Popular bioadhesives, such as fibrin, cyanoacrylate, and albumin-glutaraldehyde based materials, have been applied for clinical applications in wound healing, drug delivery, and bone and soft tissue engineering; however, their performances are limited by weak adhesion strength and rapid degradation. In this study a mussel-inspired, nanocomposite-based, biodegradable tissue adhesive is developed by blending poly(lactic-co-glycolic acid) (PLGA) or N-hydroxysuccinimide modified PLGA nanoparticles (PLGA-NHS) with mussel-inspired alginate-dopamine polymer (Alg-Dopa). Adhesive strength measurement of the nanocomposites on porcine skin-muscle constructs reveals that the incorporation of nanoparticles in Alg-Dopa significantly enhances the tissue adhesive strength compared to the mussel-inspired adhesive alone. The nanocomposite formed by PLGA-NHS nanoparticles shows higher lap shear strength of 33 ± 3 kPa, compared to that of Alg-Dopa hydrogel alone (14 ± 2 kPa). In addition, these nanocomposites are degradable and cytocompatible in vitro, and elicit in vivo minimal inflammatory responses in a rat model, suggesting clinical potential of these nanocomposites as bioadhesives.
Background: Pediatric hydrocephalus is a devastating and costly disease. The mainstay of treatment is still surgical shunting of cerebrospinal fluid (CSF). These shunts fail at a high rate and impose a significant burden on patients, their families and society. The relationship between clinical decision making and shunt failure is poorly understood and multifaceted, but catheter occlusion remains the most frequent cause of shunt complications. In order to investigate factors that affect shunt failure, we have established the Wayne State University (WSU) shunt biobank. Methods: To date, four hospital centers have contributed various components of failed shunts and CSF from patients diagnosed with hydrocephalus before adulthood. The hardware samples are transported in paraformaldehyde and transferred to phosphate-buffered saline with sodium azide upon deposit into the biobank. Once in the bank, they are then available for study. Informed consent is obtained by the local center before corresponding clinical data are entered into a REDCap database. Data such as hydrocephalus etiology and details of shunt revision history. All data are entered under a coded identifier. Results: 293 shunt samples were collected from 228 pediatric patients starting from May 2015 to September 2019. We saw a significant difference in the number of revisions per patient between centers (Kruskal-Wallis H test, p value < 0.001). The leading etiology at all centers was post-hemorrhagic hydrocephalus, a fisher's exact test showed there to be statistically significant differences in etiology between center (p = 0.01). Regression showed age (p < 0.01), race (p = 0.038) and hospital-center (p < 0.001) to explain significant variance in the number of revisions. Our model accounted for 31.9% of the variance in revisions. Generalized linear modeling showed hydrocephalus etiology (p < 0.001), age (p < 0.001), weight and physician (p < 0.001) to impact the number of ventricular obstructions. Conclusion: The retrospective analysis identified that differences exist between currently enrolled centers, although further work is needed before clinically actionable recommendations can be made. Moreover, the variables collected from this chart review explain a meaningful amount of variance in the number of revision surgeries. Future work will expand on the contribution of different site-specific and patient-specific factors to identify potential cause and effect relationships.
The neurological ICU (neuro ICU) often suffers from significant limitations due to scarce resource availability for their neurocritical care patients. Neuro ICU patients require frequent neurological evaluations, continuous monitoring of various physiological parameters, frequent imaging, and routine lab testing. This amasses large amounts of data specific to each patient. Neuro ICU teams are often overburdened by the resulting complexity of data for each patient. Machine Learning algorithms (ML), are uniquely capable of interpreting high-dimensional datasets that are too difficult for humans to comprehend. Therefore, the application of ML in the neuro ICU could alleviate the burden of analyzing big datasets for each patient. This review serves to (1) briefly summarize ML and compare the different types of MLs, (2) review recent ML applications to improve neuro ICU management and (3) describe the future implications of ML to neuro ICU management.
Background Implantation of ventricular catheters (VCs) to drain cerebrospinal fluid (CSF) is a standard approach to treat hydrocephalus. VCs fail frequently due to tissue obstructing the lumen via the drainage holes. Mechanisms driving obstruction are poorly understood. This study aimed to characterize the histological features of VC obstructions and identify links to clinical factors. Methods 343 VCs with relevant clinical data were collected from five centers. Each hole on the VCs was classified by degree of tissue obstruction after macroscopic analysis. A subgroup of 54 samples was analyzed using immunofluorescent labelling, histology and immunohistochemistry. Results 61.5% of the 343 VCs analyzed had tissue aggregates occluding at least one hole (n = 211) however the vast majority of the holes (70%) showed no tissue aggregates. Mean age at which patients with occluded VCs had their first surgeries (3.25 yrs) was lower than in patients with non-occluded VCs (5.29 yrs, p < 0.02). Mean length of time of implantation of occluded VCs, 33.22 months was greater than for non-occluded VCs, 23.8 months (p = 0.02). Patients with myelomeningocele had a greater probability of having an occluded VC (p = 0.0426). VCs with occlusions had greater numbers of macrophages and astrocytes in comparison to non-occluded VCs (p < 0.01). Microglia comprised only 2–6% of the VC-obstructing tissue aggregates. Histologic analysis showed choroid plexus occlusion in 24%, vascularized glial tissue occlusion in 24%, prevalent lymphocytic inflammation in 29%, and foreign body giant cell reactions in 5% and no ependyma. Conclusion Our data show that age of the first surgery and length of time a VC is implanted are factors that influence the degree of VC obstruction. The tissue aggregates obstructing VCs are composed predominantly of astrocytes and macrophages; microglia have a relatively small presence.
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