NASA Light Emitting Diode Medical Applications from Deep Space to Deep Sea

This work is supported and managed through the NASA Marshall Space Flight Center-SBIR Program. LED-technology developed for NASA plant growth experiments in space shows promise for delivering light deep into tissues of the body to promote wound healing and human tissue growth. We present the results of LED-treatment of cells grown in culture and the effects of LEDs on patients’ chronic and acute wounds. LED-technology is also biologically optimal for photodynamic therapy of cancer and we discuss our successes using LEDs in conjunction with light-activated chemotherapeutic drugs

Effect of NASA Light-emitting Diode Irradiation on Wound Healing

Objective: The purpose of this study was to assess the effects of hyperbaric oxygen (HBO) and near-infrared light therapy on wound healing. Background Data: Light-emitting diodes (LED), originally developed for NASA plant growth experiments in space show promise for delivering light deep into tissues of the body to promote wound healing and human tissue growth. In this paper, we review and present our new data of LED treatment on cells grown in culture, on ischemic and diabetic wounds in rat models, and on acute and chronic wounds in humans. Materials and Methods: In vitro and in vivo (animal and human) studies utilized a variety of LED wavelength, power intensity, and energy density parameters to begin to identify conditions for each biological tissue that are optimal for biostimulation. Results: LED produced in vitro increases of cell growth of 140–200% in mouse-derived fibroblasts, rat-derived osteoblasts, and rat-derived skeletal muscle cells, and increases in growth of 155–171% of normal human epithelial cells. Wound size decreased up to 36% in conjunction with HBO in ischemic rat models. LED produced improvement of greater than 40% in musculoskeletal training injuries in Navy SEAL team members, and decreased wound healing time in crew members aboard a U.S. Naval submarine. LED produced a 47% reduction in pain of children suffering from oral mucositis. Conclusion: We believe that the use of NASA LED for light therapy alone, and in conjunction with hyperbaric oxygen, will greatly enhance the natural wound healing process, and more quickly return the patient to a preinjury/ illness level of activity. This work is supported and managed through the NASA Marshall Space Flight Center–SBIR Program

TheoryGuru: A Mathematica Package to Apply Quantifier Elimination Technology to Economics

We consider the use of Quantifier Elimination (QE) technology for automated reasoning in economics. There is a great body of work considering QE applications in science and engineering but we demonstrate here that it also has use in the social sciences. We explain how many suggested theorems in economics could either be proven, or even have their hypotheses shown to be inconsistent, automatically via QE. However, economists who this technology could benefit are usually unfamiliar with QE, and the use of mathematical software generally. This motivated the development of a Mathematica Package TheoryGuru, whose purpose is to lower the costs of applying QE to economics. We describe the package's functionality and give examples of its use.Comment: To appear in Proc ICMS 201

Dimensions of a Projection Column and Architecture of VPM and POm Axons in Rat Vibrissal Cortex

This is the first article in a series of 3 studies that investigate the anatomical determinants of thalamocortical (TC) input to excitatory neurons in a cortical column of rat primary somatosensory cortex (S1). S1 receives 2 major types of TC inputs, lemiscal and paralemniscal. Lemiscal axons arise from the ventral posteromedial nucleus (VPM) of the thalamus, whereas paralemniscal fibers originate in the posteromedial nucleus (POm). While these 2 TC projections are largely complementary in L4, overlap in other cortical layers is still a matter of debate. VPM and POm axons were specifically labeled in the same rat by virus-mediated expression of different fluorescent proteins. We show that columnar and septal projection patterns are maintained throughout most of the cortical depth with a lower degree of separation in infragranular layers, where TC axons form bands along rows. Finally, we present anatomical dimensions of “TC projection domains” for a standard column in S1

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health

1Identification of genes differentially expressed in the embryonic pig cerebral cortex before and after appearance of gyration

<p>Abstract</p> <p>Background</p> <p>Mammalian evolution is characterized by a progressive expansion of the surface area of the cerebral cortex, an increase that is accompanied by gyration of the cortical surface. The mechanisms controlling this gyration process are not well characterized but mutational analyses indicate that genes involved in neuronal migration play an important function. Due to the lack of gyration of the rodent brain it is important to establish alternative models to examine brain development during the gyration process. The pig brain is gyrated and accordingly is a candidate alternative model.</p> <p>Findings</p> <p>In this study we have identified genes differentially expressed in the pig cerebral cortex before and after appearance of gyration. Pig cortical tissue from two time points in development representing a non-folded, lissencephalic, brain (embryonic day 60) and primary-folded, gyrencephalic, brain (embryonic day 80) were examined by whole genome expression microarray studies. 91 differentially expressed transcripts (fold change >3) were identified. 84 transcripts were annotated and encoding proteins involved in for example neuronal migration, calcium binding, and cytoskeletal structuring. Quantitative real-time PCR was used to confirm the regulation of a subset of the identified genes.</p> <p>Conclusion</p> <p>This study provides identification of genes which are differentially expressed in the pig cerebral cortex before and after appearance of brain gyration. The identified genes include novel candidate genes which could have functional importance for brain development.</p

A Novel Function of DELTA-NOTCH Signalling Mediates the Transition from Proliferation to Neurogenesis in Neural Progenitor Cells

A complete account of the whole developmental process of neurogenesis involves understanding a number of complex underlying molecular processes. Among them, those that govern the crucial transition from proliferative (self-replicating) to neurogenic neural progenitor (NP) cells remain largely unknown. Due to its sequential rostro-caudal gradients of proliferation and neurogenesis, the prospective spinal cord of the chick embryo is a good experimental system to study this issue. We report that the NOTCH ligand DELTA-1 is expressed in scattered cycling NP cells in the prospective chick spinal cord preceding the onset of neurogenesis. These Delta-1-expressing progenitors are placed in between the proliferating caudal neural plate (stem zone) and the rostral neurogenic zone (NZ) where neurons are born. Thus, these Delta-1-expressing progenitors define a proliferation to neurogenesis transition zone (PNTZ). Gain and loss of function experiments carried by electroporation demonstrate that the expression of Delta-1 in individual progenitors of the PNTZ is necessary and sufficient to induce neuronal generation. The activation of NOTCH signalling by DELTA-1 in the adjacent progenitors inhibits neurogenesis and is required to maintain proliferation. However, rather than inducing cell cycle exit and neuronal differentiation by a typical lateral inhibition mechanism as in the NZ, DELTA-1/NOTCH signalling functions in a distinct manner in the PNTZ. Thus, the inhibition of NOTCH signalling arrests proliferation but it is not sufficient to elicit neuronal differentiation. Moreover, after the expression of Delta-1 PNTZ NP continue cycling and induce the expression of Tis21, a gene that is upregulated in neurogenic progenitors, before generating neurons. Together, these experiments unravel a novel function of DELTA–NOTCH signalling that regulates the transition from proliferation to neurogenesis in NP cells. We hypothesize that this novel function is evolutionary conserved

Toward allele-specific targeting therapy and pharmacodynamic marker for spinocerebellar ataxia type 3

Spinocerebellar ataxia type 3 (SCA3), caused by a CAG repeat expansion in the ataxin-3 gene (ATXN3), is characterized by neuronal polyglutamine (polyQ) ATXN3 protein aggregates. Although there is no cure for SCA3, gene-silencing approaches to reduce toxic polyQ ATXN3 showed promise in preclinical models. However, a major limitation in translating putative treatments for this rare disease to the clinic is the lack of pharmacodynamic markers for use in clinical trials. Here, we developed an immunoassay that readily detects polyQ ATXN3 proteins in human biological fluids and discriminates patients with SCA3 from healthy controls and individuals with other ataxias. We show that polyQ ATXN3 serves as a marker of target engagement in human fibroblasts, which may bode well for its use in clinical trials. Last, we identified a single-nucleotide polymorphism that strongly associates with the expanded allele, thus providing an exciting drug target to abrogate detrimental events initiated by mutant ATXN3. Gene-silencing strategies for several repeat diseases are well under way, and our results are expected to improve clinical trial preparedness for SCA3 therapies

Landmarking the brain for geometric morphometric analysis: An error study

Neuroanatomic phenotypes are often assessed using volumetric analysis. Although powerful and versatile, this approach is limited in that it is unable to quantify changes in shape, to describe how regions are interrelated, or to determine whether changes in size are global or local. Statistical shape analysis using coordinate data from biologically relevant landmarks is the preferred method for testing these aspects of phenotype. To date, approximately fifty landmarks have been used to study brain shape. Of the studies that have used landmark-based statistical shape analysis of the brain, most have not published protocols for landmark identification or the results of reliability studies on these landmarks. The primary aims of this study were two-fold: (1) to collaboratively develop detailed data collection protocols for a set of brain landmarks, and (2) to complete an intra- and inter-observer validation study of the set of landmarks. Detailed protocols were developed for 29 cortical and subcortical landmarks using a sample of 10 boys aged 12 years old. Average intra-observer error for the final set of landmarks was 1.9 mm with a range of 0.72 mm-5.6 mm. Average inter-observer error was 1.1 mm with a range of 0.40 mm-3.4 mm. This study successfully establishes landmark protocols with a minimal level of error that can be used by other researchers in the assessment of neuroanatomic phenotypes. © 2014 Chollet et al

Neural correlates of evidence accumulation during value-based decisions revealed via simultaneous EEG-fMRI

Current computational accounts posit that, in simple binary choices, humans accumulate evidence in favour of the different alternatives before committing to a decision. Neural correlates of this accumulating activity have been found during perceptual decisions in parietal and prefrontal cortex; however the source of such activity in value-based choices remains unknown. Here we use simultaneous EEG–fMRI and computational modelling to identify EEG signals reflecting an accumulation process and demonstrate that the within- and across-trial variability in these signals explains fMRI responses in posterior-medial frontal cortex. Consistent with its role in integrating the evidence prior to reaching a decision, this region also exhibits task-dependent coupling with the ventromedial prefrontal cortex and the striatum, brain areas known to encode the subjective value of the decision alternatives. These results further endorse the proposition of an evidence accumulation process during value-based decisions in humans and implicate the posterior-medial frontal cortex in this process