Uncoupling of metabolism and circadian activity is associated with an increased risk of a wide spectrum of pathologies. Recently, insulin and the closely related insulin-like growth factor I (IGF-I) were shown to entrain feeding patterns with circadian rhythms. Both hormones act centrally to modulate peripheral glucose metabolism; however, whereas central targets of insulin actions are intensely scrutinized, those mediating the actions of IGF-I remain less defined. We recently showed that IGF-I targets orexin neurons in the lateral hypothalamus, and now we evaluated whether IGF-I modulates orexin neurons to align circadian rhythms with metabolism. Mice with disrupted IGF-IR activity in orexin neurons (Firoc mice) showed sexually dimorphic alterations in daily glucose rhythms and feeding activity patterns which preceded the appearance of metabolic disturbances. Thus, Firoc males developed hyperglycemia and glucose intolerance, while females developed obesity. Since IGF-I directly modulates orexin levels and hepatic expression of KLF genes involved in circadian and metabolic entrainment in an orexin-dependent manner, it seems that IGF-I entrains metabolism and circadian rhythms by modulating the activity of orexin neurons.

Perioperative vision loss (POVL) is a devastating surgical complication that impacts both the recovery from surgery and quality of life, most commonly occurring after spine surgery. With rates of spine surgery dramatically increasing, the prevalence of POVL will increase proportionately. This scoping review aims to aggregate the literature pertinent to POVL in spine surgery and consolidate recommendations and preventative measures to reduce the risk of POVL. There are several causes of POVL, and the main contribution following spine surgery is ischemic optic neuropathy (ION). Vision loss often manifests immediately following surgery and is irreversible and severe. Diffusion weighted imaging has recently surfaced as a diagnostic tool to identify ION. There are no effective treatments; therefore, risk stratification for counseling and prevention are vital. Patients undergoing prone surgery of long duration and/or with significant expected blood loss are at greatest risk. Future research is necessary to develop effective treatments.

Background: Prognostic indices for patients with brain metastases (BM) are needed to individualize treatment and stratify clinical trials. Two frequently used tools to estimate survival in patients with BM are the recursive partitioning analysis (RPA) and the diagnosis-specific graded prognostic assessment (DS-GPA). Given recent advances in therapies and improved survival for patients with BM, this study aims to validate and analyze these 2 models in a modern cohort. Methods: Patients diagnosed with BM were identified via our institution’s Tumor Board meetings. Data were retrospectively collected from the date of diagnosis with BM. The concordance of the RPA and GPA was calculated using Harrell’s C index. A Cox proportional hazards model with backwards elimination was used to generate a parsimonious model predictive of survival. Results: Our study consisted of 206 patients diagnosed with BM between 2010 and 2019. The RPA had a prediction performance characterized by Harrell’s C index of 0.588. The DS-GPA demonstrated a Harrell’s C index of 0.630. A Cox proportional hazards model assessing the effect of age, presence of lung, or liver metastases, and Eastern Cooperative Oncology Group (ECOG) performance status score of 3/4 on survival yielded a Harrell’s C index of 0.616. Revising the analysis with an uncategorized ECOG demonstrated a C index of 0.648. Conclusions: We found that the performance of the RPA remains unchanged from previous validation studies a decade earlier. The DS-GPA outperformed the RPA in predicting overall survival in our modern cohort. Analyzing variables shared by the RPA and DS-GPA produced a model that performed analogously to the DS-GPA.