Recent advances in traumatic brain injury

Abstract: Traumatic brain injury (TBI) is the most common cause of death and disability in those aged under 40 years in the UK. Higher rates of morbidity and mortality are seen in low-income and middle-income countries making it a global health challenge. There has been a secular trend towards reduced incidence of severe TBI in the first world, driven by public health interventions such as seatbelt legislation, helmet use, and workplace health and safety regulations. This has paralleled improved outcomes following TBI delivered in a large part by the widespread establishment of specialised neurointensive care. This update will focus on three key areas of advances in TBI management and research in moderate and severe TBI: refining neurointensive care protocolized therapies, the recent evidence base for decompressive craniectomy and novel pharmacological therapies. In each section, we review the developing evidence base as well as exploring future trajectories of TBI research

An Innovative Word Encoding Method For Text Classification Using Convolutional Neural Network

Text classification plays a vital role today especially with the intensive use of social networking media. Recently, different architectures of convolutional neural networks have been used for text classification in which one-hot vector, and word embedding methods are commonly used. This paper presents a new language independent word encoding method for text classification. The proposed model converts raw text data to low-level feature dimension with minimal or no preprocessing steps by using a new approach called binary unique number of word "BUNOW". BUNOW allows each unique word to have an integer ID in a dictionary that is represented as a k-dimensional vector of its binary equivalent. The output vector of this encoding is fed into a convolutional neural network (CNN) model for classification. Moreover, the proposed model reduces the neural network parameters, allows faster computation with few network layers, where a word is atomic representation the document as in word level, and decrease memory consumption for character level representation. The provided CNN model is able to work with other languages or multi-lingual text without the need for any changes in the encoding method. The model outperforms the character level and very deep character level CNNs models in terms of accuracy, network parameters, and memory consumption; the results show total classification accuracy 91.99% and error 8.01% using AG's News dataset compared to the state of art methods that have total classification accuracy 91.45% and error 8.55%, in addition to the reduction in input feature vector and neural network parameters by 62% and 34%, respectively.Comment: Accepted @ 14th International Computer Engineering Conference (ICENCO2018), Faculty of Engineering , Cairo University, Egypt, Dec. 29-30, 201

How to Translate Time: The Temporal Aspects of Rodent and Human Pathobiological Processes in Traumatic Brain Injury.

Traumatic brain injury (TBI) triggers multiple pathobiological responses with differing onsets, magnitudes, and durations. Identifying the therapeutic window of individual pathologies is critical for successful pharmacological treatment. Dozens of experimental pharmacotherapies have been successfully tested in rodent models, yet all of them (to date) have failed in clinical trials. The differing time scales of rodent and human biological and pathological processes may have contributed to these failures. We compared rodent versus human time scales of TBI-induced changes in cerebral glucose metabolism, inflammatory processes, axonal integrity, and water homeostasis based on published data. We found that the trajectories of these pathologies run on different timescales in the two species, and it appears that there is no universal "conversion rate" between rodent and human pathophysiological processes. For example, the inflammatory process appears to have an abbreviated time scale in rodents versus humans relative to cerebral glucose metabolism or axonal pathologies. Limitations toward determining conversion rates for various pathobiological processes include the use of differing outcome measures in experimental and clinical TBI studies and the rarity of longitudinal studies. In order to better translate time and close the translational gap, we suggest 1) using clinically relevant outcome measures, primarily in vivo imaging and blood-based proteomics, in experimental TBI studies and 2) collecting data at multiple post-injury time points with a frequency exceeding the expected information content by two or three times. Combined with a big data approach, we believe these measures will facilitate the translation of promising experimental treatments into clinical use

Cerebral microdialysis in clinical studies of drugs: pharmacokinetic applications.

The ability to deliver drug molecules effectively across the blood-brain barrier into the brain is important in the development of central nervous system (CNS) therapies. Cerebral microdialysis is the only existing technique for sampling molecules from the brain extracellular fluid (ECF; also termed interstitial fluid), the compartment to which the astrocytes and neurones are directly exposed. Plasma levels of drugs are often poor predictors of CNS activity. While cerebrospinal fluid (CSF) levels of drugs are often used as evidence of delivery of drug to brain, the CSF is a different compartment to the ECF. The continuous nature of microdialysis sampling of the ECF is ideal for pharmacokinetic (PK) studies, and can give valuable PK information of variations with time in drug concentrations of brain ECF versus plasma. The microdialysis technique needs careful calibration for relative recovery (extraction efficiency) of the drug if absolute quantification is required. Besides the drug, other molecules can be analysed in the microdialysates for information on downstream targets and/or energy metabolism in the brain. Cerebral microdialysis is an invasive technique, so is only useable in patients requiring neurocritical care, neurosurgery or brain biopsy. Application of results to wider patient populations, and to those with different pathologies or degrees of pathology, obviously demands caution. Nevertheless, microdialysis data can provide valuable guidelines for designing CNS therapies, and play an important role in small phase II clinical trials. In this review, we focus on the role of cerebral microdialysis in recent clinical studies of antimicrobial agents, drugs for tumour therapy, neuroprotective agents and anticonvulsants

Indocyanine green fluorescence video angiography reduces vascular injury–related morbidity during micro-neurosurgical clipping of ruptured cerebral aneurysms: a retrospective observational study

Abstract: Background: Specific procedural complications in aneurysm surgery are broadly related to vascular territory compromise and brain/nerve retraction; vascular complications account for about half of this. Intraoperative indocyanine green video angiography (ICG-VA) provides real-time high spatial resolution imaging of the cerebrovascular architecture, allowing immediate quality assurance of aneurysm occlusion and vessel integrity. The aim of this study was to examine whether the routine use of ICG-VA reduced early procedural complications related to vascular compromise or injury during micro-neurosurgical clipping of ruptured cerebral aneurysms. Methods: Retrospective comparative observational study of 412 adult good-grade (WFNS 1 or 2) SAH patients who had undergone microsurgical clipping without (n = 200, 2001–2004) or with (n = 212, 2009–2015) ICG-VA in a high-volume neurosurgical centre. Results: The ICG-VA group had a significantly lower incidence of procedural vascular complications (7/212; 3.3%) compared with the non-ICG-VA group (19/200; 9.5%) (Fisher’s exact test p = 0.0137). Conclusions: ICG-VA is a straightforward, easy-to-use, intraoperative adjunct which significantly reduces avoidable ‘technical error’ related morbidity

Principal component analysis of the cytokine and chemokine response to human traumatic brain injury.

There is a growing realisation that neuro-inflammation plays a fundamental role in the pathology of Traumatic Brain Injury (TBI). This has led to the search for biomarkers that reflect these underlying inflammatory processes using techniques such as cerebral microdialysis. The interpretation of such biomarker data has been limited by the statistical methods used. When analysing data of this sort the multiple putative interactions between mediators need to be considered as well as the timing of production and high degree of statistical co-variance in levels of these mediators. Here we present a cytokine and chemokine dataset from human brain following human traumatic brain injury and use principal component analysis and partial least squares discriminant analysis to demonstrate the pattern of production following TBI, distinct phases of the humoral inflammatory response and the differing patterns of response in brain and in peripheral blood. This technique has the added advantage of making no assumptions about the Relative Recovery (RR) of microdialysis derived parameters. Taken together these techniques can be used in complex microdialysis datasets to summarise the data succinctly and generate hypotheses for future study

Economic design of sleeve rotor induction motor using rotor ends

In this paper, the field analysis of the sleeve rotor induction motor (IM) is carried out taking the rotor ends into consideration. Here, the field system equations are derived using the cylindrical model with applying Maxwell's field equations. It is expected that, both starting and maximum torques will increase with taking the rotor ends than that without rotor ends. A simple model is used to establish the geometry of the rotor ends current density and to investigate the air gap flux density. The magnetic flux is assumed to remain radially constant through the very small air gap length between the sleeve and stator surfaces. Variation of the field in the radial direction is ignored and the skin effect in the axial direction is considered. The axial distributions of the air gap flux density, the sleeve current density components and the force density have been determined. The motor performance is carried out taking into account the effects of the rotor ends on the starting and normal operations. The sleeve rotor resistance and leakage reactance have been obtained in terms of the cylindrical geometry of the machine. These equivalent circuit parameters have been calculated and plotted as functions of the motor speed with and without the rotor ends