A Phase 1 Assessment of the Safety, Tolerability, Pharmacokinetics and Pharmacodynamics of (2R,6R)-Hydroxynorketamine in Healthy Volunteers.

(R,S)-Ketamine (ketamine) is a dissociative anesthetic that also possesses analgesic and antidepressant activity. Undesirable dissociative side effects and misuse potential limit expanded use of ketamine in several mental health disorders despite promising clinical activity and intensifying medical need. (2R,6R)-Hydroxynorketamine (RR-HNK) is a metabolite of ketamine that lacks anesthetic and dissociative activity but maintains antidepressant and analgesic activity in multiple preclinical models.

Impact assessment of metabolite instability in the development and validation of LC-MS/MS bioanalytical assays for measurement of rosuvastatin in human plasma and urine samples.

During bioanalytical assay development and validation, maintaining the stability of the parent drug and metabolites of interest is critical. While stability of the parent drug has been thoroughly investigated, the stability of unanalyzed metabolites is often overlooked. When an unstable metabolite is known or suspected to interfere with measurement of the parent drug or other metabolites of interest through back-conversion or other routes, additional tests with these unstable metabolites should be conducted.

Smoothness as a failure mode of Bayesian mixture models in brain-machine interfaces.

Various recursive Bayesian filters based on reach state equations (RSE) have been proposed to convert neural signals into reaching movements in brain-machine interfaces. When the target is known, RSE produce exquisitely smooth trajectories relative to the random walk prior in the basic Kalman filter. More realistically, the target is unknown, and gaze analysis or other side information is expected to provide a discrete set of potential targets.

Dynamic analysis of naive adaptive brain-machine interfaces.

The closed-loop operation of brain-machine interfaces (BMI) provides a context to discover foundational principles behind human-computer interaction, with emerging clinical applications to stroke, neuromuscular diseases, and trauma. In the canonical BMI, a user controls a prosthetic limb through neural signals that are recorded by electrodes and processed by a decoder into limb movements. In laboratory demonstrations with able-bodied test subjects, parameters of the decoder are commonly tuned using training data that include neural signals and corresponding overt arm movements.

Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry.

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random.

Liver proteome response of largemouth bass (Micropterus salmoides) exposed to several environmental contaminants: potential insights into biomarker development.

Liver proteome response of largemouth bass (Micropterus salmoides) exposed to environmental contaminants was analyzed to identify novel biomarkers of exposure. Adult male bass were exposed to cadmium chloride (CdCl(2)), atrazine, PCB 126, phenanthrene, or toxaphene via intraperitoneal injection with target body burdens of 0.00067, 3.

Proteomics-based approach to elucidate the mechanism of antitumor effect of curcumin in cervical cancer.

Cervical cancer is the second leading cause of cancer death for women in the world. A potential target for preventing and treating cervical cancer is cyclooxygenase-2 (cox-2). Curcumin is an anti-inflammatory agent that is known to have anti-cox-2 activity.