Dexamethasone potentiates in vitro blood-brain barrier recovery after primary blast injury by glucocorticoid receptor-mediated upregulation of ZO-1 tight junction protein

Owing to the frequent incidence of blast-induced traumatic brain injury (bTBI) in recent military conflicts, there is an urgent need to develop effective therapies for bTBI-related pathologies. Blood-brain barrier (BBB) breakdown has been reported to occur after primary blast exposure, making restoration of BBB function and integrity a promising therapeutic target. We tested the hypothesis that treatment with dexamethasone (DEX) after primary blast injury potentiates recovery of an in vitro BBB model consisting of mouse brain endothelial cells (bEnd.3). DEX treatment resulted in complete recovery of transendothelial electrical resistance and hydraulic conductivity 1 day after injury, compared with 3 days for vehicle-treated injured cultures. Administration of RU486 (mifepristone) inhibited effects of DEX, confirming that barrier restoration was mediated by glucocorticoid receptor signaling. Potentiated recovery with DEX treatment was accompanied by stronger zonula occludens (ZO)-1 tight junction immunostaining and expression, suggesting that increased ZO-1 expression was a structural correlate to BBB recovery after blast. Interestingly, augmented ZO-1 protein expression was associated with specific upregulation of the α⁺ isoform but not the α⁻ isoform. This is the first study to provide a mechanistic basis for potentiated functional recovery of an in vitro BBB model because of glucocorticoid treatment after primary blast injury.     

Blur adaptation: clinical and refractive considerations

The human visual system is amenable to a number of adaptive processes; one such process, or collection of processes, is the adaptation to blur. Blur adaptation can be observed as an improvement in vision under degraded conditions, and these changes occur relatively rapidly following exposure to blur. The potential important future directions of this research area and the clinical implications of blur adaptation are discussed.     

Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).