Evaluating Active U: an Internet-mediated physical activity program.

Background: Engaging in regular physical activity can be challenging, particularly during the winter months. To promote physical activity at the University of Michigan during the winter months, an eight-week Internet-mediated program (Active U) was developed providing participants with an online physical activity log, goal setting, motivational emails, and optional team participation and competition. Methods: This study is a program evaluation of Active U. Approximately 47,000 faculty, staff, and graduate students were invited to participate in the online Active U intervention in the winter of 2007. Participants were assigned a physical activity goal and were asked to record each physical activity episode into the activity log for eight weeks. Statistics for program reach, effectiveness, adoption, and implementation were calculated using the Re-Aim framework. Multilevel regression analyses were used to assess the decline in rates of data entry and goal attainment during the program, to assess the likelihood of joining a team by demographic characteristics, to test the association between various predictors and the number of weeks an individual met his or her goal, and to analyze server load. Results: Overall, 7,483 individuals registered with the Active U website (≈16% of eligible), and 79% participated in the program by logging valid data at least once. Staff members, older participants, and those with a BMI < 25 were more likely to meet their weekly physical activity goals, and average rate of meeting goals was higher among participants who joined a competitive team compared to those who participated individually (IRR = 1.28, P < .001). Conclusion: Internet-mediated physical activity interventions that focus on physical activity logging and goal setting while incorporating team competition may help a significant percentage of the target population maintain their physical activity during the winter months

Detecting exotic heavy leptons at the Large Hadron Collider

New almost-degenerate charged and neutral heavy leptons are a feature of a number of theories of physics beyond the Standard Model. The prospects for detecting these at the Large Hadron Collider using a time-of-flight technique are considered, along with any cosmological or experimental constraints on their masses. Based on a discovery criterion of 10 detected exotic leptons we conclude that, with an integrated luminosity of 100 fb-1, it should be possible to detect such leptons provided their masses are less than 950 GeV. It should also be possible to use the angular distribution of the produced particles to distinguish these exotic leptons from supersymmetric scalar leptons, at a better than 90% confidence level, for masses up to 580 GeV

A national survey exploring views and experience of health professionals about transferring patients from critical care home to die.

BACKGROUND: Transferring critically ill patients home to die is poorly explored in the literature to date. This practice is rare, and there is a need to understand health care professionals' (HCP) experience and views. OBJECTIVES: To examine (1) HCPs' experience of transferring patients home to die from critical care, (2) HCPs' views about transfer and (3) characteristics of patients, HCPs would hypothetically consider transferring home to die. DESIGN: A national study developing a web-based survey, which was sent to the lead doctors and nurses in critical care units. SETTING/PARTICIPANTS: Lead doctors and senior nurses (756 individuals) working in 409 critical care units across the United Kingdom were invited to participate in the survey. RESULTS: In total, 180 (23.8%) completed surveys were received. A total of 65 (36.1%) respondents had been actively involved in transferring patients home to die and 28 (15.5%) had been involved in discussions that did not lead to transfer. Respondents were supportive of the idea of transfer home to die (88.8%). Patients identified by respondents as unsuitable for transfer included unstable patients (61.8%), intubated and ventilated patients (68.5%) and patients receiving inotropes (65.7%). There were statistically significant differences in views between those with and without experience and between doctors and nurses. Nurses and those with experience tended to have more positive views. CONCLUSION: While transferring patients home to die is supported in critical care, its frequency in practice remains low. Patient stability and level of intervention are important factors in decision-making in this area. Views held about this practice are influenced by previous experience and the professional role held

The transcription factor STAT6 plays a critical role in promoting beta cell viability and is depleted in islets of individuals with type 1 diabetes

This is the final version. Available on open access from Springer Verlag via the DOI in this recordAims/hypothesis: In type 1 diabetes, selective beta cell loss occurs within the inflamed milieu of insulitic islets. This milieu is generated via the enhanced secretion of proinflammatory cytokines and by the loss of anti-inflammatory molecules such as IL-4 and IL-13. While the actions of proinflammatory cytokines have been well-studied in beta cells, the effects of their anti-inflammatory counterparts have received relatively little attention and we have addressed this. Methods: Clonal beta cells, isolated human islets and pancreas sections from control individuals and those with type 1 diabetes were employed. Gene expression was measured using targeted gene arrays and by quantitative RT-PCR. Protein expression was monitored in cell extracts by western blotting and in tissue sections by immunocytochemistry. Target proteins were knocked down selectively with interference RNA. Results: Cytoprotection achieved with IL-4 and IL-13 is mediated by the early activation of signal transducer and activator of transcription 6 (STAT6) in beta cells, leading to the upregulation of anti-apoptotic proteins, including myeloid leukaemia-1 (MCL-1) and B cell lymphoma-extra large (BCLXL). We also report the induction of signal regulatory protein-α (SIRPα), and find that knockdown of SIRPα is associated with reduced beta cell viability. These anti-apoptotic proteins and their attendant cytoprotective effects are lost following siRNA-mediated knockdown of STAT6 in beta cells. Importantly, analysis of human pancreas sections revealed that STAT6 is markedly depleted in the beta cells of individuals with type 1 diabetes, implying the loss of cytoprotective responses. Conclusions/interpretation: Selective loss of STAT6 may contribute to beta cell demise during the progression of type 1 diabetes.Diabetes UKJDR

The M33 Globular Cluster System with PAndAS Data: The Last Outer Halo Cluster?

We use CFHT/MegaCam data to search for outer halo star clusters in M33 as part of the Pan-Andromeda Archaeological Survey (PAndAS). This work extends previous studies out to a projected radius of 50 kpc and covers over 40 square degrees. We find only one new unambiguous star cluster in addition to the five previously known in the M33 outer halo (10 kpc <= r <= 50 kpc). Although we identify 2440 cluster candidates of various degrees of confidence from our objective image search procedure, almost all of these are likely background contaminants, mostly faint unresolved galaxies. We measure the luminosity, color and structural parameters of the new cluster in addition to the five previously-known outer halo clusters. At a projected radius of 22 kpc, the new cluster is slightly smaller, fainter and redder than all but one of the other outer halo clusters, and has g' ~ 19.9, (g'-i') ~ 0.6, concentration parameter c ~ 1.0, a core radius r_c ~ 3.5 pc, and a half-light radius r_h ~ 5.5 pc. For M33 to have so few outer halo clusters compared to M31 suggests either tidal stripping of M33's outer halo clusters by M31, or a very different, much calmer accretion history of M33.Comment: 37 pages, 9 figures. Accepted by the Astrophysical Journa

Revealing epilepsy type using a computational analysis of interictal EEG

This is the final version. Available from Nature Research via the DOI in this record.All materials (functional networks and code) are available upon request from the corresponding author.Seizure onset in epilepsy can usually be classified as focal or generalized, based on a combination of clinical phenomenology of the seizures, EEG recordings and MRI. This classification may be challenging when seizures and interictal epileptiform discharges are infrequent or discordant, and MRI does not reveal any apparent abnormalities. To address this challenge, we introduce the concept of Ictogenic Spread (IS) as a prediction of how pathological electrical activity associated with seizures will propagate throughout a brain network. This measure is defined using a person-specific computer representation of the functional network of the brain, constructed from interictal EEG, combined with a computer model of the transition from background to seizure-like activity within nodes of a distributed network. Applying this method to a dataset comprising scalp EEG from 38 people with epilepsy (17 with genetic generalized epilepsy (GGE), 21 with mesial temporal lobe epilepsy (mTLE)), we find that people with GGE display a higher IS in comparison to those with mTLE. We propose IS as a candidate computational biomarker to classify focal and generalized epilepsy using interictal EEG.Medical Research Council (MRC)Wellcome TrustEpilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome Trus

Revealing epilepsy type using a computational analysis of interictal EEG.

Seizure onset in epilepsy can usually be classified as focal or generalized, based on a combination of clinical phenomenology of the seizures, EEG recordings and MRI. This classification may be challenging when seizures and interictal epileptiform discharges are infrequent or discordant, and MRI does not reveal any apparent abnormalities. To address this challenge, we introduce the concept of Ictogenic Spread (IS) as a prediction of how pathological electrical activity associated with seizures will propagate throughout a brain network. This measure is defined using a person-specific computer representation of the functional network of the brain, constructed from interictal EEG, combined with a computer model of the transition from background to seizure-like activity within nodes of a distributed network. Applying this method to a dataset comprising scalp EEG from 38 people with epilepsy (17 with genetic generalized epilepsy (GGE), 21 with mesial temporal lobe epilepsy (mTLE)), we find that people with GGE display a higher IS in comparison to those with mTLE. We propose IS as a candidate computational biomarker to classify focal and generalized epilepsy using interictal EEG

A Genome-wide gene-expression analysis and database in transgenic mice during development of amyloid or tau pathology

We provide microarray data comparing genome-wide differential expression and pathology throughout life in four lines of "amyloid" transgenic mice (mutant human APP, PSEN1, or APP/PSEN1) and "TAU" transgenic mice (mutant human MAPT gene). Microarray data were validated by qPCR and by comparison to human studies, including genome-wide association study (GWAS) hits. Immune gene expression correlated tightly with plaques whereas synaptic genes correlated negatively with neurofibrillary tangles. Network analysis of immune gene modules revealed six hub genes in hippocampus of amyloid mice, four in common with cortex. The hippocampal network in TAU mice was similar except that Trem2 had hub status only in amyloid mice. The cortical network of TAU mice was entirely different with more hub genes and few in common with the other networks, suggesting reasons for specificity of cortical dysfunction in FTDP17. This Resource opens up many areas for investigation. All data are available and searchable at http://www.mouseac.org

Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy

This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recordObjective: The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework to interrogate scalp EEG and determine epilepsy lateralization to aid in electrode implantation. Methods: We use eLORETA to map source activities from seizure epochs recorded from scalp EEG and consider 15 regions of interest (ROIs). Functional networks are then constructed using the phase-locking value and studied using a mathematical model. By removing different ROIs from the network and simulating their impact on the network’s ability to generate seizures in silico, the framework provides predictions of epilepsy lateralization. We consider 15 individuals from the EPILEPSIAE database and study a total of 62 seizures. Results were assessed by taking into account actual intracranial implantations and surgical outcome. Results: The framework provided potentially useful information regarding epilepsy lateralization in 12 out of the 15 individuals (p=0.02, binomial test). Conclusions: Our results show promise for the use of this framework to better interrogate scalp EEG to determine epilepsy lateralization. Significance: The framework may aid clinicians in the decision process to define where to implant electrodes for intracranial monitoring.Medical Research CouncilEpilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome TrustEngineering and Physical Sciences Research Council (EPSRC)Innovate UKEuropean Union’s Horizon 2020Alzheimer's SocietyMedical Research Counci