Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imaging.

Traumatic brain injury (TBI) is caused by a sudden external force and can be very heterogeneous in its manifestation. In this work, we analyse T1-weighted magnetic resonance (MR) brain images that were prospectively acquired from patients who sustained mild to severe TBI. We investigate the potential of a recently proposed automatic segmentation method to support the outcome prediction of TBI. Specifically, we extract meaningful cross-sectional and longitudinal measurements from acute- and chronic-phase MR images. We calculate regional volume and asymmetry features at the acute/subacute stage of the injury (median: 19 days after injury), to predict the disability outcome of 67 patients at the chronic disease stage (median: 229 days after injury). Our results indicate that small structural volumes in the acute stage (e.g. of the hippocampus, accumbens, amygdala) can be strong predictors for unfavourable disease outcome. Further, group differences in atrophy are investigated. We find that patients with unfavourable outcome show increased atrophy. Among patients with severe disability outcome we observed a significantly higher mean reduction of cerebral white matter (3.1%) as compared to patients with low disability outcome (0.7%)

Human Serum Metabolites Associate With Severity and Patient Outcomes in Traumatic Brain Injury.

Traumatic brain injury (TBI) is a major cause of death and disability worldwide, especially in children and young adults. TBI is an example of a medical condition where there are still major lacks in diagnostics and outcome prediction. Here we apply comprehensive metabolic profiling of serum samples from TBI patients and controls in two independent cohorts. The discovery study included 144 TBI patients, with the samples taken at the time of hospitalization. The patients were diagnosed as severe (sTBI; n=22), moderate (moTBI; n=14) or mild TBI (mTBI; n=108) according to Glasgow Coma Scale. The control group (n=28) comprised of acute orthopedic non-brain injuries. The validation study included sTBI (n=23), moTBI (n=7), mTBI (n=37) patients and controls (n=27). We show that two medium-chain fatty acids (decanoic and octanoic acids) and sugar derivatives including 2,3-bisphosphoglyceric acid are strongly associated with severity of TBI, and most of them are also detected at high concentrations in brain microdialysates of TBI patients. Based on metabolite concentrations from TBI patients at the time of hospitalization, an algorithm was developed that accurately predicted the patient outcomes (AUC=0.84 in validation cohort). Addition of the metabolites to the established clinical model (CRASH), comprising clinical and computed tomography data, significantly improved prediction of patient outcomes. The identified 'TBI metabotype' in serum, that may be indicative of disrupted blood-brain barrier, of protective physiological response and altered metabolism due to head trauma, offers a new avenue for the development of diagnostic and prognostic markers of broad spectrum of TBIs.European Union FP7 project TBIcare (Grant ID: 270259), GE-NFL Head Health Challenge I Award (Grant ID: 7620), EVO (Finland), Maire Taponen Foundation, National Institute for Health Research, National Institute for Health Research Biomedical Research Centre Cambridge (Neuroscience Theme; Brain Injury and Repair Theme)This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2016.07.01

Early Levels of Glial Fibrillary Acidic Protein and Neurofilament Light Protein in Predicting the Outcome of Mild Traumatic Brain Injury

The purpose of this study was to correlate the early levels of glial fibrillary acidic protein (GFAP) and neurofilament light protein (NF-L) with outcome in patients with mild traumatic brain injury (mTBI). A total of 107 patients with mTBI (Glasgow Coma Scale ≥13) who had blood samples for GFAP and NF-L available within 24 h of arrival were included. Patients with mTBI were divided into computed tomography (CT)–positive and CT-negative groups. Glasgow Outcome Scale-Extended (GOSE) was used to assess the outcome. Outcomes were defined as complete (GOSE 8) versus incomplete (GOSE p = 0.005). The levels of GFAP and NF-L were significantly higher in patients with unfavorable outcome than in patients with favorable outcome (p = 0.002 for GFAP and p </p

Correct interpretation of nanofluid convective heat transfer

Engineers and scientist have a long tradition in trying to improve the thermophysical properties of convective heat carriers such as water and transformer oil. Technological developments of the last decades allow the dispersion of particle of sizes ranging between 10 and 100 nm in these liquids. In a large number of recent studies the resulting nanofluids have been reported to display anomalously high increase of convective heat transfer. The present study compiles experiments from five independent research teams investigating convective heat transfer in nanofluid flow in pipes, pipe with inserted twisted tape, annular counter flow heat exchanger, and coil and plate heat exchangers. The results of all these experiments unequivocally confirm that Newtonian nanofluid flow can be consistently characterized by employing Nusselt number correlations obtained for single-phase heat transfer liquids such as water when the correct thermophysical properties of the nanofluid are utilized. It is also shown that the heat transfer enhancement provided by nanofluids equals the increase in the thermal conductivity of the nanofluid as compared to the base fluid independent of the nanoparticle concentration or material. These results demonstrate that no anomalous phenomena are involved in thermal conduction and forced convection based heat transfer of nanofluids. The experiments are theoretically supported by a fundamental similarity analysis of nanoparticle motion in nanofluid flow.Peer reviewe

On the proper interpretation of nanofluid convective heat transfer

Technological developments of the last decades allow the production and the dispersion of particles of sizes ranging between 10 and 100 nm in liquids. In a large number of recent studies the resulting nanofluids have been reported to display anomalously high increase in convective heat transfer. The present study compiles experiments from five independent research teams investigating convective heat transfer in nanofluid flow in pipes (laminar and turbulent), pipe with inserted twisted tape, annular counter flow heat exchanger, and coil and plate heat exchangers. The results of all these experiments unequivocally confirm that Newtonian nanofluid flow can be consistently characterized by employing Nusselt number correlations obtained for single-phase heat transfer liquids such as water when the correct thermophysical properties of the nanofluid are utilized. It is also shown that the heat transfer enhancement provided by nanofluids equals the increase in the thermal conductivity of the nanofluid as compared to the base fluid independent of the nanoparticle concentration or material. These results demonstrate that no anomalous phenomena are involved in thermal conduction and forced convection based heat transfer of water based nanofluids. The experiments are theoretically supported by a fundamental similarity analysis of nanoparticle motion in nanofluid flow

On the proper interpretation of nanofluid convective heat transfer

Technological developments of the last decades allow the production and the dispersion of particles of sizes ranging between 10 and 100 nm in liquids. In a large number of recent studies the resulting nanofluids have been reported to display anomalously high increase in convective heat transfer. The present study compiles experiments from five independent research teams investigating convective heat transfer in nanofluid flow in pipes (laminar and turbulent), pipe with inserted twisted tape, annular counter flow heat exchanger, and coil and plate heat exchangers. The results of all these experiments unequivocally confirm that Newtonian nanofluid flow can be consistently characterized by employing Nusselt number correlations obtained for single-phase heat transfer liquids such as water when the correct thermophysical properties of the nanofluid are utilized. It is also shown that the heat transfer enhancement provided by nanofluids equals the increase in the thermal conductivity of the nanofluid as compared to the base fluid independent of the nanoparticle concentration or material. These results demonstrate that no anomalous phenomena are involved in thermal conduction and forced convection based heat transfer of water based nanofluids. The experiments are theoretically supported by a fundamental similarity analysis of nanoparticle motion in nanofluid flow

Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase-L1 as Outcome Predictors in Traumatic Brain Injury.

OBJECTIVE: Biomarkers ubiquitin C-terminal hydrolase-L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) may help detect brain injury, assess its severity, and improve outcome prediction. This study aimed to evaluate the prognostic value of these biomarkers during the first days after brain injury. METHODS: Serum UCH-L1 and GFAP were measured in 324 patients with traumatic brain injury (TBI) enrolled in a prospective study. The outcome was assessed using the Glasgow Outcome Scale (GOS) or the extended version, Glasgow Outcome Scale-Extended (GOSE). RESULTS: Patients with full recovery had lower UCH-L1 concentrations on the second day and patients with favorable outcome had lower UCH-L1 concentrations during the first 2 days compared with patients with incomplete recovery and unfavorable outcome. Patients with full recovery and favorable outcome had significantly lower GFAP concentrations in the first 2 days than patients with incomplete recovery or unfavorable outcome. There was a strong negative correlation between outcome and UCH-L1 in the first 3 days and GFAP levels in the first 2 days. On arrival, both UCH-L1 and GFAP distinguished patients with GOS score 1-3 from patients with GOS score 4-5, but not patients with GOSE score 8 from patients with GOSE score 1-7. For UCH-L1 and GFAP to predict unfavorable outcome (GOS score ≤ 3), the area under the receiver operating characteristic curve was 0.727, and 0.723, respectively. Neither UCHL-1 nor GFAP was independently able to predict the outcome when age, worst Glasgow Coma Scale score, pupil reactivity, Injury Severity Score, and Marshall score were added into the multivariate logistic regression model. CONCLUSIONS: GFAP and UCH-L1 are significantly associated with outcome, but they do not add predictive power to commonly used prognostic variables in a population of patients with TBI of varying severities.This work was partially funded by the European Commission under the 7th Framework Programme (FP7-270259-TBIcare), the United Kingdom National Institute of Health Research Biomedical Research Centre at Cambridge, and a personal EVO grant (R.S.K.T.) from Hospital District of South-West Finland. V.F.N. is supported by a Health Foundation/Academy of Medical Sciences Clinician Scientist Fellowship. J.O., J.P.C., P.H., and D.K.M. were supported by the United Kingdom National Institute of Health Research Biomedical Research Centre at Cambridge, and D.K.M. was also supported by a Senior Investigator Award from the United Kingdom National Institute of Health Research

Correlation of Blood Biomarkers and Biomarker Panels with Traumatic Findings on Computed Tomography after Traumatic Brain Injury

The aim of the study was to examine the ability of eight protein biomarkers and their combinations in discriminating computed tomography (CT)-negative and CT-positive patients with traumatic brain injury (TBI), utilizing highly sensitive immunoassays in a well-characterized cohort. Blood samples were obtained from 160 patients with acute TBI within 24 h of admission. Levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein (GFAP), heart fatty-acid binding protein (H-FABP), interleukin 10 (IL-10), neurofilament light (NF-L), S100 calcium-binding protein B (S100B), and tau were measured. Patients were divided into CT-negative (n = 65) and CT-positive (n = 95), and analyses were conducted separately for TBIs of all severities (Glasgow Coma Scale [GCS] score 3–15) and mild TBIs (mTBIs; GCS 13–15). NF-L, GFAP, and tau were the best in discriminating CT-negative and CT-positive patients, both in patients with mTBI and with all severities. In patients with all severities, area under the curve of the receiver operating characteristic (AUC) was 0.822, 0.817, and 0.781 for GFAP, NF-L, and tau, respectively. In patients with mTBI, AUC was 0.720, 0.689, and 0.676, for GFAP, tau, and NF-L, respectively. The best panel of three biomarkers for discriminating CT-negative and CT-positive patients in the group of all severities was a combination of GFAP+H-FABP+IL-10, with a sensitivity of 100% and specificity of 38.5%. In patients with mTBI, the best panel of three biomarkers was H-FABP+S100B+tau, with a sensitivity of 100% and specificity of 46.4%. Panels of biomarkers outperform individual biomarkers in separating CT-negative and CT-positive patients. Panels consisted mainly of different biomarkers than those that performed best as an individual biomarker