Cognitive dysfunction is one of the most typical characteristics in various neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease (advanced stage). Although several mechanisms like neuronal apoptosis and inflammatory responses have been recognized to be involved in the pathogenesis of cognitive dysfunction in these diseases, recent studies on neurodegeneration and cognitive dysfunction have demonstrated a significant impact of receptor modulation on cognitive changes. The pathological alterations in various receptors appear to contribute to cognitive impairment and/or deterioration with correlation to diversified mechanisms. This article recapitulates the present understandings and concepts underlying the modulation of different receptors in human beings and various experimental models of Alzheimer’s disease and Parkinson’s disease as well as a conceptual update on the underlying mechanisms. Specific roles of serotonin, adrenaline, acetylcholine, dopamine receptors, and N-methyl-D-aspartate receptors in Alzheimer’s disease and Parkinson’s disease will be interactively discussed. Complex mechanisms involved in their signaling pathways in the cognitive dysfunction associated with the neurodegenerative diseases will also be addressed. Substantial evidence has suggested that those receptors are crucial neuroregulators contributing to cognitive pathology and complicated correlations exist between those receptors and the expression of cognitive capacities. The pathological alterations in the receptors would, therefore, contribute to cognitive impairments and/or deterioration in Alzheimer’s disease and Parkinson’s disease. Future research may shed light on new clues for the treatment of cognitive dysfunction in neurodegenerative diseases by targeting specific alterations in these receptors and their signal transduction pathways in the frontal-striatal, fronto–striato–thalamic, and mesolimbic circuitries.

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer’s disease dementia (AD)) as an ‘Inception cohort’ who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an ‘Enrichment cohort’ (as of 10 April 2019). Objective: Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation. Methods: Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations. Results: AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression. Conclusion: This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims.

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.