Near-infrared reflectance spectroscopy phenomic prediction can perform similarly to genomic prediction of maize agronomic traits across environments.

For nearly two decades, genomic prediction and selection have supported efforts to increase genetic gains in plant and animal improvement programs. However, novel phenomic strategies for predicting complex traits in maize have recently proven beneficial when integrated into across-environment sparse genomic prediction models. One phenomic data modality is whole grain near-infrared spectroscopy (NIRS), which records reflectance values of biological samples (e.g., maize kernels) based on chemical composition. Predictions of hybrid maize grain yield (GY) and 500-kernel weight (KW) across 2 years (2011-2012) and two management conditions (water-stressed and well-watered) were conducted using combinations of reflectance data obtained from high-throughput, F2 whole-kernel scans and genomic data obtained from genotyping-by-sequencing within four different cross-validation (CV) schemes (CV2, CV1, CV0, and CV00). When predicting the performance of untested genotypes in characterized (CV1) environments, genomic data were better than phenomic data for GY (0.689 ± 0.024-genomic vs. 0.612 ± 0.045-phenomic), but phenomic data were better than genomic data for KW (0.535 ± 0.034-genomic vs. 0.617 ± 0.145-phenomic). Multi-kernel models (combinations of phenomic and genomic relationship matrices) did not surpass single-kernel models for GY prediction in CV1 or CV00 (prediction of untested genotypes in uncharacterized environments); however, these models did outperform the single-kernel models for prediction of KW in these same CVs. Lasso regression applied to the NIRS data set selected a subset of 216 NIRS bands that achieved comparable prediction abilities to the full phenomic data set of 3112 bands predicting GY and KW under CV1 and CV00.

Evaluating and Predicting the Performance of Sorghum Lines in an Elite by Exotic Backcross-Nested Association Mapping Population.

Maintaining or introducing genetic diversity into plant breeding programs is necessary for continual genetic gain; however, diversity at the cost of reduced performance is not something sought by breeders. To this end, backcross-nested association mapping (BC-NAM) populations, in which the recurrent parent is an elite line, can be employed as a strategy to introgress diversity from unadapted accessions while maintaining agronomic performance. This study evaluates (i) the hybrid performance of sorghum lines from 18 BC1-NAM families and (ii) the potential of genomic prediction to screen lines from BC1-NAM families for hybrid performance prior to phenotypic evaluation. Despite the diverse geographical origins and agronomic performance of the unadapted parents for BC1-NAM families, many BC1-derived lines performed significantly better in the hybrid trials than the elite recurrent parent, R.Tx436. The genomic prediction accuracies for grain yield, plant height, and days to mid-anthesis were acceptable, but the prediction accuracies for plant height were lower than expected. While the prediction accuracies increased when including more individuals in the training set, improvements tended to plateau between two and five lines per family, with larger training sets being required for more complex traits such as grain yield. Therefore, genomic prediction models can be optimized in a large BC1-NAM population with a relatively low fraction of individuals needing to be evaluated. These results suggest that genomic prediction is an effective method of pre-screening lines within BC1-NAM families prior to evaluation in extensive hybrid field trials.

Five multivariate Duchenne muscular dystrophy progression models bridging six-minute walk distance and MRI relaxometry of leg muscles.

The study aimed to provide quantitative information on the utilization of MRI transverse relaxation time constant (MRI-T2) of leg muscles in DMD clinical trials by developing multivariate disease progression models of Duchenne muscular dystrophy (DMD) using 6-min walk distance (6MWD) and MRI-T2. Clinical data were collected from the prospective and longitudinal ImagingNMD study. Disease progression models were developed by a nonlinear mixed-effect modeling approach. Univariate models of 6MWD and MRI-T2 of five muscles were developed separately. Age at assessment was the time metric. Multivariate models were developed by estimating the correlation of 6MWD and MRI-T2 model variables. Full model estimation approach for covariate analysis and five-fold cross validation were conducted. Simulations were performed to compare the models and predict the covariate effects on the trajectories of 6MWD and MRI-T2. Sigmoid Imax and Emax models best captured the profiles of 6MWD and MRI-T2 over age. Steroid use, baseline 6MWD, and baseline MRI-T2 were significant covariates. The median age at which 6MWD is half of its maximum decrease in the five models was similar, while the median age at which MRI-T2 is half of its maximum increase varied depending on the type of muscle. The models connecting 6MWD and MRI-T2 successfully quantified how individual characteristics alter disease trajectories. The models demonstrate a plausible correlation between 6MWD and MRI-T2, supporting the use of MRI-T2. The developed models will guide drug developers in using the MRI-T2 to most efficient use in DMD clinical trials.

Aphid-Induced Volatiles and Subsequent Attraction of Natural Enemies Varies among Sorghum Cultivars.

The production of herbivore-induced plant volatiles (HIPVs) is a type of indirect defense used by plants to attract natural enemies and reduce herbivory by insect pests. In many crops little is known about genotypic variation in HIPV production or how this may affect natural enemy attraction. In this study, we identified and quantified HIPVs produced by 10 sorghum (Sorghum bicolor) cultivars infested with a prominent aphid pest, the sorghum aphid (Melanaphis sorghi Theobald). Volatiles were collected using dynamic headspace sampling techniques and identified and quantified using GC-MS. The total amounts of volatiles induced by the aphids did not differ among the 10 cultivars, but overall blends of volatiles differed significantly in composition. Most notably, aphid herbivory induced higher levels of methyl salicylate (MeSA) emission in two cultivars, whereas in four cultivars, the volatile emissions did not change in response to aphid infestation. Dual-choice olfactometer assays were used to determine preference of the aphid parasitoid, Aphelinus nigritus, and predator, Chrysoperla rufilabris, between plants of the same cultivar that were un-infested or infested with aphids. Two aphid-infested cultivars were preferred by natural enemies, while four other cultivars were more attractive to natural enemies when they were free of aphids. The remaining four cultivars elicited no response from parasitoids. Our work suggests that genetic variation in HIPV emissions greatly affects parasitoid and predator attraction to aphid-infested sorghum and that screening crop cultivars for specific predator and parasitoid attractants has the potential to improve the efficacy of biological control.

Comparison of dynamic susceptibility contrast (DSC) using gadolinium and iron-based contrast agents in high-grade glioma at high-field MRI.

PURPOSE: To compare DSC-MRI using Gadolinium (GBCA) and Ferumoxytol (FBCA) in high-grade glioma at 3T and 7T MRI field strengths. We hypothesized that using FBCA at 7T would enhance the performance of DSC, as measured by contrast-to-noise ratio (CNR). METHODS: Ten patients (13 lesions) were assigned to 3T (6 patients, 6 lesions) or 7T (4 patients, 7 lesions). All lesions received 0.1 mmol/kg of GBCA on day 1. Ten lesions (4 at 3T and 6 at 7T) received a lower dose (0.6 mg/kg) of FBCA, followed by a higher dose (1.0-1.2 mg/kg), while 3 lesions (2 at 3T and 1 at 7T) received only a higher dose on Day 2. CBV maps with leakage correction for GBCA but not for FBCA were generated. The CNR and normalized CBV (nCBV) were analyzed on enhancing and non-enhancing high T2W lesions. RESULTS: Regardless of FBCA dose, GBCA showed higher CNR than FBCA at 7T, which was significant for high-dose FBCA (p < .05). Comparable CNR between GBCA and high-dose FBCA was observed at 3T. There was a trend toward higher CNR for FBCA at 3T than 7T. GBCA also showed nCBV twice that of FBCA at both MRI field strengths with significance at 7T. CONCLUSION: GBCA demonstrated higher image conspicuity, as measured by CNR, than FBCA on 7T. The stronger T2* weighting realized with higher magnetic field strength, combined with FBCA, likely results in more signal loss rather than enhanced performance on DSC. However, at clinical 3T, both GBCA and FBCA, particularly a dosage of 1.0-1.2 mg/kg (optimal for perfusion imaging), yielded comparable CNR.

Imaging chronic active lesions in multiple sclerosis: a consensus statement.

Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis (MS) and have implications for non-relapsing biological progression. In recent years, the discovery of innovative magnetic resonance imaging (MRI) and PET derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with MS, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted (T1-w) and T2-w scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification, and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a Consensus Statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this Consensus Statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge.

Prototype Description and Ex Vivo Evaluation of a System for Combined Endorectal Magnetic Resonance Imaging and In-Bore Biopsy of the Prostate.

ABSTRACT: We describe early ex vivo proof-of-concept testing of a novel system composed of a disposable endorectal coil and converging multichannel needle guide with a reusable clamp stand, embedded electronics, and baseplate to allow for endorectal magnetic resonance (MR) imaging and in-bore MRI-targeted biopsy of the prostate as a single integrated procedure. Using prostate phantoms imaged with standard T 2 -weighted sequences in a Siemens 3T Prisma MR scanner, we measured the signal-to-noise ratio in successive 1-cm distances from the novel coil and from a commercially available inflatable balloon coil and measured the lateral and longitudinal deviation of the tip of a deployed MR compatible needle from the intended target point. Signal-to-noise ratio obtained with the novel system was significantly better than the inflatable balloon coil at each of five 1-cm intervals, with a mean improvement of 78% ( P < 0.05). In a representative sampling of 15 guidance channels, the mean lateral deviation for MR imaging-guided needle positioning was 1.7 mm and the mean longitudinal deviation was 2.0 mm. Our ex vivo results suggest that our novel system provides significantly improved signal-to-noise ratio when compared with an inflatable balloon coil and is capable of accurate MRI-guided needle deployment.

Impact of stalling events on microcirculatory hemodynamics in the aged brain.

OBJECTIVE: The role of cerebral microvasculature in cognitive dysfunction can be investigated by identifying the impact of blood flow on cortical tissue oxygenation. In this paper, the impact of capillary stalls on microcirculatory characteristics such as flow and hematocrit (Ht) in the cortical angioarchitecture is studied. METHODS: Using a deterministic mathematical model to simulate blood flow in a realistic mouse cortex, hemodynamics parameters, including pressure, flow, vessel diameter-adjustable hematocrit, and transit time are calculated as a function of stalling events. RESULTS: Using a non-linear plasma skimming model, it is observed that Ht increases in the penetrating arteries from the pial vessels as a function of cortical depth. The incidence of stalling on Ht distribution along the blood network vessels shows reduction of RBCs around the tissue near occlusion sites and decreased Ht concentration downstream from the blockage points. Moreover, upstream of the occlusion, there is a noticeable increase of the Ht, leading to larger flow resistance due to higher blood viscosity. We predicted marked changes in transit time behavior due to stalls which match trends observed in mice in vivo. CONCLUSIONS: These changes to blood cell quantity and quality may be implicated in the development of Alzheimer's disease and contribute to the course of the illness.

Clinical importance of changes in magnetic resonance biomarkers for Duchenne muscular dystrophy.

OBJECTIVE: Magnetic resonance (MR) measures of muscle quality are highly sensitive to disease progression and predictive of meaningful functional milestones in Duchenne muscular dystrophy (DMD). This investigation aimed to establish the reproducibility, responsiveness to disease progression, and minimum clinically important difference (MCID) for multiple MR biomarkers at different disease stages in DMD using a large natural history dataset. METHODS: Longitudinal MR imaging and spectroscopy outcomes and ambulatory function were measured in 180 individuals with DMD at three sites, including repeated measurements on two separate days (within 1 week) in 111 participants. These data were used to calculate day-to-day reproducibility, responsiveness (standardized response mean, SRM), minimum detectable change, and MCID. A survey of experts was also performed. RESULTS: MR spectroscopy fat fraction (FF), as well as MR imaging transverse relaxation time (MRI-T2 ), measures performed in multiple leg muscles, and had high reproducibility (Pearson's R > 0.95). Responsiveness to disease progression varied by disease stage across muscles. The average FF from upper and lower leg muscles was highly responsive (SRM > 0.9) in both ambulatory and nonambulatory individuals. MCID estimated from the distribution of scores, by anchoring to function, and via expert opinion was between 0.01 and 0.05 for FF and between 0.8 and 3.7 ms for MRI-T2 . INTERPRETATION: MR measures of FF and MRI T2 are reliable and highly responsive to disease progression. The MCID for MR measures is less than or equal to the typical annualized change. These results confirm the suitability of these measures for use in DMD and potentially other muscular dystrophies.

Vascular synthesis based on hemodynamic efficiency principle recapitulates measured cerebral circulation properties in the human brain.

Quantifying anatomical and hemodynamical properties of the brain vasculature in vivo is difficult due to limited spatiotemporal resolution neuroimaging, variability between subjects, and bias between acquisition techniques. This work introduces a metabolically inspired vascular synthesis algorithm for creating a digital representation of the cortical blood supply in humans. Spatial organization and segment resistances of a cortical vascular network were generated. Cortical folding and macroscale arterial and venous vessels were reconstructed from anatomical MRI and MR angiography. The remaining network, including ensembles representing the parenchymal capillary bed, were synthesized following a mechanistic principle based on hydrodynamic efficiency of the cortical blood supply. We evaluated the digital model by comparing its simulated values with in vivo healthy human brain measurements of macrovessel blood velocity from phase contrast MRI and capillary bed transit times and bolus arrival times from dynamic susceptibility contrast. We find that measured and simulated values reasonably agree and that relevant neuroimaging observables can be recapitulated in silico. This work provides a basis for describing and testing quantitative aspects of the cerebrovascular circulation that are not directly observable. Future applications of such digital brains include the investigation of the organ-wide effects of simulated vascular and metabolic pathologies.

Number Needed to Treat (NNT): Evaluation Tool Used in Health and Wellness Program.

As life insurance companies evaluate prospective health and wellness programs, one frequently used tool is the number needed to treat (NNT) calculation. It is helpful to identify what the NNT might be for individual components of the program as well as for the whole program when all components are combined.

Multivariate modeling of magnetic resonance biomarkers and clinical outcome measures for Duchenne muscular dystrophy clinical trials.

Although regulatory agencies encourage inclusion of imaging biomarkers in clinical trials for Duchenne muscular dystrophy (DMD), industry receives minimal guidance on how to use these biomarkers most beneficially in trials. This study aims to identify the optimal use of muscle fat fraction biomarkers in DMD clinical trials through a quantitative disease-drug-trial modeling and simulation approach. We simultaneously developed two multivariate models quantifying the longitudinal associations between 6-minute walk distance (6MWD) and fat fraction measures from vastus lateralis and soleus muscles. We leveraged the longitudinal individual-level data collected for 10 years through the ImagingDMD study. Age of the individuals at assessment was chosen as the time metric. After the longitudinal dynamic of each measure was modeled separately, the selected univariate models were combined using correlation parameters. Covariates, including baseline scores of the measures and steroid use, were assessed using the full model approach. The nonlinear mixed-effects modeling was performed in Monolix. The final models showed reasonable precision of the parameter estimates. Simulation-based diagnostics and fivefold cross-validation further showed the model's adequacy. The multivariate models will guide drug developers on using fat fraction assessment most efficiently using available data, including the widely used 6MWD. The models will provide valuable information about how individual characteristics alter disease trajectories. We will extend the multivariate models to incorporate trial design parameters and hypothetical drug effects to inform better clinical trial designs through simulation, which will facilitate the design of clinical trials that are both more inclusive and more conclusive using fat fraction biomarkers.

Use of genomic prediction to screen sorghum B-lines in hybrid testcrosses.

Use of trifluoromethanesulfonamide (TFMSA), a male gametocide, increases the opportunities to identify promising B-lines because large quantities of F1 seed can be generated prior to the laborious task of B-line sterilization. Combining TFMSA technology with genomic selection could efficiently evaluate sorghum B-lines in hybrid combination to maximize the rates of genetic gain of the crop. This study used two recombinant inbred B-line populations, consisting of 217 lines, which were testcrossed to two R-lines to produce 434 hybrids. Each population of testcross hybrids were evaluated across five environments. Population-based genomic prediction models were assessed across environments using three different cross-validation (CV) schemes, each with 70% training and 30% validation sets. The validation schemes were as follows: CV1-hybrids chosen randomly for validation; CV2-B-lines were randomly chosen, and each chosen B-line had one of the two corresponding testcross hybrids randomly chosen for the validation; and CV3-B-lines were randomly chosen, and each chosen B-line had both corresponding testcross hybrids chosen for the validation. CV1 and CV2 presented the highest prediction accuracies; nonetheless, the prediction accuracies of the CV schemes were not statistically different in many environments. We determined that combining the B-line populations could improve prediction accuracies, and the genomic prediction models were able to effectively rank the poorest 70% of hybrids even when genomic prediction accuracies themselves were low. Results indicate that combining genomic prediction models and TFMSA technology can effectively aid breeders in predicting B-line hybrid performance in early generations prior to the laborious task of generating A/B-line pairs.

Genomic prediction can be used to screen sorghum B-lines for hybrid grain yield and days to mid-anthesis. Using genomic prediction and the chemical gametocide TFMSA can increase the rate of genetic gain in sorghum B-lines. Using testers to screen sorghum B-line populations is an effective method for screening with genomic prediction. Genomic prediction can effectively predict hybrid performance within and across populations of sorghum B-lines. The ability to accurately rank hybrid performance remained relatively consistent regardless of prediction accuracy.

Biophysical, Nutraceutical, and Technofunctional Features of Specialty Cereals: Pigmented Popcorn and Sorghum.

Different pigmented corn and sorghum types were evaluated to characterize their biophysical, nutraceutical, and technofunctional properties for the first time. Commercially pigmented (blue, purple, red, black, and yellow) popcorn (Zea mays var. everta) and sorghum (Sorghum bicolor L.) of yellow and red colors were analyzed. Biophysical and proximal analyses were performed using official methods. The nutraceutical profile included the total phenolic and anthocyanin content. In addition, rheological, structural, and morphological studies were conducted. The results demonstrated significant differences between the popcorn samples and grain types, especially in terms of their biophysical and proximate features. The nutraceutical profile revealed that these specialty grains contained higher concentrations of antioxidant compounds (up to 3-fold when compared with the other grains). The rheological analysis demonstrated that sorghum grains developed higher peak viscosities than popcorn. According to the structural assessments, the type A pattern displayed peaks at the interplanar spaces corresponding to the crystalline and amorphous regions in all the samples. The data obtained in this study provides a base to further investigate the products obtained using these biomaterials.

Processing speed and memory test performance are associated with different brain region volumes in Veterans and others with progressive multiple sclerosis.

Background: Cognitive dysfunction and brain atrophy are both common in progressive multiple sclerosis (MS) but are seldom examined comprehensively in clinical trials. Antioxidant treatment may affect the neurodegeneration characteristic of progressive MS and slow its symptomatic and radiographic correlates. Objectives: This study aims to evaluate cross-sectional associations between cognitive battery components of the Brief International Cognitive Assessment for Multiple Sclerosis with whole and segmented brain volumes and to determine if associations differ between secondary progressive (SPMS) and primary progressive (PPMS) MS subtypes. Design: The study was based on a baseline analysis from a multi-site randomized controlled trial of the antioxidant lipoic acid in veterans and other people with progressive MS (NCT03161028). Methods: Cognitive batteries were conducted by trained research personnel. MRIs were processed at a central processing site for maximum harmonization. Semi-partial Pearson's adjustments evaluated associations between cognitive tests and MRI volumes. Regression analyses evaluated differences in association patterns between SPMS and PPMS cohorts. Results: Of the 114 participants, 70% had SPMS. Veterans with MS made up 26% (n = 30) of the total sample and 73% had SPMS. Participants had a mean age of 59.2 and sd 8.5 years, and 54% of them were women, had a disease duration of 22.4 (sd 11.3) years, and had a median Expanded Disability Status Scale of 6.0 (with an interquartile range of 4.0-6.0, moderate disability). The Symbol Digit Modalities Test (processing speed) correlated with whole brain volume (R = 0.29, p = 0.01) and total white matter volume (R = 0.33, p < 0.01). Both the California Verbal Learning Test (verbal memory) and Brief Visuospatial Memory Test-Revised (visual memory) correlated with mean cortical thickness (R = 0.27, p = 0.02 and R = 0.35, p < 0.01, respectively). Correlation patterns were similar in subgroup analyses. Conclusion: Brain volumes showed differing patterns of correlation across cognitive tasks in progressive MS. Similar results between SPMS and PPMS cohorts suggest combining progressive MS subtypes in studies involving cognition and brain atrophy in these populations. Longitudinal assessment will determine the therapeutic effects of lipoic acid on cognitive tasks, brain atrophy, and their associations.

Rate of crop-weed hybridization in Sorghum bicolor × Sorghum halepense is influenced by genetic background, pollen load, and the environment.

The potential for gene flow between cultivated species and their weedy relatives poses agronomic and environmental concerns, particularly when there are opportunities for the transfer of adaptive or agronomic traits such as herbicide resistance into the weedy forms. Grain sorghum (Sorghum bicolor) is an important crop capable of interspecific hybridization with its weedy relative johnsongrass (Sorghum halepense). Previous findings have shown that triploid progenies resulting from S. bicolor × S. halepense crosses typically collapse with only a few developing into mature seeds, whereas tetraploids often fully develop. The objective of this experiment was to determine the impact of S. bicolor genotype and pollen competition on the frequency of hybridization between S. bicolor and S. halepense. A total of 12 different cytoplasmic male sterile S. bicolor genotypes were compared with their respective male fertile lines across 2 years, to assess the frequency of hybridization and seed set when S. halepense served as the pollinator parent. Results indicate significant differences in the frequency of interspecific hybridization among the S. bicolor genotypes, and pollen fertility in S. bicolor reduced the rate of this interspecific hybridization by up to two orders of magnitude. Further, hybridization rates greatly varied across the two study environments. Results are helpful for developing appropriate gene flow mitigation strategies and indicate that gene flow could be reduced by the selection of appropriate seed parents for sorghum hybrids.

Vascular disease risk factors in multiple sclerosis: Effect on metabolism and brain volumes.

BACKGROUND: Vascular disease risk factors (VDRF) such as hypertension, hyperlipidemia, obesity, diabetes and heart disease likely play a role in disease progression in people with multiple sclerosis (PwMS) (Marrie, Rudick et al. 2010). Studies exploring the mechanistic connection between vascular disease and MS disease progression are scant. We hypothesized that phosphate energy metabolism impairment in PwMS with VDRFs (VDRF+) will be greater compared to PwMS without VDRFs (VDRF-) and is related to increased brain atrophy in VDRF+. To test this hypothesis, we planned to study the differences in the high energy phosphate (HEP) metabolites in cerebral gray matter as assessed by 31P magnetic resonance spectroscopic imaging (MRSI) and MRI brain volumetric in the VDRF+ and VDRF- PwMS at four different timepoints over a 3 yearlong period using a 7T MR system. We present here the results from the cross-sectional evaluation of HEP metabolites and brain volumes. We also evaluated the differences in clinical impairment, blood metabolic biomarkers and quality of life in VDRF+ and VDRF- PwMS in this cohort. METHODS: Group differences in high energy phosphate metabolites were assessed from a volume of interest in the occipital region using linear mixed models. Brain parenchymal and white matter lesion volumes were determined from MR anatomic images. We present here the cross-sectional analysis of the baseline data collected as part of a longitudinal 3 yearlong study where we obtained baseline and subsequent 6-monthly clinical and laboratory data and annual 7T MRI volumetric and 31P MR spectroscopic imaging (MRSI) data on 52 PwMS with and without VDRF. Key clinical and laboratory outcomes included: body mass index (BMI), waist and thigh circumferences and disability [Expanded Disability Status Scale (EDSS)], safety (complete blood count with differential, complete metabolic), lipid panel including total cholesterol and HbA1C. We analyzed clinical and laboratory data for the group differences using student's t or χ2 test. We investigated relationship between phosphate metabolites and VDRF using mixed effect linear regression. RESULTS: Complete MRI data were available for 29 VDRF+, age 56.3 (6.8) years [mean (SD)] (83% female), and 23 VDRF-, age 52.5 (7.5) years (57% female) individuals with MS. The mean value of normalized adenosine triphosphate (ATP) (calculated as the ratio of ATP to total phosphate signal in a voxel) was decreased by 4.5% (p < .05) in VDRF+ compared to VDRF- MS group. White matter lesion (WML) volume fraction in VDRF+ individuals {0.007 (0.007)} was more than doubled compared to VDRF- participants {0.003 (0.006), p= .02}. CONCLUSIONS: We found significantly lower brain ATP and higher inorganic phosphate (Pi) in those PwMS with VDRFs compared to those without. ATP depletion may reflect mitochondrial dysfunction. Ongoing longitudinal data analysis from this study, not presented here, will evaluate the relationship of phosphate metabolites, brain atrophy and disease progression in PwMS with and without vascular disease.

Brain volumetrics across the lifespan of the rhesus macaque.

The rhesus macaque is a long-lived nonhuman primate (NHP) with a brain structure similar to humans, which may represent a valuable translational animal model in which to study human brain aging. Previous magnetic resonance imaging (MRI) studies of age in rhesus macaque brains have been prone to low statistical power, unbalanced sex ratio and lack of a complete age range. To overcome these problems, the current study surveyed structural T1-weighted magnetic resonance imaging scans of 66 animals, 34 females (aged 6-31 years) and 32 males (aged 5-27 years). Differences observed in older animals, included enlargement of the lateral ventricles and a smaller volume in the frontal cortex, caudate, putamen, hypothalamus, and thalamus. Unexpected, greater volume, were measured in older animals in the hippocampus, amygdala, and globus pallidus. There were also numerous differences between males and females with respect to age in both white and gray matter regions. As an apparent model of normative human aging, the macaque is ideal for studying induction and mitigation of neurodegenerative disease.

Evaluating Introgression Sorghum Germplasm Selected at the Population Level While Exploring Genomic Resources as a Screening Method.

To exploit the novel genetic diversity residing in tropical sorghum germplasm, an expansive backcross nested-association mapping (BC-NAM) resource was developed in which novel genetic diversity was introgressed into elite inbreds. A major limitation of exploiting this type of genetic resource in hybrid improvement programs is the required evaluation in hybrid combination of the vast number of BC-NAM populations and lines. To address this, the utility of genomic information was evaluated to predict the hybrid performance of BC-NAM populations. Two agronomically elite BC-NAM populations were chosen for evaluation in which elite inbred RTx436 was the recurrent parent. Each BC1F3 line was evaluated in hybrid combination with an elite tester in two locations with phenotypes of grain yield, plant height, and days to anthesis collected on all test cross hybrids. Lines from both populations were found to outperform their recurrent parent. Efforts to utilize genetic distance based on genotyping-by-sequence (GBS) as a predictive tool for hybrid performance was ineffective. However, utilizing genomic prediction models using additive and dominance GBLUP kernels to screen germplasm appeared to be an effective method to eliminate inferior-performing lines that will not be useful in a hybrid breeding program.

Non-Destructive Direct Pericarp Thickness Measurement of Sorghum Kernels Using Extended-Focus Optical Coherence Microscopy.

Non-destructive measurements of internal morphological structures in plant materials such as seeds are of high interest in agricultural research. The estimation of pericarp thickness is important to understand the grain quality and storage stability of seeds and can play a crucial role in improving crop yield. In this study, we demonstrate the applicability of fiber-based Bessel beam Fourier domain (FD) optical coherence microscopy (OCM) with a nearly constant high lateral resolution maintained at over ~400 µm for direct non-invasive measurement of the pericarp thickness of two different sorghum genotypes. Whereas measurements based on axial profiles need additional knowledge of the pericarp refractive index, en-face views allow for direct distance measurements. We directly determine pericarp thickness from lateral sections with a 3 µm resolution by taking the width of the signal corresponding to the pericarp at the 1/e threshold. These measurements enable differentiation of the two genotypes with 100% accuracy. We find that trading image resolution for acquisition speed and view size reduces the classification accuracy. Average pericarp thicknesses of 74 µm (thick phenotype) and 43 µm (thin phenotype) are obtained from high-resolution lateral sections, and are in good agreement with previously reported measurements of the same genotypes. Extracting the morphological features of plant seeds using Bessel beam FD-OCM is expected to provide valuable information to the food processing industry and plant breeding programs.