624 research outputs found
Preparation, structural and magnetic characterization of trinuclear and one-dimensional cyanide-bridged Co(III)-Cu(II) complexes
341-345By employing two trans-dicyanocobolt(III) building blocks K[Co(bpb)(CN)2] (bpb2- = 1,2-bis(pyridine-2-carboxamido)benzenate), K[Co(bpmb)(CN)2] (bpmb2- = 1,2-bis(pyridine-2-carboxamido)-4-methyl-benzenate) and one 14-membered macrocycle Cu(II) compound as assembling segment, two cyanide-bridged CoIII-CuII complexes {{[Cu(cyclam)][Co(bpb)(CN)2]}ClO4}n·nCH3OH·nH2O (1) and {[Cu(cyclam)][Co(bpmb)(CN)2]2}·4H2O (2) (cyclam = 1,4,8,11-tetraazacyclotetradecane) have been successfully prepared and characterized by elemental analysis, IR spectroscopy and X-ray structure determination. Single X-ray diffraction analysis shows that complex 1 can be structurally characterized as one-dimensional cationic single chain consisting of alternating units of [Cu(cyclam)]2+ and [Co(bpb)(CN)2]- with free ClO4- as balanced anion, while complex 2 presents cyanide-bridged neutral trinuclear bimetallic structure containing Co2Cu core, giving clear information that the substitute group on the cyanide precursor has obvious influence on the structure type of the target compound. Investigation over magnetic properties of complex 1 reveals the weak antiferromagnetic coupling between the neighboring Cu(II) ions through the diamagnetic cyanide building block
Degradation of switchgrass by Bacillus subtilis 1AJ3 and expression of a beta-glycoside hydrolase
Increasing demand for carbon neutrality has led to the development of new techniques and modes of low carbon production. The utilization of microbiology to convert low-cost renewable resources into more valuable chemicals is particularly important. Here, we investigated the ability of a cellulolytic bacterium, Bacillus subtilis 1AJ3, in switchgrass lignocellulose degradation. After 5 days of culture with the strain under 37°C, cellulose, xylan, and acid-insoluble lignin degradation rates were 16.13, 14.24, and 13.91%, respectively. Gas chromatography–mass spectrometry (GC-MS) analysis and field emission scanning electron microscopy (FE-SEM) indicated that the lignin and surface of switchgrass were degraded after incubation with the bacterial strain. Strain 1AJ3 can grow well below 60°C, which satisfies the optimum temperature (50°C) condition of most cellulases; subsequent results emphasize that acid-heat incubation conditions increase the reducing sugar content in a wide range of cellulosic biomass degraded by B. subtilis 1AJ3. To obtain more reducing sugars, we focused on β-glycoside hydrolase, which plays an important role in last steps of cellulose degradation to oligosaccharides. A β-glycoside hydrolase (Bgl-16A) was characterized by cloning and expression in Escherichia coli BL21 and further determined to belong to glycoside hydrolase (GH) 16 family. The Bgl-16A had an enzymatic activity of 365.29 ± 10.43 U/mg, and the enzyme’s mode of action was explained by molecular docking. Moreover, the critical influence on temperature (50°C) of Bgl-16A also explained the high-efficiency degradation of biomass by strain under acid-heat conditions. In terms of potential applications, both the strain and the recombinant enzyme showed that coffee grounds would be a suitable and valuable substrate. This study provides a new understanding of cellulose degradation by B. subtilis 1AJ3 that both the enzyme action mode and optimum temperature limitation by cellulases could impact the degradation. It also gave new sight to unique advantage utilization in the industrial production of green manufacturing
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Protein Quality Control Acts on Folding Intermediates to Shape the Effects of Mutations on Organismal Fitness
What are the molecular properties of proteins that fall on the radar of protein quality control (PQC)? Here we mutate the E. coli’s gene encoding dihydrofolate reductase (DHFR) and replace it with bacterial orthologous genes to determine how components of PQC modulate fitness effects of these genetic changes. We find that chaperonins GroEL/ES and protease Lon compete for binding to molten globule intermediate of DHFR, resulting in a peculiar symmetry in their action: overexpression of GroEL/ES and deletion of Lon both restore growth of deleterious DHFR mutants and most of the slow-growing orthologous DHFR strains. Kinetic steady-state modeling predicts and experimentation verifies that mutations affect fitness by shifting the flux balance in cellular milieu between protein production, folding, and degradation orchestrated by PQC through the interaction with folding intermediates.Chemistry and Chemical Biolog
Accelerating Generic Graph Neural Networks via Architecture, Compiler, Partition Method Co-Design
Graph neural networks (GNNs) have shown significant accuracy improvements in
a variety of graph learning domains, sparking considerable research interest.
To translate these accuracy improvements into practical applications, it is
essential to develop high-performance and efficient hardware acceleration for
GNN models. However, designing GNN accelerators faces two fundamental
challenges: the high bandwidth requirement of GNN models and the diversity of
GNN models. Previous works have addressed the first challenge by using more
expensive memory interfaces to achieve higher bandwidth. For the second
challenge, existing works either support specific GNN models or have generic
designs with poor hardware utilization.
In this work, we tackle both challenges simultaneously. First, we identify a
new type of partition-level operator fusion, which we utilize to internally
reduce the high bandwidth requirement of GNNs. Next, we introduce
partition-level multi-threading to schedule the concurrent processing of graph
partitions, utilizing different hardware resources. To further reduce the extra
on-chip memory required by multi-threading, we propose fine-grained graph
partitioning to generate denser graph partitions. Importantly, these three
methods make no assumptions about the targeted GNN models, addressing the
challenge of model variety. We implement these methods in a framework called
SwitchBlade, consisting of a compiler, a graph partitioner, and a hardware
accelerator. Our evaluation demonstrates that SwitchBlade achieves an average
speedup of and energy savings of compared to the
NVIDIA V100 GPU. Additionally, SwitchBlade delivers performance comparable to
state-of-the-art specialized accelerators
Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study
The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer’s Disease Neuroimag-ing Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme
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