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The Neurospora crassa genome has a gene cluster for the synthesis of galactosaminogalactan (GAG). The gene cluster includes the following: (1) UDP-glucose-4-epimerase to convert UDP-glucose and UDP-N-acetylglucosamine to UDP-galactose and UDP-N-acetylgalactosamine (NCU05133), (2) GAG synthase for the synthesis of an acetylated GAG (NCU05132), (3) GAG deacetylase (/NCW-1/NCU05137), (4) GH135-1, a GAG hydrolase with specificity for N-acetylgalactosamine-containing GAG (NCU05135), and (5) GH114-1, a galactosaminidase with specificity for galactosamine-containing GAG (NCU05136). The deacetylase was previously shown to be a major cell wall glycoprotein and given the name of NCW-1 (non-GPI anchored cell wall protein-1). Characterization of the polysaccharides found in the growth medium from the wild type and the GAG synthase mutant demonstrates that there is a major reduction in the levels of polysaccharides containing galactosamine and N-acetylgalactosamine in the mutant growth medium, providing evidence that the synthase is responsible for the production of a GAG. The analysis also indicates that there are other galactose-containing polysaccharides produced by the fungus. Phenotypic characterization of wild-type and mutant isolates showed that deacetylated GAG from the wild type can function as an adhesin to a glass surface and provides the fungal mat with tensile strength, demonstrating that the deacetylated GAG functions as an intercellular adhesive. The acetylated GAG produced by the deacetylase mutant was found to function as an adhesive for chitin, alumina, celite (diatomaceous earth), activated charcoal, and wheat leaf particulates. 

A burst buffer is a common method to bridge the performance gap between the I/O needs of modern supercomputing applications and the performance of the shared file system on large-scale supercomputers. However, existing I/O sharing methods require resource isolation, offline profiling, or repeated execution that significantly limit the utilization and applicability of these systems. Here we present ThemisIO, a policy-driven I/O sharing framework for a remote-shared burst buffer: a dedicated group of I/O nodes, each with a local storage device. ThemisIO preserves high utilization by implementing opportunity fairness so that it can reallocate unused I/O resources to other applications. ThemisIO accurately and efficiently allocates I/O cycles among applications, purely based on real-time I/O behavior without requiring user-supplied information or offline-profiled application characteristics. ThemisIO supports a variety of fair sharing policies, such as user-fair, size-fair, as well as composite policies, e.g., group-then-user-fair. All these features are enabled by its statistical token design. ThemisIO can alter the execution order of incoming I/O requests based on assigned tokens to precisely balance I/O cycles between applications via time slicing, thereby enforcing processing isolation. Experiments using I/O benchmarks show that ThemisIO sustains 13.5--13.7% higher I/O throughput and 19.5--40.4% lower performance variation than existing algorithms. For real applications, ThemisIO significantly reduces the slowdown by 59.1--99.8% caused by I/O interference. 

Abstract Cellulose, the main component of the plant cell wall, is synthesized by the multimeric cellulose synthase (CESA) complex (CSC). In plant cells, CSCs are assembled in the endoplasmic reticulum or Golgi and transported through the endomembrane system to the plasma membrane (PM). However, how CESA catalytic activity or conserved motifs around the catalytic core influence vesicle trafficking or protein dynamics is not well understood. Here, we used yellow fluorescent protein (YFP)-tagged AtCESA6 and created 18 mutants in key motifs of the catalytic domain to analyze how they affected seedling growth, cellulose biosynthesis, complex formation, and CSC dynamics and trafficking in Arabidopsis thaliana. Seedling growth and cellulose content were reduced by nearly all mutations. Moreover, mutations in most conserved motifs slowed CSC movement in the PM as well as delivery of CSCs to the PM. Interestingly, mutations in the DDG and QXXRW motifs affected YFP-CESA6 abundance in the Golgi. These mutations also perturbed post-Golgi trafficking of CSCs. The 18 mutations were divided into 2 groups based on their phenotypes; we propose that Group I mutations cause CSC trafficking defects, whereas Group II mutations, especially in the QXXRW motif, affect protein folding and/or CSC rosette formation. Collectively, our results demonstrate that the CESA6 catalytic domain is essential for cellulose biosynthesis as well as CSC formation, protein folding and dynamics, and vesicle trafficking. 

Abstract Stratospheric aerosol geoengineering has been proposed as a potential solution to reduce climate change and its impacts. Here, we explore the responses of the Hadley circulation (HC) intensity and the intertropical convergence zone (ITCZ) using the strategic stratospheric aerosol geoengineering, in which sulfur dioxide was injected into the stratosphere at four different locations to maintain the global-mean surface temperature and the interhemispheric and equator-to-pole temperature gradients at present-day values (baseline). Simulations show that, relative to the baseline, strategic stratospheric aerosol geoengineering generally maintains northern winter December–January–February (DJF) HC intensity under RCP8.5, while it overcompensates for the greenhouse gas (GHG)-forced southern winter June–July–August (JJA) HC intensity increase, producing a 3.5 ± 0.4% weakening. The residual change of southern HC intensity in JJA is mainly associated with stratospheric heating and tropospheric temperature response due to enhanced stratospheric aerosol concentrations. Geoengineering overcompensates for the GHG-driven northward ITCZ shifts, producing 0.7° ± 0.1° and 0.2° ± 0.1° latitude southward migrations in JJA and DJF, respectively relative to the baseline. These migrations are affected by tropical interhemispheric temperature differences both at the surface and in the free troposphere. Further strategies for reducing the residual change of HC intensity and ITCZ shifts under stratospheric aerosol geoengineering could involve minimizing stratospheric heating and restoring and preserving the present-day tropical tropospheric interhemispheric temperature differences. 

Scientific Machine Learning (SciML) is a new multidisciplinary methodology that combines the data-driven machine learning models and the principle-based computational models to improve the simulations of scientific phenomenon and uncover new scientific rules from existing measurements. This article reveals the experience of using the SciML method to discover the nonlinear dynamics that may be hard to model or be unknown in the real-world scenario. The SciML method solves the traditional principle-based differential equations by integrating a neural network to accurately model the nonlinear dynamics while respecting the scientific constraints and principles. The paper discusses the latest SciML models and apply them to the oscillator simulations and experiment. Besides better capacity to simulate, and match with the observation, the results also demonstrate a successful discovery of the hidden physics in the pendulum dynamics using SciML.