Cortical beta oscillations map to shared brain networks modulated by dopamine.

Brain rhythms can facilitate neural communication for the maintenance of brain function. Beta rhythms (13-35 Hz) have been proposed to serve multiple domains of human ability, including motor control, cognition, memory, and emotion, but the overarching organisational principles remain unknown. To uncover the circuit architecture of beta oscillations, we leverage normative brain data, analysing over 30 hr of invasive brain signals from 1772 channels from cortical areas in epilepsy patients, to demonstrate that beta is the most distributed cortical brain rhythm.

Dopamine and deep brain stimulation accelerate the neural dynamics of volitional action in Parkinson's disease.

The ability to initiate volitional action is fundamental to human behaviour. Loss of dopaminergic neurons in Parkinson's disease is associated with impaired action initiation, also termed akinesia. Both dopamine and subthalamic deep brain stimulation (DBS) can alleviate akinesia, but the underlying mechanisms are unknown.

Single threshold adaptive deep brain stimulation in Parkinson's disease depends on parameter selection, movement state and controllability of subthalamic beta activity.

Background: Deep brain stimulation (DBS) is an invasive treatment option for patients with Parkinson's disease. Recently, adaptive DBS (aDBS) systems have been developed, which adjust stimulation timing and amplitude in real-time. However, it is unknown how changes in parameters, movement states and the controllability of subthalamic beta activity affect aDBS performance.

Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants.

Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for identifying and advancing novel clinical BCI approaches does not exist. Here, we developed a platform that integrates brain signal decoding with connectomics and demonstrate its utility across 123 hours of invasively recorded brain data from 73 neurosurgical patients treated for movement disorders, depression and epilepsy.

A practical guide to invasive neurophysiology in patients with deep brain stimulation.

Deep brain stimulation (DBS) offers the unique opportunity to record human neural population activity as multiunit activity and local field potentials (LFP) directly from the target area in the depth of the brain. This has led to important discoveries through characterization of pathological activity patterns and identification of motor and cognitive correlates of basal ganglia function in patients with movement disorders. These findings have been covered extensively in a large body of literature, but the technical aspects of microelectrode and LFP recordings in DBS patients are rarely reported.

Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation.

Sensing enabled implantable devices and next-generation neurotechnology allow real-time adjustments of invasive neuromodulation. The identification of symptom and disease-specific biomarkers in invasive brain signal recordings has inspired the idea of demand dependent adaptive deep brain stimulation (aDBS). Expanding the clinical utility of aDBS with machine learning may hold the potential for the next breakthrough in the therapeutic success of clinical brain computer interfaces.

Treatment resistance analysis reveals GLUT-1-mediated glucose uptake as a major target of synthetic rocaglates in cancer cells.

Rocaglates are natural compounds that have been extensively studied for their ability to inhibit translation initiation. Rocaglates represent promising drug candidates for tumor treatment due to their growth-inhibitory effects on neoplastic cells. In contrast to natural rocaglates, synthetic analogues of rocaglates have been less comprehensively characterized, but were also shown to have similar effects on the process of protein translation.

Natural Autoimmunity to the Thyroid Hormone Monocarboxylate Transporters MCT8 and MCT10.

The monocarboxylate transporters 8 (MCT8) and 10 (MCT10) are important for thyroid hormone (TH) uptake and signaling. Reduced TH activity is associated with impaired development, weight gain and discomfort. We hypothesized that autoantibodies (aAb) to MCT8 or MCT10 are prevalent in thyroid disease and obesity.

Reduction in false-positive Aspergillus serum galactomannan enzyme immunoassay results associated with use of piperacillin-tazobactam in the United States.

Piperacillin-tazobactam (PTZ) is known to cause false-positive results in the Platelia Aspergillus enzyme-linked immunoassay (EIA), due to contamination with galactomannan (GM). We tested 32 lots of PTZ and 27 serum specimens from patients receiving PTZ. GM was not detected in the lots of PTZ; one serum specimen (3.