scholarly journals The role of salivary vesicles as a potential inflammatory biomarker to detect traumatic brain injury in mixed martial artists

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rani Matuk ◽  
Mandy Pereira ◽  
Janette Baird ◽  
Mark Dooner ◽  
Yan Cheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Head Injury ◽  
Injury Severity ◽  
Expression Profiles ◽  
High Impact ◽  
Impact Mechanism ◽  
Inflammatory Biomarker ◽  
Potential Biomarker

AbstractTraumatic brain injury (TBI) is of significant concern in the realm of high impact contact sports, including mixed martial arts (MMA). Extracellular vesicles (EVs) travel between the brain and oral cavity and may be isolated from salivary samples as a noninvasive biomarker of TBI. Salivary EVs may highlight acute neurocognitive or neuropathological changes, which may be particularly useful as a biomarker in high impact sports. Pre and post-fight samples of saliva were isolated from 8 MMA fighters and 7 from controls. Real-time PCR of salivary EVs was done using the TaqMan Human Inflammatory array. Gene expression profiles were compared pre-fight to post-fight as well as pre-fight to controls. Largest signals were noted for fighters sustaining a loss by technical knockout (higher impact mechanism of injury) or a full match culminating in referee decision (longer length of fight), while smaller signals were noted for fighters winning by joint or choke submission (lower impact mechanism as well as less time). A correlation was observed between absolute gene information signals and fight related markers of head injury severity. Gene expression was also significantly different in MMA fighters pre-fight compared to controls. Our findings suggest that salivary EVs as a potential biomarker in the acute period following head injury to identify injury severity and can help elucidate pathophysiological processes involved in TBI.

scholarly journals Study of Traumatic Brain Injury Due To Recent Earthquake in Manipal Teaching Hospital

2016 ◽  
Vol 12 (2) ◽  
pp. 63-66
Author(s):  
Bal G Karmacharya ◽  
Brijesh Sathian
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Head Injury ◽  
Teaching Hospital ◽  
Brain Injuries ◽  
Injury Severity ◽  
Traumatic Brain Injuries ◽  
The Body ◽  
Mild Head Injury ◽  
Associated Injuries

The objective of this study was to review the demographics, causes injury, severity, treatment and outcome of traumatic brain injuries in victims of the April 2015 earthquake who were admitted in Manipal Teaching Hospital, Pokhara. A total of 37 patients was admitted under Neurosurgery Services. Collapse of buildings was the commonest cause of head injury. The majority of them had mild head injury. Associated injuries to other parts of the body were present in 40.54% patients.Nepal Journal of Neuroscience 12:63-66, 2015

The impact of blood ethanol concentration on the classification of head injury severity in traumatic brain injury

Brain Injury ◽  
2015 ◽  
Vol 29 (13-14) ◽  
pp. 1648-1653 ◽  
Author(s):  
Pål Rønning ◽  
Per Ole Gunstad ◽  
Nils-Oddvar Skaga ◽  
Iver Arne Langmoen ◽  
Knut Stavem ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Head Injury ◽  
Injury Severity ◽  
Ethanol Concentration ◽  
Blood Ethanol Concentration ◽  
The Impact ◽  
Head Injury Severity

scholarly journals Traumatic brain injury—the effects of patient age on treatment intensity and mortality

BMC Neurology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ola Skaansar ◽  
Cathrine Tverdal ◽  
Pål Andre Rønning ◽  
Karoline Skogen ◽  
Tor Brommeland ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Head Injury ◽  
Injury Severity ◽  
Age Groups ◽  
Composite Score ◽  
Increased Risk ◽  
Management Intensity ◽  
Treatment Bias ◽  
Head Injury Severity

Abstract Background Ageing is associated with worse treatment outcome after traumatic brain injury (TBI). This association may lead to a self-fulfilling prophecy that affects treatment efficacy. The aim of the current study was to evaluate the role of treatment bias in patient outcomes by studying the intensity of diagnostic procedures, treatment, and overall 30-day mortality in different age groups of patients with TBI. Methods Included in this study was consecutively admitted patients with TBI, aged ≥ 15 years, with a cerebral CT showing intracranial signs of trauma, during the time-period between 2015–2018. Data were extracted from our prospective quality control registry for admitted TBI patients. As a measure of management intensity in different age groups, we made a composite score, where placement of intracranial pressure monitor, ventilator treatment, and evacuation of intracranial mass lesion each gave one point. Uni- and multivariate survival analyses were performed using logistic multinomial regression. Results A total of 1,571 patients with TBI fulfilled the inclusion criteria. The median age was 58 years (range 15–98), 70% were men, and 39% were ≥ 65 years. Head injury severity was mild in 706 patients (45%), moderate in 437 (28%), and severe in 428 (27%). Increasing age was associated with less management intensity, as measured using the composite score, irrespective of head injury severity. Multivariate analyses showed that the following parameters had a significant association with an increased risk of death within 30 days of trauma: increasing age, severe comorbidities, severe TBI, Rotterdam CT-score ≥ 3, and low management intensity. Conclusion The present study indicates that the management intensity of hospitalised patients with TBI decreased with advanced age and that low management intensity was associated with an increased risk of 30-day mortality. This suggests that the high mortality among elderly TBI patients may have an element of treatment bias and could in the future be limited with a more aggressive management regime.

scholarly journals The King's Outcome Scale for Childhood Head Injury and injury severity and outcome measures in children with traumatic brain injury

2008 ◽  
Vol 50 (6) ◽  
pp. 426-431 ◽  
Author(s):  
Sophie Calvert ◽  
Helen E Miller ◽  
Andrew Curran ◽  
Biju Hameed ◽  
Renée McCarter ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Head Injury ◽  
Outcome Measures ◽  
Injury Severity

scholarly journals What Do Machines Tell us About Dementia? Machine Learning Applied to Aging, Dementia and Traumatic Brain Injury Study

2021 ◽  
Author(s):  
Denis Arthur Pinheiro Moura ◽  
Joao Ricardo Mendes de Oliveira
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Expression Profiles ◽  
Brain Regions ◽  
Machine Learning Algorithms ◽  
Differentially Expressed ◽  
Classification Model ◽  
Specific Gene

Abstract Dementia, a syndrome characterized by the progressive deterioration of memory and cognition, arises from different pathologies, with Alzheimer's Disease (AD) its most common cause. Patterns of gene expression during dementia of different etiologies may function as generalist biomarkers of the condition. We used RNA-Seq data from the Allen Dementia and Traumatic Brain Injury Study (ADTBI) to identify differentially expressed genes in brains with dementia. Machine Learning algorithms Decision Trees (DT) and Random Forest (RF) were used to create models to identify dementia samples based on their gene expression profile. Importance analyses were conducted to identify the most relevant genes in each classification model. A total of 1629 differentially expressed (DE) genes were found in brains with the condition. Gene PAN3-AS1 was the only DE gene across more than three brain regions. The artificial intelligence models were capable of identifying correctly up to 92.85% of dementia samples. Our analyses provide interesting insights regarding using brain-specific gene expression profiles as biomarkers of dementia, identifying genes possibly involved with dementia, and guiding future studies in prediction and early identification of the syndrome.

scholarly journals Transcriptional Pathology Evolves Over Time in Rat Hippocampus Following Lateral Fluid Percussion Traumatic Brain Injury

2021 ◽  
Author(s):  
Rinaldo Catta-Preta ◽  
Iva Zdillar ◽  
Bradley Jenner ◽  
Emily T. Doisy ◽  
Kayleen Tercovich ◽  
...  
Keyword(s):  
Gene Expression ◽  
Traumatic Brain Injury ◽  
Cell Death ◽  
Brain Injury ◽  
Injury Severity ◽  
Cholesterol Metabolism ◽  
Fluid Percussion ◽  
Differential Gene ◽  
Lateral Fluid Percussion ◽  
The Brain

Traumatic brain injury (TBI) causes acute and lasting impacts on the brain, driving pathology along anatomical, cellular, and behavioral dimensions. Rodent models offer the opportunity to study TBI in a controlled setting, and enable analysis of the temporal progression that occurs from injury to recovery. We applied transcriptomic and epigenomic analysis, characterize gene expression and in ipsilateral hippocampus at 1 and 14 days following moderate lateral fluid percussion (LFP) injury. This approach enabled us to identify differential gene expression (DEG) modules with distinct expression trajectories across the two time points. The major DEG modules represented genes that were up- or downregulated acutely, but largely recovered by 14 days. As expected, DEG modules with acute upregulation were associated with cell death and astrocytosis. Interestingly, acutely downregulated DEGs related to neurotransmission mostly recovered by two weeks. Upregulated DEG modules related to inflammation were not necessarily elevated acutely, but were strongly upregulated after two weeks. We identified a smaller DEG module with delayed upregulation at 14 days including genes related to cholesterol metabolism and amyloid beta clearance. Finally, differential expression was paralleled by changes in H3K4me3 at the promoters of differentially expressed genes at one day following TBI. Following TBI, changes in cell viability, function and ultimately behavior are dynamic processes. Our results show how transcriptomics in the preclinical setting has the potential to identify biomarkers for injury severity and/or recovery, to identify potential therapeutic targets, and, in the future, to evaluate efficacy of an intervention beyond measures of cell death or spatial learning.

scholarly journals The Gene Coexpression Analysis Identifies Functional Modules Dynamically Changed After Traumatic Brain Injury

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhi-jie Zhao ◽  
Dong-po Wei ◽  
Rui-zhe Zheng ◽  
Tinghua Peng ◽  
Xiang Xiao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Cell Activation ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Protein Translation ◽  
Functional Modules ◽  
Coexpression Analysis ◽  
Gene Coexpression

Traumatic brain injury (TBI) is a major cause of morbidity and mortality, both in adult and pediatric populations. However, the dynamic changes of gene expression profiles following TBI have not been fully understood. In this study, we identified the differentially expressed genes (DEGs) following TBI. Remarkably, Serpina3n, Asf1b, Folr1, LOC100366216, Clec12a, Olr1, Timp1, Hspb1, Lcn2, and Spp1 were identified as the top 10 with the highest statistical significance. The weighted gene coexpression analysis (WGCNA) identified 12 functional modules from the DEGs, which showed specific expression patterns over time and were characterized by enrichment analysis. Specifically, the black and turquoise modules were mainly involved in energy metabolism and protein translation. The green yellow and yellow modules including Hmox1, Mif, Anxa2, Timp1, Gfap, Cd9, Gja1, Pdpn, and Gpx1 were related to response to wounding, indicating that expression of these genes such as Hmox1, Anxa2, and Timp1 could protect the brains from brain injury. The green yellow module highlighted genes involved in microglial cell activation such as Tyrobp, Cx3cr1, Grn, Trem2, C1qa, and Aif1, suggesting that these genes were responsible for the inflammatory response caused by TBI. The upregulation of these genes has been validated in an independent dataset. These results indicated that the key genes in microglia cell activation may serve as a promising therapeutic target for TBI. In summary, the present study provided a full view of the dynamic gene expression changes following TBI.

scholarly journals Traumatic brain injury - the effects of patient age on treatment intensity and mortality

2020 ◽  
Author(s):  
Ola Skaansar ◽  
Cathrine Tverdal ◽  
Pål Andre Rønning ◽  
Karoline Skogen ◽  
Tor Brommeland ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Head Injury ◽  
Injury Severity ◽  
Age Groups ◽  
Composite Score ◽  
Increased Risk ◽  
Management Intensity ◽  
Treatment Bias ◽  
Head Injury Severity

Abstract Background Ageing is associated with worse treatment outcome after traumatic brain injury (TBI). This association may lead to a self-fulfilling prophecy that affects treatment efficacy. The aim of the current study was to evaluate the role of treatment bias in patient outcomes by studying the intensity of diagnostic procedures, treatment, and overall 30-day mortality in different age groups of patients with TBI. Methods Included in this study was consecutively admitted patients with TBI, aged ≥ 15 years, with a cerebral CT showing intracranial signs of trauma, during the time-period between 2015–2018. Data were extracted from our prospective quality control registry for admitted TBI patients. As a measure of management intensity in different age groups, we made a composite score, where use of advanced TBI imaging, placement of intracranial pressure monitor, ventilator treatment, and evacuation of intracranial mass lesion each gave one point. Uni- and multivariate survival analyses were performed using logistic multinomial regression. Results A total of 1,571 patients with TBI fulfilled the inclusion criteria. The median age was 58 years (range 15–98), 70% were men, and 39% were ≥ 65 years. Head injury severity was mild in 706 patients (45%), moderate in 437 (28%), and severe in 428 (27%). Increasing age was associated with less management intensity, as measured using the composite score, irrespective of head injury severity. Multivariate analyses showed that the following parameters had a significant association with an increased risk of death within 30 days of trauma: increasing age, moderate/severe TBI, Rotterdam CT-score ≥ 4, and low management intensity (composite score ≤ 3). Conclusion The present study indicates that the management intensity of hospitalised patients with TBI decreased with advanced age and that low management intensity was associated with an increased risk of 30-day mortality. This suggests that the high mortality among elderly TBI patients may have an element of treatment bias and could in the future be limited with a more aggressive management regime.

scholarly journals Analysis of Traumatic brain injury related to Kite flying festival: An institutional study

2018 ◽  
Vol 32 (2) ◽  
pp. 355-358
Author(s):  
Manish Jaiswal ◽  
Somil Jaiswal ◽  
Bal Krishna Ojha ◽  
Sunil Kumar Singh ◽  
Anil Chandra ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Head Injury ◽  
Brain Injuries ◽  
Injury Severity ◽  
Emergency Admission ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Depressed Fracture ◽  
Injured Patients

Abstract Introduction: Makar Sankranti or Uttarayan is the kite flying festival in India. The festival marks the end of winter and the beginning of summer as the sun moves to the Tropic of Cancer bringing with it longer and warmer days. But it turns into a difficult day for those who are hospitalised after suffering from kite flying related injuries. Aims & Objectives: The objective of this cross sectional study was to review the demographics, causes injury, severity, treatment and outcome of traumatic brain injuries in victims of this kite flying festival who were admitted in department of Neurosurgery on the occasion this year in January. Patients & Methods: A total of 46 traumatic brain injured patients was admitted under Neurosurgery Services that day, out of which 18 cases were related to kite flying related injury. Data of these 18 patients were analysed and outcome were measured at discharge. Result: kite flying festival related neurotrauma increase 39% more emergency admission burden as compared to routine days in neuro-emergency ward. Most common cause of head injury among them was fall from roof. Majority of them had mild head injury. Associated injuries to other part of body were present in 46% patients. Conclusion: Children were most affected due to unsupervised kite flying on roof and road side catching of kites. Depressed fracture was commonest type of traumatic brain injury. Strict attention to safety measures and parental supervision while flying kites can avoid many preventable injuries to life.

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