RESUMO
Mild traumatic brain injury (mTBI) is an insult to the CNS often overlooked at the time of presentation due to variable symptomatology and undetectable nature on CT/MRI. Increased exposure to repetitive head injuries results in a high prevalence of mTBI among athletes and military personnel. While most patients fully recover with rest, some are at risk for long-lasting neurocognitive dysfunction, leading to a high morbidity and cost burden on the healthcare system. Currently, there are no unified symptom-based criteria or gold standard objective measurement for mTBI. Neurofilament light (Nf-L) is a highly sensitive biomarker for axonal injury with the potential to serve as an objective serum measurement for mTBI. This systematic review investigates the ability of Nf-L to accurately diagnose acute mTBI in athletes and military personnel. A comprehensive literature search of PubMed, Scopus, and Google Scholar from 2010 to 2021 using keywords neurofilament light chain, mTBI, concussion, athletes, and military identified 239 articles for eligibility screening. Ten articles met the inclusion criteria for qualitative analysis, with extracted data including Nf-L levels, recovery characteristics, and neuroimaging results. Of the 10 studies meeting inclusion criteria, one was military-related, five were sports-related, and four were mixed-focus. Six studies investigated the association between mTBI and Nf-L levels within 24 hours of injury. Four of these studies involved athletes, with three showing evidence of acute Nf-L elevations. No evidence of acute Nf-L elevations was reported among military personnel or emergency department patients. Nf-L elevations were recorded at various time points greater than 24 hours post-injury in athletes (two studies) and emergency department patients (one study). Positive associations were found between Nf-L levels and loss of consciousness/post-traumatic amnesia (one study), positive neuroimaging findings (three studies), and prolonged recovery times (three studies). We are unable to conclude whether Nf-L has the capacity for acute diagnosis of mTBI or the optimal time for serum measurement. Nf-L does, however, shows promise as a prognostic factor for mTBI complications, neuroimaging findings, and recovery. Additional studies are warranted, as the use of Nf-L in early diagnosis of mTBI in the future would improve clinical management while decreasing complications and healthcare costs.
RESUMO
Adipose tissue macrophages (ATM) are crucial for maintaining adipose tissue homeostasis and mediating obesity-induced metabolic abnormalities, including prediabetic conditions and type 2 diabetes mellitus. Despite their key functions in regulating adipose tissue metabolic and immunologic homeostasis under normal and obese conditions, a high-resolution transcriptome annotation system that can capture ATM multifaceted activation profiles has not yet been developed. This is primarily attributed to the complexity of their differentiation/activation process in adipose tissue and their diverse activation profiles in response to microenvironmental cues. Although the concept of multifaceted macrophage action is well-accepted, no current model precisely depicts their dynamically regulated in vivo features. To address this knowledge gap, we generated single-cell transcriptome data from primary bone marrow-derived macrophages under polarizing and non-polarizing conditions to develop new high-resolution algorithms. The outcome was creation of a two-index platform, MacSpectrum (https://macspectrum.uconn.edu), that enables comprehensive high-resolution mapping of macrophage activation states from diverse mixed cell populations. MacSpectrum captured dynamic transitions of macrophage subpopulations under both in vitro and in vivo conditions. Importantly, MacSpectrum revealed unique "signature" gene sets in ATMs and circulating monocytes that displayed significant correlation with BMI and homeostasis model assessment of insulin resistance (HOMA-IR) in obese human patients. Thus, MacSpectrum provides unprecedented resolution to decode macrophage heterogeneity and will open new areas of clinical translation.