Utility of FRET in studies of membrane protein oligomerization: The concept of the effective dissociation constant.

The activity of many membrane receptors is controlled through their lateral association into dimers or higher-order oligomers. Although Förster resonance energy transfer (FRET) measurements have been used extensively to characterize the stability of receptor dimers, the utility of FRET in studies of larger oligomers has been limited. Here we introduce an effective equilibrium dissociation constant that can be extracted from FRET measurements for EphA2, a receptor tyrosine kinase (RTK) known to form active oligomers of heterogeneous distributions in response to its ligand ephrinA1-Fc. The newly introduced effective equilibrium dissociation constant has a well-defined physical meaning and biological significance. It denotes the receptor concentration for which half of the receptors are monomeric and inactive, and the other half are associated into oligomers and are active, irrespective of the exact oligomer size. This work introduces a new dimension to the utility of FRET in studies of membrane receptor association and signaling in the plasma membrane.

The efficacy of receptor tyrosine kinase EphA2 autophosphorylation increases with EphA2 oligomer size.

The receptor tyrosine kinase (RTK) EphA2 is expressed in epithelial and endothelial cells and controls the assembly of cell-cell junctions. EphA2 has also been implicated in many diseases, including cancer. Unlike most RTKs, which signal predominantly as dimers, EphA2 readily forms high-order oligomers upon ligand binding. Here, we investigated if a correlation exists between EphA2 signaling properties and the size of the EphA2 oligomers induced by multiple ligands, including the widely used ephrinA1-Fc ligand, the soluble monomeric m-ephrinA1, and novel engineered peptide ligands. We used fluorescence intensity fluctuation (FIF) spectrometry to characterize the EphA2 oligomer populations induced by the different ligands. Interestingly, we found that different monomeric and dimeric ligands induce EphA2 oligomers with widely different size distributions. Our comparison of FIF brightness distribution parameters and EphA2 signaling parameters reveals that the efficacy of EphA2 phosphorylation on tyrosine 588, an autophosphorylation response contributing to EphA2 activation, correlates with EphA2 mean oligomer size. However, we found that other characteristics, such as the efficacy of AKT inhibition and ligand bias coefficients, appear to be independent of EphA2 oligomer size. Taken together, this work highlights the utility of FIF in RTK signaling research and demonstrates a quantitative correlation between the architecture of EphA2 signaling complexes and signaling features.

Vidian Canal as a Transcranial Landmark: Anatomy, Technique, and Illustrative Cases.

Objective The vidian nerve can be accessed in transcranial approaches in carefully selected patients to ensure its preservation and to serve as a landmark for sphenoid sinus entry. This report is to review a technique, evaluate it in laboratory settings, and present two illustrative cases. Design The study involves cadaveric dissection and illustrative cases. Setting The study conducted in a cadaveric dissection laboratory. Participants The object of the study is one cadaveric head and two illustrative clinical cases. Main Outcome Measures Two cases using this approach were illustrated, and a cadaver dissection was performed in a step-by-step fashion. Results: The vidian canal can be accessed by drilling the anterolateral triangle. Two illustrated cases were presented; in one, the vidian nerve was used as part of a corridor to access the sphenoid sinus for tumor delivery, and in the other, the technique was used to find and preserve the vidian nerve during transcranial resection. Conclusion Careful identification of the vidian canal in transcranial surgery is a beneficial technique in carefully selected cases which allows identification of the nerve both for its preservation in selected cases and to create the vidian-maxillary corridor for tumor resection. Knowing the anatomy and pneumatization variants is important in the surgical approach.

Utility of machine learning algorithms in degenerative cervical and lumbar spine disease: a systematic review.

Machine learning is a rapidly evolving field that offers physicians an innovative and comprehensive mechanism to examine various aspects of patient data. Cervical and lumbar degenerative spine disorders are commonly age-related disease processes that can utilize machine learning to improve patient outcomes with careful patient selection and intervention. The aim of this study is to examine the current applications of machine learning in cervical and lumbar degenerative spine disease. A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A search of PubMed, Embase, Medline, and Cochrane was conducted through May 31st, 2020, using the following terms: "artificial intelligence" OR "machine learning" AND "neurosurgery" AND "spine." Studies were included if original research on machine learning was utilized in patient care for degenerative spine disease, including radiographic machine learning applications. Studies focusing on robotic applications in neurosurgery, navigation, or stereotactic radiosurgery were excluded. The literature search identified 296 papers, with 35 articles meeting inclusion criteria. There were nine studies involving cervical degenerative spine disease and 26 studies on lumbar degenerative spine disease. The majority of studies for both cervical and lumbar spines utilized machine learning for the prediction of postoperative outcomes, with 5 (55.6%) and 15 (61.5%) studies, respectively. Machine learning applications focusing on degenerative lumbar spine greatly outnumber the current volume of cervical spine studies. The current research in lumbar spine also demonstrates more advanced clinical applications of radiographic, diagnostic, and predictive machine learning models.

Robotics in spine surgery: A systematic review.

Robotic systems to assist with pedicle screw placement have recently emerged in the field of spine surgery. Here, the authors systematically reviewed the literature for evidence of these robotic systems and their utility. Thirty-four studies that reported the use of spinal instrumentation with robotic assistance and met inclusion criteria were identified. The outcome measures gathered included: pedicle screw accuracy, indications for surgery, rates of conversion to an alternative surgical method, radiation exposure, and learning curve. In our search there were five different robotic systems identified. All studies reported accuracy and the most commonly used accuracy grading scale was the Gertzbein Robbins scale (GRS). Accuracy of clinically acceptable pedicle screws, defined as < 2 mm cortical breech, ranged from 80% to 100%. Many studies categorized indications for robotic surgery with the most common being degenerative entities. Some studies reported rates of conversion from robotic assistance to manual instrumentation due to many reasons, with robotic failure as the most common. Radiation exposure data revealed a majority of studies reported less radiation using robotic systems. Studies looking at a learning curve effect with surgeon use of robotic assistance were not consistent across the literature. Robotic systems for assistance in spine surgery have continued to improve and the accuracy of pedicle screw placement remains superior when compared to free-hand technique, however rates of manual conversion are significant. Currently, these systems are successfully employed in various pathological entities where trained spine surgeons can be safe and accurate regardless of robotic training.