900 research outputs found

    The United Chemicals of Cannabis: Beneficial Effects of Cannabis Phytochemicals on the Brain and Cognition

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    ‘Medicinal cannabis’ can be defined as pharmaceutical grade cannabis-based products used for the treatment of illness. Beneficial treatment effects of cannabidiol (CBD), a major non-intoxicating compound isolated from the cannabis plant, have been shown in multiple states of cognitive impairment, including neurodegenerative (Alzheimer’s, Huntington’s and Parkinson’s disease), neuroinflammatory (sepsis-induced encephalopathy) and neurological disorders (ischemic brain injury). CBD can also treat some of the symptoms of schizophrenia, including cognitive deficits (impairments in learning and memory), which is a major symptom domain of the illness that is largely resistant to existing antipsychotic medications. However, empirical evidence suggests the presence of an ‘entourage effect’ in cannabis; that is, observations that medicinal cannabis seems to work better in some instances when administered as a whole-plant extract. While scientific evidence highlights isolated CBD as a strong candidate for treating cognitive impairment, the entourage effect suggests that the co-operation of other plant molecules could provide further benefits. This chapter explores the scientific evidence surrounding the benefits of CBD and other specific key phytochemicals in cannabis: linalool, α-pinene, β-caryophyllene, flavonoids and anthocyanin, on brain health and cognition

    Effect of cannabidiol on cognition in a maternal immune activation (poly IC) model of schizophrenia

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    Abstract of a poster presentation

    Relative seismic velocity variations correlate with deformation at Kīlauea volcano, Hawai'i

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    Seismic noise interferometry allows the continuous and real-time measurement of relative seismic velocity through a volcanic edifice. Because seismic velocity is sensitive to the pressurization state of the system, this method is an exciting new monitoring tool at active volcanoes. Despite the potential of this tool, no studies have yet comprehensively compared velocity to other geophysical observables on a short-term time scale at a volcano over a significant length of time. We use volcanic tremor (~0.3 to 1.0 Hz) at Kīlauea as a passive source for interferometry to measure relative velocity changes with time. By cross-correlating the vertical component of day-long seismic records between ~230 station pairs, we extract coherent and temporally consistent coda wave signals with time lags of up to 120 s. Our resulting time series of relative velocity shows a remarkable correlation between relative velocity and the radial tilt record measured at Kīlauea summit, consistently correlating on a time scale of days to weeks for almost the entire study period (June 2011 to November 2015). As the summit continually deforms in deflation-inflation events, the velocity decreases and increases, respectively. Modeling of strain at Kīlauea suggests that, during inflation of the shallow magma reservoir (1 to 2 km below the surface), most of the edifice is dominated by compression—hence closing cracks and producing faster velocities—and vice versa. The excellent correlation between relative velocity and deformation in this study provides an opportunity to understand better the mechanisms causing seismic velocity changes at volcanoes, and therefore realize the potential of passive interferometry as a monitoring tool

    Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods

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    The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach

    Will improving wastewater treatment impact shorebirds? Effects of sewage discharges on estuarine invertebrates and birds

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    Human communities often discharge wastewaters into estuaries, influencing their organic and pollutant loading, benthic community and trophic structure. The implementation of the Water Framework Directive has encouraged the treatment of wastewater discharges across European estuaries, but the implications for invertebrate and waterbird communities are poorly understood. We explore the effects of untreated sewage discharges on the distribution and abundance of foraging black-tailed godwits Limosa limosa and their main benthic prey (bivalves and polychaetes) on the Tejo estuary in Portugal, a major European Special Protection Area with ongoing wastewater improvements. Patches of mudflat in close proximity to sewage streams (70 m), and godwits foraging in these areas can attain the highest intake rates recorded for the estuary. However, high intake rates can also be attained on bivalve prey, and bivalve biomass and density increase slightly with distance from sewage streams. As the organic input from sewage outfalls influences invertebrate abundance and godwit foraging rates over relatively small areas, the ongoing implementation of a sewage treatment network on the Tejo estuary seems likely to have only a limited impact on the wintering godwit population. The localized effect of untreated sewage discharges on benthic communities suggests that the implications for predatory birds are relatively minor where alternative prey are available, but may be more severe in locations with more depauperate, polychaete-dominated invertebrate communities

    Basic science behind the cardiovascular benefits of exercise

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    Cardiorespiratory fitness is a strong predictor of cardiovascular (CV) disease and all-cause mortality, with increases in cardiorespiratory fitness associated with corresponding decreases in CV disease risk. The effects of exercise upon the myocardium and vascular system are dependent upon the frequency, intensity and duration of the exercise itself. Following a prolonged period (≥6 months) of regular intensive exercise in previously untrained individuals, resting and submaximal exercising heart rates are typically 5–20 beats lower, with an increase in stroke volume of ∼20% and enhanced myocardial contractility. Structurally, all four heart chambers increase in volume with mild increases in wall thickness, resulting in greater cardiac mass due to increased myocardial cell size. With this in mind, the present paper aims to review the basic science behind the CV benefits of exercise. Attention will be paid to understanding (1) the relationship between exercise and cardiac remodelling; (2) the cardiac cellular and molecular adaptations in response to exercise, including the examination of molecular mechanisms of physiological cardiac growth and applying these mechanisms to identify new therapeutic targets to prevent or reverse pathological remodelling and heart failure; and (3) vascular adaptations in response to exercise. Finally, this review will briefly examine how to optimise the CV benefits of exercise by considering how much and how intense exercise should be

    Sensory percepts elicited by chronic macro-sieve electrode stimulation of the rat sciatic nerve

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    Objective: Intuitive control of conventional prostheses is hampered by their inability to provide the real-time tactile and proprioceptive feedback of natural sensory pathways. The macro-sieve electrode (MSE) is a candidate interface to amputees’ truncated peripheral nerves for introducing sensory feedback from external sensors to facilitate prosthetic control. Its unique geometry enables selective control of the complete nerve cross-section by current steering. Unlike previously studied interfaces that target intact nerve, the MSE’s implantation requires transection and subsequent regeneration of the target nerve. Therefore, a key determinant of the MSE’s suitability for this task is whether it can elicit sensory percepts at low current levels in the face of altered morphology and caliber distribution inherent to axon regeneration. The present in vivo study describes a combined rat sciatic nerve and behavioral model developed to answer this question.Approach: Rats learned a go/no-go detection task using auditory stimuli and then underwent surgery to implant the MSE in the sciatic nerve. After healing, they were trained with monopolar electrical stimuli with one multi-channel and eight single-channel stimulus configurations. Psychometric curves derived by the method of constant stimuli (MCS) were used to calculate 50% detection thresholds and associated psychometric slopes. Thresholds and slopes were calculated at two time points 3 weeks apart.Main Results: For the multi-channel stimulus configuration, the average current required for stimulus detection was 19.37 μA (3.87 nC) per channel. Single-channel thresholds for leads located near the nerve’s center were, on average, half those of leads located near the periphery (54.92 μA vs. 110.71 μA, or 10.98 nC vs. 22.14 nC). Longitudinally, 3 of 5 leads’ thresholds decreased or remained stable over the 3-week span. The remaining two leads’ thresholds increased by 70–74%, possibly due to scarring or device failure.Significance: This work represents an important first step in establishing the MSE’s viability as a sensory feedback interface. It further lays the groundwork for future experiments that will extend this model to the study of other devices, stimulus parameters, and task paradigms

    The IUCN Red List of Ecosystems: motivations, challenges, and applications

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    Abstract In response to growing demand for ecosystem-level risk assessment in biodiversity conservation, and rapid proliferation of locally tailored protocols, the IUCN recently endorsed new Red List criteria as a global standard for ecosystem risk assessment. Four qualities were sought in the design of the IUCN criteria: generality; precision; realism; and simplicity. Drawing from extensive global consultation, we explore trade-offs among these qualities when dealing with key challenges, including ecosystem classification, measuring ecosystem dynamics, degradation and collapse, and setting decision thresholds to delimit ordinal categories of threat. Experience from countries with national lists of threatened ecosystems demonstrates well-balanced trade-offs in current and potential applications of Red Lists of Ecosystems in legislation, policy, environmental management and education. The IUCN Red List of Ecosystems should be judged by whether it achieves conservation ends and improves natural resource management, whether its limitations are outweighed by its benefits, and whether it performs better than alternative methods. Future development of the Red List of Ecosystems will benefit from the history of the Red List of Threatened Species which was trialed and adjusted iteratively over 50 years from rudimentary beginnings. We anticipate the Red List of Ecosystems will promote policy focus on conservation outcomes in situ across whole landscapes and seascapes
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