The Bone Morphogenetic Protein (BMP) signaling pathway is essential for normal development and tissue homeostasis. BMP signal transduction occurs when ligands interact with a complex of type 1 and type 2 receptors to activate downstream transcription factors. It is well established that a single BMP receptor may bind multiple BMP ligands with varying affinity, and this has been largely attributed to conformation at the amino acid level. However, all three type 2 BMP receptors (BMPR2, ACVR2A/B) contain consensus N-glycosylation sites in their extracellular domains (ECDs), which could play a role in modulating interaction with ligand. Here, we show a differential pattern of N-glycosylation between BMPR2 and ACVR2A/B. Site-directed mutagenesis reveals that BMPR2 is uniquely glycosylated near its ligand binding domain and at a position that is mutated in patients with Heritable Pulmonary Arterial Hypertension. We further demonstrate using a cell-free pulldown assay that N-glycosylation of the BMPR2-ECD enhances its ability to bind BMP2 ligand but has no impact on binding by the closely-related ACVR2B. Our results illuminate a novel aspect of BMP signaling pathway mechanics and demonstrate a functional difference resulting from post-translational modification of type 2 BMP receptors. Additionally, since BMPR2 is required for several aspects of normal development and defects in its function are strongly implicated in human disease, our findings are likely relevant in several biological contexts in normal and abnormal human physiology.

Visual rehabilitation with secondary iris-claw IOL implantation in aphakic eyes without capsular support seems to be an effective and safe procedure. As expected, uncomplicated cataract surgery with posterior chamber IOL implantation showed lower endothelial cell count loss. Close monitoring of the corneal endothelium is mandatory.

OBJECTIVE A major obstacle to improving bedside neurosurgical procedure safety and accuracy with image guidance technologies is the lack of a rapidly deployable, real-time registration and tracking system for a moving patient. This deficiency explains the persistence of freehand placement of external ventricular drains, which has an inherent risk of inaccurate positioning, multiple passes, tract hemorrhage, and injury to adjacent brain parenchyma. Here, the authors introduce and validate a novel image registration and real-time tracking system for frameless stereotactic neuronavigation and catheter placement in the nonimmobilized patient. METHODS Computer vision technology was used to develop an algorithm that performed near-continuous, automatic, and marker-less image registration. The program fuses a subject’s preprocedure CT scans to live 3D camera images (Snap-Surface), and patient movement is incorporated by artificial intelligence–driven recalibration (Real-Track). The surface registration error (SRE) and target registration error (TRE) were calculated for 5 cadaveric heads that underwent serial movements (fast and slow velocity roll, pitch, and yaw motions) and several test conditions, such as surgical draping with limited anatomical exposure and differential subject lighting. Six catheters were placed in each cadaveric head (30 total placements) with a simulated sterile technique. Postprocedure CT scans allowed comparison of planned and actual catheter positions for user error calculation. RESULTS Registration was successful for all 5 cadaveric specimens, with an overall mean (± standard deviation) SRE of 0.429 ± 0.108 mm for the catheter placements. Accuracy of TRE was maintained under 1.2 mm throughout specimen movements of low and high velocities of roll, pitch, and yaw, with the slowest recalibration time of 0.23 seconds. There were no statistically significant differences in SRE when the specimens were draped or fully undraped (p = 0.336). Performing registration in a bright versus a dimly lit environment had no statistically significant effect on SRE (p = 0.742 and 0.859, respectively). For the catheter placements, mean TRE was 0.862 ± 0.322 mm and mean user error (difference between target and actual catheter tip) was 1.674 ± 1.195 mm. CONCLUSIONS This computer vision–based registration system provided real-time tracking of cadaveric heads with a recalibration time of less than one-quarter of a second with submillimetric accuracy and enabled catheter placements with millimetric accuracy. Using this approach to guide bedside ventriculostomy could reduce complications, improve safety, and be extrapolated to other frameless stereotactic applications in awake, nonimmobilized patients.

INTRODUCTION:A major obstacle to improving ventriculostomy safety and accuracy with image guidance technologies is the lack of a rapidly deployable, real-time registration and tracking system for a moving patient.METHODS:Computer vision technology was used to develop an algorithm for near continuous, automatic, and marker-less image registration. The program fuses a subject’s pre-procedure CT scan to live 3D camera images (Snap-Surface), and movement is incorporated by artificial intelligence driven recalibration (Real-Track). Surface registration error (SRE) and target registration error (TRE) were calculated for five cadaver heads that underwent serial movements (fast and slow velocity roll, pitch, and yaw motions), and several test conditions. Six catheters were placed in each cadaver (30 placements). Post-procedure CT scans allowed comparison of planned and actual catheter position for user error calculation.RESULTS:Registration was successful for all five cadaveric specimens (average SRE 0.429 mm, ±0.108). Accuracy of TRE was under 1.2mm throughout specimen movements of low and high velocities of roll, pitch, and yaw movements, with the slowest recalibration time of 0.23 seconds. There were no statistically significant differences in SRE when the specimens were draped or fully undraped (p-value = 0.336). Addition of bright light or performance under dim light did not significantly affect SRE (p-value = 0.742 and 0.859, respectively). Average TRE for catheter placements was 0.862 mm (±0.322), and average user error for the was 1.674 mm (±1.195).CONCLUSION:This computer vision-based registration system provides real-time tracking of cadaveric heads with recalibration time of less than one-quarter of a second with sub-millimetric accuracy, and enabled catheter placements with millimetric accuracy. Using this approach to guide bedside ventriculostomy could reduce complications, improve safety, and could be extrapolated to other frameless stereotactic applications in awake, non-immobilized patients.