A comparative assessment of two different methods, using devices Optiscan-TP and Optigrade-MCP, for predicting the lean meat percentage of pig carcasses in Greece in relation to the European reference method

Lean Meat Percentage (LMP) is a key index for assessing pork carcass quality as well as determining carcass classification and price. This framework offers to farmers the incentive to achieve the desired organoleptic features; therefore LMP must be measured objectively online, by means of various measuring instruments. The aim of this work was to assess two different methods for predicting the lean meat percentage of pig carcasses in Greece in comparison to the European reference method. For this reason, the same 130 pig carcasses (65 males and 65 females) were measured using 2 prediction devices (Optiscan-TP and Optigrade-MCP) and subsequently were assessed according to European reference method. A formula corresponding to each device was constructed using the ordinary least squares (OLS)method and excluding the same outliers. Calculated RMSEP for all 130 carcasses was 2.46518 for Optiscan-TP and 2.48489 for Optigrade-MCP. It can be concluded that both methods perform entirely according to EU legislation (Commission Regulation (EC) 1249/2008, European Union, 2008), and results obtained are similar regardless of different measurement points and technologies

Texture classification of proteins using support vector machines and bio-inspired metaheuristics

6th International Joint Conference, BIOSTEC 2013, Barcelona, Spain, February 11-14, 2013[Abstract] In this paper, a novel classification method of two-dimensional polyacrylamide gel electrophoresis images is presented. Such a method uses textural features obtained by means of a feature selection process for whose implementation we compare Genetic Algorithms and Particle Swarm Optimization. Then, the selected features, among which the most decisive and representative ones appear to be those related to the second order co-occurrence matrix, are used as inputs for a Support Vector Machine. The accuracy of the proposed method is around 94 %, a statistically better performance than the classification based on the entire feature set. This classification step can be very useful for discarding over-segmented areas after a protein segmentation or identification process

A Dynamic Bayesian Network Approach to Behavioral Modelling of Elderly People during a Home-based Augmented Reality Balance Physiotherapy Programme

In this study, we propose a dynamic Bayesian network (DBN)-based approach to behavioral modelling of community dwelling older adults at risk for falls during the daily sessions of a hologram-enabled vestibular rehabilitation therapy programme. The component of human behavior being modelled is the level of frustration experienced by the user at each exercise, as it is assessed by the NASA Task Load Index. Herein, we present the topology of the DBN and test its inference performance on real-patient data.Clinical Relevance- Precise behavioral modelling will provide an indicator for tailoring the rehabilitation programme to each individual's personal psychological needs

Analysis of the sentiments of the participants in a clinical study to evaluate a balance rehabilitation intervention delivered by a Virtual Coach

Multiple studies for balance rehabilitation interventions have been accomplished aiming to demonstrate that sensory interventions and cognitive functionality are crucial for postural control and improvement of the quality of patient's daily life. However, none of the existing studies is filling the lack of expert physiotherapists availability. A pilot randomized study was conducted to assess the acceptability of the HOLOBalance telerehabilitation system. HOLOBalance is an interactive AR rehabilitation system which encompasses multi-sensory training program to enhance balance and cognitive coaching, for older adults at falls risk. In this work, we present a sentiment analysis of the patients participating in this study using the VADER methodology to evaluate and quantify their attitude towards the HOLOBalance system. Our results highlight the importance of findings positive polarity towards the AR interaction, which is based on the use of a holographic virtual physiotherapist. The compound score of 0.185 indicates the valuable positive feedback gained from the user experience

MRI assessment of the effects of acetazolamide and external lumbar drainage in idiopathic Normal Pressure Hydrocephalus

BACKGROUND: The objective was to identify changes in quantitative MRI measures in patients with idiopathic normal pressure hydrocephalus (iNPH) occurring in common after oral acetazolamide (ACZ) and external lumbar drainage (ELD) interventions. METHODS: A total of 25 iNPH patients from two clinical sites underwent serial MRIs and clinical assessments. Eight received ACZ (125-375 mg/day) over 3 months and 12 underwent ELD for up to 72 hours. Five clinically-stable iNPH patients who were scanned serially without interventions served as controls for the MRI component of the study. Subjects were divided into responders and non-responders to the intervention based on gait and cognition assessments made by clinicians blinded to MRI results. The MRI modalities analyzed included T1-weighted images, diffusion tensor Imaging (DTI) and arterial spin labelling (ASL) perfusion studies. Automated threshold techniques were used to define regions of T1 hypo-intensities. RESULTS: Decreased volume of T1-hypointensities and decreased mean diffusivity (MD) within remaining hypointensities was observed after ACZ and ELD but not in controls. Patients responding positively to these interventions had more extensive decreases in T1-hypointensites than non-responders: ACZ-responders (4,651 ± 2,909 mm(3)), ELD responders (2,338 ± 1,140 mm(3)), ELD non-responders (44 ± 1,188 mm(3)). Changes in DTI MD within T1-hypointensities were greater in ACZ-responders (7.9% ± 2%) and ELD-responders (8.2% ± 3.1%) compared to ELD non-responders (2.1% ± 3%). All the acetazolamide-responders showed increases in whole-brain-average cerebral blood flow (wbCBF) estimated by ASL (18.8% ± 8.7%). The only observed decrease in wbCBF (9.6%) occurred in an acetazolamide-non-responder. A possible association between cerebral atrophy and response was observed, with subjects having the least cortical atrophy (as indicated by a positive z-score on cortical thickness measurements) showing greater clinical improvement after ACZ and ELD. CONCLUSIONS: T1-hypointensity volume and DTI MD measures decreased in the brains of iNPH patients following oral ACZ and ELD. The magnitude of the decrease was greater in treatment responders than non-responders. Despite having different mechanisms of action, both ELD and ACZ may decrease interstitial brain water and increase cerebral blood flow in patients with iNPH. Quantitative MRI measurements appear useful for objectively monitoring response to acetazolamide, ELD and potentially other therapeutic interventions in patients with iNPH

Machine learning methods to reverse engineer dynamic gene regulatory networks governing cell state transitions

ABSTRACTDeciphering the dynamic gene regulatory mechanisms driving cells to make fate decisions remains elusive. We present a novel unsupervised machine learning methodology that can be used to analyze a dataset of heterogeneous single-cell gene expressions profiles, determine the most probable number of states (major cellular phenotypes) represented and extract the corresponding cell sub-populations. Most importantly, for any transition of interest from a source to a destination state, our methodology can zoom in, identify the cells most specific for studying the dynamics of this transition, order them along a trajectory of biological progression in posterior probabilities space, determine the "key-player" genes governing the transition dynamics, partition the trajectory into consecutive phases (transition "micro-states"), and finally reconstruct causal gene regulatory networks for each phase. Application of the end-to-end methodology provides new insights on key-player genes and their dynamic interactions during the important HSC-to-LMPP cell state transition involved in hematopoiesis. Moreover, it allows us to reconstruct a probabilistic representation of the “epigenetic landscape” of transitions and identify correctly the major ones in the hematopoiesis hierarchy of states.</jats:p