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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Cell Walls and the Developmental Anatomy of the Brachypodium distachyon Stem Internode

While many aspects of plant cell wall polymer structure are known, their spatial and temporal distribution within the stem are not well understood. Here, we studied vascular system and fiber development, which has implication for both biofuel feedstock conversion efficiency and crop yield. The subject of this study, Brachypodium distachyon, has emerged as a grass model for food and energy crop research. Here, we conducted our investigation using B. distachyon by applying various histological approaches and Fourier transform infrared spectroscopy to the stem internode from three key developmental stages. While vascular bundle size and number did not change over time, the size of the interfascicular region increased dramatically, as did cell wall thickness. We also describe internal stem internode anatomy and demonstrate that lignin deposition continues after crystalline cellulose and xylan accumulation ceases. The vascular bundle anatomy of B. distachyon appears to be highly similar to domesticated grasses. While the arrangement of bundles within the stem is highly variable across grasses, B. distachyon appears to be a suitable model for the rind of large C4 grass crops. A better understanding of growth and various anatomical and cell wall features of B. distachyon will further our understanding of plant biomass accumulation processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

TU-CD-207-12: Impact of Anatomical Noise On Detection Performance of Microcalcifications in Multi-Contrast Breast Imaging

Purpose: The anatomical noise power spectra (NPS) for differential phase contrast (DPC) and dark field (DF) imaging have recently been characterized using a power-law model with two parameters, alpha and beta, an innovative extension to the methodology used in x-ray attenuation based breast imaging such as mammography, DBT, or cone-beam CT. Beta values of 3.6, 2.6, and 1.3 have been measured for absorption, DPC, and DF respectively for cadaver breasts imaged in the coronal plane; these dramatic differences should be reflected in their detection performance. The purpose of this study was to determine the impact of anatomical noise on breast calcification detection and compare the detection performance of the three contrast mechanisms of a multi-contrast x-ray imaging system. Methods: In our studies, a calcification image object was segmented out of the multi-contrast images of a cadaver breast specimen. 50 measured total NPS were measured from breast cadavers directly. The ideal model observer detectability was calculated for a range of doses (5–100%) and a range of calcification sizes (diameter = 0.25–2.5 mm). Results: Overall we found the highest average detectability corresponded to DPC imaging (7.4 for 1 mm calc.), with DF the next highest (3.8 for 1 mm calc.), and absorption the lowest (3.2 for 1 mm calc.). However, absorption imaging also showed the slowest dependence on dose of the three modalities due to the significant anatomical noise. DPC showed a peak detectability for calcifications ∼1.25 mm in diameter, DF showed a peak for calcifications around 0.75 mm in diameter, and absorption imaging had no such peak in the range explored. Conclusion: Understanding imaging performance for DPC and DF is critical to transition these modalities to the clinic. The results presented here offer new insight into how these modalities complement absorption imaging to maximize the likelihood of detecting early breast cancers. J. Garrett, Y. Ge, K. Li: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1984

Sensitivity of bone cell populations to weightlessness and simulated weightlessness

A rat suspension model for simulating certain aspects of weightlessness is discussed. Perturbations in physiological systems induced by this head down suspension model are verified by flight data. Findings of a suppression of osteoblast differentiation help explain the inhibition of bone formation inflight and during Earth-bound simulations. Since the anatomical site for these studies was in the maxilla, which is gravity loaded but non weightbearing in ground-based simulations, the similarity of bone cell kinetic changes, both inflight and in the ground-based model, suggest that fluid shifts rather than unloading may play an important role in bone alterations, at least at this sampling site.

Roberts, W. E.↗
DOE OSTI2014

TU-C-17A-10: Patient Features Based Dosimetric Pareto Front Prediction In Esophagus Cancer Radiotherapy

Purpose: The purpose of this study is to study the feasibility of the dosimetric pareto front (PF) prediction based on patient anatomic and dosimetric parameters for esophagus cancer patients. Methods: Sixty esophagus patients in our institution were enrolled in this study. A total 2920 IMRT plans were created to generated PF for each patient. On average, each patient had 48 plans. The anatomic and dosimetric features were extracted from those plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose and PTV homogeneous index (PTVHI) were recorded for each plan. The principal component analysis (PCA) was used to extract overlap volume histogram (OVH) features between PTV and other critical organs. The full dataset was separated into two parts include the training dataset and the validation dataset. The prediction outcomes were the MHD and MLD for the current study. The spearman rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The PF was fit by the the stepwise multiple regression method. The cross-validation method was used to evaluation the model. Results: The mean prediction error of the MHD was 465 cGy with 100 repetitions. The most correlated factors were the first principal components of the OVH between heart and PTV, and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 195 cGy. The most correlated factors were the first principal components of the OVH between lung and PTV, and the overlap between lung and PTV in Z-axis. Conclusion: It is feasible to use patients anatomic and dosimetric features to generate a predicted PF. Additional samples and further studies were required to get a better prediction model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-D-BRB-01: A Predictive Planning Tool for Stereotactic Radiosurgery

Purpose: To demonstrate the feasibility of a predictive planning tool which provides SRS planning guidance based on simple patient anatomical properties: PTV size, PTV shape and distance from critical structures. Methods: Ten framed SRS cases treated at Winship Cancer Institute of Emory University were analyzed to extract data on PTV size, sphericity (shape), and distance from critical structures such as the brainstem and optic chiasm. The cases consisted of five pairs. Each pair consisted of two cases with a similar diagnosis (such as pituitary adenoma or arteriovenous malformation) that were treated with different techniques: DCA, or IMRS. A Naive Bayes Classifier was trained on this data to establish the conditions under which each treatment modality was used. This model was validated by classifying ten other randomly-selected cases into DCA or IMRS classes, calculating the probability of each technique, and comparing results to the treated technique. Results: Of the ten cases used to validate the model, nine had their technique predicted correctly. The three cases treated with IMRS were all identified as such. Their probabilities of being treated with IMRS ranged between 59% and 100%. Six of the seven cases treated with DCA were correctly classified. These probabilities ranged between 51% and 95%. One case treated with DCA was incorrectly predicted to be an IMRS plan. The model’s confidence in this case was 91%. Conclusion: These findings indicate that a predictive planning tool based on simple patient anatomical properties can predict the SRS technique used for treatment. The algorithm operated with 90% accuracy. With further validation on larger patient populations, this tool may be used clinically to guide planners in choosing an appropriate treatment technique. The prediction algorithm could also be adapted to guide selection of treatment parameters such as treatment modality and number of fields for radiotherapy across anatomical sites.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2002

Single-Trial Analysis of V1 Responses Suggests Two Transmission States

Sensory processing in the visual, auditory, and somatosensory systems is often studied by recording electrical activity in response to a stimulus of interest. Typically, multiple trial responses to the stimulus are averaged to isolate the stereotypic response from noise. However, averaging ignores dynamic variability in the neuronal response, which is potentially critical to understanding stimulus-processing schemes. Thus, we developed the multiple component, Event-Related Potential (mcERP) model. This model asserts that multiple components, defined as stereotypic waveforms, comprise the stimulus-evoked response and that these components may vary in amplitude and latency from trial to trial. Application of this model to data recorded simultaneously from all six laminae of V1 in an awake, behaving monkey performing a visual discrimination yielded three components. The first component localized to granular V1, the second was located in supragranular V1, and the final component displayed a multi-laminar distribution. These modeling results, which take into account single-trial response dynamics, illustrated that the initial activation of VI occurs in the granular layer followed by activation in the supragranular layers. This finding is expected because the average response in those layers demonstrates the same progression and because anatomical evidence suggests that the feedforward input in V1 enters the granular layer and progresses to supragranular layers. In addition to these findings, the granular component of the model displayed several interesting trial-to-trial characteristics including (1) a bimodal latency distribution, (2) a latency-related variation in response amplitude, (3) a latency correlation with the supragranular component, and (4) an amplitude and latency association with the multi-laminar component. Direct analyses of the single-trial data were consistent with these model predictions. These findings suggest that V1 has at least 2 transmission states, which may be modulated by various effects such as attention, dynamics in local EEG rhythm, or variation in sensory inputs.

Shah, A. S.↗
NASA NTRS1993

Alveolar ventilation to perfusion heterogeneity and diffusion impairment in a mathematical model of gas exchange

This study describes a two-compartment model of pulmonary gas exchange in which alveolar ventilation to perfusion (VA/Q) heterogeneity and impairment of pulmonary diffusing capacity (D) are simultaneously taken into account. The mathematical model uses as input data measurements usually obtained in the lung function laboratory. It consists of two compartments and an anatomical shunt. Each compartment receives fractions of alveolar ventilation and blood flow. Mass balance equations and integration of Fick's law of diffusion are used to compute alveolar and blood O2 and CO2 values compatible with input O2 uptake and CO2 elimination. Two applications are presented. The first is a method to partition O2 and CO2 alveolar-arterial gradients into VA/Q and D components. The technique is evaluated in data of patients with chronic obstructive pulmonary disease (COPD). The second is a theoretical analysis of the effects of blood flow variation in alveolar and blood O2 partial pressures. The results show the importance of simultaneous consideration of D to estimate VA/Q heterogeneity in patients with diffusion impairment. This factor plays an increasing role in gas alveolar-arterial gradients as severity of COPD increases. Association of VA/Q heterogeneity and D may produce an increase of O2 arterial pressure with decreasing QT which would not be observed if only D were considered. We conclude that the presented computer model is a useful tool for description and interpretation of data from COPD patients and for performing theoretical analysis of variables involved in the gas exchange process.

NASA Discipline Environmental Health↗
DOE OSTI2015

SU-E-J-176: Characterization of Inter-Fraction Breast Variability and the Implications On Delivered Dose

Purpose: To systematically characterize inter-fraction breast variability and determine implications on delivered dose. Methods: Weekly port films were used to characterize breast setup variability. Five evenly spaced representative positions across the contour of each breast were chosen on the electronic port film in reference to graticule, and window and level was set such that the skin surface of the breast was visible. Measurements from the skin surface to treatment field edge were taken on each port film at each position and compared to the planning DRR, quantifying the variability. The systematic measurement technique was repeated for all port films for 20 recently treated breast cancer patients. Measured setup variability for each patient was modeled as a normal distribution. The distribution was randomly sampled from the model and applied as isocentric shifts in the treatment planning computer, representing setup variability for each fraction. Dose was calculated for each shifted fraction and summed to obtain DVHs and BEDs that modeled the dose with daily setup variability. Patients were categorized in to relevant groupings that were chosen to investigate the rigorousness of immobilization types, treatment techniques, and inherent anatomical difficulties. Mean position differences and dosimetric differences were evaluated between planned and delivered doses. Results: The setup variability was found to follow a normal distribution with mean position differences between the DRR and port film between − 8.6–3.5 mm with sigma range of 5.3–9.8 mm. Setup position was not found to be significantly different than zero. The mean seroma or whole breast PTV dosimetric difference, calculated as BED, ranged from a −0.23 to +1.13Gy. Conclusion: A systematic technique to quantify and model setup variability was used to calculate the dose in 20 breast cancer patients including variable setup. No statistically significant PTV or OAR BED differences were found between immobilization, treatment or anatomical differences investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

NMR relaxometry characterization of water adsorption in corn stover anatomical fractions

Nuclear magnetic resonance (NMR) relaxometry is applied to provide direct measurement of water adsorption in anatomical fractions of corn stover. NMR transverse T 2 relaxation time distribution measurements indicate multiple water populations, which vary with anatomical fraction and water adsorption. Measured T 2 data are used to calculate thermodynamic properties of Brunauer-Emmet-Teller adsorption theory using a model to estimate mono and bilayer relaxation. T 2 data are used directly to determine rotational diffusion correlation times indicating adsorption interaction strength. T 1 -T 2 longitudinal-transverse relaxation time correlation measurements quantify differences in the molecular level structural order of the adsorbate surface water as a function of water activity, i.e. relative humidity or water vapor partial pressure. The T 1 /T 2 ratio provides a measure of the surface energy related to the adsorption strength and surface diffusive mobility of the water adsorbate and differentiates the anatomical fractions. Furthermore, the results indicate that direct measurement of NMR relaxation times can be used to characterize corn stover biomass water adsorption, data relevant to processing and handling considerations.

09 BIOMASS FUELS↗
DOE OSTI2014

SU-E-I-92: Is Photon Starvation Preventing Metal Artifact Reduction Algorithm From Working in KVCT?

Purpose: High density/high atomic number metallic objects create shading and streaking metal artifacts in the CT image that can cause inaccurate delineation of anatomical structures or inaccurate radiation dose calculation. A modified iterative maximum-likelihood polychromatic algorithm for CT (mIMPACT) that models the energy response of detectors, photon interaction processes and beam polychromaticity has successfully reduced metal artifacts in MVCT. Our extension of mIMPACT in kVCT did not significantly reduce metal artifacts for high density metal like steel. We hypothesize that photon starvation may result in the measured data in a commercial kVCT imaging beam. Methods: We measured attenuation of a range of steel plate thicknesses, sandwiched between two 12cm thick solid water blocks, using a Phillips Big Bore CTTM scanner in scout acquisition mode with 120kVp and 200mAs. The transmitted signal (y) was normalized to the air scan signal (y{sub 0}) to get attenuation [i.e., ln(y/y{sub 0})] data for a detector. Results: Below steel plate thickness of 13.4mm, the variations in measured attenuation as a function of view number are characterized by a quantum noise and show increased attenuation with metal thickness. On or above this thickness the attenuation shows discrete levels in addition to the quantum noise. Some views have saturated attenuation value. The histograms of the measured attenuation for up to 36.7mm of steel show this trend. The detector signal is so small that the quantization levels in the analog to digital (A-to-D) converter are visible, a clear indication of photon starvation. Conclusion: Photons reaching the kVCT detector after passing through a thick metal plate are either so low in number that the signal measured has large quantum noise, or are completely absorbed inside the plate creating photon starvation. This is un-interpretable by the mIMPACT algorithm and cannot reduce metal artifacts in kVCT for certain realistic thicknesses of steel hip implants. Moti Raj Paudel is supported by the Vanier Canada Graduate Scholarship, the Endowed Graduate Scholarship in Oncology and the Dissertation Fellowship at the University of Alberta. The authors acknowledge the CIHR operating grant number MOP 53254.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

MO-FG-209-02: Development of a Virtual Breast Phantom From a Multi-Modality Perspective

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-209-05: Towards a Feature-Based Anthropomorphic Model Observer

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Modeling the Dynamics and Migratory Pathways of Virus-Specific Antibody-Secreting Cell Populations in Primary Influenza Infection

The B cell response to influenza infection of the respiratory tract contributes to viral clearance and establishes profound resistance to reinfection by related viruses. Numerous studies have measured virus-specific antibody-secreting cell (ASC) frequencies in different anatomical compartments after influenza infection and provided a general picture of the kinetics of ASC formation and dispersion. However, the dynamics of ASC populations are difficult to determine experimentally and have received little attention. Here, we applied mathematical modeling to investigate the dynamics of ASC growth, death, and migration over the 2-week period following primary influenza infection in mice. Experimental data for model fitting came from high frequency measurements of virus-specific IgM, IgG, and IgA ASCs in the mediastinal lymph node (MLN), spleen, and lung. Model construction was based on a set of assumptions about ASC gain and loss from the sampled sites, and also on the directionality of ASC trafficking pathways. Most notably, modeling results suggest that differences in ASC fate and trafficking patterns reflect the site of formation and the expressed antibody class. Essentially all early IgA ASCs in the MLN migrated to spleen or lung, whereas cell death was likely the major reason for IgM and IgG ASC loss from the MLN. In contrast, the spleen contributed most of the IgM and IgG ASCs that migrated to the lung, but essentially none of the IgA ASCs. This finding points to a critical role for regional lymph nodes such as the MLN in the rapid generation of IgA ASCs that seed the lung. Results for the MLN also suggest that ASC death is a significant early feature of the B cell response. Overall, our analysis is consistent with accepted concepts in many regards, but it also indicates novel features of the B cell response to influenza that warrant further investigation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improving five-year survival prediction via multitask learning across HPV-related cancers

Oncology is a highly siloed field of research in which sub-disciplinary specialization has limited the amount of information shared between researchers of distinct cancer types. This can be attributed to legitimate differences in the physiology and carcinogenesis of cancers affecting distinct anatomical sites. However, underlying processes that are shared across seemingly disparate cancers probably affect prognosis. The objective of the current study is to investigate whether multitask learning improves 5-year survival cancer patient survival prediction by leveraging information across anatomically distinct HPV related cancers. Furthermore, data were obtained from the Surveillance, Epidemiology, and End Results (SEER) program database. The study cohort consisted of 29,768 primary cancer cases diagnosed in the United States between 2004 and 2015. Ten different cancer diagnoses were selected, all with a known association with HPV risk. In the analysis, the cancer diagnoses were categorized into three distinct topography groups of varying specificity. The most specific topography grouping consisted of 10 original cancer diagnoses differentiated by the first two digits of the ICD-O-3 topography code. The second topography grouping consisted of cancer diagnoses categorized into six distinct organ groups. Finally, the third topography grouping consisted of just two groups, head-neck cancers and ano-genital cancers. The tasks were to predict 5-year survival for patients within the different topography groups using 14 predictive features which were selected among descriptive variables available in the SEER database. The information from the predictive features was shared between tasks in three different ways, resulting in three distinct predictive models: 1) Information was not shared between patients assigned to different tasks (single task learning); 2) Information was shared between all patients, regardless of task (pooled model); 3) Only relevant information was shared between patients grouped to different tasks (multitask learning). Prediction performance was evaluated with Brier scores. All three models were evaluated against one another on each of the three distinct topography-defined tasks. The results showed that multitask classifiers achieved relative improvement for the majority of the scenarios studied compared to single task learning and pooled baseline methods. In this study, we have demonstrated that sharing information among anatomically distinct cancer types can lead to improved predictive survival models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Systemic effects of rising atmospheric vapor pressure deficit on plant physiology and productivity

Abstract Earth is currently undergoing a global increase in atmospheric vapor pressure deficit (VPD), a trend which is expected to continue as climate warms. This phenomenon has been associated with productivity decreases in ecosystems and yield penalties in crops, with these losses attributed to photosynthetic limitations arising from decreased stomatal conductance. Such VPD increases, however, have occurred over decades, which raises the possibility that stomatal acclimation to VPD plays an important role in determining plant productivity under high VPD. Furthermore, evidence points to more far‐ranging and complex effects of elevated VPD on plant physiology, extending to the anatomical, biochemical, and developmental levels, which could vary substantially across species. Because these complex effects are typically not considered in modeling frameworks, we conducted a quantitative literature review documenting temperature‐independent VPD effects on 112 species and 59 traits and physiological variables, in order to develop an integrated and mechanistic physiological framework. We found that VPD increase reduced yield and primary productivity, an effect that was partially mediated by stomatal acclimation, and also linked with changes in leaf anatomy, nutrient, and hormonal status. The productivity decrease was also associated with negative effects on reproductive development, and changes in architecture and growth rates that could decrease the evaporative surface or minimize embolism risk. Cross‐species quantitative relationships were found between levels of VPD increase and trait responses, and we found differences across plant groups, indicating that future VPD impacts will depend on community assembly and crop functional diversity. Our analysis confirms predictions arising from the hydraulic corollary to Darcy's law, outlines a systemic physiological framework of plant responses to rising VPD, and provides recommendations for future research to better understand and mitigate VPD‐mediated climate change effects on ecosystems and agro‐systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Predicting the Longitudinally and Radially Varying Gut Microbiota Composition Using Multi-Scale Microbial Metabolic Modeling

Background: The gut microbiota is a heterogeneous group of microbes that is spatially distributed along various sections of the intestines and across the mucosa and lumen in each section. Understanding the dynamics between the spatially differential microbial populations and the driving forces for the observed spatial organization will provide valuable insights into important questions such as the nature of colonization of the infant gut and different types of inflammatory bowel disease localized in different regions of the intestines. However, in most studies, the microbiota is sampled only at a single site (often feces) or from a particular anatomical site of the intestines. Differential oxygen availability is putatively a key factor shaping the spatial organization. Results: To test this hypothesis, we constructed a community genome-scale metabolic model consisting of representative organisms for the major phyla present in the human gut microbiome. By solving step-wise optimization problems embedded in a dynamic framework to predict community metabolism and integrate the mucosally-adherent with the luminal microbiome between consecutive sections along the intestines, we were able to capture (i) the essential features of the spatially differential composition of obligate anaerobes vs. facultative anaerobes and aerobes determined experimentally, and (ii) the accumulation of microbial biomass in the lumen. Sensitivity analysis suggests that the spatial organization depends primarily on the oxygen-per-microbe availability in each region. Oxygen availability is reduced relative to the ~100-fold increase in mucosal microbial density along the intestines, causing the switch between aerobes and anaerobes. Conclusion: The proposed integrated dynamic framework is able to predict spatially differential gut microbiota composition using microbial genome-scale metabolic models and test hypotheses regarding the dynamics of the gut microbiota. It can potentially become a valuable tool for exploring therapeutic strategies for site-specific perturbation of the gut microbiota and the associated metabolic activities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Neural Connectivity and Immunocytochemical Studies of Anatomical Sites Related to Nauseogenic and Emetic Reflexes

The studies conducted in this research project examined several aspects of neuroanatomical structures and neurochemical processes related to motion sickness in animal models. A principle objective of these studies was to investigate neurochemical changes in the central nervous system that are related to motion sickness with the objective of defining neural mechanisms important to this malady. For purposes of exposition, the studies and research finding have been classified into five categories. These are: immunoreactivity in the brainstem, vasopressin effects, lesion studies of area postrema, role of the vagus nerve, and central nervous system structure related to adaptation to microgravity.

Fox, Robert A.↗