Brain Energy

Abstract Following the pragmatic practices of anesthesiologists, a person is defined to be in the state of consciousness by the ability to respond to stimuli. C Magnetic Resonance Spectroscopy (MRS), Positron Emission Tomography (PET), and electrophysiology experiments have been directed towards these goals. These studies have measured brain energy production in the form of glucose oxidation in the resting baseline and anesthetized states and have followed regional changes during stimulation from these states. PET and MRS methods have measured the total or baseline energies while neuroimaging studies, by fMRI and PET, have determined the incremental energies during cognitive or sensory stimulations. The most striking result is that the energy consumption supporting neuronal firing in the conscious-awake, baseline state is one to two orders of magnitude larger than the energy changes during stimulation Early functional imaging studies by It soon became clear, however, that the brain did not follow the simple assumptions of "pure insertion" which expects the incremental brain neuronal response to a mental process to be independent of its context. The dependence of brain responses upon their context created problems for cognitive psychology, which had assumed, for example, that all acts of remembering would require brain to use a similar module of "memory". Jerry Fodor, a founder of the field, concluded in 2000 that this original formulation was not supported experimentally and in his book with that title recognized that "the mind does not work that way" In the face of these results, prominent neuroimagers tried to retain the potential value of cognitive concepts by considering that the dependence upon context arose from the non-linear nature of brain responses In this report we examine what neuroimaging can tell us about a human in the state of consciousness by using an alternate approach which does not assume that consciousness is supported by hypothesized mental processes. In our study, brain experiments are used to determine neuronal and energetic properties of a behavioral state, as distinguished from the claims that imaging results localize theorized mental processes in the brain. Furthermore, we include a central role for the high baseline level of neuronal activity that is removed by differencing in the large majority of functional imaging studies. In both these respects they offer a previously untried methodology for relating brain activities to observable behavior. We believe that baseline brain activities provide necessary support for behavioral processes that are characteristic of the human or rodent in the state of consciousness. In our view, memory, intent, etcetera are contingent assumptions of mental processes presumed to underlie actions performed by the person. Rather than hypothesizing and then localizing psychological assumptions about the contents of consciousness, in our studies the subjects, rat or human, are defined as being in a conscious state by observations of reproducible behavior. In our definition, the state of consciousness enables a person to perform the many actions that Zeman ( 2002) called the Psyche, Vol 15, No 2 (2009) Brain Energy 62 contents of consciousness. These are the actions, feelings, thoughts, sensory interconnections, etcetera, which are described in common parlance as being caused by mental processes. These observables are postulated in neuroimaging studies to be identified with concepts, for example, memory, attention or recognition, and are then sought in localized brain activities. Uncertainties in this methodology have been revealed by the widely recognized dependence of these concepts upon the context in which they are embedded. To avoid these complexities we are correlating brain activities not with such specific assumptions about the contents of consciousness, but rather with the state of consciousness of a human or of the rat. We describe the state of consciousness simply by the subject's ability to respond to stimuli using the criteria established in anesthesia We propose that high cerebral energy (and by inference its coupled neuronal activity) in the awake state defines a necessary property of the consciousness state; when the energy is reduced sufficiently, there is loss of consciousness. Two additional brain properties that we have measured are the fMRI activation patterns and neuronal population activity with change with baseline state. In this paper, we first review the methods developed (primarily in our laboratory) to measure brain energy consumption and their use in studies of the coupled neuronal signaling, which is the work of the brain (Section I). These studies have shown that, above a relatively small level of non-functional energy, brain energy consumption is coupled to the firing of glutamatergic neurons in the cerebral cortex and the coupled ATP consumption during neuronal signaling (e.g., action and field potentials, neurotransmitter release, and recycling, etc). Then we describe experimental measurements of brain properties of the state of consciousness (Section II). The brain energy distribution and the range of energy consumption in the fully awake state measured by PET and fMRI studies are reviewed. Overall, it is shown that in the state of consciousness, the brain energy, and by inference the neuronal signaling, is evenly distributed throughout the cortex. Fluctuations in energy are small compared to the resting brain energy in the fully awake state. PET reports of subjects undergoing graded anesthesia are then reviewed to show the reduced energy levels (and its regional distribution) at which subjects lose consciousness, as defined by the loss of response to stimuli. Next we discuss two additional brain properties, fMRI activation patterns and the firing rates of neuronal populations that change significantly with baseline energy. Finally, we discuss implications of our proposal that measurable brain properties provide insight to the state of consciousness (Section III). Current definitions, philosophies, and theories for the state of consciousness are discussed to demonstrate how measurable brain properties are beginning to sketch a physical understanding of the interconnected behavior representing that state, without a priori assumptions about underlying mental processes

Oral microbial communities in children, caregivers, and associations with salivary biomeasures and environmental tobacco smoke exposure

Human oral microbial communities are diverse, with implications for oral and systemic health. Oral microbial communities change over time; thus, it is important to understand how healthy versus dysbiotic oral microbiomes differ, especially within and between families. There is also a need to understand how the oral microbiome composition is changed within an individual including by factors such as environmental tobacco smoke (ETS) exposure, metabolic regulation, inflammation, and antioxidant potential. Using archived saliva samples collected from caregivers and children during a 90-month follow-up assessment in a longitudinal study of child development in the context of rural poverty, we used 16S rRNA gene sequencing to determine the salivary microbiome. A total of 724 saliva samples were available, 448 of which were from caregiver/child dyads, an additional 70 from children and 206 from adults. We compared children’s and caregivers’ oral microbiomes, performed “stomatotype” analyses, and examined microbial relations with concentrations of salivary markers associated with ETS exposure, metabolic regulation, inflammation, and antioxidant potential (i.e., salivary cotinine, adiponectin, C-reactive protein, and uric acid) assayed from the same biospecimens. Our results indicate that children and caregivers share much of their oral microbiome diversity, but there are distinct differences. Microbiomes from intrafamily individuals are more similar than microbiomes from nonfamily individuals, with child/caregiver dyad explaining 52% of overall microbial variation. Notably, children harbor fewer potential pathogens than caregivers, and participants’ microbiomes clustered into two groups, with major differences being driven by Streptococcus spp. Differences in salivary microbiome composition associated with ETS exposure, and taxa associated with salivary analytes representing potential associations between antioxidant potential, metabolic regulation, and the oral microbiome

Longitudinal impact of process-oriented guided inquiry learning on the attitudes, self-efficacy and experiences of pre-medical chemistry students

A follow-up study was conducted with foundation-year chemistry students who were taught in an inquiry- and role-based, small-group active learning environment in order to evaluate their attitudes, experiences and self-efficacy during pre-medical chemistry courses. The study adopted a mixedmethods research design that involved both experimental and comparison groups. Using the CAEQ (Chemistry Attitudes and Experiences Questionnaire) and the ASCI v2 (Attitude toward the Study of Chemistry Inventory), the findings of this study indicated that inquiry-based chemistry learning experience improves the students’ intellectual accessibility and emotional satisfaction as well as develops their self-efficacy levels while pursuing intensive pre-medical courses in chemistry. The results of the qualitative data analyses using a course experience questionnaire indicated that the process-oriented guided inquiry learning (POGIL) experience helped the students succeed in rigorous pre-medical chemistry courses and gained some process skills required in the medical programme as listed by the AAMC (American Association of Medical Colleges)

The Building Blocks of Interoperability. A Multisite Analysis of Patient Demographic Attributes Available for Matching.

BackgroundPatient matching is a key barrier to achieving interoperability. Patient demographic elements must be consistently collected over time and region to be valuable elements for patient matching.ObjectivesWe sought to determine what patient demographic attributes are collected at multiple institutions in the United States and see how their availability changes over time and across clinical sites.MethodsWe compiled a list of 36 demographic elements that stakeholders previously identified as essential patient demographic attributes that should be collected for the purpose of linking patient records. We studied a convenience sample of 9 health care systems from geographically distinct sites around the country. We identified changes in the availability of individual patient demographic attributes over time and across clinical sites.ResultsSeveral attributes were consistently available over the study period (2005-2014) including last name (99.96%), first name (99.95%), date of birth (98.82%), gender/sex (99.73%), postal code (94.71%), and full street address (94.65%). Other attributes changed significantly from 2005-2014: Social security number (SSN) availability declined from 83.3% to 50.44% (p<0.0001). Email address availability increased from 8.94% up to 54% availability (p<0.0001). Work phone number increased from 20.61% to 52.33% (p<0.0001).ConclusionsOverall, first name, last name, date of birth, gender/sex and address were widely collected across institutional sites and over time. Availability of emerging attributes such as email and phone numbers are increasing while SSN use is declining. Understanding the relative availability of patient attributes can inform strategies for optimal matching in healthcare

Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain

Because the human brain consumes a disproportionate fraction of the resting body’s energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMRglc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMRglc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMRglc alterations compared to control were detected in all conditions except in congenitally blind where regional CMRglc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMRglc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMRglc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMRglc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMRglc data in health and disease

Trajectories of Brain Lactate and Re-visited Oxygen-Glucose Index Calculations Do Not Support Elevated Non-oxidative Metabolism of Glucose Across Childhood

Brain growth across childhood is a dynamic process associated with specific energy requirements. A disproportionately higher rate of glucose utilization (CMRglucose) compared with oxygen consumption (CMRO2) was documented in children's brain and suggestive of non-oxidative metabolism of glucose. Several candidate metabolic pathways may explain the CMRglucose-CMRO2 mismatch, and lactate production is considered a major contender. The ~33% excess CMRglucose equals 0.18 μmol glucose/g/min and predicts lactate release of 0.36 μmol/g/min. To validate such scenario, we measured the brain lactate concentration ([Lac]) in 65 children to determine if indeed lactate accumulates and is high enough to (1) account for the glucose consumed in excess of oxygen and (2) support a high rate of lactate efflux from the young brain. Across childhood, brain [Lac] was lower than predicted, and below the range for adult brain. In addition, we re-calculated the CMRglucose-CMRO2 mismatch itself by using updated lumped constant values. The calculated cerebral metabolic rate of lactate indicated a net influx of 0.04 μmol/g/min, or in terms of CMRglucose, of 0.02 μmol glucose/g/min. Accumulation of [Lac] and calculated efflux of lactate from brain are not consistent with the increase in non-oxidative metabolism of glucose. In addition, the value for the lumped constant for [18F]fluorodeoxyglucose has a high impact on calculated CMRglucose and use of updated values alters or eliminates the CMRglucose-CMRO2 mismatch in developing brain. We conclude that the presently-accepted notion of non-oxidative metabolism of glucose during childhood must be revisited and deserves further investigations

Diffuse white matter loss in a transgenic rat model of cerebral amyloid angiopathy

Diffuse white matter (WM) disease is highly prevalent in elderly with cerebral small vessel disease (cSVD). In humans, cSVD such as cerebral amyloid angiopathy (CAA) often coexists with Alzheimer’s disease imposing a significant impediment for characterizing their distinct effects on WM. Here we studied the burden of age-related CAA pathology on WM disease in a novel transgenic rat model of CAA type 1 (rTg-DI). A cohort of rTg-DI and wild-type rats was scanned longitudinally using MRI for characterization of morphometry, cerebral microbleeds (CMB) and WM integrity. In rTg-DI rats, a distinct pattern of WM loss was observed at 9 M and 11 M. MRI also revealed manifestation of small CMB in thalamus at 6 M, which preceded WM loss and progressively enlarged until the moribund disease stage. Histology revealed myelin loss in the corpus callosum and thalamic CMB in all rTg-DI rats, the latter of which manifested in close proximity to occluded and calcified microvessels. The quantitation of CAA load in rTg-DI rats revealed that the most extensive microvascular Aβ deposition occurred in the thalamus. For the first time using in vivo MRI, we show that CAA type 1 pathology alone is associated with a distinct pattern of WM loss