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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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620 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Direct binding of F actin to the cytoplasmic domain of the alpha 2 integrin chain in vitro

The transmembrane integrins have been shown to interact with the cytoskeleton via noncovalent binding between cytoplasmic domains (CDs) of integrin beta chains and various actin binding proteins within the focal adhesion complex. Direct or indirect integrin alpha chain CD binding to the actin cytoskeleton has not been reported. We show here that actin, as an abundant constituent of focal adhesion complex proteins isolated from fibroblasts, binds strongly and specifically to alpha 2 CD, but not to alpha 1 CD peptide. Similar specific binding to alpha 2 CD peptide was seen for highly purified F actin, free of putative actin-binding proteins. The bound complex of actin and peptide was visualized directly by coprecipitation, and actin binding was abrogated by removal of a five amino acid sequence from the alpha 2 CD peptide. Our findings may explain the earlier observation that, while integrins alpha 2 beta 1 and alpha 1 beta 1 both bind to collagen, only alpha 2 beta 1 can mediate contraction of extracellular collagen matrices.

Non-NASA Center↗
NASA NTRS1995

Staphylococcal enterotoxins bind H-2Db molecules on macrophages

We screened a panel of monoclonal antibodies against selected macrophage cell surface molecules for their ability to inhibit enterotoxin binding to major histocompatibility complex class II-negative C2D (H-2b) macrophages. Two monoclonal antibodies, HB36 and TIB126, that are specific for the alpha 2 domain of major histocompatibility complex class I, blocked staphylococcal enterotoxins A and B (SEA and SEB, respectively) binding to C2D macrophages in a specific and concentration-dependent manner. Inhibitory activities were haplotype-specific in that SEA and SEB binding to H-2k or H-2d macrophages was not inhibited by either monoclonal antibody. HB36, but not TIB126, inhibited enterotoxin-induced secretion of cytokines by H-2b macrophages. Lastly, passive protection of D-galactosamine-sensitized C2D mice by injection with HB36 antibody prevented SEB-induced death. Therefore, SEA and SEB binding to the alpha 2 domain of the H-2Db molecule induces biological activity and has physiological consequences.

Non-NASA Center↗
NASA NTRS1994

Binding and activation of major histocompatibility complex class II-deficient macrophages by staphylococcal exotoxins

Macrophages from C2D transgenic mice deficient in the expression of major histocompatibility complex (MHC) class II proteins were used to identify binding sites for superantigens distinct from the MHC class II molecule. Iodinated staphylococcal enterotoxins A and B (SEA and SEB) and exfoliative toxins A and B (ETA and ETB) bound to C2D macrophages in a concentration-dependent and competitive manner. All four toxins increased F-actin concentration within 30 s of their addition to C2D macrophages, indicating that signal transduction occurred in response to toxin in the absence of class II MHC. Furthermore, ETA, ETB, SEA, and, to a lesser extent, SEB induced C2D macrophages to produce interleukin 6. Several molecular species on C2D macrophages with molecular masses of 140, 97, 61, 52, 43, and 37 kDa bound SEA in immunoprecipitation experiments. These data indicate the presence of novel, functionally active toxin binding sites on murine macrophages distinct from MHC class II molecules.

Non-NASA Center↗
NASA NTRS1993

Mechanotransduction across the cell surface and through the cytoskeleton

Mechanical stresses were applied directly to cell surface receptors with a magnetic twisting device. The extracellular matrix receptor, integrin beta 1, induced focal adhesion formation and supported a force-dependent stiffening response, whereas nonadhesion receptors did not. The cytoskeletal stiffness (ratio of stress to strain) increased in direct proportion to the applied stress and required intact microtubules and intermediate filaments as well as microfilaments. Tensegrity models that incorporate mechanically interdependent struts and strings that reorient globally in response to a localized stress mimicked this response. These results suggest that integrins act as mechanoreceptors and transmit mechanical signals to the cytoskeleton. Mechanotransduction, in turn, may be mediated simultaneously at multiple locations inside the cell through force-induced rearrangements within a tensionally integrated cytoskeleton.

Non-NASA Center↗
NASA NTRS2003

Modelling protein functional domains in signal transduction using Maude

Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

Signal Transduction↗
NASA NTRS2005

Skeletal phenotype of growing transgenic mice that express a function-perturbing form of beta1 integrin in osteoblasts

Skeletal modeling entails the deposition of large amounts of extracellular matrix (ECM) to form structures tailored to withstand increasing mechanical loads during rapid growth. Specific ECM molecules bind to integrin receptors on the cell surface, thereby triggering a cascade of signaling events that affect critical cell functions. To evaluate the role of integrins during skeletal growth, transgenic mice were engineered to express a function-perturbing fragment of beta1 integrin consisting of the transmembrane domain and cytoplasmic tail under the control of the osteocalcin promoter (TG mice). Thus, transgene expression was targeted to mature cells of the osteoblast lineage, and herein we show that cultured cells resembling osteocytes from 90-day-old TG mice display impaired adhesion to collagen I, a ligand for beta1 integrin. To determine the influence of beta1 integrin on bones that are responsible for providing structural support during periods of rapid growth, we examined the phenotype of the appendicular skeleton in TG mice compared to wild type (WT) mice. According to radiographs, bones from mice of both genotypes between 14 and 90 days of age appeared similar in gross structure and density, although proximal tibiae from 35-90 days old TG mice were less curved than those of WT mice (72-92% TG/WT). Although there were only mild and transient differences in absolute bone mass and strength, once normalized to body mass, the tibial dry mass (79.1% TG/WT females), ash mass (78.5% TG/WT females), and femoral strength in torsion (71.6% TG/WT females) were reduced in TG mice compared to WT mice at 90 days of age. Similar effects of genotype on bone mass and curvature were observed in 1-year-old retired breeders, indicating that these phenotypic differences between TG and WT mice were stable well into adulthood. Effects of genotype on histomorphometric indices of cancellous bone turnover were minimal and evident only transiently during growth, but when present they demonstrated differences in osteoblast rather than osteoclast parameters. Together, these results suggest that integrin signals generated during growth enhance the acquisition of a skeletal mass, structure, and strength to withstand the mechanical loads generated by weight-bearing.

Antigens, CD29/genetics/metabolism↗
NASA NTRS2004

Radiation-induced bystander effect and adaptive response in mammalian cells

Two conflicting phenomena, bystander effect and adaptive response, are important in determining the biological responses at low doses of radiation and have the potential to impact the shape of the dose-response relationship. Using the Columbia University charged-particle microbeam and the highly sensitive AL cell mutagenic assay, we show here that non-irradiated cells acquire mutagenesis through direct contact with cells whose nuclei have been traversed with a single alpha particle each. Pretreatment of cells with a low dose of X-rays four hours before alpha particle irradiation significantly decreased this bystander mutagenic response. Results from the present study address some of the fundamental issues regarding both the actual target and radiation dose effect and can contribute to our current understanding in radiation risk assessment. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

NASA Discipline Radiation Health↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗