ABSTRACT
Biomaterials are implanted in millions of individuals worldwide each year. Both naturally derived and synthetic biomaterials induce a foreign body reaction that often culminates in fibrotic encapsulation and reduced functional lifespan. In ophthalmology, glaucoma drainage implants (GDIs) are implanted in the eye to reduce intraocular pressure (IOP) in order to prevent glaucoma progression and vision loss. Despite recent efforts towards miniaturization and surface chemistry modification, clinically available GDIs are susceptible to high rates of fibrosis and surgical failure. Here, we describe the development of synthetic, nanofiber-based GDIs with partially degradable inner cores. We evaluated GDIs with nanofiber or smooth surfaces to investigate the effect of surface topography on implant performance. We observed in vitro that nanofiber surfaces supported fibroblast integration and quiescence, even in the presence of pro-fibrotic signals, compared to smooth surfaces. In rabbit eyes, GDIs with a nanofiber architecture were biocompatible, prevented hypotony, and provided a volumetric aqueous outflow comparable to commercially available GDIs, though with significantly reduced fibrotic encapsulation and expression of key fibrotic markers in the surrounding tissue. We propose that the physical cues provided by the surface of the nanofiber-based GDIs mimic healthy extracellular matrix structure, mitigating fibroblast activation and potentially extending functional GDI lifespan.
ABSTRACT
Purpose: Trunk stability, an important prerequisite for many activities of daily living, can be impaired in children with movement disorders. Current treatment options can be costly and fail to fully engage young participants. We developed an affordable, smart screen-based intervention and tested if it engages young children in physical therapy goal driven exercises. Methods: Here we describe the ADAPT system, Aiding Distanced and Accessible Physical Therapy, which is a large touch-interactive device with customizable games. One such game, "Bubble Popper," encourages high repetitions of weight shifts, reaching, and balance training as the participant pops bubbles in sitting, kneeling, or standing positions. Results: Sixteen participants aged 2-18 years were tested during physical therapy sessions. The number of screen touches and length of game play indicate high participant engagement. In trials lasting less than 3 min, on average, older participants (12-18 years) made 159 screen touches per trial while the younger participants (2-7 years) made 97. In a 30-min session, on average, older participants actively played the game for 12.49 min while younger participants played for 11.22 min. Conclusion: The ADAPT system is a feasible means to engage young participants in reaching and balance training during physical therapy.
ABSTRACT
Traumatic brain injury (TBI) is a leading neurological cause of death and disability across the world. Early characterization of TBI severity could provide a window for therapeutic intervention and contribute to improved outcome. We hypothesized that granular electronic health record data available in the first 24 h following admission to the intensive care unit (ICU) can be used to differentiate outcomes at discharge. Working from two ICU datasets we focused on patients with a primary admission diagnosis of TBI whose length of stay in ICU was ≥ 24 h (N = 1689 and 127). Features derived from clinical, laboratory, medication, and physiological time series data in the first 24 h after ICU admission were used to train elastic-net regularized Generalized Linear Models for the prediction of mortality and neurological function at ICU discharge. Model discrimination, determined by area under the receiver operating characteristic curve (AUC) analysis, was 0.903 and 0.874 for mortality and neurological function, respectively. Model performance was successfully validated in an external dataset (AUC 0.958 and 0.878 for mortality and neurological function, respectively). These results demonstrate that computational analysis of data routinely collected in the first 24 h after admission accurately and reliably predict discharge outcomes in ICU stratum TBI patients.
