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Ethics Biology: Are There Ethical Genomes?
Published in Howard Winet, Ethics for Bioengineering Scientists, 2021
This experiment could not legally be performed because it would violate the Helsinki Declaration of 1964, as we shall see in Chapter 11. Must we conclude, then, that we shall never be able to test our hypothesis? Not necessarily. There are two indirect approaches that have shed light on our quest for a moral/ethical genome. The first is medical and the second biological. There are clinical cases of patients who have been injured so as to lose function of certain areas of the brain, in particular involving the anterior cingulate cortex (ACC; Kennerly et al. 2006). As a result they were unable to exhibit moral/ethical behavior present before the injury. Where the loss was specific enough to have no apparent effect on non-normative behavior, there was evidence that the ACC played a crucial role in the moral/ethical behavior in question. The DNA sequences responsible for the ACC would then be part of the moral/ethical genome.
An Overview of Operator Fatigue
Published in Gerald Matthews, Paula A. Desmond, Catherine Neubauer, P.A. Hancock, The Handbook of Operator Fatigue, 2017
Gerald Matthews, Paula A. Desmond, Catherine Neubauer, P.A. Hancock
Chronic fatigue may be generated by the biochemical pathways of the body. Watanabe, Kuratsune & Kajimoto (Chapter 14, this volume) survey research on possible biomarkers of fatigue. In fact, multiple biomarkers may exist reflecting different mechanisms. They include metabolites of cellular energy production, hormones produced by the hypothalamo–pituitary–adrenal axis (linking fatigue to stress), and immunological abnormalities. The physiological model advanced by Watanabe et al. is consistent with evidence from brain-imaging studies that implicate serotonergic regulation of the prefrontal cortex and anterior cingulate cortex in fatigue. Correspondingly, Banks, Jackson & Van Dongen (Chapter 11) suggest that the high metabolic rate of the prefrontal cortex confers on it the greatest need for recovery and metabolic slowing during sleep.
Pain Assessment Using Near-Infrared Spectroscopy
Published in Yu Chen, Babak Kateb, Neurophotonics and Brain Mapping, 2017
Kambiz Pourrezaei, Ahmad Pourshoghi, Zeinab Barati, Issa Zakeri
In another group of studies, machine learning methods, such as support vector machine (SVM), have been used to analyze and classify fMRI signals during painful stimulations. Whole-brain patterns of activity were used to train an SVM to distinguish painful from nonpainful thermal stimulation (Brown et al., 2011). An accuracy of 81% was reported for distinguishing painful from nonpainful stimuli. Pain-processing regions of the brain, including the primary somatosensory cortex, secondary somatosensory cortex, insular cortex, primary motor cortex, and cingulate cortex had major contribution to the SVM performance; however, region of interest (ROI) analyses revealed that whole-brain patterns of activity led to a more accurate classification than localized activity from individual brain regions (Brown et al., 2011). In another study (Wager et al., 2013), machine-learning analyses was used to identify a pattern of fMRI activity across brain regions—a neurologic signature—that was associated with heat-induced pain. The pattern included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray matter, and other regions. This group of studies shows that the BOLD signal is sufficiently consistent between individuals to potentially train a physiology-based pain classifier that performs accurately when trained on one group of subjects and tested on another (Brown et al., 2011).
Carnosine in health and disease
Published in European Journal of Sport Science, 2019
Guilherme Giannini Artioli, Craig Sale, Rebecca Louise Jones
Carnosine synthase, an enzyme present in the human skeletal muscle, has been reported in different areas of the mammalian brain (Murakami & Furuse, 2010). As well as carnosine, this ATP-dependent enzyme can synthesise homocarnosine, although this occurs at a lower efficiency. Carnosine is likely to be taken up into brain regions following its release from glial cells, since neurons, mainly those of the olfactory bulb (where carnosine is in greater concentrations), are unable to synthesise carnosine (Hoffmann, Bakardjiev & Bauer, 1996). β-Alanine can be rapidly transported into the brain, with research in rodents demonstrating increased carnosine content in the cerebral cortex and hypothalamus following β-alanine supplementation (Murakami & Furuse, 2010). In vitro studies with isolated human retina showed that β-alanine can be transported into and can accumulate in neuronal cells (Bruun & Ehinger, 1974). It is unclear, however, whether brain carnosine can be increased with β-alanine supplementation and, if so, in what regions this would occur. An in vivo study assessing the effects of β-alanine supplementation on brain carnosine in humans has shown no increase in carnosine in the posterior cingulate cortex following four weeks of β-alanine supplementation (Solis et al., 2015). Notably, the posterior cingulate cortex is highly active and fulfils various functions, such as memory, focus of attention, processing and learning. It must be noted, however, that there are limitations in non-invasive quantification of carnosine in the human brain, such as the inability to distinguish carnosine from homocarnosine signals. It remains unknown whether other areas can benefit from β-alanine supplementation.