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Results for “Cell Death”

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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

The effect of in situ freezing on rabbit patellar tendon. A histologic, biochemical, and biomechanical analysis

Cell necrosis has been well documented as one of the many changes that occur in autogenous tendon when it is used to reconstruct the anterior cruciate ligament. The purpose of this experiment was to isolate cell necrosis as a variable and study its effect on the patellar tendon. To accomplish this, both knees of 25 New Zealand White rabbits were operated on. In one knee, a 5-mm wide band of patellar tendon was subjected to two rapid freeze-thaw cycles, while the other knee underwent sham surgery. Histologic evaluation showed a zone of necrosis at 2 and 4 weeks with cellular repopulation complete at 8 weeks. patellar tendon cross-sectional area was 0.118 cm2 at 8 weeks for the frozen specimens compared to 0.102 cm2 for the sham-operated controls. This difference was significant at the P = 0.025 level. Mechanical testing at 4 and 8 weeks revealed no significant changes in tendon length, maximum load, or stiffness. The collagen content was also unchanged at both 4 and 8 weeks.

Non-NASA Center↗
NASA NTRSDate not supplied

AMMPER: a user-friendly agent-based model that recapitulates simple metabolic responses of yeast to deep-space radiation

For humans venturing to deep space, radiation exposure poses a major health risk. Fundamental research into the biological effects of space radiation are essential for enabling exploration, and the first experimental organisms we send to deep space will be microbial. Yet there are many ways in which microorganisms are likely to experience the effects of high-energy particle radiation (such as Galactic Cosmic Rays) differently from multicellular animals, partly due to the simple fact that microbes are small and unicellular-- less likely to get hit in the first place, and less likely to communicate damage between cells. Computational modeling can aid in designing experiments and predicting the biological effects of radiation, but thus far particle radiation models have not focused on microbes. Here we present the latest developments in AMMPER, the Agent-based Model for Microbial Populations Exposed to Radiation. Originally written in 2021, AMMPER is a Python-based model that incorporates radiation track data from NASA's RITRACKS software and simulates the growth, damage, and death of yeast cells in 3D. It is now freely available as an open-source package on NASA's GitHub repository. Recent improvements include the ability to simulate the dynamics of alamarBlue, a color-changing redox dye commonly used to track metabolic activity in microbial spaceflight experiments. We demonstrate that a simple blue-pink-clear transition model is able to recapitulate key features observed in empirical data from ground studies. AMMPER also includes a new graphical user interface and introductory tutorial to facilitate ease of use by a wider audience. AMMPER can help us to understand how spatially heterogeneous particle radiation damage at the single-cell level can translate to growth differences at the population level, ultimately allowing us to better interpret experiments using microbes as model organisms and how well their results apply to humans.

yeast↗
NASA NTRS2001

Extracellular signaling through the microenvironment: a hypothesis relating carcinogenesis, bystander effects, and genomic instability

Cell growth, differentiation and death are directed in large part by extracellular signaling through the interactions of cells with other cells and with the extracellular matrix; these interactions are in turn modulated by cytokines and growth factors, i.e. the microenvironment. Here we discuss the idea that extracellular signaling integrates multicellular damage responses that are important deterrents to the development of cancer through mechanisms that eliminate abnormal cells and inhibit neoplastic behavior. As an example, we discuss the action of transforming growth factor beta (TGFB1) as an extracellular sensor of damage. We propose that radiation-induced bystander effects and genomic instability are, respectively, positive and negative manifestations of this homeostatic process. Bystander effects exhibited predominantly after a low-dose or a nonhomogeneous radiation exposure are extracellular signaling pathways that modulate cellular repair and death programs. Persistent disruption of extracellular signaling after exposure to relatively high doses of ionizing radiation may lead to the accumulation of aberrant cells that are genomically unstable. Understanding radiation effects in terms of coordinated multicellular responses that affect decisions regarding the fate of a cell may necessitate re-evaluation of radiation dose and risk concepts and provide avenues for intervention.

NASA Discipline Radiation Health↗
NASA NTRS1988

Hydrodynamic effects on cell growth in agitated microcarrier bioreactors

The net growth rate of bovine embryonic kidney cells in microcarrier bioreactor is the result of a variable death rate imposed on a cell culture trying to grow at a constant intrinsic growth rate. The death rate is a function of the agitation conditions in the system, and increases at higher agitation because of increasingly energetic interactions of the cell covered microcarriers with turbulent eddies in the fluid. At very low agitation rates bead-bead bridging becomes important; the large clumps formed by bridging can interact with larger eddies than single beads, leading to a higher death rate at low agitation. The growth and death rate were correlated with a dimensionless eddy number which compares eddy forces to the buoyant force on the bead.

Cherry, Robert S.↗
NASA NTRS1989

Life on Mars - How it disappeared (if it was ever there)

Information available on Mars chemistry suggest that conditions on early Mars may have been suitable for life. This paper examines the possible events that led to the disappearance of life, assuming it existed, from the surface of Mars. The sequence of events leading to life extinction on early Mars assumes the following steps: (1) a decrease of temperature and humidity levels, leading to a selection of microorganisms for tolerance of low temperatures and arid conditions; (2) further deterioration of environment leading to withdrawal of cold-adapted organisms to protected niches under the surface; (3) further cooling producing heavy stresses in these organisms; and (4) further deterioration of the environment resulting in extinction. This sequence of events is considered parallel events documented for the microbial community in the Ross Desert of Antarctica, where TEM examinations of the material detected progressive stages of cell damage and death.

Friedmann, E. Imre↗
NASA NTRS2017

Role of Mitochondrial Oxidative Stress in Spaceflight-Induced Tissue Degeneration

Microgravity and ionizing radiation in the spaceflight environment poses multiple challenges to homeostasis and may contribute to cellular stress. Effects may include increased generation of reactive oxygen species (ROS), DNA damage and repair error, cell cycle arrest, cell senescence or death. Our central hypothesis is that prolonged exposure to the spaceflight environment leads to the excess production of ROS and oxidative damage, culminating in accelerated tissue degeneration. The main goal of this project is to determine the importance of cellular redox defense for physiological adaptations and tissue degeneration in the space environment.

transgenic mic↗
NASA NTRS2018

Aging and Spaceflight: Catalase Targeted to Mitochondria Alters Skeletal Structure and Responses to Musculoskeletal Disuse

Microgravity and ionizing radiation in the spaceflight environment pose multiple challenges to homeostasis and may contribute to cellular stress. Effects may include increased generation of reactive oxygen species (ROS), DNA damage and repair error, cell cycle arrest, cell senescence or death. Our central hypothesis is that prolonged exposure to the spaceflight environment leads to excess production of ROS and oxidative damage, culminating in accelerated tissue degeneration which resembles aging. The main goal of this project is to determine the importance of cellular redox defense for physiological adaptations and tissue degeneration in the space environment. To accomplish this, we will use both wildtype (WT) mice and a well-established, genetically-engineered animal model (mCAT mice) which displays extended lifespan (Schriner et al. 2005). The animal model selected to test these ideas is engineered to quench ROS in mitochondria by targeted over-expression of the human catalase gene to the mitochondrial matrix. We showed previously that mCAT mice express the catalase transgene in skeletal tissues, bone forming osteoblasts, and bone resorbing osteoclasts. In addition, mCAT mice also display increased catalase activity in bone. Our findings revealed that exposure of adult, male, C57Bl/6J mice to simulated spaceflight (hindlimb unloading and gamma radiation) led to an increase in markers of oxidative damage (malondialdehyde, 4-hydroxynonenol) in skeletal tissue of WT mice but not mCAT mice. To extend our hypothesis to other, spaceflight-relevant tissues, we are performing a ground-based study simulating 30 days of spaceflight by hindlimb unloading to determine potential protective effects of mitochondrial catalase activity on aging of multiple tissues (cardiovascular, nervous and skeletal).

transgenic mice↗
DOE OSTI2025

Multi-omics data compendium of pancreatic islet and β cell responses to pro-inflammatory cytokines

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
NASA NTRS2001

Stromal cells can contribute oncogenic signals

The majority of studies of neoplastic transformation have focused attention on events that occur within transformed cells. These cell autonomous events result in the disruption of molecular pathways that regulate basic activities of the cells such as proliferation, death, movement and genomic integrity. Other studies have addressed the microenvironment of tumor cells and documented its importance in supporting tumor progression. Recent work has begun to expand on these initial studies of tumor microenvironment and now provide novel insights into the possible initiation and progression of malignant cells. This review will address the transforming effect of stromal cells on epithelial components. Copyright 2001 Academic Press.

Review↗
DOE OSTI2024

Morphologic characterization and cytokine response of chicken bone-marrow derived dendritic cells to infection with high and low pathogenic avian influenza virus

Dendritic cells (DCs) are professional antigen-presenting cells, which are key components of the immune system and involved in early immune responses. DCs are specialized in capturing, processing, and presenting antigens to facilitate immune interactions. Chickens infected with avian influenza virus (AIV) demonstrate a wide range of clinical symptoms, based on pathogenicity of the virus. Low pathogenic avian influenza (LPAI) viruses typically induce mild clinical signs, whereas high pathogenic avian influenza (HPAI) induce more severe disease, which can lead to death. For this study, chicken bone marrow-derived DC (ckBM-DC)s were produced and infected with high and low pathogenic avian influenza viruses of H5N2 or H7N3 subtypes to characterize innate immune responses, study effect on cell morphologies, and evaluate virus replication. A strong proinflammatory response was observed at 8 hours post infection, via upregulation of chicken interleukin-1β and stimulation of the interferon response pathway. Microscopically, the DCs underwent morphological changes from classic elongated dendrites to a more general rounded shape that eventually led to cell death with the presence of scattered cellular debris. Differences in onset of morphologic changes were observed between H5 and H7 subtypes. Increases in viral titers demonstrated that both HPAI and LPAI are capable of infecting and replicating in DCs. The increase in activation of infected DCs may be indicative of a dysregulated immune response typically seen with HPAI infections.

Immunology↗
DOE OSTI2025

Multi-omics data compendium: Data package 10 (Pck010)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2025

Multi-omics data compendium: Data package 11 (Pck011)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2025

Multi-omics data compendium: Data package 12 (Pck012)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2025

Multi-omics data compendium: Data package 13 (Pck013)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2025

Multi-omics data compendium: Data package 14 (Pck014)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2025

Multi-omics data compendium: Data package 15 (Pck015)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2025

Multi-omics data compendium: Data package 16 (Pck016)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2025

Multi-omics data compendium: Data package 17 (Pck017)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗