Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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Systematic differences in membrane acyl composition associated with varying body mass in mammals occur in all phospholipid classes : an analysis of kidney and brain

The acyl composition of membrane phospholipids in kidney and brain of mammals of different body mass was examined. It was hypothesized that reduction in unsaturation index (number of double bonds per 100 acyl chains) of membrane phospholipids with increasing body mass in mammals would be made-up of similar changes in acyl composition across all phospholipid classes and that phospholipid class distribution would be regulated and similar in the same tissues of the different-sized mammals. The results of this study supported both hypotheses. Differences in membrane phospholipid acyl composition (i. e. decreased omega-3 fats, increased monounsaturated fats and decreased unsaturation index with increasing body size) were not restricted to any specific phospholipid molecule or to any specific phospholipid class but were observed in all phospholipid classes. With increase in body mass of mammals both monounsaturates and use of less unsaturated polyunsaturates increases at the expense of the long-chain highly unsaturated omega-3 and omega-6 polyunsaturates, producing decreases in membrane unsaturation. The distribution of membrane phospholipid classes was essentially the same in the different-sized mammals with phosphatidylcholine (PC) and phosphatidylethanolamine (PE) together constituting similar to 91% and similar to 88% of all phospholipids in kidney and brain, respectively. The lack of sphingomyelin in the mouse tissues and higher levels in larger mammals suggests an increased presence of membrane lipid rafts in larger mammals. The results of this study support the proposal that the physical properties of membranes are likely to be involved in changing metabolic rate.

Validity of accelerometry for measurement of activity in people with brain injury

Purpose To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

International hermelin brain tumor symposium on matricellular proteins in normal and cancer cell-matrix interactions

The second of the Hermelin Brain Tumor Center Symposia was held once again at Henry Ford Hospital in Detroit, Michigan on October 24th and 25th, 2003. A public conference was held on the 24th while a closed-door session took place on the 25th. The purpose of these symposia is to bring together experts in a particular field of study with the aim to share information with each other and the public, but then to meet privately to present novel data, hold discussions, and share concepts. While the interaction is intended to benefit all involved, the incentive is the expectation that the shared information will aid researchers at the Hermelin Brain Tumor Center in their quest to identify potential therapeutic targets and explore translational therapeutic strategies for the treatment of patients suffering nervous system tumors...

Improving the detection of donations within the RHD negative blood donor panel which weakly express the RHD antigen

This project improved the detection and classification of very weakly expressed RhD variants in the Australian blood donor panel and contributed to the knowledge of anti-D reactivity patterns of RHD alleles that are undescribed. As such, the management of donations possessing these RHD alleles can be improved upon and the overall safety of transfusion medicine pertaining to the Rh blood group system will be increased. Future projects at ARCBS will be able to utilise the procedures developed in this project, thereby decreasing throughput time. The specificity of current testing will be improved and the need for outsourced RHD testing diminished.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

The brain-specific microRNA miR-128b regulates the formation of fear-extinction memory

MicroRNAs are small non-coding RNAs that mediate post-transcriptional gene silencing. Fear-extinction learning in C57/Bl6J mice led to increased expression of the brain-specific microRNA miR-128b, which disrupted stability of several plasticity-related target genes and regulated formation of fear-extinction memory. Increased miR-128b activity may therefore facilitate the transition from retrieval of the original fear memory toward the formation of a new fear-extinction memory.

Brain networks subserving the evaluation of static and dynamic facial expressions

Because moving depictions of face emotion have greater ecological validity than their static counterparts, it has been suggested that still photographs may not engage ‘authentic’ mechanisms used to recognize facial expressions in everyday life. To date, however, no neuroimaging studies have adequately addressed the question of whether the processing of static and dynamic expressions rely upon different brain substrates. To address this, we performed an functional magnetic resonance imaging (fMRI) experiment wherein participants made emotional expression discrimination and Sex discrimination judgements to static and moving face images. Compared to Sex discrimination, Emotion discrimination was associated with widespread increased activation in regions of occipito-temporal, parietal and frontal cortex. These regions were activated both by moving and by static emotional stimuli, indicating a general role in the interpretation of emotion. However, portions of the inferior frontal gyri and supplementary/pre-supplementary motor area showed task by motion interaction. These regions were most active during emotion judgements to static faces. Our results demonstrate a common neural substrate for recognizing static and moving facial expressions, but suggest a role for the inferior frontal gyrus in supporting simulation processes that are invoked more strongly to disambiguate static emotional cues.

Role of capsule and O antigen in the virulence of uropathogenic Escherichia coli

Urinary tract infection (UTI) is one of the most common bacterial infections in humans, with uropathogenic Escherichia coli (UPEC) the leading causative organism. UPEC has a number of virulence factors that enable it to overcome host defenses within the urinary tract and establish infection. The O antigen and the capsular polysaccharide are two such factors that provide a survival advantage to UPEC. Here we describe the application of the rpsL counter selection system to construct capsule (kpsD) and O antigen (waaL) mutants and complemented derivatives of three reference UPEC strains: CFT073 (O6:K2:H1), RS218 (O18:K1:H7) and 1177 (O1:K1:H7). We observed that while the O1, O6 and O18 antigens were required for survival in human serum, the role of the capsule was less clear and linked to O antigen type. In contrast, both the K1 and K2 capsular antigens provided a survival advantage to UPEC in whole blood. In the mouse urinary tract, mutation of the O6 antigen significantly attenuated CFT073 bladder colonization. Overall, this study contrasts the role of capsule and O antigen in three common UPEC serotypes using defined mutant and complemented strains. The combined mutagenesis-complementation strategy can be applied to study other virulence factors with complex functions both in vitro and in vivo.

The antigen 43 structure reveals a molecular velcro-like mechanism of autotransporter-mediated bacterial clumping

Aggregation and biofilm formation are critical mechanisms for bacterial resistance to host immune factors and antibiotics. Autotransporter (AT) proteins, which represent the largest group of outer-membrane and secreted proteins in Gram-negative bacteria, contribute significantly to these phenotypes. Despite their abundance and role in bacterial pathogenesis, most AT proteins have not been structurally characterized, and there is a paucity of detailed information with regard to their mode of action. Here we report the structure–function relationships of Antigen 43 (Ag43a), a prototypic self-associating AT protein from uropathogenic Escherichia coli. The functional domain of Ag43a displays a twisted L-shaped β-helical structure firmly stabilized by a 3D hydrogen-bonded scaffold. Notably, the distinctive Ag43a L shape facilitates self-association and cell aggregation. Combining all our data, we define a molecular “Velcro-like” mechanism of AT-mediated bacterial clumping, which can be tailored to fit different bacterial lifestyles such as the formation of biofilms.

The glycosphingolipid P1 is an ovarian cancer-associated carbohydrate antigen involved in migration

Background The level of plasma-derived naturally circulating anti-glycan antibodies (AGA) to P1 trisaccharide has previously been shown to significantly discriminate between ovarian cancer patients and healthy women. Here we aim to identify the Ig class that causes this discrimination, to identify on cancer cells the corresponding P1 antigen recognised by circulating anti-P1 antibodies and to shed light into the possible function of this glycosphingolipid. Method An independent Australian cohort was assessed for the presence of anti-P1 IgG and IgM class antibodies using suspension array. Monoclonal and human derived anti-glycan antibodies were verified using three independent glycan-based immunoassays and flow cytometry-based inhibition assay. The P1 antigen was detected by LC-MS/MS and flow cytometry. FACS-sorted cell lines were studied on the cellular migration by colorimetric assay and real-time measurement using xCELLigence system. Results Here we show in a second independent cohort (n=155) that the discrimination of cancer patients is mediated by the IgM class of anti-P1 antibodies (P=0.0002). The presence of corresponding antigen P1 and structurally related epitopes in fresh tissue specimens and cultured cancer cells is demonstrated. We further link the antibody and antigen (P1) by showing that human naturally circulating and affinity-purified anti-P1 IgM isolated from patients ascites can bind to naturally expressed P1 on the cell surface of ovarian cancer cells. Cell-sorted IGROV1 was used to obtain two study subpopulations (P1-high, 66.1%; and P1-low, 33.3%) and observed that cells expressing high P1-levels migrate significantly faster than those with low P1-levels. Conclusions This is the first report showing that P1 antigen, known to be expressed on erythrocytes only, is also present on ovarian cancer cells. This suggests that P1 is a novel tumour-associated carbohydrate antigen recognised by the immune system in patients and may have a role in cell migration. The clinical value of our data may be both diagnostic and prognostic; patients with low anti-P1 IgM antibodies present with a more aggressive phenotype and earlier relapse.

Functional magnetic resonance brain imaging of executive cognitive performance in young first-episode schizophrenia patients and age-matched long-term cannabis users

Converging evidence from epidemiological, clinical and neuropsychological research suggests a link between cannabis use and increased risk of psychosis. Long-term cannabis use has also been related to deficit-like “negative” symptoms and cognitive impairment that resemble some of the clinical and cognitive features of schizophrenia. The current functional brain imaging study investigated the impact of a history of heavy cannabis use on impaired executive function in first-episode schizophrenia patients. Whilst performing the Tower of London task in a magnetic resonance imaging scanner, event-related blood oxygenation level-dependent (BOLD) brain activation was compared between four age and gender-matched groups: 12 first-episode schizophrenia patients; 17 long-term cannabis users; seven cannabis using first-episode schizophrenia patients; and 17 healthy control subjects. BOLD activation was assessed as a function of increasing task difficulty within and between groups as well as the main effects of cannabis use and the diagnosis of schizophrenia. Cannabis users and non-drug using first-episode schizophrenia patients exhibited equivalently reduced dorsolateral prefrontal activation in response to task difficulty. A trend towards additional prefrontal and left superior parietal cortical activation deficits was observed in cannabis-using first-episode schizophrenia patients while a history of cannabis use accounted for increased activation in the visual cortex. Cannabis users and schizophrenia patients fail to adequately activate the dorsolateral prefrontal cortex, thus pointing to a common working memory impairment which is particularly evident in cannabis-using first-episode schizophrenia patients. A history of heavy cannabis use, on the other hand, accounted for increased primary visual processing, suggesting compensatory imagery processing of the task.

The influence of psychosocial factors on expectations and persistent symptom report after mild traumatic brain injury

This thesis examines how psychosocial factors influence the report of persistent symptoms after mild traumatic brain injury. Using quasi-experimental methods, the research program demonstrates how factors unrelated to trauma-induced physiological brain damage can contribute to persistent symptoms after a mild traumatic brain injury. The results of this thesis highlight the possibility that outcome from mild traumatic brain injury could be improved by targeting psychosocial factors.