Outcomes after neoadjuvant or adjuvant chemotherapy for cT2-4N0-1 non–small cell lung cancer: A propensity-matched analysis

Objective

Comparative survival between neoadjuvant chemotherapy and adjuvant chemotherapy for patients with cT2-4N0-1M0 non–small cell lung cancer has not been extensively studied.

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.     

Marr and Reductionism

David Marr's three-level method for completely understanding a cognitive system and the importance he attaches to the computational level are so familiar as to scarcely need repeating. Fewer seem to recognize that Marr defends his famous method by criticizing the “reductionistic approach.” This sets up a more interesting relationship between Marr and reductionism than is usually acknowledged. I argue that Marr was correct in his criticism of the reductionists of his time—they were only describing (cellular activity), not explaining (cognitive functions). But a careful metascientific account of reductionistic neuroscience over the past two decades reveals that Marr's criticisms no longer have force. Contemporary neuroscience now explains cognition directly, although in a fashion—causal-mechanistically—quite different than Marr recommended. So while Marr was correct to reject the reductionism of his day and offer an alternative method for genuinely explaining cognition, contemporary cognitive scientists now owe us a new defense of Marr's famous method and the advantages of its explanations over the type now pursued successfully in current reductionist neuroscience. There are familiar reasons for thinking that this debt will not be paid easily.     

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).