Inositol trisphosphate and ryanodine receptor signaling distinctly regulate neurite pathfinding in response to engineered micropatterned surfaces.

Micro and nanoscale patterning of surface features and biochemical cues have emerged as tools to precisely direct neurite growth into close proximity with next generation neural prosthesis electrodes. Biophysical cues can exert greater influence on neurite pathfinding compared to the more well studied biochemical cues; yet the signaling events underlying the ability of growth cones to respond to these microfeatures remain obscure. Intracellular Ca2+ signaling plays a critical role in how a growth cone senses and grows in response to various cues (biophysical features, repulsive peptides, chemo-attractive gradients).

The geometry of photopolymerized topography influences neurite pathfinding by directing growth cone morphology and migration.

. Cochlear implants provide auditory perception to those with severe to profound sensorineural hearing loss: however, the quality of sound perceived by users does not approximate natural hearing. This limitation is due in part to the large physical gap between the stimulating electrodes and their target neurons.

The geometry of photopolymerized topography influences neurite pathfinding by directing growth cone morphology and migration.

Cochlear implants (CIs) provide auditory perception to those with profound sensorineural hearing loss: however, the quality of sound perceived by a CI user does not approximate natural hearing. This limitation is due in part to the large physical gap between the stimulating electrodes and their target neurons. Therefore, directing the controlled outgrowth of processes from spiral ganglion neurons (SGNs) into close proximity to the electrode array could provide significantly increased hearing function.

Sensitivity of CNN image analysis to multifaceted measurements of neurite growth.

Quantitative analysis of neurite growth and morphology is essential for understanding the determinants of neural development and regeneration, however, it is complicated by the labor-intensive process of measuring diverse parameters of neurite outgrowth. Consequently, automated approaches have been developed to study neurite morphology in a high-throughput and comprehensive manner. These approaches include computer-automated algorithms known as 'convolutional neural networks' (CNNs)-powerful models capable of learning complex tasks without the biases of hand-crafted models.

Uterine Dehiscence and Subsequent Pregnancy Management: A Review of the Literature.

Importance: Uterine dehiscence is a separation of the uterine musculature with intact uterine serosa. Uterine dehiscence can be encountered at the time of cesarean delivery, be suspected on obstetric ultrasound, or be diagnosed in between pregnancies. Management is a conundrum for obstetricians, regardless of timing of onset.