Shooting under cardiovascular load: Electroencephalographic activity in preparation for biathlon shooting

AbstractThis study explored the influence of sub-maximal cardiovascular load on electroencephalographic (EEG) activity preceding biathlon shooting. Frontal-midline theta and alpha power were examined to assess monitoring processes and cortical inhibition, respectively. Thirteen experienced biathletes (mean age: 17years; 5 males, 8 females) fired sets of five consecutive shots from the standing position at a 50-meter-distant target, under two fixed-order conditions: (i) at rest and (ii) immediately after 3-minute exercise on a bicycle ergometer at 90% of maximum heart rate (HR). HR and rate of physical exertion (RPE) were measured as manipulation checks. Shooting accuracy was assessed in target rings for each shot. Frontal-midline theta and alpha power were computed in the last second preceding each shot from average-reference 61-channel EEG and inter-individual differences were minimized through a median-scaled log transformation (Appendix). HR and RPE increased under cardiovascular load, however, shooting accuracy did not change. Pre-shooting frontal-midline theta power decreased, whereas alpha power increased over temporal and occipital – but not central – regions. These changes were larger for greater HR values. Additionally, higher frontal-midline theta, lower left-central alpha, and higher left-temporal alpha power were associated with more accurate shooting. These findings suggest that monitoring processes are beneficial to shooting performance but can be impaired by sub-maximal cardiovascular load. Greater inhibition of movement-irrelevant regions (temporal, occipital) and concomitant activation of movement-related regions (central) indicate that greater neural efficiency is beneficial to shooting performance and can allow trained biathletes to shoot accurately despite physically demanding conditions

Optimisation of machine learning methods for cancer detection using vibrational spectroscopy

Early cancer detection drastically improves the chances of cure and therefore methods are required, which allow early detection and screening in a fast, reliable and inexpensive manner. A prospective method, featuring all these characteristics, is vibrational spectroscopy. In order to take the next step towards the development of this technology into a clinical diagnostic tool, classification and imaging methods for an automated diagnosis based on spectral data are required. For this study, Raman spectra, derived from axillary lymph node tissue from breast cancer patients, were used to develop a diagnostic model. For this purpose different classification methods were investigated. A support vector machine (SVM) proved to be the best choice of classification method since it classified 100% of the unseen test set correctly. The resulting diagnostic models were thoroughly tested for their robustness to the spectral corruptions that would be expected to occur during routine clinical analysis. It showed that sufficient robustness is provided for a future diagnostic routine application. SVMs demonstrated to be a powerful classifier for Raman data and due to that they were also investigated for infrared spectroscopic data. Since it was found that a single SVM was not capable of reliably predicting breast cancer pathology based on tissue calcifications measured by infrared micro-spectroscopy a SVM ensemble system was implemented. The resulting multi-class SVM ensemble predicted the pathology of the unseen test set with an accuracy of 88.9%, in comparison a single SVM assessed with the same unseen test set achieved 66.7% accuracy. In addition, the ensemble system was extended for analysing complete infrared maps obtained from breast tissue specimens. The resulting imaging method successfully detected and staged calcification in infrared maps. Furthermore, this imaging approach revealed new insights into the calcification process in malignant development, which was not previously well understood.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The relationship between visual function and performance in rifle shooting for athletes with vision impairment

Background: Paralympic sports provide opportunities for those who have an impairment that might otherwise be a barrier to participation in regular sporting competition. Rifle shooting represents an ideal sport for persons with vision impairment (VI) because the direction of the rifle can be guided by auditory information when vision is impaired. However, it is unknown whether those with some remaining vision when shooting with auditory guidance would be at an advantage when compared with those with no vision at all. If this were the case then it would be necessary for those with and without remaining vision to compete in separate classes of competition. Materials and method: The associations between shooting performance and 3 measures of visual function thought important for shooting were assessed for 10 elite VI shooters currently classified as VI. A conventional audiogram was also obtained. Results: The sample size, though small, included the majority of European VI shooters competing at this level. The relationships between visual functions and performance confirmed that individuals with residual vision had no advantage over those without vision when auditory guidance was available. Auditory function was within normal limits for age, and showed no relationship with performance. Summary: The findings suggest that rifle-shooting athletes with VI are able to use auditory information to overcome their impairment and optimise performance. Paralympic competition should be structured in a way that ensures that all shooters who qualify to compete in VI shooting participate within the same class irrespective of their level of VI

A blood gene expression marker of early Alzheimer's disease.

PublishedJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tA marker of Alzheimer's disease (AD) that can accurately diagnose disease at the earliest stage would significantly support efforts to develop treatments for early intervention. We have sought to determine the sensitivity and specificity of peripheral blood gene expression as a diagnostic marker of AD using data generated on HT-12v3 BeadChips. We first developed an AD diagnostic classifier in a training cohort of 78 AD and 78 control blood samples and then tested its performance in a validation group of 26 AD and 26 control and 118 mild cognitive impairment (MCI) subjects who were likely to have an AD-endpoint. A 48 gene classifier achieved an accuracy of 75% in the AD and control validation group. Comparisons were made with a classifier developed using structural MRI measures, where both measures were available in the same individuals. In AD and control subjects, the gene expression classifier achieved an accuracy of 70% compared to 85% using MRI. Bootstrapping validation produced expression and MRI classifiers with mean accuracies of 76% and 82%, respectively, demonstrating better concordance between these two classifiers than achieved in a single validation population. We conclude there is potential for blood expression to be a marker for AD. The classifier also predicts a large number of people with MCI, who are likely to develop AD, are more AD-like than normal with 76% of subjects classified as AD rather than control. Many of these people do not have overt brain atrophy, which is known to emerge around the time of AD diagnosis, suggesting the expression classifier may detect AD earlier in the prodromal phase. However, we accept these results could also represent a marker of diseases sharing common etiology.InnoMed, European Union of the Sixth Framework programAlzheimer’s Research UKJohn and Lucille van Geest FoundationNIHRBiomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation TrustInstitute of Psychiatry Kings College LondonNIA/NIH RC

Circulating Proteomic Signatures of Chronological Age

To elucidate the proteomic features of aging in plasma, the subproteome targeted by the SOMAscan assay was profiled in blood samples from 202 females from the TwinsUK cohort. Findings were replicated in 677 independent individuals from the AddNeuroMed, Alzheimer's Research UK, and Dementia Case Registry cohorts. Results were further validated using RNAseq data from whole blood in TwinsUK and the most significant proteins were tested for association with aging-related phenotypes after adjustment for age. Eleven proteins were associated with chronological age and were replicated at protein level in an independent population. These were further investigated at gene expression level in 384 females from the TwinsUK cohort. The two most strongly associated proteins were chordin-like protein 1 (meta-analysis β [SE] = 0.013 [0.001], p = 3.66 × 10−46) and pleiotrophin (0.012 [0.005], p = 3.88 × 10−41). Chordin-like protein 1 was also significantly correlated with birthweight (0.06 [0.02], p = 0.005) and with the individual Framingham 10-years cardiovascular risk scores in TwinsUK (0.71 [0.18], p = 9.9 × 10−5). Pleiotrophin is a secreted growth factor with a plethora of functions in multiple tissues and known to be a marker for cardiovascular risk and osteoporosis. Our study highlights the importance of proteomics to identify some molecular mechanisms involved in human health and agin

Mitochondrial dysfunction and immune activation are detectable in early Alzheimer's disease blood.

PublishedJournal ArticleResearch Support, Non-U.S. Gov'tAlzheimer's disease (AD), like other dementias, is characterized by progressive neuronal loss and neuroinflammation in the brain. The peripheral leukocyte response occurring alongside these brain changes has not been extensively studied, but might inform therapeutic approaches and provide relevant disease biomarkers. Using microarrays, we assessed blood gene expression alterations occurring in people with AD and those with mild cognitive changes at increased risk of developing AD. Of the 2,908 differentially expressed probes identified between the three groups (p < 0.01), a quarter were altered in blood from mild cognitive impairment (MCI) and AD subjects, relative to controls, suggesting a peripheral response to pathology may occur very early. There was strong evidence for mitochondrial dysfunction with decreased expression of many of the respiratory complex I-V genes and subunits of the core mitochondrial ribosome complex. This mirrors changes previously observed in AD brain. A number of genes encoding cell adhesion molecules were increased, along with other immune-related genes. These changes are consistent with leukocyte activation and their increased the transition from circulation into the brain. In addition to expression changes, we also found increased numbers of basophils in people with MCI and AD, and increased monocytes in people with an AD diagnosis. Taken together this study provides both an insight into the functional response of circulating leukocytes during neurodegeneration and also identifies potential targets such as the respiratory chain for designing and monitoring future therapeutic interventions using blood.InnoMed, European Union of the Sixth Framework programAlzheimer’s Research TrustJohn and Lucille van Geest FoundationNIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation TrustInstitute of Psychiatry Kings College Londo

An epigenome-wide association study of Alzheimer's disease blood highlights robust DNA hypermethylation in the HOXB6 gene

This is the final version. Available from the publisher via the DOI in this record.A growing number of epigenome-wide association studies have demonstrated a role for DNA methylation in the brain in Alzheimer's disease. With the aim of exploring peripheral biomarker potential, we have examined DNA methylation patterns in whole blood collected from 284 individuals in the AddNeuroMed study, which included 89 nondemented controls, 86 patients with Alzheimer's disease, and 109 individuals with mild cognitive impairment, including 38 individuals who progressed to Alzheimer's disease within 1 year. We identified significant differentially methylated regions, including 12 adjacent hypermethylated probes in the HOXB6 gene in Alzheimer's disease, which we validated using pyrosequencing. Using weighted gene correlation network analysis, we identified comethylated modules of genes that were associated with key variables such as APOE genotype and diagnosis. In summary, this study represents the first large-scale epigenome-wide association study of Alzheimer's disease and mild cognitive impairment using blood. We highlight the differences in various loci and pathways in early disease, suggesting that these patterns relate to cognitive decline at an early stage.Alzheimer's Society, United KingdomMedical Research Council (MRC)NIH, United States, R01 grantAlzheimer's Research U

Plasma proteins predict conversion to dementia from prodromal disease.

PublishedJournal ArticleMulticenter StudyResearch Support, Non-U.S. Gov'tBACKGROUND: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. METHODS: Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. RESULTS: Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). CONCLUSIONS: We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.Medical Research Council (MRC)Alzheimer’s Research UKThe National Institute for Health Research (NIHR) Biomedical Research CentreBiomedical Research Unit for DementiaAddNeuroMed through the EU FP6 programInnovative Medicines Initiative Joint Undertaking under an EMIF grantEuropean Union’s Seventh Framework Programme (FP7/2007-2013

Evaluation of gas chromatography mass spectrometry and pattern recognition for the identification of bladder cancer from urine headspace

Previous studies have indicated that volatile organic compounds specific to bladder cancer may exist in urine headspace, raising the possibility that they may be of diagnostic value for this particular cancer. To further examine this hypothesis, urine samples were collected from patients diagnosed with either bladder cancer or a non-cancerous urological disease/infection, and from healthy volunteers, from which the volatile metabolomes were analysed using gas chromatography mass spectrometry. The acquired data were subjected to a specifically designed pattern recognition algorithm, involving cross-model validation. The best diagnostic performance, achieved with independent test data provided by healthy volunteers and bladder cancer patients, was 89% overall accuracy (90% sensitivity and 88% specificity). Permutation tests showed that these were statistically significant, providing further evidence of the potential for volatile biomarkers to form the basis of a non-invasive diagnostic technique