Relating multi-sequence longitudinal intensity profiles and clinical covariates in new multiple sclerosis lesions

Structural magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients. The formation of these lesions is a complex process involving inflammation, tissue damage, and tissue repair, all of which are visible on MRI. Here we characterize the lesion formation process on longitudinal, multi-sequence structural MRI from 34 MS patients and relate the longitudinal changes we observe within lesions to therapeutic interventions. In this article, we first outline a pipeline to extract voxel level, multi-sequence longitudinal profiles from four MRI sequences within lesion tissue. We then propose two models to relate clinical covariates to the longitudinal profiles. The first model is a principal component analysis (PCA) regression model, which collapses the information from all four profiles into a scalar value. We find that the score on the first PC identifies areas of slow, long-term intensity changes within the lesion at a voxel level, as validated by two experienced clinicians, a neuroradiologist and a neurologist. On a quality scale of 1 to 4 (4 being the highest) the neuroradiologist gave the score on the first PC a median rating of 4 (95% CI: [4,4]), and the neurologist gave it a median rating of 3 (95% CI: [3,3]). In the PCA regression model, we find that treatment with disease modifying therapies (p-value < 0.01), steroids (p-value < 0.01), and being closer to the boundary of abnormal signal intensity (p-value < 0.01) are associated with a return of a voxel to intensity values closer to that of normal-appearing tissue. The second model is a function-on-scalar regression, which allows for assessment of the individual time points at which the covariates are associated with the profiles. In the function-on-scalar regression both age and distance to the boundary were found to have a statistically significant association with the profiles

Laminin Potentiates Differentiation of PCC4uva Embryonal Carcinoma into Neurons

The embryonal carcinoma PCC4uva differentiates into neurons in response to treatment with retinoic acid and dbcAMP. We used this in vitro model system to study the effects of laminin on early neural differentiation. Laminin substrata markedly potentiate neural differentiation of retinoic acid and dbcAMP-treated cultures. Only laminin induced more rapid neural cell body clustering, neurite growth and neurite fasciculation as compared to type IV collagen, type I collagen, and fibronectin substrata. Exogenous laminin substrata promoted greater cell attachment, cellular spreading and growth to confluence than type IV collagen, type I collagen, fibronectin and glass substrata. Laminin-induced effects were inhibited by addition of laminin antibodies or the synthetic laminin-derived peptide Ile-Gly-Ser-Arg-NH2 (YIGSR-NH2). Treatment with YIGSR-NH2 also inhibited neural differentiation in the absence of exogenous laminin substrata, whereas synthetic peptides containing the RGD sequence and a control peptide YIGSK-NH2 showed no inhibitory effects. These results are consistent with the hypothesis that specific interactions between an early differentiating cell population(s) and extracellular laminin are required during neural differentiation

Boiling the Frog Slowly:The Immersion of C-Suite Financial Executives into Fraud

This study explores how financial executives retrospectively account for their crossing the line into financial statement fraud while acting within or reacting to a financialized corporate environment. We conduct our investigation through face-to-face interviews with 13 former C-suite financial executives who were involved in and indicted for major cases of accounting fraud. Five different themes of accounts emerged from the narratives, characterizing executives' fraud immersion as a meaning-making process by which the particulars of the proximal social context (the influence of social actors and contextual characteristics) and individual motivations collectively molded executives' vocabularies of fraud immersion. Our executives' narratives portray their fraud entanglement as typically occurring in small, incremental steps. Their accounts expand our understanding of the influence of socialization on executive-level financial fraud beyond the individualized focus of the fraud triangle model

The nonlinear time-dependent response of isotactic polypropylene

Tensile creep tests, tensile relaxation tests and a tensile test with a constant rate of strain are performed on injection-molded isotactic polypropylene at room temperature in the vicinity of the yield point. A constitutive model is derived for the time-dependent behavior of semi-crystalline polymers. A polymer is treated as an equivalent network of chains bridged by permanent junctions. The network is modelled as an ensemble of passive meso-regions (with affine nodes) and active meso-domains (where junctions slip with respect to their positions in the bulk medium with various rates). The distribution of activation energies for sliding in active meso-regions is described by a random energy model. Adjustable parameters in the stress--strain relations are found by fitting experimental data. It is demonstrated that the concentration of active meso-domains monotonically grows with strain, whereas the average potential energy for sliding of junctions and the standard deviation of activation energies suffer substantial drops at the yield point. With reference to the concept of dual population of crystalline lamellae, these changes in material parameters are attributed to transition from breakage of subsidiary (thin) lamellae in the sub-yield region to fragmentation of primary (thick) lamellae in the post-yield region of deformation.Comment: 29 pages, 12 figure

Nurses\u27 Alumnae Association Bulletin, December 1968

President\u27s Message Officers and Committee Chairman Financial Report Report to Alumnae Association Annual Report to Alumnae Association School of Practical Nursing Report Student Activities Nursing Service Staff Association Letter from Vietnam Resume of Alumnae Meetings Ways and Means Report Social Committee Building Fund Report Bulletin Committee Report Class News Notice

Theory and design of Inx_{x}Ga1−x_{1-x}As1−y_{1-y}Biy_{y} mid-infrared semiconductor lasers: type-I quantum wells for emission beyond 3 μ\mum on InP substrates

We present a theoretical analysis and optimisation of the properties and performance of mid-infrared semiconductor lasers based on the dilute bismide alloy In$_{x}$Ga$_{1-x}$As$_{1-y}$Bi$_{y}$, grown on conventional (001) InP substrates. The ability to independently vary the epitaxial strain and emission wavelength in this quaternary alloy provides significant scope for band structure engineering. Our calculations demonstrate that structures based on compressively strained In$_{x}$Ga$_{1-x}$As$_{1-y}$Bi$_{y}$ quantum wells (QWs) can readily achieve emission wavelengths in the 3 -- 5 $\mu$m range, and that these QWs have large type-I band offsets. As such, these structures have the potential to overcome a number of limitations commonly associated with this application-rich but technologically challenging wavelength range. By considering structures having (i) fixed QW thickness and variable strain, and (ii) fixed strain and variable QW thickness, we quantify key trends in the properties and performance as functions of the alloy composition, structural properties, and emission wavelength, and on this basis identify routes towards the realisation of optimised devices for practical applications. Our analysis suggests that simple laser structures -- incorporating In$_{x}$Ga$_{1-x}$As$_{1-y}$Bi$_{y}$ QWs and unstrained ternary In$_{0.53}$Ga$_{0.47}$As barriers -- which are compatible with established epitaxial growth, provide a route to realising InP-based mid-infrared diode lasers.Comment: Submitted versio

Removing inter-subject technical variability in magnetic resonance imaging studies

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, 2008, Gagnon-Bartsch and Speed, 2012], two batch effect correction tools largely used in genomics, we decompose the voxel intensities of images registered to a template into a biological component and an unwanted variation component. The unwanted variation component is estimated from a control region obtained from the cerebrospinal fluid (CSF), where intensities are known to be unassociated with disease status and other clinical covariates. We perform a singular value decomposition (SVD) of the control voxels to estimate factors of unwanted variation. We then estimate the unwanted factors using linear regression for every voxel of the brain and take the residuals as the RAVEL-corrected intensities. We assess the performance of RAVEL using T1-weighted (T1-w) images from more than 900 subjects with Alzheimer’s disease (AD) and mild cognitive impairment (MCI), as well as healthy controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. We compare RAVEL to intensity-normalization-only methods, histogram matching, and White Stripe. We show that RAVEL performs best at improving the replicability of the brain regions that are empirically found to be most associated with AD, and that these regions are significantly more present in structures impacted by AD (hippocampus, amygdala, parahippocampal gyrus, enthorinal area and fornix stria terminals). In addition, we show that the RAVEL-corrected intensities have the best performance in distinguishing between MCI subjects and healthy subjects by using the mean hippocampal intensity (AUC=67%), a marked improvement compared to results from intensity normalization alone (AUC=63% and 59% for histogram matching and White Stripe, respectively). RAVEL is generalizable to many imaging modalities, and shows promise for longitudinal studies. Additionally, because the choice of the control region is left to the user, RAVEL can be applied in studies of many brain disorders