Representation of probabilistic scientific knowledge

This article is available through the Brunel Open Access Publishing Fund. Copyright © 2013 Soldatova et al; licensee BioMed Central Ltd.The theory of probability is widely used in biomedical research for data analysis and modelling. In previous work the probabilities of the research hypotheses have been recorded as experimental metadata. The ontology HELO is designed to support probabilistic reasoning, and provides semantic descriptors for reporting on research that involves operations with probabilities. HELO explicitly links research statements such as hypotheses, models, laws, conclusions, etc. to the associated probabilities of these statements being true. HELO enables the explicit semantic representation and accurate recording of probabilities in hypotheses, as well as the inference methods used to generate and update those hypotheses. We demonstrate the utility of HELO on three worked examples: changes in the probability of the hypothesis that sirtuins regulate human life span; changes in the probability of hypotheses about gene functions in the S. cerevisiae aromatic amino acid pathway; and the use of active learning in drug design (quantitative structure activity relation learning), where a strategy for the selection of compounds with the highest probability of improving on the best known compound was used. HELO is open source and available at https://github.com/larisa-soldatova/HELO.This work was partially supported by grant BB/F008228/1 from the UK Biotechnology & Biological Sciences Research Council, from the European Commission under the FP7 Collaborative Programme, UNICELLSYS, KU Leuven GOA/08/008 and ERC Starting Grant 240186

Crossover and coexistence of quasiparticle excitations in the fractional quantum Hall regime at nu <= 1/3

New low-lying excitations are observed by inelastic light scattering at filling factors nu=p/(phip+/-1) of the fractional quantum Hall regime with phi=4. Coexisting with these modes throughout the range nuless than or equal to1/3 are phi=2 excitations seen at 1/3. Both phi=2 and phi=4 excitations have distinct behaviors with temperature and filling factor. The abrupt first appearance of the new modes in the low-energy excitation spectrum at nuless than or similar to1/3 suggests a marked change in the quantum ground state on crossing the phi=2-->phi=4 boundary at nu=1/3

Multimodal optical characterisation of collagen photodegradation by femtosecond infrared laser ablation.

Collagen is a structural component of the human body, as a connective tissue it can become altered as a result of pathophysiological conditions. Although the collagen degradation mechanism is not fully understood, it plays an important role in ageing, disease progression and applications in therapeutic laser treatments. To fully understand the mechanism of collagen alteration, in our study photo-disruptive effects were induced in collagen I matrix by point-irradiation with a femtosecond Ti-sapphire laser under controlled laser ablation settings. This was followed by multi-modal imaging of the irradiated and surrounding areas to analyse the degradation mechanism. Our multi-modal methodology was based on second harmonic generation (SHG), scanning electron microscope (SEM), autofluorescence (AF) average intensities and the average fluorescence lifetime. This allowed us to quantitatively characterise the degraded area into four distinct zones: (1) depolymerised zone in the laser focal spot as indicated by the loss of SHG signal, (2) enhanced crosslinking zone in the inner boundary of the laser induced cavity as represented by the high fluorescence ring, (3) reduced crosslinking zone formed the outer boundary of the cavity as marked by the increased SHG signal and (4) native collagen. These identified distinct zones were in good agreement with the expected photochemical changes shown using Raman spectroscopy. In addition, imaging using polarisation-resolved SHG (p-SHG) revealed both a high degree of fibre re-orientation and a SHG change in tensor ratios around the irradiation spot. Our multi-modal optical imaging approach can provide a new methodology for defining distinct zones that can be used in a clinical setting to determine suitable thresholds for applying safe laser treatments without affecting the surrounding tissues. Furthermore this technique can be extended to address challenges observed in collagen based tissue engineering and used as a minimally invasive diagnostic tool to characterise diseased and non-diseased collagen rich tissues

The association between alcohol consumption and sleep disorders among older people in the general population

The relationship between alcohol consumption and sleep disturbance is complex. The association of alcohol dependence with insomnia is likely to be bidirectional in nature. Alcohol use is common among older people in many societies and the prevalence of insomnia tends to increase with age, therefore this group warrants particular consideration. We explored the cross sectional and long term (30 years) associations between alcohol drinking (volume and hazardous drinking) and sleep duration and insomnia in a general population study of older adults (6,117 male and female civil servants followed for 30 years). For men, drinking more than 21 units (approximately 168 grams) of alcohol per week, compared with not drinking, was associated with waking several times a night (odds ratio 1.30, confidence intervals 1.02-1.66). Men who maintained a heavy volume of drinking over the three decades of observation, or who had an unstable consumption pattern, tended to have worse sleep profiles in terms of waking tired and waking several times. Sustained male hazardous drinking (as measured by the AUDIT-C scale) was also associated with worse sleep profiles. Findings for women were not so clear. In this population based setting, drinking high volumes of alcohol may contribute to the prevalence of sleep problems in older age, particularly for men. People in this age group should be discouraged from using alcohol as a sleep aid

Glucose Content of Sago Waste After Chloride Acid Pre- Treatment Hydrolysis For Bioethanol Production

Indonesia is a country with abundant agricultural biological resources. One of the plants as a biological source is sago. Sago processing wastes such as bark and waste about 72%. Jepara district has rich sago waste, piled on the side of the road and the river so it is very disturbing. In generally, sago industrial wastes utilization is still lacking, especially as a source of energy. Sago waste consists mainly of cellulose and has the potential to be processed into bioethanol. Glucose contained in cellulosic biomass is the main ingredient in the manufacture of bioethanol and need to know the glucose content after of sago waste cellulose hydrolysis process to determine the highest amount of ethanol. This study aims to determine the glucose content of sago wastewater using acid catalysis with different concentrations of the hydrolysis process, and to know the appropriate concentration of acid to produce the highest glucose and bioethanol in all type of waste. The result showed that type of waste had no effect on glucose content. Glucose content of sago waste showed no difference between the effect of chlorida acid concentration with glucose content. However, hydrolysis at concentration tends to produce the highest glucose

A Novel Hybrid CNN-AIS Visual Pattern Recognition Engine

Machine learning methods are used today for most recognition problems. Convolutional Neural Networks (CNN) have time and again proved successful for many image processing tasks primarily for their architecture. In this paper we propose to apply CNN to small data sets like for example, personal albums or other similar environs where the size of training dataset is a limitation, within the framework of a proposed hybrid CNN-AIS model. We use Artificial Immune System Principles to enhance small size of training data set. A layer of Clonal Selection is added to the local filtering and max pooling of CNN Architecture. The proposed Architecture is evaluated using the standard MNIST dataset by limiting the data size and also with a small personal data sample belonging to two different classes. Experimental results show that the proposed hybrid CNN-AIS based recognition engine works well when the size of training data is limited in siz

EXACT2: the semantics of biomedical protocols

© 2014 Soldatova et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background: The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods: We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously ‘unseen’ (not used for the construction of EXACT2) protocols. Results: The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions: The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format.This work has been partially funded by the Brunel University BRIEF award and a grant from Occams Resources