Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases

BACKGROUND: Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL). METHODS: We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients. RESULTS: Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei. CONCLUSION: The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls

Unravelling the structural variation of lizard osteoderms

Vertebrate skin is a remarkable organ that supports and protects the body. It consists of two layers, the epidermis and the underlying dermis. In some tetrapods, the dermis includes mineralised organs known as osteoderms (OD). Lizards, with over 7,000 species, show the greatest diversity in OD morphology and distribution, yet we barely understand what drives this diversity. This multiscale analysis of five species of lizards, whose lineages diverged ∼100–150 million years ago, compared the micro- and macrostructure, material properties, and bending rigidity of their ODs, and examined the underlying bones of the skull roof and jaw (including teeth when possible). Unsurprisingly, OD shape, taken alone, impacts bending rigidity, with the ODs of Corucia zebrata being most flexible and those of Timon lepidus being most rigid. Macroscopic variation is also reflected in microstructural diversity, with differences in tissue composition and arrangement. However, the properties of the core bony tissues, in both ODs and cranial bones, were found to be similar across taxa, although the hard, capping tissue on the ODs of Heloderma and Pseudopus had material properties similar to those of tooth enamel. The results offer evidence on the functional adaptations of cranial ODs, but questions remain regarding the factors driving their diversity

Involvement of patients or their representatives in quality management functions in EU hospitals:implementation and impact on patient-centred care strategies

OBJECTIVE: The objective of this study was to describe the involvement of patients or their representatives in quality management (QM) functions and to assess associations between levels of involvement and the implementation of patient-centred care strategies. DESIGN: A cross-sectional, multilevel STUDY DESIGN: that surveyed quality managers and department heads and data from an organizational audit. SETTING: Randomly selected hospitals (n = 74) from seven European countries (The Czech Republic, France, Germany, Poland, Portugal, Spain and Turkey). PARTICIPANTS: Hospital quality managers (n = 74) and heads of clinical departments (n = 262) in charge of four patient pathways (acute myocardial infarction, stroke, hip fracture and deliveries) participated in the data collection between May 2011 and February 2012. MAIN OUTCOME MEASURES: Four items reflecting essential patient-centred care strategies based on an on-site hospital visit: (1) formal survey seeking views of patients and carers, (2) written policies on patients' rights, (3) patient information literature including guidelines and (4) fact sheets for post-discharge care. The main predictors were patient involvement in QM at the (i) hospital level and (ii) pathway level. RESULTS: Current levels of involving patients and their representatives in QM functions in European hospitals are low at hospital level (mean score 1.6 on a scale of 0 to 5, SD 0.7), but even lower at departmental level (mean 0.6, SD 0.7). We did not detect associations between levels of involving patients and their representatives in QM functions and the implementation of patient-centred care strategies; however, the smallest hospitals were more likely to have implemented patient-centred care strategies. CONCLUSIONS: There is insufficient evidence that involving patients and their representatives in QM leads to establishing or implementing strategies and procedures that facilitate patient-centred care; however, lack of evidence should not be interpreted as evidence of no effect

Influence of the temperature on the carrier capture into self-assembled InAs/GaAs quantum dots

Photoluminescence (PL) spectroscopy and atomic-force microscopy (AFM) were used to investigate the size evolution of InAs quantum dots on GaAs(001) as a function of the amount of InAs material. Different families of islands were observed in the AFM images and unambiguously identified in the PL spectra, together with the signal of the wetting layer. PL measurements carried out at low and intermediate temperatures showed a thermal carrier redistribution among dots belonging to different families. The physical origin of this behavior is explained in terms of the different temperature dependence of the carrier-capture rate into the quantum dots. At high temperatures, an enhancement of the total PL-integrated intensity of the largest-sized quantum dots was attributed to the increase of diffusivity of the photogenerated carriers inside the wetting layer. (C) 2003 American Institute of Physics.931016279628

Support vector machine-based classification of neuroimages in Alzheimer’s disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals

OBJECTIVE: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flow single-photon emission computed tomography (rCBF-SPECT) in Alzheimer's disease (AD). METHOD: Brain T1-MRI, FDG-PET and rCBF-SPECT scans were acquired from a sample of mild AD patients (n=20) and healthy elderly controls (n=18). SVM-based diagnostic accuracy indices were calculated using whole-brain information and leave-one-out cross-validation. RESULTS: The accuracy obtained using PET and SPECT data were similar. PET accuracy was 68∼71% and area under curve (AUC) 0.77∼0.81; SPECT accuracy was 68∼74% and AUC 0.75∼0.79, and both had better performance than analysis with T1-MRI data (accuracy of 58%, AUC 0.67). The addition of PET or SPECT to MRI produced higher accuracy indices (68∼74%; AUC: 0.74∼0.82) than T1-MRI alone, but these were not clearly superior to the isolated neurofunctional modalities. CONCLUSION: In line with previous evidence, FDG-PET and rCBF-SPECT more accurately identified patients with AD than T1-MRI, and the addition of either PET or SPECT to T1-MRI data yielded increased accuracy. The comparable SPECT and PET performances, directly demonstrated for the first time in the present study, support the view that rCBF-SPECT still has a role to play in AD diagnosis