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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Novel CHI3L1 ‐Associated Angiogenic Phenotypes Define Glioma Microenvironments: Insights From Multi‐Omics Integration

ABSTRACT The CHI3L1 signaling pathway significantly influences glioma angiogenesis, but its role in the tumor microenvironment (TME) remains elusive. We propose a novelCHI3L1‐associated vascular phenotype classification for glioma through integrative analyses of multiple datasets with bulk and single‐cell transcriptome, genomics, digital pathology, and clinical data. We investigated the biological characteristics, genomic alterations, therapeutic vulnerabilities, and immune profiles within these phenotypes through a comprehensive multi‐omics approach. We constructed the vascular‐related risk (VR) score based onCHI3L1‐associated vascular signatures (CAVS) identified by machine learning algorithms. Utilizing unsupervised consensus clustering, gliomas were stratified into three distinct vascular phenotypes: Cluster A, marked by high vascularization and stromal activation with a relatively low levels of tumor‐infiltrating lymphocytes (TILs); Cluster B, characterized by moderate vascularization and stromal activity, coupled with a high density of TILs; and Cluster C, defined by low vascularization and sparse immune cell infiltration. We observed that the CAVS effectively indicated glioma‐associated angiogenesis and immune suppression by single‐cell RNA‐seq analysis. Moreover, the high‐VR‐score group exhibited enhanced angiogenic activity, reduced immune response, resistance to immunotherapy, and poorer clinical outcomes. The VR score independently predicted glioma prognosis and, combined with a nomogram, provided a robust clinical decision‐making tool. Potential drug prediction based on transcription factors for high‐risk patients was also performed. Our study reveals thatCHI3L1‐associated vascular phenotypes shape distinct immune landscapes in gliomas, offering insights for optimizing therapeutic strategies to improve patient outcomes.

Oncology↗
DOE OSTI2024

Quantitative phenotyping of crop roots with spectral electrical impedance tomography: a rhizotron study with optimized measurement design

Background: Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results: Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass (R 2 = 0.82) and root surface area (R 2 = 0.8). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion: Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Spatial analysis of cell patterning to aid genetic and phenotypic understanding of grass stomatal density: A case study in maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Post-composing ontology terms for efficient phenotyping in plant breeding

Abstract Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization on the one hand and flexibility on the other. In many instances of Breedbase, a digital ecosystem for plant breeding designed for genomic selection, the goal is to capture phenotypic data using highly curated and rigorous crop ontologies, while adapting to the specific requirements of plant breeders to record data quickly and efficiently. For example, post-composing enables users to tailor ontology terms to suit specific and granular use cases such as repeated measurements on different plant parts and special sample preparation techniques. To achieve this, we have implemented a post-composing tool based on orthogonal ontologies providing users with the ability to introduce additional levels of phenotyping granularity tailored to unique experimental designs. Post-composed terms are designed to be reused by all breeding programs within a Breedbase instance but are not exported to the crop reference ontologies. Breedbase users can post-compose terms across various categories, such as plant anatomy, treatments, temporal events, and breeding cycles, and, as a result, generate highly specific terms for more accurate phenotyping.

Mathematical & Computational Biology↗
DOE OSTI2024

Bridging the gap: linking Torulaspora delbrueckii genotypes to fermentation phenotypes and wine aroma

Abstract Climate change and consumer preferences are driving innovation in winemaking, with a growing interest in non-Saccharomyces species. Among these, Torulaspora delbrueckii (Td) has gained recognition for its ability to reduce volatile acidity and enhance aromatic complexity in wine. However, knowledge regarding its phenotypic and genomic diversity impacting alcoholic fermentation remains limited. Aiming to elucidate the metabolic differences between Td and Saccharomyces cerevisiae (Sc) and the Td intraspecies diversity, we conducted a comprehensive metabolic characterization of 15 Td strains. This analysis delved beyond standard fermentation parameters (kinetics and major metabolites production) to explore non-conventional aromas and establish genotype-phenotype links. Our findings confirmed that most Td strains produce less acetic acid and more succinate and glycerol than Sc. The overall aromatic profiles of Td strains differed from Sc, exhibiting higher levels of monoterpenes and higher alcohols, while producing less acetate esters, fatty acids, their corresponding ethyl esters, and lactones. Moreover, we identified the absence of genes responsible for specific aroma profiles, such as decreased ethyl esters production, as well as the absence of cell wall genes, which might negatively affect Td performance when compared to Sc. This work highlights the significant diversity within Td and underscores potential links between its genotype and phenotype.

Silva-Sousa, Flávia (ORCID:0000000307383190)↗
DOE OSTI2024

Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning

Abstract Artificial intelligence and machine learning (AI/ML) can be used to automatically analyze large image datasets. One valuable application of this approach is estimation of plant trait data contained within images. Here we review 39 papers that describe the development and/or application of such models for estimation of stomatal traits from epidermal micrographs. In doing so, we hope to provide plant biologists with a foundational understanding of AI/ML and summarize the current capabilities and limitations of published tools. While most models show human-level performance for stomatal density (SD) quantification at superhuman speed, they are often likely to be limited in how broadly they can be applied across phenotypic diversity associated with genetic, environmental, or developmental variation. Other models can make predictions across greater phenotypic diversity and/or additional stomatal/epidermal traits, but require significantly greater time investment to generate ground-truth data. We discuss the challenges and opportunities presented by AI/ML-enabled computer vision analysis, and make recommendations for future work to advance accelerated stomatal phenotyping.

Plant Sciences↗
DOE OSTI2025

Rapid quantification of whole seed fatty acid amount, composition, and shape phenotypes from diverse oilseed species with large differences in seed size

Seed oils are widely used in the food, biofuel, and industrial feedstock industries, with their utility and value determined by total oil content and fatty acid composition. Current high throughput seed oil analysis methods either lack accuracy in total fatty acid profiling or require extensive labor for lipid extraction prior to derivatization to fatty acid methyl esters (FAME) and quantification by gas chromatography (GC). Alternatively, direct whole seed FAME production methods have been developed for the very small seeds in the model species Arabidopsis thaliana but these have generally not been adapted to larger seeds of most oilseed crops. High-throughput direct whole seed FAME production methods were optimized for seeds up to 5 mg each utilizing acid-catalyzed esterification. For the oilseed species Camelina sativa, Thlaspi avernse (pennycress), Cuphea viscosissima, and Brassica napus (var. Canola), the total seed fatty acid content and composition from direct seed esterification to FAME matched that of lipid extract derivatization demonstrating the accuracy of the methods. In combination with seed phenotyping using GridFree, this approach enabled the development of a rapid pipeline for simultaneous seed weight, count, size/shape phenotyping, and oil analysis. For the larger and tougher seeds produced by Limnanthes alba (Meadowfoam) and Cannabis sativa L. (hemp) the whole seed acid-based method proved insufficient, and prior laborious homogenization of seeds was required. Therefore, a rapid one-tube bead homogenization and base catalyzed-esterification method was developed. Base-derived fatty acid esterification cannot derivatize free fatty acids leading to slightly lower total seed fatty acid than acid-catalyzed methods, however the seed oil content and fatty acid composition that is valuable for screening large numbers of samples in research populations was accurately measured. New rapid whole seed fatty acid esterification and phenotyping protocols were developed to accurately assess oilseed lipid content. These methods are particularly valuable in oilseed research, breeding, and engineering applications where efficient analysis of large numbers of samples and accurate oil fatty acid profiling is essential. While having been developed for current and emerging oilseed crops, these methods also provide a foundation from which protocols might be established for new and emerging crop species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comparative transcriptomic and phenotypic analysis of monoclonal and polyclonal Populus deltoides genotypes

Populus species are highly valued for bioenergy and bioproducts due to their rapid growth and productivity. Polyclonal plantings, or mixtures of Populus clones, have shown the potential to enhance resource utilization and productivity, likely due to phenotypic differences arising from niche differentiation. In this study, we investigated gene expression and productivity in monoclonal and polyclonal stands of P. deltoides . Phenotypic results showed that polyclonal plots exhibited higher leaf area index (LAI; p < 0.01, 2.96 ± 0.057 m 2 ) and total biomass (p < 0.01, 2.74 ± 0.06) compared to monoclonal plots, indicating superior productivity. RNA sequencing revealed upregulation of key genes such as exocyst subunit exo70 family protein H7 (EXO70H7), NDH-dependent cyclic electron flow 5 (NDF5) , and expansin-like A3 (EXLA3) . We also observed enrichment in phenylalanine metabolism and other secondary metabolic pathways in clone S7C8. Phenotypic results, upregulated genes and enriched biological pathways identified in this study may explain the enhanced productivity, increased nitrate content, and expanded canopy in polyclonal plantings. Overall, this study provides a foundation for future research to enhance forest productivity by linking molecular mechanisms to practical applications in field plantings.

differential gene expression↗
NASA NTRS1991

Three Hierarchies in Skeletal Muscle Fibre Classification Allotype, Isotype and Phenotype

Immunocytochemical analyses using specific anti-myosin antibodies of mammalian muscle fibers during regeneration, development, and after denervation have revealed two distinct myogenic components determining fiber phenotype. The jaw-closing muscles of the cat contain superfast fibers which express a unique myosin not found in limb muscles. When superfast muscle is transplanted into a limb muscle bed, regenerating myotubes synthesize superfast myosin independent of innervation. Reinnervation by the nerve to a fast muscle leads to the expression of superfast and not fast myosin, while reinnervation by the nerve to a slow muscle leads to the expression of a slow myosin. When limb muscle is transplanted into the jaw muscle bed, only limb myosins are synthesized. Thus jaw and limb muscles belong to distinct allotypes, each with a unique range of phenotype options, the expressions of which may be modulated by the nerve. Primary and secondary myotubes in developing jaw and limb muscles are observed to belong to different categories characterized by different patterns of myosin gene expression. By taking into consideration the pattern of myosins synthesized and the changes in fiber size after denervation, 3 types of primary (fast, slow, and intermediate) fibers can be distinguished in rat fast limb muscles. All primaries synthesize slow myosin soon after their formation, but this is withdrawn in fast and intermediate primaries at different times. After neonatal denervation, slow and intermediate primaries express slow primaries hypertrophy with other fibers atrophy. In the mature rat, the number of slow fibers in the EDL is less than the number of slow primaries. Upon denervation, hypertrophic slow fibers matching the number and topographic distribution of slow primaries appear, suggesting that a subpopulation of the slow primaries acquire the fast phenotype during adult life, but reveal their original identity as slow primaries in response to denervation by hypertrophying and synthesizing slow myosin. It is proposed that within each muscle allotype, the various isotypes of primary and secondary fibers are myogenically determined, and are derived from different lineage of myoblasts.

Hoh, Joseph F. Y.↗
NASA NTRS2017

Skin-Based DNA Repair Phenotype for Cancer Risk from GCR in Genetically Diverse Populations

Predicting cancer risk associated with cosmic radiation remains a mission-critical challenge for NASA radiation health scientists and mission planners. Epidemiological data are lacking and risk methods do not take individual radiation sensitivity into account. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and cell death are ideal tools to predict risk and monitor potential health effects post-flight. At this workshop, we will be reporting the work we have done over the first 9 months of this proposal. Skin cells from 15 different strains of mice already characterized for radiation-induced cancer sensitivity (B6C3F; BALB/cByJ, C57BL/6J, CBA/CaJ, C3H/HeMsNrsf), and 10 strains from the DOE collaborative cross-mouse model were expanded from ear biopsy and cultivated until Passage 3. On average, 3 males and 3 females for each strain were expanded and frozen for further characterization at the NSRL beam line during the NSRL16C run for three LET (350 MeV/n Si, 350 MeV/n Ar and 600 MeV/n Fe) and two ion fluences (1 and 3 particles per cell). The mice work has established new metrics for the usage of Radiation Induced Foci as a marker for various aspect of DNA repair deficiencies. In year 2, we propose to continue characterization of the mouse lines with low LET to identify loci specific to high- versus low- LET and establish genetic linkage for the various DNA repair biomarkers. Correlation with cancer risk from each animals strain and gender will also be investigated. On the human side, we will start characterizing the DNA damage response induced ex-vivo in 200 human's blood donors for radiation sensitivity with a tentative 500 donors by the end of this project. All ex-vivo phenotypic data will be correlated to genetic characterization of each individual human donors using SNP arrays characterization as done for mice. Similarly, ex-vivo phenotypic features from mice will be associated to cancer risk, to identify which biomarkers correlate the most with cancer risk. Genetic traits across humans will also be associated to radiation phenotypic features as a function of age and gender.

radiation space biology↗
NASA NTRSDate not supplied

Genomic and Phenotypic Associations to Predict Human Sensitivity to SpaceRadiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350MeV/n 28Si, 350MeV/n 40Ar and 600MeV/n 56Fe particles, at 1.1 and 3 particles/100 sq.m fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1+ radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radio sensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radio sensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radio sensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS radiation human↗
NASA NTRSDate not supplied

Genomic and Phenotypic Predictors of Human Ex Vivo Sensitivity to Simulated Deep Space Radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe particles, at 1.1 and 3 particles/100 sq.m fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1+ radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radiosensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radiosensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radiosensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS↗
NASA NTRSDate not supplied

Genomic and phenotypic predictors of human ex vivo sensitivity to simulated deep space radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350MeV/n (28)Si, 350MeV/n (40)Ar and 600MeV/n (56)Fe particles, at 1.1 and 3 particles/100µm^(2) fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1^(+) radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radiosensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radiosensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radiosensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS↗
DOE OSTI2025

Bacterial and fungal growth on fungal necromass and its diverse components: Shared profiles and divergent constraints revealed by high‐throughput phenotyping

1. While fungal necromass is increasingly recognized as a major source of persistent carbon (C) in soils, the relative functional roles of bacteria and fungi in decomposing necromass are not fully resolved, and the processes that select for necromass decomposer communities from the broader soil microbial community are an emerging area of interest. 2. In this study, we characterized the growth of 52 bacterial and 83 fungal strains isolated from necromass and soil on 22 C substrates, including different necromass phenotypes, fungal cell wall polymers, dimers and monomers. 3. We found that the isolation habitat of the strains used in this experiment (necromass vs. soil) had no effect on the substrates they were able to use. Isolates from both microbial domains were able to grow on different labile carbon substrates, polymers and necromass phenotypes. However, fungal growth was most limited by necromass melanin content, while bacterial growth was more limited by the abundance of cell wall polysaccharides. Additionally, overall differences in substrate use between bacteria and fungi were most pronounced on polymer substrates. 4. Collectively, our results suggest that there is substantial functional overlap in necromass substrate use across microbial domains, but some notable differences in bacterial and fungal utilization of cell wall polymers, which can function as a direct energy source or a means of accessing other compounds within necromass. Future studies assessing bacteria and fungi decomposing necromass together rather than in isolation will help to uncover potential physical and chemical interactions within and between these two domains during the decay of this important source of persistent soil C.

dead fungal biomass↗
DOE OSTI2026

Improving 3D reconstruction quality for root phenotyping: assessing the impact of camera calibration and imaging parameters

Arate 3D reconstruction is essential for high-throughput plant phenotyping, particularly for studying complex structures such as root systems. While photogrammetry and Structure from Motion (SfM) techniques have become widely used for 3D root imaging, the camera settings used are often underreported in studies, and the impact of camera calibration on model accuracyccu remains largely underexplored in plant science. In this study, we systematically evaluate the effects of focus, aperture, exposure time, and gain settings on the quality of 3D root models made with a multi-camera scanning system. We show through a series of experiments that calibration significantly improves model quality, with focus misalignment and shallow depth of field (DoF) being the most important factors affecting reconstruction accuracy. Our results further show that proper calibration has a greater effect on reducing noise than filtering it during post-processing, emphasizing the importance of optimizing image acquisition rather than relying solely on computational corrections. This work improves the repeatability and accuracy of 3D root imaging for phenotyping pipelines by giving useful calibration guidelines. This leads to better trait quantification for use in crop research and plant breeding in downstream analysis.

3D reconstruction↗
NASA NTRS1989

Ethylene-associated phase change from juvenile to mature phenotype of daylily (Hemerocallis) in vitro

Hemerocallis plantlets maintained in vitro for extended periods of time in tightly closed culture vessels frequently show a phenotype, albeit on a miniaturized scale, typical of more mature, field-grown plants. The positive relationship of elevated ethylene in the headspace of such vessels to the phase shift from juvenile to mature form is established. Rigorous restriction in air exchange with the external environment by means of silicone grease seals hastens the phase change and improves uniformity of response. Although some plantlets may take longer to accumulate enough ethylene in sealed jars to undergo change, added ethylene and ethylene-releasing agents promote it. Ethylene adsorbants (e.g. mercuric perchlorate) block the shift of juvenile to mature form. Critical ambient ethylene level for the shift is ca 1 microliter l-1. Levels up to 1000 microliters l-1 do not hasten the response but are not toxic. The phase change is fully reversible when air exchange permits ethylene to drop below 1 microliter l-1. At least 1 microliter l-1 ethylene is required to sustain the mature phenotype. The ethylene synthesis inhibitor aminoethoxyvinylglycine (AVG) prevents the phase change, while the ethylene biosynthesis intermediate 1-aminocyclopropanecarboxylic acid (ACC) improves it. KOH, as a CO2 absorbent, does not prevent the phase change. Histology sections demonstrate subtle changes in the form of shoot tips of plantlets undergoing phase change.

NASA Discipline Plant Biology↗
NASA NTRS1985

Mature phenotype in Hemerocallis plantlets fortuitously generated in vitro

Daylily plantlets generated on semi-solid media from morphogenetically competent cells or morphogenetically competent cells regenerated from protoplasts can give rise in aseptic culture to plantlets with a mature phenotype. The individual leaves of these plantlets open to the extreme base so that no encircling leaf sheath is present. This permits the overlapping bases and leaves to assume an open fan-like arrangement. The occurrence of fans correlates with exceptionally tightly sealed culture vessels and experiments to date suggest a gaseous component is associated with this change of growth form. It has not been possible to fix the mature growth mode, however, and new leaf growth assumes the more normal juvenile phenotype when the gaseous environment is altered by admitting or exposure to room air.

NASA Discipline Plant Biology↗
NASA NTRS2001

A vestibular phenotype for Waardenburg syndrome?

OBJECTIVE: To investigate vestibular abnormalities in subjects with Waardenburg syndrome. STUDY DESIGN: Retrospective record review. SETTING: Tertiary referral neurotology clinic. SUBJECTS: Twenty-two adult white subjects with clinical diagnosis of Waardenburg syndrome (10 type I and 12 type II). INTERVENTIONS: Evaluation for Waardenburg phenotype, history of vestibular and auditory symptoms, tests of vestibular and auditory function. MAIN OUTCOME MEASURES: Results of phenotyping, results of vestibular and auditory symptom review (history), results of vestibular and auditory function testing. RESULTS: Seventeen subjects were women, and 5 were men. Their ages ranged from 21 to 58 years (mean, 38 years). Sixteen of the 22 subjects sought treatment for vertigo, dizziness, or imbalance. For subjects with vestibular symptoms, the results of vestibuloocular tests (calorics, vestibular autorotation, and/or pseudorandom rotation) were abnormal in 77%, and the results of vestibulospinal function tests (computerized dynamic posturography, EquiTest) were abnormal in 57%, but there were no specific patterns of abnormality. Six had objective sensorineural hearing loss. Thirteen had an elevated summating/action potential (>0.40) on electrocochleography. All subjects except those with severe hearing loss (n = 3) had normal auditory brainstem response results. CONCLUSION: Patients with Waardenburg syndrome may experience primarily vestibular symptoms without hearing loss. Electrocochleography and vestibular function tests appear to be the most sensitive measures of otologic abnormalities in such patients.

NASA Discipline Neuroscience↗