In the human body, the central regulatory system of homeostasis is maintained by the brain. Its complexity is mesmerizing and many of its functions are largely uncharted. Unfortunately, its functionality is often impaired through neoplastic growths, like gliomas, which are devastating to patients and their families. Annually, gliomas are the most common primary brain tumours affecting over 20,000 people in the United States. However, despite their status as the third most common cause of cancer related death for individuals between ages 20 and 39, the aetiology of gliomas remains unknown. This paper aims to review the latest information regarding the 2016 World Health Organization (WHO) 4th edition classifications of gliomas, their malignant effects, and disparities within these classifications, as well as identify areas for further research. These suggestions for future inquiry may contribute to a better understanding of the pathology of these cancers enabling improvement in prevention, screening, and treatment.

We used ultra-high field (7 T) fMRI and parallel imaging to scan the superior parietal lobule (SPL) of human subjects as they mentally traversed a maze path in one of four directions (up, down, left, right). A counterbalanced design for maze presentation and a quasi-isotropic voxel (1.46 × 1.46 × 2 mm thick) collection were implemented. Fifty-one percent of single voxels in the SPL were tuned to the direction of the maze path. Tuned voxels were distributed throughout the SPL, bilaterally. A nearest neighbor analysis revealed a "honeycomb" arrangement such that voxels tuned to a particular direction tended to occur in clusters. Three-dimensional (3D) directional clusters were identified in SPL as oriented centroids traversing the cortical depth. There were 13 same-direction clusters per hemisphere containing 22 voxels per cluster, on the average; the mean nearest-neighbor, same-direction intercluster distance was 9.4 mm. These results provide a much finer detail of the directional tuning in SPL, as compared to those obtained previously at 4 T (Gourtzelidis et al. Exp Brain Res 165:273-282, 2005). The more accurate estimates of quantitative clustering parameters in 3D brain space in this study were made possible by the higher signal-to-noise and contrast-to-noise ratios afforded by the higher magnetic field of 7 T as well as the quasi-isotropic design of voxel data collection.

Background and objectives: Glial brain cancers affect nearly 20,000 individuals in the United States (USA) annually. SEER database data exploring the relationship between race and gliomas is now available and have shown that cerebral gliomas occur at a higher frequency in Caucasian men. However, such analyses did not include demographic data specific to the state of Florida. This study assessed the association between race and glial vs. non-glial Central Nervous System (CNS) cancers in Florida, USA. Materials and Methods: This case-control study utilized the Florida Cancer Data Registry (FCDS), in which race was considered the exposure and development of glioma as the measured outcome. The sample was comprised of patients in Florida diagnosed with brain tumors from 1981 to 2013. Relative racial frequencies were compared between patients with glial brain tumors and those with other CNS tumors. Data was analyzed using logistic regression in order to determine any associations between race and frequency of diagnosis adjusting for several confounders (age, sex, smoking status, year of diagnosis, and insurance status). Results: Between 1981 and 2013 a total of 14,092 patients meeting the inclusion and exclusion criteria were diagnosed in Florida with a primary brain tumor. Being of non-white race was associated with 60% decreased odds of glioma diagnosis compared to the reference white population (adjusted OR 0.4, 95% CI 0.34–0.47). Secondary findings include associations between increasing age and male sex with increased odds of glioma diagnosis. Decreased adjusted odds of glioma diagnosis were found with former smoking status (reference non-smokers), diagnosis between 2001 and 2010 (reference 1981–1990), and Medicaid or Medicare insurance (reference private insurance). Hispanic ethnicity, current smoking status, no insurance/self-pay, and geographical location (urban vs. rural) all had no association with glioma diagnosis. Conclusions: These findings are consistent with and help reinforce previous studies utilizing national databases (SEER) which also showed increasing odds of glioma diagnosis in older white males. Various potential explanations for these findings include genetic predisposition, lifestyle and behavioral factors, and socioeconomic status, including access to healthcare. Future research aims at identifying potential genetic etiologies.