Factors Dictating Carbene Formation at (PNP)Ir

The mechanistic subtleties involved with the interaction of an amido/bis(phosphine)-supported (PNP)Ir fragment with a series of linear and cyclic ethers have been investigated using density functional theory. Our analysis has revealed the factors dictating reaction direction toward either an iridium-supported carbene or a vinyl ether adduct. The (PNP)Ir structure will allow carbene formation only from accessible carbons α to the ethereal oxygen, such that d electron back-donation from the metal to the carbene ligand is possible. Should these conditions be unavailable, the main competing pathway to form vinyl ether can occur, but only if the (PNP)Ir framework does not sterically interfere with the reacting ether. In situations where steric hindrance prevents unimpeded access to both pathways, the reaction may progress to the initial C−H activation but no further. Our mechanistic analysis is density functional independent and whenever possible confirmed experimentally by trapping intermediate species experimentally. We have also highlighted an interesting systematic error present in the DFT analysis of reactions where steric environment alters considerably within a reaction

Apathy, but not depression, is associated with executive dysfunction in cerebral small vessel disease.

OBJECTIVE: To determine the prevalence of apathy and depression in cerebral small vessel disease (SVD), and the relationships between both apathy and depression with cognition. To examine whether apathy is specifically related to impairment in executive functioning and processing speed. METHODS: 196 patients with a clinical lacunar stroke and an anatomically corresponding lacunar infarct on MRI were compared to 300 stroke-free controls. Apathy and depression were measured using the Geriatric Depression Scale, and cognitive functioning was assessed using an SVD cognitive screening tool, the Brief Memory and Executive Test, which measures executive functioning/processing speed and memory/orientation. Path analysis and binary logistic regression were used to assess the relation between apathy, depression and cognitive impairment. RESULTS: 31 participants with SVD (15.8%) met criteria for apathy only, 23 (11.8%) for both apathy and depression, and 2 (1.0%) for depression only. In the SVD group the presence of apathy was related to global cognition, and specifically to impaired executive functioning/processing speed, but not memory/orientation. The presence of depression was not related to global cognition, impaired executive functioning/processing speed or memory/orientation. CONCLUSIONS: Apathy is a common feature of SVD and is associated with impaired executive functioning/processing speed suggesting the two may share biological mechanisms. Screening for apathy should be considered in SVD, and further work is required to develop and evaluate effective apathy treatment or management in SVD.This work was supported by a Priority Program Grant from the Stroke Association (TSA PPA 2015-02; www.stroke.org.uk). The BMET Study was supported by a grant from the Stroke Association (TSA2008/10). Valerie Lohner is supported by a Stroke Association/British Heart Foundation Program Grant (TSA BHF 2010/01; www.bhf.org.uk). Rebecca Brookes is supported by a BHF Project Grant (PG/13/30/30005). Recruitment to the BMET Study was supported by the English National Institute of Health Research (NIHR) Clinical Stroke Research Network (www.crn.nihr.ac.uk/stroke). Hugh Markus is supported by an NIHR Senior Investigator award (www.nihr.ac.uk) and his work is supported by the Cambridge University Hospital Comprehensive NIHR Biomedical Research Unit (www.cambridge-brc.org.uk)

Brief Screening of Vascular Cognitive Impairment in Patients With Cerebral Autosomal-Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy Without Dementia.

BACKGROUND AND PURPOSE: Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a monogenic form of cerebral small vessel disease leading to early-onset stroke and dementia, with younger patients frequently showing subclinical deficits in cognition. At present, there are no targeted cognitive screening measures for this population. However, the Brief Memory and Executive Test (BMET) and the Montreal Cognitive Assessment (MoCA) have shown utility in detecting cognitive impairment in sporadic small vessel disease. This study assesses the BMET and the MoCA as clinical tools for detecting mild cognitive deficits in CADASIL. METHODS: Sixty-six prospectively recruited patients with CADASIL, and 66 matched controls completed the BMET, with a subset of these also completing the MoCA. Receiver operating characteristic curves were calculated to examine the sensitivity and specificity of clinical cutoffs for the detection of vascular cognitive impairment and reduced activities of daily living. RESULTS: Patients with CADASIL showed more cognitive impairment overall and were poorer on both executive/processing and memory indices of the BMET relative to controls. The BMET showed good accuracy in predicting vascular cognitive impairment (85% sensitivity and 84% specificity) and impaired instrumental activities of daily living (92% sensitivity and 77% specificity). The MoCA also showed good predictive validity for vascular cognitive impairment (80% sensitivity and 78% specificity) and instrumental activities of daily living (75% sensitivity and 76% specificity). The most important background predictor of vascular cognitive impairment was a history of stroke. CONCLUSIONS: The results indicate that the BMET and the MoCA are clinically useful and sensitive screening measures for early cognitive impairment in patients with CADASIL.Stroke Association (Grant ID: TSA2008/10), British Heart Foundation (Grant ID: PG/13/30/30005), Stroke Association/British Heart Foundation (Grant ID: TSA BHF 2010/01), Agency for Science, Technology and Research, Singapore, National Institute for Health Research (Senior Investigator award), Cambridge University Hospital Comprehensive National Institute for Health Research Biomedical Research UnitThis is the final version of the article. It first appeared from Wolters Kluwer via http://dx.doi.org/10.1161/STROKEAHA.116.01376

The effect of physical fatigue on oscillatory dynamics of the sensorimotor cortex

AIM: While physical fatigue is known to arise in part from supraspinal mechanisms within the brain exactly how brain activity is modulated during fatigue is not well understood. Therefore, this study examined how typical neural oscillatory responses to voluntary muscle contractions were affected by fatigue. METHODS: Eleven healthy adults (age 27±4 years) completed two experimental sessions in a randomised crossover design. Both sessions first assessed baseline maximal voluntary isometric wrist-flexion force (MVFb ). Participants then performed an identical series of fourteen test contractions (2 × 100%MVFb , 10 × 40%MVFb , 2 × 100%MVFb ) both before and after one of two interventions: forty 12-s contractions at 55%MVFb (fatigue intervention) or 5%MVFb (control intervention). Magnetoencephalography (MEG) was used to characterise both the movement-related mu and beta decrease (MRMD and MRBD) and the post-movement beta rebound (PMBR) within the contralateral sensorimotor cortex during the 40%MVFb test contractions, while the 100%MVFb test contractions were used to monitor physical fatigue. RESULTS: The fatigue intervention induced a substantial physical fatigue that endured throughout the post-intervention measurements (28.9-29.5% decrease in MVF, P<0.001). Fatigue had a significant effect on both PMBR (ANOVA, session × time-point interaction: P=0.018) and MRBD (P=0.021): the magnitude of PMBR increased following the fatigue but not the control interventions, whereas MRBD was decreased post-control but not post-fatigue. Mu oscillations were unchanged throughout both sessions. CONCLUSION: Physical fatigue resulted in an increased PMBR, and offset attenuations in MRBD associated with task habituation. This article is protected by copyright. All rights reserved

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures

An Iterative Implementation of the Signal Space Separation Method for Magnetoencephalography Systems with Low Channel Counts

The signal space separation (SSS) method is routinely employed in the analysis of multichannel magnetic field recordings (such as magnetoencephalography (MEG) data). In the SSS method, signal vectors are posed as a multipole expansion of the magnetic field, allowing contributions from sources internal and external to a sensor array to be separated via computation of the pseudo-inverse of a matrix of the basis vectors. Although powerful, the standard implementation of the SSS method on MEG systems based on optically pumped magnetometers (OPMs) is unstable due to the approximate parity of the required number of dimensions of the SSS basis and the number of channels in the data. Here we exploit the hierarchical nature of the multipole expansion to perform a stable, iterative implementation of the SSS method. We describe the method and investigate its performance via a simulation study on a 192-channel OPM-MEG helmet. We assess performance for different levels of truncation of the SSS basis and a varying number of iterations. Results show that the iterative method provides stable performance, with a clear separation of internal and external sources

How do spatially distinct frequency specific MEG networks emerge from one underlying structural connectome? The role of the structural eigenmodes

Functional networks obtained from magnetoencephalography (MEG) from different frequency bands show distinct spatial patterns. It remains to be elucidated how distinct spatial patterns in MEG networks emerge given a single underlying structural network. Recent work has suggested that the eigenmodes of the structural network might serve as a basis set for functional network patterns in the case of functional MRI. Here, we take this notion further in the context of frequency band specific MEG networks. We show that a selected set of eigenmodes of the structural network can predict different frequency band specific networks in the resting state, ranging from delta (1–4 Hz) to the high gamma band (40–70 Hz). These predictions outperform predictions based from surrogate data, suggesting a genuine relationship between eigenmodes of the structural network and frequency specific MEG networks. We then show that the relevant set of eigenmodes can be excited in a network of neural mass models using linear stability analysis only by including delays. Excitation of an eigenmode in this context refers to a dynamic instability of a network steady state to a spatial pattern with a corresponding coherent temporal oscillation. Simulations verify the results from linear stability analysis and suggest that theta, alpha and beta band networks emerge very near to the bifurcation. The delta and gamma bands in the resting state emerges further away from the bifurcation. These results show for the first time how delayed interactions can excite the relevant set of eigenmodes that give rise to frequency specific functional connectivity patterns

Optimising experimental design for MEG resting state functional connectivity measurement

The study of functional connectivity using magnetoencephalography (MEG) is an expanding area of neuroimaging, and adds an extra dimension to the more common assessments made using fMRI. The importance of such metrics is growing, with recent demonstrations of their utility in clinical research, however previous reports suggest that whilst group level resting state connectivity is robust, single session recordings lack repeatability. Such robustness is critical if MEG measures in individual subjects are to prove clinically valuable. In the present paper, we test how practical aspects of experimental design affect the intra-subject repeatability of MEG findings; specifically we assess the effect of co-registration method and data recording duration. We show that the use of a foam head-cast, which is known to improve co-registration accuracy, increased significantly the between session repeatability of both beamformer reconstruction and connectivity estimation. We also show that recording duration is a critical parameter, with large improvements in repeatability apparent when using ten minute, compared to five minute recordings. Further analyses suggest that the origin of this latter effect is not underpinned by technical aspects of source reconstruction, but rather by a genuine effect of brain state; short recordings are simply inefficient at capturing the canonical MEG network in a single subject. Our results provide important insights on experimental design and will prove valuable for future MEG connectivity studies