated that it oxidizes an intermediate in GGE catabolism, β-hydroxypropiovanillone, to vanilloyl acetaldehyde. Identification of this enzyme and its key role in GGE catabolism furthers our understanding of catabolic pathways for lignin-derived aromatic compounds.
59 BASIC BIOLOGICAL SCIENCES↗
Novel scalings of neutron star properties from analyzing dimensionless Tolman–Oppenheimer–Volkoff equations
The Tolman–Oppenheimer–Volkoff (TOV) equations govern the radial evolution of pressure and energy density in static neutron stars (NSs) in hydrodynamical equilibrium. Using the reduced pressure and energy density with respect to the NS central energy density, the original TOV equations can be recast into dimensionless forms. While the traditionally used integral approach for solving the original TOV equations require an input nuclear Equation of State (EOS), the dimensionless TOV equations can be anatomized by using the reduced pressure and energy density as polynomials of the reduced radial coordinate without using any input nuclear EOS. It has been shown in several of our recent works that interesting and novel perspectives about NS core EOS can be extracted directly from NS observables by using the latter approach. Our approach is based on intrinsic and perturbative analyses of the dimensionless (IPAD) TOV equations (IPAD-TOV). In this review article, we first discuss the length and energy density scales of NSs as well as the dimensionless TOV equations for scaled variables and their perturbative solutions near NS cores. We then review several new insights into NS physics gained from solving perturbatively the scaled TOV equations. Whenever appropriate, comparisons with the traditional approach from solving the original TOV equations will be made. In particular, we first show that the nonlinearity of the TOV equations basically excludes a linear EOS for dense matter in NS cores. We then show that perturbative analyses of the scaled TOV equations enable us to reveal novel scalings of the NS mass, radius and the compactness with certain combinations of the NS central pressure and energy density. Thus, observational data on either mass, radius or compactness can be used to constrain directly the core EOS of NS matter independent of the still very uncertain nuclear EOS models. As examples, the EOS of the densest visible matter in our Universe before the most massive neutron stars collapse into black holes (BHs) as well as the central EOS of a canonical or a 2.1 solar mass NS are extracted without using any nuclear EOS model. In addition, we show that causality in NSs sets an upper bound of about 0.374 for the ratio of pressure over energy density and correspondingly a lower limit for trace anomaly in supra-dense matter. We also demonstrate that the strong-field gravity plays a fundamental role in extruding a peak in the density/radius profile of the speed of sound squared (SSS) in massive NS cores independent of the nuclear EOS. Finally, some future perspectives of NS research using the new approach reviewed here by solving perturbatively the dimensionless TOV equations are outlined.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
On completeness and generalized symmetries in quantum field theory
We review a notion of completeness in QFT arising from the analysis of basic properties of the set of operator algebras attached to regions. In words, this completeness asserts that the physical observable algebras produced by local degrees of freedom are the maximal ones compatible with causality. We elaborate on equivalent statements to this completeness principle such as the non-existence of generalized symmetries and the uniqueness of the net of algebras. We clarify that for non-complete theories, the existence of generalized symmetries is unavoidable and further that they always come in dual pairs with precisely the same “size”. Moreover, the dual symmetries are always broken together, be it explicitly or effectively. Finally, we comment on several issues raised in recent literature, such as the relationship between completeness and modular invariance, dense sets of charges, and absence of generalized symmetries in the bulk of holographic theories.
Astronomy & Astrophysics↗
The vecro hypothesis
We consider three fundamental issues in quantum gravity: (a) the black hole information paradox (b) the unboundedness of entropy that can be stored inside a black hole horizon (c) the relation between the black hole horizon and the cosmological horizon. With help from the small corrections theorem, we convert each of these issues into a sharp conflict. We then argue that all three conflicts can be resolved by the following hypothesis: the vacuum wave functional of quantum gravity contains a “vecro” component made of virtual fluctuations of configurations of the same type that arise in the fuzzball structure of black hole microstates. Further, if we assume that causality holds to leading order in gently curved spacetime, then we must have such a vecro component in order to resolve the above conflicts. The term vecro stands for “Virtual Extended Compression-Resistant Object”, and characterizes the nature of the vacuum fluctuations that resolve the puzzles. It is interesting that puzzle (c) may relate the role of quantum gravity in black holes to observations in the sky.
Astronomy & Astrophysics↗