Somatosensory dysfunction is masked by variable cognitive deficits across patients on the Alzheimer’s disease spectrum

Background: Alzheimer’s disease (AD) is generally thought to spare primary sensory function; however, such interpretations have drawn from a literature that has rarely taken into account the variable cognitive declines seen in patients with AD. As these cognitive domains are now known to modulate cortical somato-sensory processing, it remains possible that abnormalities in somatosensory function in patients with AD have been suppressed by neuropsychological variability in previous research. Methods: In this study, we combine magnetoencephalographic (MEG) brain imaging during a paired-pulse somatosensory gating task with an extensive battery of neuropsychological tests to investigate the influence of cognitive variability on estimated differences in somatosensory function between biomarker-confirmed patients on the AD spectrum and cognitively-normal older adults. Findings: We show that patients on the AD spectrum exhibit largely non-significant differences in somato-sensory function when cognitive variability is not considered (p-value range: .020-.842). However, once attention and processing speed abilities are considered, robust differences in gamma-frequency somatosensory response amplitude (p \u3c .001) and gating (p = .004) emerge, accompanied by significant statistical suppression effects. Interpretation: These findings suggest that patients with AD exhibit insults to functional somatosensory processing in primary sensory cortices, but these effects are masked by variability in cognitive decline across individuals

development of measures of polyneuropathy impairment in hattr amyloidosis from nis to mnis 7

Abstract Hereditary transthyretin-mediated amyloidosis (hATTR amyloidosis) is a rare, life-threatening disease, caused by point mutations in the transthyretin gene. It is a heterogeneous, multisystem disease with rapidly progressing polyneuropathy (including sensory, motor, and autonomic impairments) and cardiac dysfunction. Measures used to assess polyneuropathy in other diseases have been tested as endpoints in hATTR amyloidosis clinical trials (i.e. Neuropathy Impairment Score [NIS], NIS-lower limb, and NIS + 7), yet the unique nature of the polyneuropathy in this disease has necessitated modifications to these scales. In particular, the heterogeneous impairment and the aggressive disease course have been key drivers in developing scales that better capture the disease burden and progression of polyneuropathy in hATTR amyloidosis. The modified NIS + 7 (mNIS + 7) scale was specifically designed to assess polyneuropathy impairment in patients with hATTR amyloidosis, and has been the primary endpoint in two recent, phase III studies in this disease. The mNIS + 7 uses highly standardized, quantitative, and referenced assessments to quantify decreased muscle weakness, muscle stretch reflexes, sensory loss, and autonomic impairment. Physicians using this scale in clinical trials should be specifically trained and monitored to minimize variability. This article discusses the different scales that have been/are being used to assess polyneuropathy in patients with hATTR amyloidosis, their correlation with other disease assessments, and reflects on how and why scales have evolved to the latest iteration of mNIS + 7

Automated extraction of potential migraine biomarkers using a semantic graph

Problem Biomedical literature and databases contain important clues for the identification of potential disease biomarkers. However, searching these enormous knowledge reservoirs and integrating findings across heterogeneous sources is costly and difficult. Here we demonstrate how semantically integrated knowledge, extracted from biomedical literature and structured databases, can be used to automatically identify potential migraine biomarkers. Method We used a knowledge graph containing more than 3.5 million biomedical concepts and 68.4 million relationships. Biochemical compound concepts were filtered and ranked by their potential as biomarkers based on their connections to a subgraph of migraine-related concepts. The ranked results were evaluated against the results of a systematic literature review that was performed manually by migraine researchers. Weight points were assigned to these reference compounds to indicate their relative importance. Results Ranked results automatically generated by the knowledge graph were highly consistent with results from the manual literature review. Out of 222 reference compounds, 163 (73%) ranked in the top 2000, with 547 out of the 644 (85%) weight points assigned to the reference compounds. For reference compounds that were not in the top of the list, an extensive error analysis has been performed. When evaluating the overall performance, we obtained a ROC-AUC of 0.974. Discussion Semantic knowledge graphs composed of information integrated from multiple and varying sources can assist researchers in identifying potential disease biomarkers

Phytochemical profile and antioxidant capacity of virgin olive oil obtained from the olive cultivar 'Roghiani' from different regions of northern Libya

The aim of this work was to determine the fatty acids (FA), tocopherols, phenols, and antioxidant capacity (AC) of five virgin olive oils (VOO) obtained from the olive cultivar 'Roghiani', from different regions of northern Libya during the crop year 2015. The parameters determined for the oils were investigated for the first time. Seven principal FAs were detected in the VOO samples. Oleic, palmitic, and linoleic acids were the dominant ones. The highest percentage of palmitic acid was found in Tripoli VOO (P lt = 0.05). Oleic acid was dominant in all the VOO samples. Gharyan VOO possessed the highest value of oleic acid, O/L ratio, monounsaturated fatty acids (MUFA), total phenols content (TPC), total tocopherol and tocotrienol contents (TTC), and AC(DPPH)% (P lt = 0.05). A strong positive relationship between TPC and (AC) as (1/EC50DPPH) was observed, (r) was +0.831. On the other hand, (1/EC50DPPH) showed a positive correlation with TTC, (r) was +0.768

Enhancing interoperability: ontology-mapping in an electronic institution

The automation of B2B processes requires a high level of interoperability between potentially disparate systems. We model such systems using software agents (representing enterprises), which interact using specific protocols. When considering open environments, interoperability problems are even more challenging. Addressing business automation as a task that intends to align businesses through a tight integration of processes may not be desirable, because business relationships may be temporary and dynamic. Furthermore, openness implies heterogeneity of technologies, processes, and even domain ontologies. After discussing these issues, this paper presents, in the context of an Electronic Institution, an ontology-mapping service that enables the automation of negotiation protocols when agents may use different ontologies to represent their domain knowledge. The ontology-mapping service employs two approaches used for lexical and semantic similarity, namely N-Grams and WordNet, and poses few requirements on the ontologies' representation format. Examples are provided that illustrate the integration of ontology-mapping with automated negotiation. © 2009 Springer Berlin Heidelberg

Benefits and problems of electronic information exchange as perceived by health care professionals: an interview study

<p>Abstract</p> <p>Background</p> <p>Various countries are currently implementing a national electronic patient record (n-EPR). Despite the assumed positive effects of n-EPRs, their overall adoption remains low and meets resistance from health care providers. This study aims to increase our understanding of health care providers' attitude towards the n-EPR, by investigating their perceptions of the benefits and problems of electronic information exchange in health care and the n-EPR in particular.</p> <p>Methods</p> <p>The study was conducted in three Dutch health care settings: acute care, diabetes care, and ambulatory mental health care. Two health care organisations were included per setting. Between January and June 2010, interviews were conducted with 17 stakeholders working in these organisations. Relevant themes were deduced by means of thematic qualitative analysis.</p> <p>Results</p> <p>Health care providers perceived electronic information exchange to promote the efficiency and quality of care. The problems they perceived in electronic information exchange mainly concerned the confidentiality and safety of information exchange and the reliability and quality of patient data. Many problems perceived by health care providers did not specifically apply to the n-EPR, but to electronic information exchange in general.</p> <p>Conclusions</p> <p>The implementation of the Dutch n-EPR has mainly followed a top-down approach, thereby neglecting the fact that the perceptions and preferences of its users (health care providers) need to be addressed in order to achieve successful implementation. The results of this study provide valuable suggestions about how to promote health care providers' willingness to adopt electronic information exchange, which can be useful for other countries currently implementing an n-EPR. Apart from providing information about the benefits and usefulness of electronic information exchange, efforts should be focused on minimising the problems as perceived by health care providers. The safety and confidentiality of electronic information exchange can be improved by developing tools to evaluate the legitimacy of access to electronic records, by increasing health care providers' awareness of the need to be careful when using patient data, and by measures to limit access to sensitive patient data. Improving health care providers' recording behaviour is important to improve the reliability and quality of electronically exchanged patient data.</p

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets