Characterization of metabolites in infiltrating gliomas using ex vivo &supl;H high-resolution magic angle spinning spectroscopy.

Gliomas are routinely graded according to histopathological criteria established by the World Health Organization. Although this classification can be used to understand some of the variance in the clinical outcome of patients, there is still substantial heterogeneity within and between lesions of the same grade. This study evaluated image-guided tissue samples acquired from a large cohort of patients presenting with either new or recurrent gliomas of grades II-IV using ex vivo proton high-resolution magic angle spinning spectroscopy. The quantification of metabolite levels revealed several discrete profiles associated with primary glioma subtypes, as well as secondary subtypes that had undergone transformation to a higher grade at the time of recurrence. Statistical modeling further demonstrated that these metabolomic profiles could be differentially classified with respect to pathological grading and inter-grade conversions. Importantly, the myo-inositol to total choline index allowed for a separation of recurrent low-grade gliomas on different pathological trajectories, the heightened ratio of phosphocholine to glycerophosphocholine uniformly characterized several forms of glioblastoma multiforme, and the onco-metabolite D-2-hydroxyglutarate was shown to help distinguish secondary from primary grade IV glioma, as well as grade II and III from grade IV glioma. These data provide evidence that metabolite levels are of interest in the assessment of both intra-grade and intra-lesional malignancy. Such information could be used to enhance the diagnostic specificity of in vivo spectroscopy and to aid in the selection of the most appropriate therapy for individual patients.

Assignment strategies for large proteins by magic-angle spinning NMR: the 21-kDa disulfide-bond-forming enzyme DsbA.

We present strategies for chemical shift assignments of large proteins by magic-angle spinning solid-state NMR, using the 21-kDa disulfide-bond-forming enzyme DsbA as prototype. Previous studies have demonstrated that complete de novo assignments are possible for proteins up to approximately 17 kDa, and partial assignments have been performed for several larger proteins. Here we show that combinations of isotopic labeling strategies, high field correlation spectroscopy, and three-dimensional (3D) and four-dimensional (4D) backbone correlation experiments yield highly confident assignments for more than 90% of backbone resonances in DsbA. Samples were prepared as nanocrystalline precipitates by a dialysis procedure, resulting in heterogeneous linewidths below 0.2 ppm. Thus, high magnetic fields, selective decoupling pulse sequences, and sparse isotopic labeling all improved spectral resolution. Assignments by amino acid type were facilitated by particular combinations of pulse sequences and isotopic labeling; for example, transferred echo double resonance experiments enhanced sensitivity for Pro and Gly residues; [2-(13)C]glycerol labeling clarified Val, Ile, and Leu assignments; in-phase anti-phase correlation spectra enabled interpretation of otherwise crowded Glx/Asx side-chain regions; and 3D NCACX experiments on [2-(13)C]glycerol samples provided unique sets of aromatic (Phe, Tyr, and Trp) correlations. Together with high-sensitivity CANCOCA 4D experiments and CANCOCX 3D experiments, unambiguous backbone walks could be performed throughout the majority of the sequence. At 189 residues, DsbA represents the largest monomeric unit for which essentially complete solid-state NMR assignments have so far been achieved. These results will facilitate studies of nanocrystalline DsbA structure and dynamics and will enable analysis of its 41-kDa covalent complex with the membrane protein DsbB, for which we demonstrate a high-resolution two-dimensional (13)C-(13)C spectrum.

Biases of the ordinary least squares and instrumental variables estimators of the intergenerational earnings elasticity : revisited in the light of panel data

The OLS estimator of the intergenerational earnings correlation is biased towards zero, while the instrumental variables estimator is biased upwards. The first of these results arises because of measurement error, while the latter rests on the presumption that the education of the parent family is an invalid instrument. We propose a panel data framework for quantifying the asymptotic biases of these estimators, as well as a mis-specification test for the IV estimator. [Author]

Merlin, a "Magic" Linker between Extracellular Cues and Intracellular Signaling Pathways that Regulate Cell Motility, Proliferation, and Survival.

Genetic alterations of neurofibromatosis type 2 (NF2) gene lead to the development of schwannomas, meningiomas, and ependymomas. Mutations of NF2 gene were also found in thyroid cancer, mesothelioma, and melanoma, suggesting that it functions as a tumor suppressor in a wide spectrum of cells. The product of NF2 gene is merlin (moesin-ezrin-radixin-like protein), a member of the Band 4.1 superfamily proteins. Merlin shares significant sequence homology with the ERM (Ezrin-Radixin-Moesin) family proteins and serves as a linker between transmembrane proteins and the actin-cytoskeleton. Merlin is a multifunctional protein and involved in integrating and regulating the extracellular cues and intracellular signaling pathways that control cell fate, shape, proliferation, survival, and motility. Recent studies showed that merlin regulates the cell-cell and cell-matrix adhesions and functions of the cell surface adhesion/extracellular matrix receptors including CD44 and that merlin and CD44 antagonize each other's function and work upstream of the mammalian Hippo signaling pathway. Furthermore, merlin plays important roles in stabilizing the contact inhibition of proliferation and in regulating activities of several receptor tyrosine kinases. Accumulating data also suggested an emerging role of merlin as a negative regulator of growth and progression of several non-NF2 associated cancer types. Together, these recent advances have improved our basic understanding about merlin function, its regulation, and the major signaling pathways regulated by merlin and provided the foundation for future translation of these findings into the clinic for patients bearing the cancers in which merlin function and/or its downstream signaling pathways are impaired or altered.

Reflections on Partial Least Squares Path Modeling

The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics (Rönkkö & Evermann, 2013) and proponents (Henseler et al., 2014) of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (1) can be truly characterized as a technique for structural equation modeling (SEM); (2) is able to correct for measurement error; (3) can be used to validate measurement models; (4) accommodates small sample sizes; (5) is able to provide null hypothesis tests for path coefficients; and (6) can be employed in an exploratory, model-building fashion. We summarize and elaborate further on the key arguments underlying the exchange, drawing from the broader methodological and statistical literature in order to offer additional thoughts concerning the utility of PLS-PM and ways in which the technique might be improved. We conclude with recommendations as to whether and how PLS-PM serves as a viable contender to SEM approaches for estimating and evaluating theoretical models.

Priming psychic and conjuring abilities of a magic demonstration influences event interpretation and random number generation biases

Magical ideation and belief in the paranormal is considered to represent a trait-like character; people either believe in it or not. Yet, anecdotes indicate that exposure to an anomalous event can turn skeptics into believers. This transformation is likely to be accompanied by altered cognitive functioning such as impaired judgments of event likelihood. Here, we investigated whether the exposure to an anomalous event changes individuals' explicit traditional (religious) and non-traditional (e.g., paranormal) beliefs as well as cognitive biases that have previously been associated with non-traditional beliefs, e.g., repetition avoidance when producing random numbers in a mental dice task. In a classroom, 91 students saw a magic demonstration after their psychology lecture. Before the demonstration, half of the students were told that the performance was done respectively by a conjuror (magician group) or a psychic (psychic group). The instruction influenced participants' explanations of the anomalous event. Participants in the magician, as compared to the psychic group, were more likely to explain the event through conjuring abilities while the reverse was true for psychic abilities. Moreover, these explanations correlated positively with their prior traditional and non-traditional beliefs. Finally, we observed that the psychic group showed more repetition avoidance than the magician group, and this effect remained the same regardless of whether assessed before or after the magic demonstration. We conclude that pre-existing beliefs and contextual suggestions both influence people's interpretations of anomalous events and associated cognitive biases. Beliefs and associated cognitive biases are likely flexible well into adulthood and change with actual life events.

On the Adoption of Partial Least Squares in Psychological Research: Caveat Emptor

The partial least squares technique (PLS) has been touted as a viable alternative to latent variable structural equation modeling (SEM) for evaluating theoretical models in the differential psychology domain. We bring some balance to the discussion by reviewing the broader methodological literature to highlight: (1) the misleading characterization of PLS as an SEM method; (2) limitations of PLS for global model testing; (3) problems in testing the significance of path coefficients; (4) extremely high false positive rates when using empirical confidence intervals in conjunction with a new "sign change correction" for path coefficients; (5) misconceptions surrounding the supposedly superior ability of PLS to handle small sample sizes and non-normality; and (6) conceptual and statistical problems with formative measurement and the application of PLS to such models. Additionally, we also reanalyze the dataset provided by Willaby et al. (2015; doi:10.1016/j.paid.2014.09.008) to highlight the limitations of PLS. Our broader review and analysis of the available evidence makes it clear that PLS is not useful for statistical estimation and testing.