Many studies have examined brain states in an effort to predict individual differences in the capacity for learning, with overall moderate results. The present study investigated how measures of cortical network function acquired at rest using dense-array EEG (256 leads) predict subsequent acquisition of a new motor skill. Brain activity was recorded in 17 healthy young subjects during 3min of wakeful rest prior to a single motor skill training session on a digital version of the pursuit rotor task. Practice was associated with significant gains in task performance (% time on target increased from 24% to 41%, p<0.0001). Using a partial least squares regression (PLS) model, coherence with the region of the left primary motor area (M1) in resting EEG data was a strong predictor of motor skill acquisition (R(2)=0.81 in a leave-one-out cross-validation analysis), exceeding the information provided by baseline behavior and demographics. Within this PLS model, greater skill acquisition was predicted by higher connectivity between M1 and left parietal cortex, possibly reflecting greater capacity for visuomotor integration, and by lower connectivity between M1 and left frontal-premotor areas, possibly reflecting differences in motor planning strategies. EEG coherence, which reflects functional connectivity, predicts individual motor skill acquisition with a level of accuracy that is remarkably high compared to prior reports using EEG or fMRI measures.

The tumor suppressor BRCA1-BARD1 complex regulates many cellular processes; of critical importance to its tumor suppressor function is its role in genome integrity. Although RING E3 ubiquitin ligase activity is the only known enzymatic activity of the complex, the in vivo requirement for BRCA1-BARD1 E3 ubiquitin ligase activity has been controversial. Here we probe the role of BRCA1-BARD1 E3 ubiquitin ligase activity in vivo using C. elegans. Genetic, cell biological, and biochemical analyses of mutants defective for E3 ligase activity suggest there is both E3 ligase-dependent and independent functions of the complex in the context of DNA damage repair and meiosis. We show that E3 ligase activity is important for nuclear accumulation of the complex and specifically to concentrate at meiotic recombination sites but not at DNA damage sites in proliferating germ cells. While BRCA1 alone is capable of monoubiquitylation, BARD1 is required with BRCA1 to promote polyubiquitylation. We find that the requirement for E3 ligase activity and BARD1 in DNA damage signaling and repair can be partially alleviated by driving the nuclear accumulation and self-association of BRCA1. Our data suggest that in addition to E3 ligase activity, BRCA1 may serve a structural role for DNA damage signaling and repair while BARD1 plays an accessory role to enhance BRCA1 function.

Biological sex affects numerous aspects of biology, yet how sex influences different biological processes have not been extensively studied at the molecular level. Caenorhabditis elegans, with both hermaphrodites (functionally females as adults) and males, is an excellent system to uncover how sex influences physiology. Here, we describe a method to isolate large quantities of C. elegans males by conditionally degrading DPY-27, a component of the dosage compensation complex essential for hermaphrodite, but not male, development. We show that germ cells from males isolated following DPY-27 degradation undergo meiosis and spermiogenesis like wild type and these males are competent to mate and sire viable offspring. We further demonstrate the efficacy of this system by analyzing gene expression and performing affinity pull-downs from male worm extracts.

BACKGROUND: Early diagnosis of stroke optimizes reperfusion therapies, but behavioral measures have incomplete accuracy. Electroencephalogram (EEG) has high sensitivity for immediately detecting brain ischemia. This pilot study aimed to evaluate feasibility and utility of EEG for identifying patients with a large acute ischemic stroke during Emergency Department (ED) evaluation, as these data might be useful in the prehospital setting. METHODS: A 3-minute resting EEG was recorded using a dense-array (256-lead) system in patients with suspected acute stroke arriving at the ED of a US Comprehensive Stroke Center. RESULTS: An EEG was recorded in 24 subjects, 14 with acute cerebral ischemia (including 5 with large acute ischemic stroke) and 10 without acute cerebral ischemia. Median time from stroke onset to EEG was 6.6 hours; and from ED arrival to EEG, 1.9 hours. Delta band power (P = .004) and the alpha/delta frequency band ratio (P = .0006) each significantly distinguished patients with large acute ischemic stroke (n = 5) from all other patients with suspected stroke (n = 19), with the best diagnostic utility coming from contralesional hemisphere signals. Larger infarct volume correlated with higher EEG power in the alpha/delta frequency band ratio within both the ipsilesional (r = -0.64, P = .013) and the contralesional (r = -0.78, P = .001) hemispheres. CONCLUSIONS: Within hours of stroke onset, EEG measures (1) identify patients with large acute ischemic stroke and (2) correlate with infarct volume. These results suggest that EEG measures of brain function may be useful to improve diagnosis of large acute ischemic stroke in the ED, findings that might be useful to pre-hospital applications.

Background

Early diagnosis of stroke optimizes reperfusion therapies, but behavioral measures have incomplete accuracy. Electroencephalogram (EEG) has high sensitivity for immediately detecting brain ischemia. This pilot study aimed to evaluate feasibility and utility of EEG for identifying patients with a large acute ischemic stroke during Emergency Department (ED) evaluation, as these data might be useful in the prehospital setting.

Methods

A 3-minute resting EEG was recorded using a dense-array (256-lead) system in patients with suspected acute stroke arriving at the ED of a US Comprehensive Stroke Center.

Results

An EEG was recorded in 24 subjects, 14 with acute cerebral ischemia (including 5 with large acute ischemic stroke) and 10 without acute cerebral ischemia. Median time from stroke onset to EEG was 6.6 hours; and from ED arrival to EEG, 1.9 hours. Delta band power (P = .004) and the alpha/delta frequency band ratio (P = .0006) each significantly distinguished patients with large acute ischemic stroke (n = 5) from all other patients with suspected stroke (n = 19), with the best diagnostic utility coming from contralesional hemisphere signals. Larger infarct volume correlated with higher EEG power in the alpha/delta frequency band ratio within both the ipsilesional (r = -0.64, P = .013) and the contralesional (r = -0.78, P = .001) hemispheres.

Conclusions

Within hours of stroke onset, EEG measures (1) identify patients with large acute ischemic stroke and (2) correlate with infarct volume. These results suggest that EEG measures of brain function may be useful to improve diagnosis of large acute ischemic stroke in the ED, findings that might be useful to pre-hospital applications.