Multiple Statistical Analysis Techniques Corroborate Intratumor Heterogeneity in Imaging Mass Spectrometry Datasets of Myxofibrosarcoma

MALDI mass spectrometry can generate profiles that contain hundreds of biomolecular ions directly from tissue. Spatially-correlated analysis, MALDI imaging MS, can simultaneously reveal how each of these biomolecular ions varies in clinical tissue samples. The use of statistical data analysis tools to identify regions containing correlated mass spectrometry profiles is referred to as imaging MS-based molecular histology because of its ability to annotate tissues solely on the basis of the imaging MS data. Several reports have indicated that imaging MS-based molecular histology may be able to complement established histological and histochemical techniques by distinguishing between pathologies with overlapping/identical morphologies and revealing biomolecular intratumor heterogeneity. A data analysis pipeline that identifies regions of imaging MS datasets with correlated mass spectrometry profiles could lead to the development of novel methods for improved diagnosis (differentiating subgroups within distinct histological groups) and annotating the spatio-chemical makeup of tumors. Here it is demonstrated that highlighting the regions within imaging MS datasets whose mass spectrometry profiles were found to be correlated by five independent multivariate methods provides a consistently accurate summary of the spatio-chemical heterogeneity. The corroboration provided by using multiple multivariate methods, efficiently applied in an automated routine, provides assurance that the identified regions are indeed characterized by distinct mass spectrometry profiles, a crucial requirement for its development as a complementary histological tool. When simultaneously applied to imaging MS datasets from multiple patient samples of intermediate-grade myxofibrosarcoma, a heterogeneous soft tissue sarcoma, nodules with mass spectrometry profiles found to be distinct by five different multivariate methods were detected within morphologically identical regions of all patient tissue samples. To aid the further development of imaging MS based molecular histology as a complementary histological tool the Matlab code of the agreement analysis, instructions and a reduced dataset are included as supporting information

The interactions of disability and impairment

Theoretical work on disability is going through an expansive period, built on the growing recognition of disability studies as a discipline and out of the political and analytical push to bring disability into a prominent position within accounts of the intersecting social categories that shape people's lives. A current debate within critical disability studies is whether that study should include impairment and embodiment within its focus. This article argues it should and does so by drawing from symbolic interactionism and embodiment literatures in order to explore how differences in what bodies can do-defined as impairments-come to play a role in how people make sense of themselves through social interaction. We argue that these everyday interactions and the stories we tell within them and about them are important spaces and narratives through which impairment and disability are produced. Interactions and stories are significant both in how they are shaped by wider social norms, collective stories and institutional processes, and also how they at times can provide points of resistance and challenges to such norms, stories and institutions. Therefore, the significance of impairment and interaction is the role they play in both informing self-identity and also broader dynamics of power and inequality

Neurovascular unit dysfunction with blood-brain barrier hyperpermeability contributes to major depressive disorder: a review of clinical and experimental evidence

About one-third of people with major depressive disorder (MDD) fail at least two antidepressant drug trials at 1 year. Together with clinical and experimental evidence indicating that the pathophysiology of MDD is multifactorial, this observation underscores the importance of elucidating mechanisms beyond monoaminergic dysregulation that can contribute to the genesis and persistence of MDD. Oxidative stress and neuroinflammation are mechanistically linked to the presence of neurovascular dysfunction with blood-brain barrier (BBB) hyperpermeability in selected neurological disorders, such as stroke, epilepsy, multiple sclerosis, traumatic brain injury, and Alzheimer’s disease. In contrast to other major psychiatric disorders, MDD is frequently comorbid with such neurological disorders and constitutes an independent risk factor for morbidity and mortality in disorders characterized by vascular endothelial dysfunction (cardiovascular disease and diabetes mellitus). Oxidative stress and neuroinflammation are implicated in the neurobiology of MDD. More recent evidence links neurovascular dysfunction with BBB hyperpermeability to MDD without neurological comorbidity. We review this emerging literature and present a theoretical integration between these abnormalities to those involving oxidative stress and neuroinflammation in MDD. We discuss our hypothesis that alterations in endothelial nitric oxide levels and endothelial nitric oxide synthase uncoupling are central mechanistic links in this regard. Understanding the contribution of neurovascular dysfunction with BBB hyperpermeability to the pathophysiology of MDD may help to identify novel therapeutic and preventative approaches

Residual States for Modal Models Identified from Accelerance Data

Residual stiffness and mass terms are often employed in frequency response synthesis to compensate for outside band eigenmodes in the identification of modal models from test data. For structures that have strongly participating modes above the test frequency band, it has been observed that in particular direct accelerances with strong outside-band modal contribution tend to render modal models that give poor fit to test data. For such problems it may be insufficient to just add residual mass and stiffness terms to the accelerance modal series to get a sufficiently improved fit. For accelerance, such residual terms are constant and quadratic in frequency. Another, residual term that is quasi-linear over the frequency range of interest has been found to augment the identified model. In this paper that complementary term is added to the constant and quadratic terms in a state-space model identification with a subspace state-space identification method. A comparison is performed to an alternative residualisation method. The methods\u27 results are compared on simulated finite element test data from of an automotive component