Trends in alcohol-related injury admissions in adolescents in Western Australia and England: population-based cohort study

BACKGROUND: Alcohol-related harm in young people is now a global health priority. We examined trends in hospital admissions for alcohol-related injuries for adolescents in Western Australia (WA) and in England, identified groups most at risk and determined causes of injuries. METHODS: Annual incidence rates for alcohol-related injury rates were calculated using population-level hospital admissions data for WA and England. We compared trends in different types of alcohol-related injury by age and gender. RESULTS: Despite a decrease in the overall rate of injury admissions for people aged 13-17 years in WA, alcohol-related injuries have increased significantly from 1990 to 2009 (from 8 to 12 per 10 000). Conversely, alcohol-related injury rates have declined in England since 2007. In England, self-harm is the most frequently recorded cause of alcohol-related injury. In WA, unintentional injury is most common; however, violence-related harm is increasing for boys and girls. CONCLUSION: Alcohol-related harm of sufficient severity to require hospital admission is increasing among adolescents in WA. Declining trends in England suggest that this trend is not inevitable or irreversible. More needs to be done to address alcohol-related harm, and on-going monitoring is required to assess the effectiveness of strategies

Impact of physiological noise correction on detecting blood oxygenation level-dependent contrast in the breast.

Physiological fluctuations are expected to be a dominant source of noise in blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) experiments to assess tumour oxygenation and angiogenesis. This work investigates the impact of various physiological noise regressors: retrospective image correction (RETROICOR), heart rate (HR) and respiratory volume per unit time (RVT), on signal variance and the detection of BOLD contrast in the breast in response to a modulated respiratory stimulus. BOLD MRI was performed at 3 T in ten volunteers at rest and during cycles of oxygen and carbogen gas breathing. RETROICOR was optimized using F-tests to determine which cardiac and respiratory phase terms accounted for a significant amount of signal variance. A nested regression analysis was performed to assess the effect of RETROICOR, HR and RVT on the model fit residuals, temporal signal-to-noise ratio, and BOLD activation parameters. The optimized RETROICOR model accounted for the largest amount of signal variance ([Formula: see text]  =  3.3  ±  2.1%) and improved the detection of BOLD activation (P  =  0.002). Inclusion of HR and RVT regressors explained additional signal variance, but had a negative impact on activation parameter estimation (P  <  0.001). Fluctuations in HR and RVT appeared to be correlated with the stimulus and may contribute to apparent BOLD signal reactivity.This work was supported by the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre and the CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester (C197/A16465 and C8742/A18097)

Dynamic contrast enhanced CT in nodule characterization: How we review and report

Incidental indeterminate solitary pulmonary nodules (SPN) that measure less than 3 cm in size are an increasingly common finding on computed tomography (CT) worldwide. Once identified there are a number of imaging strategies that can be performed to help with nodule characterization. These include interval CT, dynamic contrast enhanced computed tomography (DCE-CT), $^{18}$F-fluorodeoxyglucose positron emission tomography-computed tomography ($^{18}$F-FDG-PET-CT). To date the most cost effective and efficient non-invasive test or combination of tests for optimal nodule characterization has yet to be determined.DCE-CT is a functional test that involves the acquisition of a dynamic series of images of a nodule before and following the administration of intravenous iodinated contrast medium. This article provides an overview of the current indications and limitations of DCE- CT in nodule characterization and a systematic approach to how to perform, analyse and interpret a DCE-CT scan.NIHR Health Technology Assessment programme (Grant ID: 09/22/117), Cambridge Biomedical Research Centre, CRUK Cambridge and Manchester Cancer Imaging Centr

Targeted Molecular Imaging in Adrenal Disease—An Emerging Role for Metomidate PET-CT

Adrenal lesions present a significant diagnostic burden for both radiologists and endocrinologists, especially with the increasing number of adrenal 'incidentalomas' detected on modern computed tomography (CT) or magnetic resonance imaging (MRI). A key objective is the reliable distinction of benign disease from either primary adrenal malignancy (e.g., adrenocortical carcinoma or malignant forms of pheochromocytoma/paraganglioma (PPGL)) or metastases (e.g., bronchial, renal). Benign lesions may still be associated with adverse sequelae through autonomous hormone hypersecretion (e.g., primary aldosteronism, Cushing's syndrome, phaeochromocytoma). Here, identifying a causative lesion, or lateralising the disease to a single adrenal gland, is key to effective management, as unilateral adrenalectomy may offer the potential for curing conditions that are typically associated with significant excess morbidity and mortality. This review considers the evolving role of positron emission tomography (PET) imaging in addressing the limitations of traditional cross-sectional imaging and adjunctive techniques, such as venous sampling, in the management of adrenal disorders. We review the development of targeted molecular imaging to the adrenocortical enzymes CYP11B1 and CYP11B2 with different radiolabeled metomidate compounds. Particular consideration is given to iodo-metomidate PET tracers for the diagnosis and management of adrenocortical carcinoma, and the increasingly recognized utility of $^{11}$C-metomidate PET-CT in primary aldosteronism.NIHR Cambridge Biomedical Research Centr

A longitudinal study of muscle rehabilitation in the lower leg after cast removal using magnetic resonance imaging and strength assessment

Magnetic resonance imaging (MRI) was used to investigate muscle rehabilitation following cast immobilization. The aim was to explore MRI as an imaging biomarker of muscle function. Sixteen patients completed an eight-week rehabilitation programme following six weeks of cast immobilization for an ankle fracture. MRI of the lower leg was performed at two-week intervals for 14 weeks. Total volume and anatomical cross-sectional areas at 70% of the distance from lateral malleolus to tibial tuberosity (ACSA) were measured for tibialis anterior (TA), medial and lateral gastrocnemius (GM and GL) and soleus (SOL). Pennation angle of muscle fascicules was measured at the same position in GM. Fractional fat/water contents and T2 relaxation times before and after exercise were calculated. Strength was measured as maximum isometric torque developed in plantar- and dorsi-flexion. Torque increased by (mean [SD]) 1.10 (0.32) N m day−1 in males, 0.74 (0.43) N m day−1 in females in plantar-flexion (0.9% of final strength per day), and 0.36 (0.15) N m day−1 in males, 0.28 (0.19) N m day−1 in females in dorsi-flexion (1.1% per day). Neither difference between males and females was significant. Volume and ACSA of muscles recovered by week 14 apart from SOL which was still 6.8% smaller (p = 0.006) than the contralateral leg. T2 peaked at the end of the cast period for TA and SOL, and at week 8 for GM before returning to baseline. Pennation angle recovered rapidly following cast removal. Quantitative MRI can generate markers of muscle biomechanics and indicates that many of these return to baseline within eight weeks of remobilization

Scalar and vector Slepian functions, spherical signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and, particularly for applications in the geosciences, for scalar and vectorial signals defined on the surface of a unit sphere.Comment: Submitted to the 2nd Edition of the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verlag. This is a slightly modified but expanded version of the paper arxiv:0909.5368 that appeared in the 1st Edition of the Handbook, when it was called: Slepian functions and their use in signal estimation and spectral analysi

Enteric dysbiosis and fecal calprotectin expression in premature infants.

BackgroundPremature infants often develop enteric dysbiosis with a preponderance of Gammaproteobacteria, which has been related to adverse clinical outcomes. We investigated the relationship between increasing fecal Gammaproteobacteria and mucosal inflammation, measured by fecal calprotectin (FC).MethodsStool samples were collected from very-low-birth weight (VLBW) infants at ≤2, 3, and 4 weeks' postnatal age. Fecal microbiome was surveyed using polymerase chain reaction amplification of the V4 region of 16S ribosomal RNA, and FC was measured by enzyme immunoassay.ResultsWe enrolled 45 VLBW infants (gestation 27.9 ± 2.2 weeks, birth weight 1126 ± 208 g) and obtained stool samples at 9.9 ± 3, 20.7 ± 4.1, and 29.4 ± 4.9 days. FC was positively correlated with the genus Klebsiella (r = 0.207, p = 0.034) and its dominant amplicon sequence variant (r = 0.290, p = 0.003), but not with the relative abundance of total Gammaproteobacteria. Klebsiella colonized the gut in two distinct patterns: some infants started with low Klebsiella abundance and gained these bacteria over time, whereas others began with very high Klebsiella abundance.ConclusionIn premature infants, FC correlated with relative abundance of a specific pathobiont, Klebsiella, and not with that of the class Gammaproteobacteria. These findings indicate a need to define dysbiosis at genera or higher levels of resolution

Robot life: simulation and participation in the study of evolution and social behavior.

This paper explores the case of using robots to simulate evolution, in particular the case of Hamilton's Law. The uses of robots raises several questions that this paper seeks to address. The first concerns the role of the robots in biological research: do they simulate something (life, evolution, sociality) or do they participate in something? The second question concerns the physicality of the robots: what difference does embodiment make to the role of the robot in these experiments. Thirdly, how do life, embodiment and social behavior relate in contemporary biology and why is it possible for robots to illuminate this relation? These questions are provoked by a strange similarity that has not been noted before: between the problem of simulation in philosophy of science, and Deleuze's reading of Plato on the relationship of ideas, copies and simulacra

Slepian functions and their use in signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and on the surface of a sphere.Comment: Submitted to the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verla