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At least 649 records · Page 36

Secreted Effector Proteins of Poplar Leaf Spot and Stem Canker Pathogen Sphaerulina musiva Manipulate Plant Immunity and Contribute to Virulence in Diverse Ways

We report fungal effectors play critical roles in manipulating plant immune responses and promoting colonization. Sphaerulina musiva is a heterothallic ascomycete fungus that causes Septoria leaf spot and stem canker disease in poplar (Populus spp.) plantations. This disease can result in premature defoliation, branch and stem breakage, increased mortality, and plantation failure. However, little is known about the interaction between S. musiva and poplar. Previous work predicted 142 candidate secreted effector proteins in S. musiva (SmCSEPs), 19 of which were selected for further functional characterization in this study. SmCSEP3 induced plant cell death in Nicotiana benthamiana, while 8 out of 19 tested SmCSEPs suppressed cell death. The signal peptides of these eight SmCSEPs exhibited secretory activity in a yeast signal sequence trap assay. Confocal microscopy revealed that four of these eight SmCSEPs target both the cytoplasm and the nucleus, whereas four predominantly localize to discrete punctate structures. Pathogen challenge assays in N. benthamiana demonstrated that the transient expression of six SmCSEPs promoted Fusarium proliferatum infection. The expression of these six SmCSEP genes were induced during infection. SmCSEP2, SmCSEP13, and SmCSEP25 suppressed chitin-triggered reactive oxygen species burst and callose deposition in N. benthamiana. The candidate secreted effector proteins of S. musiva target multiple compartments in the plant cell and modulate different pattern-triggered immunity pathways.

59 BASIC BIOLOGICAL SCIENCES↗

Bioinformatics and 3D Structural Analysis of the Coronavirus Main Protease Active Site Diversity

Coronaviruses (Coronaviridae) such as SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus) and MERS‐CoV (Middle East respiratory syndrome coronavirus) have been the source of recent outbreaks and global health concerns. While vaccines have been essential for controlling the SARS‐CoV‐2 (COVID‐19) pandemic, it is uncertain whether they will be effective against future coronavirus strains. Therefore, identification or design of a broad‐spectrum drug that targets highly conserved regions of the main protease of multiple coronavirus strains is essential in the long term. As part of a virtual summer research experience with the RCSB PDB, bioinformatics tools were employed to predict and construct 3D models of the coronavirus main protease (MPro) using SARS‐CoV‐2 as the template, with a focus on mutational trends and active sites. This study focused on the active sites of MPro, a cysteine protease essential for viral assembly and replication. Sequence alignments and structure modeling of MPro structures has identified conserved regions across multiple coronavirus strains. Inhibition of MPro halts coronavirus replication, making it an ideal drug target, and studies of MPro may foster and accelerate the discovery of high affinity broad‐spectrum drugs.

Wu Wu, Amy↗

Synthetic diversity in the preparation of metallic uranium

Uranium metal is associated with several aspects of nuclear technology; it is used as fuel for research and power reactors, targets for medical isotope productions, explosive for nuclear weapons and precursors in synthetic chemistry. The study of uranium metal at the laboratory scale presents the opportunity to evaluate metallic nuclear fuels, develop new methods for metallic spent fuel reprocessing and advance the science relevant to nuclear forensics and medical isotope production. Since its first isolation in 1841, from the reaction of uranium chloride and potassium metal, uranium metal has been prepared by solid-state reactions and in solution by electrochemical, chemical and radiochemical methods. The present review summarizes the methods outlined above and describes the chemistry associated with each preparation.

36 MATERIALS SCIENCE↗

Diverse magnetic phase diagram and anomalous Hall effect in antiferromagnetic LuMn 6⁢ Sn 6

The interactions between conduction electrons and magnetism can significantly enhance the Hall signal, a phenomenon known as the anomalous Hall effect (AHE). While the AHE is generally not expected in antiferromagnets, a large AHE is observed in certain antiferromagnets with noncollinear spin textures and nonvanishing Berry curvature. In this work, we present a rich temperature and magnetic phase diagram with eight distinct magnetic phases for the antiferromagnetic kagome compound LuMn 6 Sn 6 . The Hall effect analysis in LuMn 6 Sn 6 reveals both intriguing physical phenomena and methodological challenges. In the coplanar canted antiferromagnetic phase, we observe an AHE, which likely originates from the intrinsic effects. At low temperatures, upon entering the ferromagnetic phase, the AHE sharply increases and exceeds the conventional limits expected from intrinsic mechanisms. We also demonstrate the limitations of standard experimental methods in extracting the topological contribution to the Hall effect data. In particular, we show that accounting for magnetoresistance anisotropy helps reduce spurious contribution that can mimic topological Hall signals, although it does not fully resolve it. Furthermore, these shortcomings in current approaches in partitioning the Hall response necessitate new tools to interpret transport results in complex magnetic materials such as LuMn 6 Sn 6 .

Anomalous Hall effect↗

Spectral Similarity Masks Structural Diversity at Hydrophobic Water Interfaces

The air-water and graphene-water interfaces represent quintessential examples of the liquid-gas and liquid-solid boundaries, respectively. While the sum-frequency generation (SFG) spectra of these interfaces show similarities, a consensus on their signals and interpretations has yet to be reached. Leveraging deep learning, we computed first-principles SFG spectra for both systems, addressing experimental discrepancies. Here, our findings reveal that similarities in SFG signals do not translate into comparable interfacial microscopic properties. Instead, graphene-water and air-water interfaces exhibit fundamental differences in SFG-active thicknesses, hydrogen-bonding networks, and surface dynamics. These distinctions underscore roughness suppression and electronic interactions present at the solid-liquid interface but absent at the gas-liquid interface.

Wang, Yong [Princeton Univ., NJ (United States)] (↗

Diverse electronic topography in a distorted kagome metal LaTi 3 ⁢Bi 4

Recent reports on a family of kagome metals of the form 𝐿⁢𝑛⁢Ti 3 ⁢Bi 4 (𝐿⁢𝑛 = Lanthanide) have stoked interest due to the combination of highly anisotropic magnetism and a rich electronic structure. The electronic structure near the Fermi level is proposed to exhibit Dirac points and van Hove singularities (VHSs). Here, in this manuscript, we use angle-resolved photoemission spectroscopy measurements in combination with density functional theory calculations to investigate the electronic structure of an interesting kagome metal LaTi 3 ⁢Bi 4 . Our results reveal multiple VHSs with one VHS located in the vicinity of the Fermi level. We clearly observe two flat bands, which originate from the destructive interference of wave functions within the Ti kagome motif. These flat bands and VHSs originate from Ti 𝑑 orbitals and are very responsive to the polarization of the incident beam. We notice a significant anisotropy in the electronic structure, resulting from the breaking of sixfold rotational symmetry in this material. Our findings demonstrate this member of Ti based kagome materials as a promising platform to explore novel emerging phenomena in the wider 𝐿⁢𝑛⁢Ti 3⁢ Bi 4 (𝐿⁢𝑛 = lanthanide) family.

electronic structure↗

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered a promising approach to address some challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications are contingent upon their efficient execution on the underlying hardware infrastructure. Specialized Al accelerator hardware systems have recently become available for accelerating Al applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT-2 model, and (iii) an 1,I,M-driven science use case, GenSLM. We present our findings and analyses of the models' performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, and sensitivity to gradient accumulation steps.

Emani, Murali↗

Building a Diverse and Inclusive HPC Community for Mission-Driven Team Science

The U.S. Department of Energy (DOE) has been a long-standing leader in driving advances in science and technology through advanced computing. However, DOE laboratories are currently facing urgent workforce challenges, particularly in terms of underrepresentation from key communities, including people of color, women, persons with disabilities, and first-generation scholars. This paper introduces the work carried out as part of the Exascale Computing Project (ECP) Broadening Participation Initiative, which aims to address workforce challenges through a lens that considers the distinct needs and culture of high-performance computing (HPC). The work focuses on three main efforts: hosting Intro to HPC Bootcamps, expanding the Sustainable Research Pathways (SRP) internship and workforce development program, and establishing an HPC Workforce Development and Retention Action Group. Finally, the paper also highlights various workforce efforts throughout the computational science community and explores opportunities for future work aimed at broadening participation in HPC.

97 MATHEMATICS AND COMPUTING↗

Safeguarding the Grid: Diverse Resources for Resilience [In My View]

Reports on the vulnerability of the power grid. From wildfires, hurricanes, and floods to cyberattacks, the grid is vulnerable to natural and human-made disasters, which can cause widespread outages that last from hours to months and leave lasting economic impacts. Imagine a coastal region in the United States that has just been hit by a hurricane and lost all power. Besides the electricity infrastructure going out, communications networks, rail transportation, and gasoline pumps may also stop working after the emergency event, which often delays repair efforts to the grid. Unresponsive communications make it difficult to dispatch workers to repair the grid, and missing transportation links delay shipments of replacement equipment for the grid’s restoration.

cybersecurity↗

Diverse fates of ancient horizontal gene transfers in extremophilic red algae

Abstract Horizontal genetic transfer (HGT) is a common phenomenon in eukaryotic genomes. However, the mechanisms by which HGT‐derived genes persist and integrate into other pathways remain unclear. This topic is of significant interest because, over time, the stressors that initially favoured the fixation of HGT may diminish or disappear. Despite this, the foreign genes may continue to exist if they become part of a broader stress response or other pathways. The conventional model suggests that the acquisition of HGT equates to adaptation. However, this model may evolve into more complex interactions between gene products, a concept we refer to as the ‘Integrated HGT Model’ (IHM). To explore this concept further, we studied specialized HGT‐derived genes that encode heavy metal detoxification functions. The recruitment of these genes into other pathways could provide clear examples of IHM. In our study, we exposed two anciently diverged species of polyextremophilic red algae from the Galdieria genus to arsenic and mercury stress in laboratory cultures. We then analysed the transcriptome data using differential and coexpression analysis. Our findings revealed that mercury detoxification follows a ‘one gene‐one function’ model, resulting in an indivisible response. In contrast, the ars H gene in the arsenite response pathway demonstrated a complex pattern of duplication, divergence and potential neofunctionalization, consistent with the IHM. Our research sheds light on the fate and integration of ancient HGTs, providing a novel perspective on the ecology of extremophiles.

59 BASIC BIOLOGICAL SCIENCES↗

Revisiting a ‘simple’ fungal metabolic pathway reveals redundancy, complexity and diversity

Next to d-glucose, the pentoses l-arabinose and d-xylose are the main monosaccharide components of plant cell wall polysaccharides and are therefore of major importance in biotechnological applications that use plant biomass as a substrate. Pentose catabolism is one of the best-studied pathways of primary metabolism of Aspergillus niger, and an initial outline of this pathway with individual enzymes covering each step of the pathway has been previously established. However, although growth on l-arabinose and/or d-xylose of most pentose catabolic pathway (PCP) single deletion mutants of A. niger has been shown to be negatively affected, it was not abolished, suggesting the involvement of additional enzymes. Detailed analysis of the single deletion mutants of the known A. niger PCP genes led to the identification of additional genes involved in the pathway. These results reveal a high level of complexity and redundancy in this pathway, emphasizing the need for a comprehensive understanding of metabolic pathways before entering metabolic engineering of such pathways for the generation of more efficient fungal cell factories.

59 BASIC BIOLOGICAL SCIENCES↗