Mycobacterium avium paratuberculosis and Mycobacterium avium complex and related subspecies as causative agents of zoonotic and occupational diseases

Mycobacterium avium complex (MAC) and Mycobacterium avium paratuberculosis (MAP) cause zoonotic infections transmitted by birds and livestock herds. These pathogens have remained as serious economic and health threats in most areas of the world. As zoonotic diseases, the risk of development of occupational disease and even death outcome necessitate implementation of control strategies to prevent its spread. Zoonotic MAP infections include Crohn's disease, inflammatory bowel disease, ulcerative colitis, sarcoidosis, diabetes mellitus, and immune-related diseases (such as Hashimoto's thyroiditis). Paratuberculosis has classified as type B epidemic zoonotic disease according to world health organization which is transmitted to human through consumption of dairy and meat products. In addition, MAC causes pulmonary manifestations and lymphadenitis in normal hosts and human immunodeficiency virus (HIV) progression (by serotypes 1, 4, and 8). Furthermore, other subspecies have caused respiratory abscesses, neck lymph nodes, and disseminated osteomyelitis in children and ulcers. However, the data over the occupational relatedness of these subspecies is rare. These agents can cause occupational infections in susceptible herd breeders. Several molecular methods have been recognized as proper strategies for tracking the infection. In this study, some zoonotic aspects, worldwide prevalence and control strategies regarding infections due to MAP and MAC and related subspecies has been reviewe

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION: The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015. METHODS: We used standard searches to find publications using ADNI data. RESULTS: (1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers. DISCUSSION: Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial desig

Investigating the effectiveness of clickthrough data for document reordering

User clicks¿also known as clickthrough data¿have been cited as an implicit form of relevance feedback. Previous work suggests that relative preferences between documents can be accurately derived from user clicks. In this paper, we analyze the impact of document reordering¿based on clickthrough¿on search effectiveness, measured using both TREC and user relevance judgments. We also propose new strategies for document reordering that can outperform current techniques. Preliminary results show that current reordering methods do not lead to consistent improvements of search quality, but may even lead to poorer results if not used with care

Differentiating benign and malignant mass and non-mass lesions in breast DCE-MRI using normalized frequency-based features

Contains fulltext : 217331.pdf (publisher's version ) (Closed access