This study extended the findings of Tighe and Schatschneider (2015) by investigating the predictive utility of separate dimensions of morphological awareness as well as vocabulary knowledge to reading comprehension in adult basic education (ABE) students. We competed two- and three-factor structural equation models of reading comprehension. A three-factor model of real word morphological awareness, pseudoword morphological awareness, and vocabulary knowledge emerged as the best fit and accounted for 79% of the reading comprehension variance. The results indicated that the constructs contributed jointly to reading comprehension; however, vocabulary knowledge was the only potentially unique predictor (p = 0.052), accounting for an additional 5.6% of the variance. This study demonstrates the feasibility of applying a latent variable modeling approach to examine individual differences in the reading comprehension skills of ABE students. Further, this study replicates the findings of Tighe and Schatschneider (2015) on the importance of differentiating among dimensions of morphological awareness in this population.

Our previous studies show reduced abundance of the β-subunit of mitochondrial H+-ATP synthase (β-F1-ATPase) in skeletal muscle of obese individuals. The β-F1-ATPase forms the catalytic core of the ATP synthase, and it is critical for ATP production in muscle. The mechanism(s) impairing β-F1-ATPase metabolism in obesity, however, are not completely understood. First, we studied total muscle protein synthesis and the translation efficiency of β-F1-ATPase in obese (BMI, 36±1 kg/m²) and lean (BMI, 22±1 kg/m²) subjects. Both total protein synthesis (0.044±0.006 vs 0.066±0.006%·h^-1) and translation efficiency of β-F1-ATPase (0.0031±0.0007 vs 0.0073±0.0004) were lower in muscle from the obese subjects when compared to the lean controls (P<0.05). We then evaluated these same responses in a primary cell culture model, and tested the specific hypothesis that circulating non-esterified fatty acids (NEFA) in obesity play a role in the responses observed in humans. The findings on total protein synthesis and translation efficiency of β-F1-ATPase in primary myotubes cultured from a lean subject, and after exposure to NEFA extracted from serum of an obese subject, were similar to those obtained in humans. Among candidate microRNAs (i.e., non-coding RNAs regulating gene expression), we identified miR-127-5p in preventing the production of β-F1-ATPase. Muscle expression of miR-127-5p negatively correlated with β-F1-ATPase protein translation efficiency in humans (r = – 0.6744; P<0.01), and could be modeled in vitro by prolonged exposure of primary myotubes derived from the lean subject to NEFA extracted from the obese subject. On the other hand, locked nucleic acid inhibitor synthesized to target miR-127-5p significantly increased β-F1-ATPase translation efficiency in myotubes (0.6±0.1 vs 1.3±0.3, in control vs exposure to 50 nM inhibitor; P<0.05). Our experiments implicate circulating NEFA in obesity in suppressing muscle protein metabolism, and establish impaired β-F1-ATPase translation as an important consequence of obesity.

Background: Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM.

Methods: We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set.

Results: We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients).

Conclusion: Multi-parametric MRI and texture analysis can help characterize and visualize GBM’s spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

Recent advances in nonequilibrium statistical physics have provided unprecedented insight into the thermodynamics of dynamic processes. The author recently used these advances to extend Landauer’s semi-formal reasoning concerning the thermodynamics of bit erasure, to derive the minimal free energy required to implement an arbitrary computation. Here, I extend this analysis, deriving the minimal free energy required by an organism to run a given (stochastic) map π from its sensor inputs to its actuator outputs. I use this result to calculate the input-output map π of an organism that optimally trades off the free energy needed to run π with the phenotypic fitness that results from implementing π. I end with a general discussion of the limits imposed on the rate of the terrestrial biosphere’s information processing by the flux of sunlight on the Earth.

The production, characterization, and antioxidant capacity of the carotenoid fucoxanthin from the marine diatom Odontella aurita were investigated. The results showed that low light and nitrogen-replete culture medium enhanced the biosynthesis of fucoxanthin. The maximum biomass concentration of 6.36 g L^-1 and maximum fucoxanthin concentration of 18.47 mg g^-1 were obtained in cultures grown in a bubble column photobioreactor (Ø 3.0 cm inner diameter), resulting in a fucoxanthin volumetric productivity of 7.96 mg L^-1 day^-1. A slight reduction in biomass production was observed in the scaling up of O. aurita culture in a flat plate photobioreactor, yet yielded a comparable fucoxanthin volumetric productivity. A rapid method was developed for extraction and purification of fucoxanthin. The purified fucoxanthin was identified as all-trans-fucoxanthin, which exhibited strong antioxidant properties, with the effective concentration for 50% scavenging (EC₅₀) of 1,1-dihpenyl-2-picrylhydrazyl (DPPH) radical and 2,2′-Azino-bis(3-ethylbenzthiazoline-6-sulfonic acid (ABTS) radical being 0.14 and 0.03 mg mL^-1, respectively. Our results suggested that O. aurita can be a natural source of fucoxanthin for human health and nutrition.