Brain energy metabolism: A roadmap for future research

Although we have learned much about how the brain fuels its functions over the last decades, there remains much still to discover in an organ that is so complex. This article lays out major gaps in our knowledge of interrelationships between brain metabolism and brain function, including biochemical, cellular, and subcellular aspects of functional metabolism and its imaging in adult brain, as well as during development, aging, and disease. The focus is on unknowns in metabolism of major brain substrates and associated transporters, the roles of insulin and of lipid droplets, the emerging role of metabolism in microglia, mysteries about the major brain cofactor and signaling molecule NAD+, as well as unsolved problems underlying brain metabolism in pathologies such as traumatic brain injury, epilepsy, and metabolic downregulation during hibernation. It describes our current level of understanding of these facets of brain energy metabolism as well as a roadmap for future research

Detection of the PAX3-FKHR fusion gene in paediatric rhabdomyosarcoma: a reproducible predictor of outcome?

Rhabdomyosarcoma has 2 major histological subtypes, embryonal and alveolar. Alveolar histology is associated with the fusion genes PAX3-FKHR and PAX7-FKHR. Definition of alveolar has been complicated by changes in terminology and subjectivity. It is currently unclear whether adverse clinical behaviour is better predicted by the presence of these fusion genes or by alveolar histology. We have determined the presence of the PAX3/7-FKHR fusion genes in 91 primary rhabdomyosarcoma tumours using a combination of classical cytogenetics, FISH and RT-PCR, with a view to determining the clinical characteristics of tumours with and without the characteristic translocations. There were 37 patients with t(2;13)/PAX3-FKHR, 8 with t(1;13) PAX7-FKHR and 46 with neither translocation. One or other of the characteristic translocations was found in 31/38 (82%) of alveolar cases. Univariate survival analysis revealed the presence of the translocation t(2;13)/PAX3-FKHR to be an adverse prognostic factor. With the difficulties in morphological diagnosis of alveolar rhabdomyosarcoma on increasingly used small needle biopsy specimens, these data suggest that molecular analysis for PAX3-FKHR will be a clinically useful tool in treatment stratification in the future. This hypothesis requires testing in a prospective study. Variant t(1;13)/PAX7-FKHR appears biologically different, occurring in younger patients with more localised disease. © 2001 Cancer Research Campaignhttp://www.bjcancer.co

Modelling a Historic Oil-Tank Fire Allows an Estimation of the Sensitivity of the Infrared Receptors in Pyrophilous Melanophila Beetles

Pyrophilous jewel beetles of the genus Melanophila approach forest fires and there is considerable evidence that these beetles can detect fires from great distances of more than 60 km. Because Melanophila beetles are equipped with infrared receptors and are also attracted by hot surfaces it can be concluded that these infrared receptors are used for fire detection

What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology

Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations—e.g., random noise—cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being “suboptimal”. Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the “neural code”. Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise—via stochastic resonance or otherwise—than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing “noise benefits”, and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology