Expression, regulation and putative nutrient-sensing function of taste GPCRs in the heart

G protein-coupled receptors (GPCRs) are critical for cardiovascular physiology. Cardiac cells express >100 nonchemosensory GPCRs, indicating that important physiological and potential therapeutic targets remain to be discovered. Moreover, there is a growing appreciation that members of the large, distinct taste and odorant GPCR families have specific functions in tissues beyond the oronasal cavity, including in the brain, gastrointestinal tract and respiratory system. To date, these chemosensory GPCRs have not been systematically studied in the heart. We performed RT-qPCR taste receptor screens in rodent and human heart tissues that revealed discrete subsets of type 2 taste receptors (TAS2/Tas2) as well as Tas1r1 and Tas1r3 (comprising the umami receptor) are expressed. These taste GPCRs are present in cultured cardiac myocytes and fibroblasts, and are enriched in myocytes, which we corroborated using in situ hybridization. Tas1r1 gene-targeted mice (Tas1r1Cre/Rosa26tdRFP) strikingly recapitulated these data. In vivo taste receptor expression levels were developmentally regulated in the postnatal period. Intriguingly, several Tas2rs were upregulated in cultured rat myocytes and in mouse heart in vivo following starvation. The discovery of taste GPCRs in the heart opens an exciting new field of cardiac research. We predict that these taste receptors may function as nutrient sensors in the heart.

Investigation of brain derived neurotrophic factor (BDNF) gene variants in migraine

A number of observations have suggested that brain derived neurotrophic factor (BDNF) plays a role in migraine pathophysiology. This study investigates whether variants in the BDNF gene are associated with migraine in an Australian case-control population. Background. Brain derived neurotrophic factor (BDNF) has an important role in neural growth, development and survival in the central nervous system and is an important modulator of central and peripheral pain responses. Variants in BDNF, in particular the functional Val66Met polymorphism (rs6265), have been found to be associated with a number of psychiatric disorders, cognitive function and obesity. As BDNF has been found to be differentially expressed in a number of aspects related to migraine, we tested for association between single nucleotide polymorphisms (SNPs) in BDNF and migraine. Methods. Five SNPs in the BDNF locus (rs1519480, rs6265, rs712507, rs2049046 and rs12273363) were genotyped initially in a cohort of 277 migraine cases, including 172 diagnosed with migraine with aura (MA) and 105 with migraine without aura (MO), and 277 age- and sex-matched controls. Three of these SNPs (rs6265, rs2049046 and rs12273363) were subsequently genotyped in a second cohort of 580 migraineurs, including 473 diagnosed with MA and 105 with O, and 580 matched controls. Results. – BDNF SNPs rs1519480, rs6265, rs712507 and rs12273363 were not significantly associated with migraine. However, rs2049046 showed a significant association with migraine, and in particular, MA in the first cohort. In the second cohort, although an increase in the rs2049046 T-allele frequency was observed in migraine cases, and in both MA and MO subgroups, it was not significantly different from controls. Analysis of data combined from both cohorts for rs2049046 showed significant differences in the genotypic and allelic distributions for this marker in both migraine and the MA sub-group. Conclusion. This study confirmed previous studies that the functional BDNF SNP rs6265 (Val66Met) is not associated with migraine. However, we found that rs2049046, which resides at the 5’ end of 3 one the BDNF transcripts, may be associated with migraine, suggesting that further investigations of this SNP may be warranted.

Rodent Scope: A User-Configurable Digital Wireless Telemetry System for Freely Behaving Animals

This paper describes the design and implementation of a wireless neural telemetry system that enables new experimental paradigms, such as neural recordings during rodent navigation in large outdoor environments. RoSco, short for Rodent Scope, is a small lightweight user-configurable module suitable for digital wireless recording from freely behaving small animals. Due to the digital transmission technology, RoSco has advantages over most other wireless modules of noise immunity and online user-configurable settings. RoSco digitally transmits entire neural waveforms for 14 of 16 channels at 20 kHz with 8-bit encoding which are streamed to the PC as standard USB audio packets. Up to 31 RoSco wireless modules can coexist in the same environment on non-overlapping independent channels. The design has spatial diversity reception via two antennas, which makes wireless communication resilient to fading and obstacles. In comparison with most existing wireless systems, this system has online user-selectable independent gain control of each channel in 8 factors from 500 to 32,000 times, two selectable ground references from a subset of channels, selectable channel grounding to disable noisy electrodes, and selectable bandwidth suitable for action potentials (300 Hz–3 kHz) and low frequency field potentials (4 Hz–3 kHz). Indoor and outdoor recordings taken from freely behaving rodents are shown to be comparable to a commercial wired system in sorting for neural populations. The module has low input referred noise, battery life of 1.5 hours and transmission losses of 0.1% up to a range of 10 m.

Ghrelin and the brain-gut axis as a pharmacological target for appetite control

Appetite regulation is highly complex and involves a large number of orexigenic and anorexigenic peptide hormones. These are small, processed, secreted peptides derived from larger prepropeptide precursors. These peptides are important targets for the development of therapeutics for obesity, a global health epidemic. As a case study, we consider the ghrelin axis. The ghrelin axis is likely to be a particularly useful drug target, as it also plays a role in energy homeostasis, adipogenesis, insulin regulation and reward associated with food intake. Ghrelin is the only known circulating gut orexigenic peptide hormone. As it appears to play a role in diet-induced obesity, blocking the action of ghrelin is likely to be effective for treating and preventing obesity. The ghrelin peptide has been targeted using a number of approaches, with ghrelin mirror-image oligonucleotides (Spiegelmers) and immunotherapy showing some promise. The ghrelin receptor, the growth hormone secretagogue receptor, may also provide a useful target and a number of antagonists and inverse agonists have been developed. A particularly promising new target is the enzyme which octanoylates ghrelin, ghrelin O-acyltransferase (GOAT), and drugs that inhibit GOAT are likely to circumvent pharmacological issues associated with approaches that directly target ghrelin or its receptor.

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. Rev. , 36 (2--3), 2001, 108--118. doi:10.1016/S0165-0173(01)00086-8 S. Ogawa, R. S. Menon, S. G. Kim and K. Ugurbil, On the characteristics of functional magnetic resonance imaging of the brain, Annu. Rev. Bioph. Biom. , 27 , 1998, 447--474. doi:10.1146/annurev.biophys.27.1.447 C. D. Binnie and H. Stefan, Modern electroencephalography: its role in epilepsy management, Clin. Neurophysiol. , 110 (10), 1999, 1671--1697. doi:10.1016/S1388-2457(99)00125-X J. X. Tao, A. Ray, S. Hawes-Ebersole and J. S. Ebersole, Intracranial eeg substrates of scalp eeg interictal spikes, Epilepsia , 46 (5), 2005, 669--76. doi:10.1111/j.1528-1167.2005.11404.x S. Ogawa, D. W. Tank, R. Menon, J. M. Ellermann, S. G. Kim, H. Merkle and K. Ugurbil, Intrinsic signal changes accompanying sensory stimulation: Functional brain mapping with magnetic resonance imaging, P. Natl. Acad. Sci. USA , 89 (13), 1992, 5951--5955. doi:10.1073/pnas.89.13.5951 J. Engel Jr., Report of the ilae classification core group, Epilepsia , 47 (9), 2006, 1558--1568. doi:10.1111/j.1528-1167.2006.00215.x L. Lemieux, A. Salek-Haddadi, O. Josephs, P. Allen, N. Toms, C. Scott, K. Krakow, R. Turner and D. R. Fish, Event-related fmri with simultaneous and continuous eeg: description of the method and initial case r port, NeuroImage , 14 (3), 2001, 780--7. doi:10.1006/nimg.2001.0853 P. Federico, D. F. Abbott, R. S. Briellmann, A. S. Harvey and G. D. Jackson, Functional mri of the pre-ictal state, Brain , 128 (8), 2005, 1811-7. doi:10.1093/brain/awh533 C. S. Hawco, A. P. Bagshaw, Y. Lu, F. Dubeau and J. Gotman, bold changes occur prior to epileptic spikes seen on scalp eeg, NeuroImage , 35 (4), 2007, 1450--1458. doi:10.1016/j.neuroimage.2006.12.042 F. Moeller, H. R. Siebner, S. Wolff, H. Muhle, R. Boor, O. Granert, O. Jansen, U. Stephani and M. Siniatchkin, Changes in activity of striato-thalamo-cortical network precede generalized spike wave discharges, NeuroImage , 39 (4), 2008, 1839--1849. doi:10.1016/j.neuroimage.2007.10.058 V. Osharina, E. Ponchel, A. Aarabi, R. Grebe and F. Wallois, Local haemodynamic changes preceding interictal spikes: A simultaneous electrocorticography (ecog) and near-infrared spectroscopy (nirs) analysis in rats, NeuroImage , 50 (2), 2010, 600--607. doi:10.1016/j.neuroimage.2010.01.009 R. S. Fisher, W. Boas, W. Blume, C. Elger, P. Genton, P. Lee and J. Engel, Epileptic seizures and epilepsy: Definitions proposed by the international league against epilepsy (ilae) and the international bureau for epilepsy (ibe), Epilepsia , 46 (4), 2005, 470--472. doi:10.1111/j.0013-9580.2005.66104.x H. Berger, Electroencephalogram in humans, Arch. Psychiat. Nerven. , 87 , 1929, 527--570. C. M. Michel, M. M. Murray, G. Lantz, S. Gonzalez, L. Spinelli and R. G. de Peralta, eeg source imaging, Clin. Neurophysiol. , 115 (10), 2004, 2195--2222. doi:10.1016/j.clinph.2004.06.001 P. L. Nunez and R. B. Silberstein, On the relationship of synaptic activity to macroscopic measurements: Does co-registration of eeg with fmri make sense?, Brain Topogr. , 13 (2), 2000, 79--96. doi:10.1023/A:1026683200895 S. Ogawa, T. M. Lee, A. R. Kay and D. W. Tank, Brain magnetic resonance imaging with contrast dependent on blood oxygenation, P. Natl. Acad. Sci. USA , 87 (24), 1990, 9868--9872. doi:10.1073/pnas.87.24.9868 J. S. Gati, R. S. Menon, K. Ugurbil and B. K. Rutt, Experimental determination of the bold field strength dependence in vessels and tissue, Magn. Reson. Med. , 38 (2), 1997, 296--302. doi:10.1002/mrm.1910380220 P. A. Bandettini, E. C. Wong, R. S. Hinks, R. S. Tikofsky and J. S. Hyde, Time course EPI of human brain function during task activation, Magn. Reson. Med. , 25 (2), 1992, 390--397. K. K. Kwong, J. W. Belliveau, D. A. Chesler, I. E. Goldberg, R. M. Weisskoff, B. P. Poncelet, D. N. Kennedy, B. E. Hoppelm, M. S. Cohen and R. Turner, Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation, P. Natl. Acad. Sci. USA , 89 (12), 1992, 5675--5679. doi:10.1073/pnas.89.12.5675 J. Frahm, K. D. Merboldt and W. Hnicke, Functional mri of human brain activation at high spatial resolution, Magn. Reson. Med. , 29 (1), 1993, 139--144. P. A. Bandettini, A. Jesmanowicz, E. C. Wong and J. S. Hyde, Processing strategies for time-course data sets in functional MRI of the human brain, Magn. Reson. Med. , 30 (2), 1993, 161--173. K. J. Friston, P. Jezzard and R. Turner, Analysis of functional MRI time-series, Hum. Brain Mapp. , 1 (2), 1994, 153--171. B. Biswal, F. Z. Yetkin, V. M. Haughton and J. S. Hyde, Functional connectivity in the motor cortex of resting human brain using echo-planar mri, Mag. Reson. Med. , 34 (4), 1995, 537--541. doi:10.1002/mrm.1910340409 K. J. Friston, J. Ashburner, C. D. Frith, J. Poline, J. D. Heather and R. S. J. Frackowiak, Spatial registration and normalization of images, Hum. Brain Mapp. , 3 (3), 1995, 165--189. K. J. Friston, S. Williams, R. Howard, R. S. Frackowiak and R. Turner, Movement-related effects in fmri time-series, Magn. Reson. Med. , 35 (3), 1996, 346--355. G. H. Glover, T. Q. Li and D. Ress, Image-based method for retrospective correction of physiological motion effects in fmri: Retroicor, Magn. Reson. Med. , 44 (1), 2000, 162--167. doi:10.1002/1522-2594(200007)44:13.0.CO;2-E K. J. Friston, O. Josephs, G. Rees and R. Turner, Nonlinear event-related responses in fmri, Magn. Reson. Med. , 39 (1), 1998, 41--52. doi:10.1002/mrm.1910390109 K. Ugurbil, L. Toth and D. Kim, How accurate is magnetic resonance imaging of brain function?, Trends Neurosci. , 26 (2), 2003, 108--114. doi:10.1016/S0166-2236(02)00039-5 D. S. Kim, I. Ronen, C. Olman, S. G. Kim, K. Ugurbil and L. J. Toth, Spatial relationship between neuronal activity and bold functional mri, NeuroImage , 21 (3), 2004, 876--885. doi:10.1016/j.neuroimage.2003.10.018 A. Connelly, G. D. Jackson, R. S. Frackowiak, J. W. Belliveau, F. Vargha-Khadem and D. G. Gadian, Functional mapping of activated human primary cortex with a clinical mr imaging system, Radiology , 188 (1), 1993, 125--130. L. Allison, Hidden Markov Models, Technical Report , School of Computer and Software Engineering, Monash University, 2000. R. J. Elliott, L. Aggoun and J.B. Moore, Hidden Markov Models: Estimation and Control, Appl. Math.-Czech. , 2004. B. Bhavnagri, Discontinuities of plane functions projected from a surface with methods for finding these , Technical Report, 2009. B. Bhavnagri, Computer Vision using Shape Spaces , Technical Report,1996, University of Adelaide. B. Bhavnagri, A method for representing shape based on an equivalence relation on polygons, Pattern Recogn. , 27 (2), 1994, 247--260. doi:10.1016/0031-3203(94)90057-4 D. F. Abbott, A. B. Waites, A. S. Harvey and G. D. Jackson, Exploring epileptic seizure onset with fmri, NeuroImage , 36(S1) (344TH-PM), 2007. M. C. Mackey and L. Glass, Oscillation and chaos in physiological control systems, Science , 197 , 1977, 287--289. S. H. Strogatz, SYNC - The Emerging Science of Spontaneous Order , Theia, New York, 2003. J. W. Kim, J. A. Roberts and P. A. Robinson, Dynamics of epileptic seizures: Evolution, spreading, and suppression, J. Theor. Biol. , 257 (4), 2009, 527--532. doi:10.1016/j.jtbi.2008.12.009 Y. Kuramoto, T. Aoyagi, I. Nishikawa, T. Chawanya T and K. Okuda, Neural network model carrying phase information with application to collective dynamics, J. Theor. Phys. , 87 (5), 1992, 1119--1126. V. B. Mountcastle, The columnar organization of the neocortex, Brain , 120 (4), 1997, 701. doi:10.1093/brain/120.4.701 F. L. Silva, W. Blanes, S. N. Kalitzin, J. Parra, P. Suffczynski and D. N. Velis, Epilepsies as dynamical diseases of brain systems: Basic models of the transition between normal and epileptic activity, Epilepsia , 44 (12), 2003, 72--83. F. H. Lopes da Silva, W. Blanes, S. N. Kalitzin, J. Parra, P. Suffczynski and D. N. Velis, Dynamical diseases of brain systems: different routes to epileptic seizures, ieee T. Bio-Med. Eng. , 50 (5), 2003, 540. L.D. Iasemidis, Epileptic seizure prediction and control, ieee T. Bio-Med. Eng. , 50 (5), 2003, 549--558. L. D. Iasemidis, D. S. Shiau, W. Chaovalitwongse, J. C. Sackellares, P. M. Pardalos, J. C. Principe, P. R. Carney, A. Prasad, B. Veeramani, and K. Tsakalis, Adaptive epileptic seizure prediction system, ieee T. Bio-Med. Eng. , 50 (5), 2003, 616--627. K. Lehnertz, F. Mormann, T. Kreuz, R.G. Andrzejak, C. Rieke, P. David and C. E. Elger, Seizure prediction by nonlinear eeg analysis, ieee Eng. Med. Biol. , 22 (1), 2003, 57--63. doi:10.1109/MEMB.2003.1191451 K. Lehnertz, R. G. Andrzejak, J. Arnhold, T. Kreuz, F. Mormann, C. Rieke, G. Widman and C. E. Elger, Nonlinear eeg analysis in epilepsy: Its possible use for interictal focus localization, seizure anticipation, and prevention, J. Clin. Neurophysiol. , 18 (3), 2001, 209. B. Litt and K. Lehnertz, Seizure prediction and the preseizure period, Curr. Opin. Neurol. , 15 (2), 2002, 173. doi:10.1097/00019052-200204000-00008 B. Litt and J. Echauz, Prediction of epileptic seizures, Lancet Neurol. , 1 (1), 2002, 22--30. doi:10.1016/S1474-4422(02)00003-0 M. M{a}kiranta, J. Ruohonen, K Suominen, J. Niinim{a}ki, E. Sonkaj{a}rvi, V. Kiviniemi, T. Sepp{a}nen, S. Alahuhta, V. J{a}ntti and O. Tervonen, {bold} signal increase preceeds eeg spike activity--a dynamic penicillin induced focal epilepsy in deep anesthesia, NeuroImage , 27 (4), 2005, 715--724. doi:10.1016/j.neuroimage.2005.05.025 K. Lehnertz, F. Mormann, H. Osterhage, A. M{u}ller, J. Prusseit, A. Chernihovskyi, M. Staniek, D. Krug, S. Bialonski and C. E. Elger, State-of-the-art of seizure prediction, J. Clin. Neurophysiol. , 24 (2), 2007, 147. doi:10.1097/WNP.0b013e3180336f16 F. Mormann, T. Kreuz, C. Rieke, R. G. Andrzejak, A. Kraskov, P. David, C. E. Elger and K. Lehnertz, On the predictability of epileptic seizures, Clin. Neurophysiol. , 116 (3), 2005, 569--587. doi:10.1016/j.clinph.2004.08.025 F. Mormann, R. G. Andrzejak, C. E. Elger and K. Lehnertz, Seizure prediction: the long and winding road, Brain , 130 (2), 2007, 314--333. doi:10.1093/brain/awl241 Z. Rogowski, I. Gath and E. Bental, On the prediction of epileptic seizures, Biol. Cybern. , 42 (1), 1981, 9--15. Y. Salant, I. Gath, O. Henriksen, Prediction of epileptic seizures from two-channel eeg, Med. Biol. Eng. Comput. , 36 (5), 1998, 549--556. doi:10.1007/BF02524422 J. Gotman and D.J. Koffler, Interictal spiking increases after seizures but does not after decrease in medication, Evoked Potential , 72 (1), 1989, 7--15. J. Gotman and M. G. Marciani, Electroencephalographic spiking activity, drug levels, and seizure occurence in epileptic patients, Ann. Neurol. , 17 (6), 1985, 59--603. A. Katz, D. A. Marks, G. McCarthy and S. S. Spencer, Does interictal spiking change prior to seizures?, Electroen. Clin. Neuro. , 79 (2), 1991, 153--156. A. Granada, R. M. Hennig, B. Ronacher, A. Kramer and H. Herzel, Phase Response Curves: Elucidating the dynamics of couples oscillators, Method Enzymol. , 454 (A), 2009, 1--27. doi:10.1016/S0076-6879(08)03801-9 doi:10.1016/S0076-6879(08)03801-9 H. Kantz and T. Schreiber, Nonlinear time series analysis , 2004, Cambridge Univ Press. M. V. L. Bennett and R. S Zukin, Electrical coupling and neuronal synchronization in the mammalian brain, Neuron , 41 (4), 2004, 495 --511. doi:10.1016/S0896-6273(04)00043-1 L.D. Iasemidis, J. Chris Sackellares, H. P. Zaveri and W. J. Williams, Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures, Brain Topogr. , 2 (3), 1990, 187--201. doi:10.1007/BF01140588 M. Le Van Quyen, J. Martinerie, V. Navarro, M. Baulac and F. J. Varela, Characterizing neurodynamic changes before seizures, J. Clin. Neurophysiol. , 18 (3), 2001, 191. J. Martinerie, C. Adam, M. Le Van Quyen, M. Baulac, S. Clemenceau, B. Renault and F. J. Varela, Epileptic seizures can be anticipated by non-linear analysis, Nat. Med. , 4 (10), 1998, 1173--1176. doi:10.1038/2667 A. Pikovsky, M. Rosenblum, J. Kurths and R. C. Hilborn, Synchronization: A universal concept in nonlinear science, Amer. J. Phys. , 70 , 2002, 655. H. R. Wilson and J. D. Cowan, Excitatory and inhibitory interactions in localized populations of model neurons, Biophys. J. , 12 (1), 1972, 1--24. D. Cumin and C. P. Unsworth, Generalising the Kuramoto model for the study of neuronal synchronisation in the brain, Physica D , 226 (2), 2007, 181--196. doi:10.1016/j.physd.2006.12.004 F. K. Skinner, H. Bazzazi and S. A. Campbell, Two-cell to N-cell heterogeneous, inhibitory networks: Precise linking of multistable and coherent properties, J. Comput. Neurosci. , 18 (3), 2005, 343--352. doi:10.1007/s10827-005-0331-1 W. W. Lytton, Computer modelling of epilepsy, Nat. Rev. Neurosci. , 9 (8), 2008, 626--637. doi:10.1038/nrn2416 R. D. Traub, A. Bibbig, F. E. N. LeBeau, E. H. Buhl and M. A. Whittington, Cellular mechanisms of neuronal population oscillations in the hippocampus in vitro, Ann. Rev. , 2004. R. D. Traub, A. Draguhn, M. A. Whittington, T. Baldeweg, A. Bibbig, E. H. Buhl and D. Schmitz, Axonal gap junc ions between principal neurons: A novel source of network oscillations, and perhaps epileptogenesis., Rev. Neuroscience , 13 (1), 2002, 1. doi:10.1146/annurev.neuro.27.070203.144303 M. Scheffer, J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, H. Held, E. H. van Nes, M. Rietkerk and G. Sugihara, Early-warning signals for critical transitions, Nature , 461 (7260), 2009, 53--59. doi:10.1038/nature08227 K. Murphy, A Brief Introduction to Graphical Models and Bayesian Networks , 2008, http://www.cs.ubc.ca/murphyk/Bayes/bnintro.html . R. C. Bradley, An elementary

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...

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.

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.

The current state of play in human neural stem cell models : what we have learnt from the rodent

Rodent (mouse and rat) models have been crucial in developing our understanding of human neurogenesis and neural stem cell (NSC) biology. The study of neurogenesis in rodents has allowed us to begin to understand adult human neurogenesis and in particular, protocols established for isolation and in vitro propagation of rodent NSCs have successfully been applied to the expansion of human NSCs. Furthermore, rodent models have played a central role in studying NSC function in vivo and in the development of NSC transplantation strategies for cell therapy applications. Rodents and humans share many similarities in the process of neurogenesis and NSC biology however distinct species differences are important considerations for the development of more efficient human NSC therapeutic applications. Here we review the important contributions rodent studies have had to our understanding of human neurogenesis and to the development of in vitro and in vivo NSC research. Species differences will be discussed to identify key areas in need of further development for human NSC therapy applications.