Towards Understanding Spontaneous Speech: Word Accuracy vs. Concept Accuracy

In this paper we describe an approach to automatic evaluation of both the speech recognition and understanding capabilities of a spoken dialogue system for train time table information. We use word accuracy for recognition and concept accuracy for understanding performance judgement. Both measures are calculated by comparing these modules' output with a correct reference answer. We report evaluation results for a spontaneous speech corpus with about 10000 utterances. We observed a nearly linear relationship between word accuracy and concept accuracy.Comment: 4 pages PS, Latex2e source importing 2 eps figures, uses icslp.cls, caption.sty, psfig.sty; to appear in the Proceedings of the Fourth International Conference on Spoken Language Processing (ICSLP 96

Chemometric Strategies for Sensitive Annotation and Validation of Anatomical Regions of Interest in Complex Imaging Mass Spectrometry Data

Imaging mass spectrometry (IMS) is a promising new chemical imaging modality that generates a large body of complex imaging data, which in turn can be approached using multivariate analysis approaches for image analysis and segmentation. Processing IMS raw data is critically important for proper data interpretation and has significant effects on the outcome of data analysis, in particular statistical modeling. Commonly, data processing methods are chosen based on rational motivations rather than comparative metrics, though no quantitative measures to assess and compare processing options have been suggested. We here present a data processing and analysis pipeline for IMS data interrogation, processing and ROI annotation, segmentation, and validation. This workflow includes (1) objective evaluation of processing methods for IMS datasets based on multivariate analysis using PCA. This was then followed by (2) ROI annotation and classification through region-based active contours (AC) segmentation based on the PCA component scores matrix. This provided class information for subsequent (3) OPLS-DA modeling to evaluate IMS data processing based on the quality metrics of their respective multivariate models and for robust quantification of ROI-specific signal localization. This workflow provides an unbiased strategy for sensitive annotation of anatomical regions of interest combined with quantitative comparison of processing procedures for multivariate analysis allowing robust ROI annotation and quantification of the associated molecular histology

Chemical Imaging of Evolving Amyloid Plaque Pathology and Associated Aβ Peptide Aggregation in a Transgenic Mouse Model of Alzheimer's Disease

One of the major hallmarks of Alzheimer's disease (AD) pathology is the formation of extracellular amyloid β (Aβ) plaques. While Aβ has been suggested to be critical in inducing and, potentially, driving the disease, the molecular basis of AD pathogenesis is still under debate. Extracellular Aβ plaque pathology manifests itself upon aggregation of distinct Aβ peptides, resulting in morphologically different plaque morphotypes, including mainly diffuse and cored senile plaques. As plaque pathology precipitates long before any clinical symptoms occur, targeting the Aβ aggregation processes provides a promising target for early interventions. However, the chain of events of when, where and what Aβ species aggregate and form plaques remains unclear. The aim of the current study was to investigate the potential of MALDI-IMS as a tool to study the evolving pathology in transgenic mouse models for AD. To that end, we used an emerging, chemical imaging modality - MALDI imaging mass spectrometry - that allows for delineating Aβ aggregation with specificity at the single plaque level. We identified that plaque formation occurs first in cortical regions and that these younger plaques contain higher levels of 42 amino acid-long Aβ (Aβ1-42). Plaque maturation was found to be characterized by a relative increase in deposition of Aβ1-40, which was associated with the appearance of a cored morphology of the plaques. Finally, other C-terminally truncated Aβ species (Aβ1-38 and Aβ1-39) exhibited a similar aggregation pattern as Aβ1-40, suggesting that these species have similar aggregation characteristics. These results suggest that initial plaque formation is seeded by Aβ1-42; a process that is followed by plaque maturation upon deposition of Aβ1-40 as well as deposition by other C-terminally modified Aβ species

Multimodal Chemical Imaging of Amyloid Plaque Polymorphism Reveals A beta Aggregation Dependent Anionic Lipid Accumulations and Metabolism

Amyloid plaque formation constitutes one of the main pathological hallmarks of Alzheimer’s disease (AD) and is suggested to be a critical factor driving disease pathogenesis. Interestingly, in patients that display amyloid pathology but remain cognitively normal, Aβ deposits are predominantly of diffuse morphology suggesting that cored plaque formation is primarily associated with cognitive deterioration and AD pathogenesis. Little is known about the molecular mechanism responsible for conversion of monomeric Aβ into neurotoxic aggregates and the predominantly cored deposits observed in AD. The structural diversity among Aβ plaques, including cored/compact- and diffuse, may be linked to their distinct Aβ profile and other chemical species including neuronal lipids. We developed a novel, chemical imaging paradigm combining matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) and fluorescent amyloid staining. This multimodal imaging approach was used to probe the lipid chemistry associated with structural plaque heterogeneity in transgenic AD mice (tgAPPSwe) and was correlated to Aβ profiles determined by subsequent laser microdissection and immunoprecipitation-mass spectrometry. Multivariate image analysis revealed an inverse localization of ceramides and their matching metabolites to diffuse and cored structures within single plaques, respectively. Moreover, phosphatidylinositols implicated in AD pathogenesis, were found to localize to the diffuse Aβ structures and correlate with Aβ1–42. Further, lysophospholipids implicated in neuroinflammation were increased in all Aβ deposits. The results support previous clinical findings on the importance of lipid disturbances in AD pathophysiology and associated sphingolipid processing. These data highlight the potential of multimodal imaging as a powerful technology to probe neuropathological mechanisms

Correlative Chemical Imaging and Spatial Chemometrics Delineate Alzheimer Plaque Heterogeneity at High Spatial Resolution

We present a novel, correlative chemical imaging strategy based on multimodal matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), hyperspectral microscopy, and spatial chemometrics. Our workflow overcomes challenges associated with correlative MSI data acquisition and alignment by implementing 1 + 1-evolutionary image registration for precise geometric alignment of multimodal imaging data and their integration in a common, truly multimodal imaging data matrix with maintained MSI resolution (10 μm). This enabled multivariate statistical modeling of multimodal imaging data using a novel multiblock orthogonal component analysis approach to identify covariations of biochemical signatures between and within imaging modalities at MSI pixel resolution. We demonstrate the method’s potential through its application toward delineating chemical traits of Alzheimer’s disease (AD) pathology. Here, trimodal MALDI MSI of transgenic AD mouse brain delineates beta-amyloid (Aβ) plaque-associated co-localization of lipids and Aβ peptides. Finally, we establish an improved image fusion approach for correlative MSI and functional fluorescence microscopy. This allowed for high spatial resolution (300 nm) prediction of correlative, multimodal MSI signatures toward distinct amyloid structures within single plaque features critically implicated in Aβ pathogenicity

Computational Analysis of Alzheimer Amyloid Plaque Composition in 2D- and Elastically Reconstructed 3D-MALDI MS Images

MALDI mass spectrometry imaging (MSI) enables label-free, spatially resolved analysis of a wide range of analytes in tissue sections. Quantitative analysis of MSI datasets is typically performed on single pixels or manually assigned regions of interest (ROIs). However, many sparse, small objects such as Alzheimer’s disease (AD) brain deposits of amyloid peptides called plaques are neither single pixels nor ROIs. Here, we propose a new approach to facilitate the comparative computational evaluation of amyloid plaque-like objects by MSI: a fast PLAQUE PICKER tool that enables a statistical evaluation of heterogeneous amyloid peptide composition. Comparing two AD mouse models, APP NL-G-F and APP PS1, we identified distinct heterogeneous plaque populations in the NL-G-F model but only one class of plaques in the PS1 model. We propose quantitative metrics for the comparison of technical and biological MSI replicates. Furthermore, we reconstructed a high-accuracy 3D-model of amyloid plaques in a fully automated fashion, employing rigid and elastic MSI image registration using structured and plaque-unrelated reference ion images. Statistical single-plaque analysis in reconstructed 3D-MSI objects revealed the Aβ1–42Arc peptide to be located either in the core of larger plaques or in small plaques without colocalization of other Aβ isoforms. In 3D, a substantially larger number of small plaques were observed than that indicated by the 2D-MSI data, suggesting that quantitative analysis of molecularly diverse sparsely-distributed features may benefit from 3D-reconstruction. Data are available via ProteomeXchange with identifier PXD020824

Following spatial Aβ aggregation dynamics in evolving Alzheimer's disease pathology by imaging stable isotope labeling kinetics.

β-Amyloid (Aβ) plaque formation is the major pathological hallmark of Alzheimer’s disease (AD) and constitutes a potentially critical, early inducer driving AD pathogenesis as it precedes other pathological events and cognitive symptoms by decades. It is therefore critical to understand how Aβ pathology is initiated and where and when distinct Aβ species aggregate. Here, we used metabolic isotope labeling in APPNL-G-F knock-in mice together with mass spectrometry imaging to monitor the earliest seeds of Aβ deposition through ongoing plaque development. This allowed visualizing Aβ aggregation dynamics within single plaques across different brain regions. We show that formation of structurally distinct plaques is associated with differential Aβ peptide deposition. Specifically, Aβ1-42 is forming an initial core structure followed by radial outgrowth and late secretion and deposition of Aβ1-38. These data describe a detailed picture of the earliest events of precipitating amyloid pathology at scales not previously possible

Structural Amyloid Plaque Polymorphism is Associated with Distinct Lipid Accumulations Revealed by Trapped Ion Mobility Mass Spectrometry Imaging (TIMS MSI)

Understanding of Alzheimer’s disease (AD) pathophysiology, requires molecular assessment of how key pathological factors, specifically amyloid β (Aβ) plaques, influence the surrounding microenvironment. Here, neuronal lipids have been implicated in Aβ) plaque pathology, though the lipid microenvironment in direct proximity to Aβ plaques are still not fully resolved. A further challenge is the microenvironmental molecular heterogeneity, across structurally polymorphic Aβ features - such as diffuse, immature and mature, fibrillary aggregates, whose resolution requires the integration of advanced, multimodal chemical imaging tools. Herein, we used matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) trapped ion mobility spectrometry Time-of-Flight (TIMS TOF) in combination with hyperspectral confocal microscopy to probe the lipidomic microenvironment associated with structural polymorphism of Aβ plaques in transgenic Alzheimer’s disease mice (tgAPPSWE). Using on tissue and ex situ validation, TIMS MS/MS facilitated unambiguous identification of isobaric lipid species that showed plaque pathology associated localizations. Integrated multivariate imaging data analysis revealed multiple, Aβ plaque enriched lipid patterns for gangliosides (GM), phosphoinositols (PI), phosphoethanolamines (PE) and phosphatidic acids (PA). Conversely, sulfatides (ST), cardiolipins (CL) and polyunsaturated fatty acid conjugated -phosphoserines (PS) and - PE were depleted at plaques. Hyperspectral amyloid imaging further delineated unique distribution of PA, PE to mature plaque core regions, while PI, LPI, GM2 and GM3 localized to immature Aβ aggregates present within the periphery of individual Aβ plaques. Finally, we followed AD pathology associated lipid changes over time, identifying plaque growth and maturation to be characterized by peripheral accumulation of PI (18:0/22:6). Together, these data demonstrate the potential of multimodal imaging approaches to overcome limitations associated with conventional advanced MS imaging applications. This allowed for differentiation of both distinct lipid components in a complex micro environment, as well as their correlation to disease relevant amyloid plaque polymorphs

Novel Trimodal MALDI Imaging Mass Spectrometry (IMS3) at 10 mu m Reveals Spatial Lipid and Peptide Correlates Implicated in A beta Plaque Pathology in Alzheimer's Disease

Multimodal chemical imaging using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) can provide comprehensive molecular information in situ within the same tissue sections. This is of relevance for studying different brain pathologies such as Alzheimer’s disease (AD), where recent data suggest a critical relevance of colocalizing Aβ peptides and neuronal lipids. We here developed a novel trimodal, high-resolution (10 μm) MALDI imaging MS (IMS) paradigm for negative and positive ion mode lipid analysis and subsequent protein ion imaging on the same tissue section. Matrix sublimation of 1,5-diaminonaphthalene (1,5-DAN) enabled dual polarity lipid MALDI IMS on the same pixel points at high spatial resolutions (10 μm) and with high spectral quality. This was followed by 10 μm resolution protein imaging on the same measurement area, which allowed correlation of lipid signals with protein distribution patterns within distinct cerebellar regions in mouse brain. The demonstrated trimodal imaging strategy (IMS3) was further shown to be an efficient approach for simultaneously probing Aβ plaque-associated lipids and Aβ peptides within the hippocampus of 18 month-old transgenic AD mice (tgArcSwe). Here, IMS3 revealed a strong colocalization of distinct lipid species including ceramides, phosphatidylinositols, sulfatides (Cer 18:0, PI 38:4, ST 24:0) and lysophosphatidylcholines (LPC 16:0, LPC 18:0) with plaque-associated Aβ isoforms (Aβ 1–37, Aβ 1–38, Aβ 1–40). This highlights the potential of IMS3 as an alternative, superior approach to consecutively performed immuno-based Aβ staining strategies. Furthermore, the IMS3 workflow allowed for multimodal in situ MS/MS analysis of both lipids and Aβ peptides. Altogether, the here presented IMS3 approach shows great potential for comprehensive, high-resolution molecular analysis of histological features at cellular length scales with high chemical specificity. It therefore represents a powerful approach for probing the complex molecular pathology of, e.g., neurodegenerative diseases that are characterized by neurotoxic protein aggregation