Low-grade gliomas (LGGs) are tumors that affect mostly adults. These neoplasms are comprised mainly of oligodendrogliomas and diffuse astrocytomas. LGGs remain vexing to current management and therapeutic modalities although they exhibit more favorable survival rates compared with high-grade gliomas (HGGs). The specific genetic subtypes that these tumors exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of an LGG pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). The introduction of radiomics as a high throughput quantitative imaging technique that allows for improved diagnostic, prognostic and predictive indices has created more interest for such techniques in cancer research and especially in neurooncology (MRI-based classification of LGGs, predicting Isocitrate dehydrogenase (IDH) and Telomerase reverse transcriptase (TERT) promoter mutations and predicting LGG associated seizures). Radiogenomics refers to the linkage of imaging findings with the tumor/tissue genomics. Numerous applications of radiomics and radiogenomics have been described in the clinical context and management of LGGs. In this review, we describe the recently published studies discussing the potential application of radiomics and radiogenomics in LGGs. We also highlight the potential pitfalls of the above-mentioned high throughput computerized techniques and, most excitingly, explore the use of machine learning artificial intelligence technologies as standalone and adjunct imaging tools en route to enhance a personalized MRI-based tumor diagnosis and management plan design.

The ability to switch between glycolysis and ketosis promotes survival by enabling metabolism through fat oxidation during periods of fasting. Carbohydrate restriction or stress can also elicit metabolic switching. Ketoadapting from glycolysis is delayed in aged rats, but factors mediating this age-related impairment have not been identified. We measured metabolic switching between glycolysis and ketosis, as well as glycogen dynamics, in young and aged rats undergoing time-restricted feeding (TRF) with a standard diet or a low carbohydrate ketogenic diet (KD). TRF alone reversed markers of insulin-related metabolic deficits and accelerated metabolic switching in aged animals. A KD+TRF, however, provided additive benefits on these variables. Remarkably, the ability to keto-adapt was not related to glycogen levels and KD-fed rats showed an enhanced elevation in glucose following epinephrine administration. This study provides new insights into the mechanisms of keto-adaptation demonstrating the utility of dietary interventions to treat metabolic impairments across the lifespan.

ABSTRACTThe ability to switch between glycolysis and ketosis promotes survival by enabling metabolism through fat oxidation during periods of fasting. Carbohydrate restriction or stress can also elicit metabolic switching. Keto-adapting from glycolysis is delayed in aged rats, but factors mediating this age-related impairment have not been identified. We measured metabolic switching between glycolysis and ketosis, as well as glycogen dynamics, in young and aged rats undergoing time-restricted feeding (TRF) with a standard diet or a low carbohydrate ketogenic diet (KD). TRF alone reversed markers of insulin-related metabolic deficits and accelerated metabolic switching in aged animals. A KD+TRF, however, provided additive benefits on these variables. Remarkably, the ability to keto-adapt was not related to glycogen levels and KD-fed rats showed an enhanced elevation in glucose following epinephrine administration. This study provides new insights into the mechanisms of keto-adaptation demonstrating the utility of dietary interventions to treat metabolic impairments across the lifespan.

Human brain organoids are models derived from human embryonic or induced pluripotent stem cells that mimic basic cerebral microanatomy and demonstrate simple functional neuronal networks. Brain organoids have been a rapidly expanding avenue for biomedical research in general and specifically: neural development, regeneration, and central nervous system pathophysiology. However, technology replicating functional aspects of the human brain, including electrically active neural networks, requires a responsible code of conduct. In this review, we focus the discussion on intrinsic and extrinsic ethical factors associated with organoids: intrinsic considerations arise with the growing complexity of human brain organoids, including human-animal chimerism, consciousness development, and questions of where these human-like beings fall in a moral hierarchy. Extrinsic considerations explore ethics on obtainment, manufacturing, and production of sophisticated human products. In summary, a thoughtful code of conduct using human brain organoids towards the advancement of science and medicine is crucial. This article shall facilitate a structured thought process approaching the moral landscape of organoid technology.