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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Cellular fluidics

The natural world provides many examples of multiphase transport and reaction processes that have been optimized by evolution. These phenomena take place at multiple length and time scales and typically include gas–liquid–solid interfaces and capillary phenomena in porous media. Many biological and living systems have evolved to optimize fluidic transport. However, living things are exceptionally complex and very difficult to replicate, and human-made microfluidic devices (which are typically planar and enclosed) are highly limited for multiphase process engineering. In this paper, we introduce the concept of cellular fluidics: a platform of unit-cell-based, three-dimensional structures—enabled by emerging 3D printing methods—for the deterministic control of multiphase flow, transport and reaction processes. We show that flow in these structures can be ‘programmed’ through architected design of cell type, size and relative density. We demonstrate gas–liquid transport processes such as transpiration and absorption, using evaporative cooling and CO 2 capture as examples. We design and demonstrate preferential liquid and gas transport pathways in three-dimensional cellular fluidic devices with capillary-driven and actively pumped liquid flow, and present examples of selective metallization of pre-programmed patterns. Our results show that the design and fabrication of architected cellular materials, coupled with analytical and numerical predictions of steady-state and dynamic behaviour of multiphase interfaces, provide deterministic control of fluidic transport in three dimensions. Cellular fluidics may transform the design space for spatial and temporal control of multiphase transport and reaction processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Staircases of passive and active scalar concentration in cellular flow

This paper develops a unified model for staircase formation in both passive and active scalar systems, building upon prior numerical studies by offering new heuristic and physical insights. While prior studies primarily reported numerical results, they did not explore the underlying unifying physics that governs both types of scalar transport; this work addresses that gap by identifying shared mechanisms across both cases. Results of studies of passive and active scalar staircase formation in cellular flows are presented. Staircase formation in cellular flows occurs due to the interplay of fast mixing within cells and slow transport across the inter-cell boundary. The cell boundary emerges as a de facto transport barrier. Special attention is focused on the effects of cellular fluctuations and noise upon staircase structure. A forced, fluctuating vortex array model is used to drive the underlying flow structure. Cellular Peclet number and staircase profile curvature are identified as figures-of-merit to quantify the resiliency of layering. These are related to simple, multi-scatterer scalar random walk models. Results for Peclet number and curvature scaling with flow excitation are presented. We also study staircases of magnetic potential evolving in two-dimensional magnetohydrodynamics as examples of layering of active scalar concentration. Formation of magnetic potential staircases is indeed observed. Flux expulsion inhibits the intercellular transport of magnetic potential and strengthens staircase barriers. Magnetic staircases can be supported against resistive decay by magnetic potential noise forcing. Implications for staircase formation in magnetic confinement experiments are discussed.

Control theory↗

DOE OSTI2020

The surface stress of biomedical silicones is a stimulant of cellular response

Silicones are commonly used for lubrication of syringes, encapsulation of medical devices, and fabrication of surgical implants. While silicones are generally viewed as relatively inert to the cellular milieu, they can mediate a variety of inflammatory responses and other deleterious effects, but the mechanisms underlying the bioactivity of silicones remain unresolved. Here, we report that silicone liquids and gels have high surface stresses that can strongly resist deformation at cellular length scales. Biomedical silicones, including syringe lubricants and fillings from FDA-approved breast implants, readily adsorb matrix proteins and activate canonical rigidity sensing pathways through their surface stresses. In 3D culture models, liquid silicone droplets support robust cellular adhesion and the formation of multinucleated monocyte-derived cell masses that recapitulate phenotypic aspects of granuloma formation in the foreign body response. Together, our findings implicate surface stress as a cellular stimulant that should be considered in application of silicones for biomedical purposes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Cellular response of keratinocytes to the entry and accumulation of nanoplastic particles

Plastic accumulation in the environment is rapidly increasing, and nanoplastics (NP), byproducts of environmental weathering of bulk plastic waste, pose a significant public health risk. Particles may enter the human body through many possible routes such as ingestion, inhalation, and skin absorption. However, studies on NP penetration and accumulation in human skin are limited. Loss or reduction of the keratinized skin barrier may enhance the skin penetration of NPs. The present study investigated the entry of NPs into a human skin system modeling skin with compromised barrier functions and cellular responses to the intracellular accumulations of NPs. Two in vitro models were employed to simulate human skin lacking keratinized barriers. The first model was an ex vivo human skin culture with the keratinized dermal layer (stratum corneum) removed. The second model was a 3D keratinocyte/dermal fibroblast cell co-culture model with stratified keratinocytes on the top and a monolayer of skin fibroblast cells co-cultured at the bottom. The penetration and accumulation of the NPs in different cell types were observed using fluorescent microscopy, confocal microscopy, and cryogenic electron microscopy (cryo-EM). The cellular responses of keratinocytes and dermal fibroblast cells to stress induced by NPs stress were measured. The genetic regulatory pathway of keratinocytes to the intracellular NPs was identified using transcript analyses and KEGG pathway analysis. The cellular uptake of NPs by skin cells was confirmed by imaging analyses. Transepidermal transport and penetration of NPs through the skin epidermis were observed. According to the gene expression and pathway analyses, an IL-17 signaling pathway was identified as the trigger for cellular responses to internal NP accumulation in the keratinocytes. The transepidermal NPs were also found in co-cultured dermal fibroblast cells and resulted in a large-scale transition from fibroblast cells to myofibroblast cells with enhanced production of α-smooth muscle actin and pro-Collagen Ia. The upregulation of inflammatory factors and cell activation may result in skin inflammation and ultimately trigger immune responses.

36 MATERIALS SCIENCE↗

DOE OSTI2020

DEEP CELLULAR RECURRENT NEURAL ARCHITECTURE FOR EFFICIENT MULTIDIMENSIONAL TIME-SERIES DATA PROCESSING

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in complexity and size to accommodate the additional dimensionality of time. Specifically, the biologically inspired learning based models known as artificial neural networks that have shown extraordinary success in pattern recognition, tend to grow prohibitively large and cumbersome in the presence of large scale multi-dimensional time series biomedical data such as EEG. Consequently, this work aims to develop representative ML and DL models for robust and efficient large scale time series processing. First, we design a novel ML pipeline with efficient feature engineering to process a large scale multi-channel scalp EEG dataset for automated detection of epileptic seizures. With the use of a sophisticated yet computationally efficient time-frequency analysis technique known as harmonic wavelet packet transform and an efficient self-similarity computation based on fractal dimension, we achieve state-of-the-art performance for automated seizure detection in EEG data. Subsequently, we investigate the development of a novel efficient deep recurrent learning model for large scale time series processing. For this, we first study the functionality and training of a biologically inspired neural network architecture known as cellular simultaneous recurrent neural network (CSRN). We obtain a generalization of this network for multiple topological image processing tasks and investigate the learning efficacy of the complex cellular architecture using several state-of-the?art training methods. Finally, we develop a novel deep cellular recurrent neural network (CDRNN) architecture based on the biologically inspired distributed processing used in CSRN for processing time series data. The proposed DCRNN leverages the cellular recurrent architecture to promote extensive weight sharing and efficient, individualized, synchronous processing of multi-source time series data. Experiments on a large scale multi-channel scalp EEG, and a machine fault detection dataset show that the proposed DCRNN offers state-of-the-art recognition performance while using substantially fewer trainable recurrent units.

Vidyaratne, Lasitha S.↗

DOE OSTI2023

Convolutional Neural Network for Segmenting Micro-X-ray Computed Tomography Images of Wood Cellular Structures

To further enhance the performance of wood products, improved tools are needed to study in situ cellular scale phenomena like mechanical deformations and moisture swelling. Micro-X-ray computed tomography (μXCT) using brilliant synchrotron light sources now has the spatial and temporal resolution for real-time visualization of phenomena in three-dimensional cellular structures. However, the tradeoff for speed includes the loss of intensity contrast between different types of materials within the imaged structure, such as cell wall and air in wood. This loss of contrast prevents traditional histogram-based segmentation methods from being used effectively. A new convolutional neural network (CNN) approach was therefore developed to segment fast μXCT images of wood into cell wall and air volumes. The fast μXCT and segmentation were demonstrated in the study of moisture swelling in loblolly pine (Pinus taeda) earlywood and latewood cellular structures conditioned at 0%, 33%, 75%, and 95% relative humidity (RH). The CNN segmentation results had a mean intersection over union (IoU) metric accuracy of 96%. Initial analysis of the swelling in the latewood revealed cell walls swelled about 25% when conditioned from 0% to 95% RH. Additionally, the widths of ray cell lumina in the transverse plane of latewood could be observed to increase at higher RH. The segmentation method presented here will facilitate future quantitative analyses in in situ μXCT studies of wood and other similar cellular materials.

Arzola-Villegas, Xavier (ORCID:0000000305369766)↗

NASA NTRS1991

Cellular: Toward personal communications

The cellular industry is one of the fastest growing segment of the telecommunications industry. With an estimated penetration rate of 20 percent in the near future, cellular is becoming an ubiquitous telecommunications service in the U.S. In this paper we will examine the major advancements in the cellular industry: customer equipment, cellular networks, engineering tools, customer support, and nationwide seamless service.

Heffernan, Stuart↗

NASA NTRS1993

A scientific role for Space Station Freedom: Research at the cellular level

The scientific importance of Space Station Freedom is discussed in light of the valuable information that can be gained in cellular and developmental biology with regard to the microgravity environment on the cellular cytoskeleton, cellular responses to extracellular signal molecules, morphology, events associated with cell division, and cellular physiology. Examples of studies in basic cell biology, as well as their potential importance to concerns for future enabling strategies, are presented.

Johnson, Terry C.↗

NASA NTRS1993

Integration of mobile satellite and cellular systems

By integrating the ground based infrastructure component of a mobile satellite system with the infrastructure systems of terrestrial 800 MHz cellular service providers, a seamless network of universal coverage can be established. Users equipped for both cellular and satellite service can take advantage of a number of features made possible by such integration, including seamless handoff and universal roaming. To provide maximum benefit at lowest posible cost, the means by which these systems are integrated must be carefully considered. Mobile satellite hub stations must be configured to efficiently interface with cellular Mobile Telephone Switching Offices (MTSO's), and cost effective mobile units that provide both cellular and satellite capability must be developed.

Drucker, Elliott H.↗

NASA NTRS2001

Latitudinal Transport of Angular Momentum by Cellular Flows Observed with MDI

We have analyzed Doppler velocity images from the MDI instrument on SOHO to determine the latitudinal transport of angular momentum by the cellular photospheric flows. Doppler velocity images from 60-days in May to July of 1996 were processed to remove the p-mode oscillations, the convective blue shift, the axisymmetric flows, and any instrumental artifacts. The remaining cellular flows were examined for evidence of latitudinal angular momentum transport. Small cells show no evidence of any such transport. Cells the size of supergranules (30,000 km in diameter) show strong evidence for a poleward transport of angular momentum. This would be expected if supergranules are influenced by the Coriolis force, and if the cells are elongated in an east-west direction. We find good evidence for just such an east-west elongation of the supergranules. This elongation may be the result of differential rotation shearing the cellular structures. Data simulations of this effect support the conclusion that elongated supergranules transport angular momentum from the equator toward the poles, Cells somewhat larger than supergranules do not show evidence for this poleward transport. Further analysis of the data is planned to determine if the direction of angular momentum transport reverses for even larger cellular structures. The Sun's rapidly rotating equator must be maintained by such transport somewhere within the convection zone.

Hathaway, David H.↗

NASA NTRS2000

Computer Modeling of the Earliest Cellular Structures and Functions

In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells). the most direct way to test our understanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform proto-cellular functions. Many of these functions, such as import of nutrients, capture and storage of energy. and response to changes in the environment are carried out by proteins bound to membrane< We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (eg. channels), and (c) by what mechanisms such aggregates perform essential proto-cellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each item in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10(exp 6)-10(exp 8) time steps.

Pohorille, Andrew↗

NASA NTRS1987

Influence of microgravity on cellular differentiation in root caps of Zea mays

We launched imbibed seeds of Zea mays into outer space aboard the space shuttle Columbia to determine the influence of microgravity on cellular differentiation in root caps. The influence of microgravity varied with different stages of cellular differentiation. Overall, microgravity tended to 1) increase relative volumes of hyaloplasm and lipid bodies, 2) decrease the relative volumes of plastids, mitochondria, dictyosomes, and the vacuome, and 3) exert no influence on the relative volume of nuclei in cells comprising the root cap. The reduced allocation of dictyosomal volume in peripheral cells of flight-grown seedlings correlated positively with their secretion of significantly less mucilage than peripheral cells of Earth-grown seedlings. These results indicate that 1) microgravity alters the patterns of cellular differentiation and structures of all cell types comprising the root cap, and 2) the influence of microgravity on cellular differentiation in root caps of Zea mays is organelle specific.

NASA Program Space Biology↗

NASA NTRS1999

Predicting cancer rates in astronauts from animal carcinogenesis studies and cellular markers

The radiation space environment includes particles such as protons and multiple species of heavy ions, with much of the exposure to these radiations occurring at extremely low average dose-rates. Limitations in databases needed to predict cancer hazards in human beings from such radiations are significant and currently do not provide confidence that such predictions are acceptably precise or accurate. In this article, we outline the need for animal carcinogenesis data based on a more sophisticated understanding of the dose-response relationship for induction of cancer and correlative cellular endpoints by representative space radiations. We stress the need for a model that can interrelate human and animal carcinogenesis data with cellular mechanisms. Using a broad model for dose-response patterns which we term the "subalpha-alpha-omega (SAO) model", we explore examples in the literature for radiation-induced cancer and for radiation-induced cellular events to illustrate the need for data that define the dose-response patterns more precisely over specific dose ranges, with special attention to low dose, low dose-rate exposure. We present data for multiple endpoints in cells, which vary in their radiosensitivity, that also support the proposed model. We have measured induction of complex chromosome aberrations in multiple cell types by two space radiations, Fe-ions and protons, and compared these to photons delivered at high dose-rate or low dose-rate. Our data demonstrate that at least three factors modulate the relative efficacy of Fe-ions compared to photons: (i) intrinsic radiosensitivity of irradiated cells; (ii) dose-rate; and (iii) another unspecified effect perhaps related to reparability of DNA lesions. These factors can produce respectively up to at least 7-, 6- and 3-fold variability. These data demonstrate the need to understand better the role of intrinsic radiosensitivity and dose-rate effects in mammalian cell response to ionizing radiation. Such understanding is critical in extrapolating databases between cellular response, animal carcinogenesis and human carcinogenesis, and we suggest that the SAO model is a useful tool for such extrapolation.

Non-NASA Center↗

DOE OSTI2023

Integrative visualization of the molecular structure of a cellular microdomain

Abstract An integrative approach to visualization is used to create a visual snapshot of the structural biology of the polar microdomain of Caulobacter crescentus . The visualization is based on the current state of molecular and cellular knowledge of the microdomain and its cellular context. The collaborative process of researching and executing the visualization has identified aspects that are well determined and areas that require further study. The visualization is useful for dissemination, education, and outreach, and the study lays the groundwork for future 3D modeling and simulation of this well‐studied example of a cellular condensate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information

Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extraction often involve huge computational cost with high dimensional data. Deep recurrent neural networks have shown promise in automated feature learning for improved time-series processing. However, generic deep recurrent models grow in scale and depth with increased complexity of the data. This is particularly challenging in presence of high dimensional data with temporal and spatial characteristics. Consequently, this work proposes a novel deep cellular recurrent neural network (DCRNN) architecture to efficiently process complex multi-dimensional time series data with spatial information. Here, the cellular recurrent architecture in the proposed model allows for location-aware synchronous processing of time series data from spatially distributed sensor signal sources. Extensive trainable parameter sharing due to cellularity in the proposed architecture ensures efficiency in the use of recurrent processing units with high-dimensional inputs. This study also investigates the versatility of the proposed DCRNN model for classification of multi-class time series data from different application domains. Consequently, the proposed DCRNN architecture is evaluated using two time-series datasets: a multichannel scalp EEG dataset for seizure detection, and a machine fault detection dataset obtained in-house. The results suggest that the proposed architecture achieves state-of-the-art performance while utilizing substantially less trainable parameters when compared to comparable methods in the literature.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Intermittent supplementation with fisetin improves arterial function in old mice by decreasing cellular senescence

Cellular senescence and the senescence-associated secretory phenotype (SASP) contribute to age-related arterial dysfunction, in part, by promoting oxidative stress and inflammation, which reduce the bioavailability of the vasodilatory molecule nitric oxide (NO). In the present study, we assessed the efficacy of fisetin, a natural compound, as a senolytic to reduce vascular cell senescence and SASP factors and improve arterial function in old mice. We found that fisetin decreased cellular senescence in human endothelial cell culture. In old mice, vascular cell senescence and SASP-related inflammation were lower 1 week after the final dose of oral intermittent (1 week on—2 weeks off—1 weeks on dosing) fisetin supplementation. Old fisetin-supplemented mice had higher endothelial function. Leveraging old p16-3MR mice, a transgenic model allowing genetic clearance of p16 INK4A -positive senescent cells, we found that ex vivo removal of senescent cells from arteries isolated from vehicle- but not fisetin-treated mice increased endothelium-dependent dilation, demonstrating that fisetin improved endothelial function through senolysis. Enhanced endothelial function with fisetin was mediated by increased NO bioavailability and reduced cellular- and mitochondrial-related oxidative stress. Arterial stiffness was lower in fisetin-treated mice. Ex vivo genetic senolysis in aorta rings from p16-3MR mice did not further reduce mechanical wall stiffness in fisetin-treated mice, demonstrating lower arterial stiffness after fisetin was due to senolysis. Lower arterial stiffness with fisetin was accompanied by favorable arterial wall remodeling. The findings from this study identify fisetin as promising therapy for clinical translation to target excess cell senescence to treat age-related arterial dysfunction.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Probing Cellular Activity Via Charge‐Sensitive Quantum Nanoprobes

Nitrogen‐vacancy (NV) based quantum sensors hold great potential for real‐time single‐cell sensing with far‐reaching applications in fundamental biology and medical diagnostics. Although highly sensitive, the mapping of quantum measurements onto cellular physiological states has remained an exceptional challenge. Here, we introduce a novel quantum sensing modality capable of detecting changes in cellular activity. Our approach is based on the detection of environment‐induced charge depletion within an individual particle that, owing to a previously unaccounted transverse dipole term, induces systematic shifts in the zero‐field splitting (ZFS). Importantly, these charge‐induced shifts serve as a reliable indicator for lipopolysaccharide (LPS)‐mediated inflammatory response in macrophages. Furthermore, we demonstrate that surface modification of our diamond nanoprobes effectively suppresses these environment‐induced ZFS shifts, providing an important tool for differentiating electrostatic shifts caused by the environment from other unrelated effects, such as temperature variations. Notably, this surface modification also leads to significant reductions in particle‐induced toxicity and inflammation. Our findings shed light on systematic drifts and sensitivity limits of NV spectroscopy in a biological environment with ramifications for the critical discussion surrounding single‐cell thermogenesis. Notably, this work establishes the foundation for a novel sensing modality capable of probing complex cellular processes through straightforward physical measurements.

band bending↗

DOE OSTI2024

Hierarchical Composites Patterned via 3D Printed Cellular Fluidics

Additive manufacturing of freeform structures containing multiple materials with deterministic spatial arrangement and interactions remains a challenge for most 3D printing processes, due to complex fabrication tool requirements and limitations in printability of some material classes. Here, in this paper, a versatile method is reported to produce architected composites using the concept of cellular fluidics, in which lattices of unit cells are used as templating scaffolds to guide flowable infill materials in a programmed spatial pattern, upon which they are cured in place to produce a deterministically ordered multimaterial solid. The lattice design relies on the unit cell size, type, strut diameter, surface wetting, and distribution of cellular structures to control liquid flow and retention. Individual unit cells are tuned to achieve reliable infilling and combined into higher-order architectures to achieve multiscale composite materials with disparate mechanical properties, including those considered non-printable. Lattice design considerations for leveraging capillary phenomena and demonstrate several methods of patterning polymers in 3D-printed cellular fluidic structures are presented. The concept of tuning the compressive response of an architected composite using a flexible-elastomer as the lattice and a stiff-epoxy as the infill material is illustrated.

36 MATERIALS SCIENCE↗