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Pershing's tankers : personal accounts of the AEF Tank Corps in World War I
\"In Pershing's Tankers, Lawrence M. Kaplan compiles 47 official personal experience reports, 27 unofficial accounts, and six letters written by George Patton to his family to provide insight into the human dimension of US tank operations in World War I. These narratives vary in size, scope and depth, and cover a range of topics, including the organizing, training, combat operations, and equipping of the Tank Corps. Kaplan offers accounts from a broad cross-section of men from senior leaders down to the platoon level\"-- Provided by publisher.
Book
SLIPMAT: A pipeline for extracting tissue-specific spectral profiles from 1H MR spectroscopic imaging data
•A new processing pipeline is presented for extracting neurometabolic profiles.•White and grey matter profiles are separated using spectral decomposition.•Method is validated by distinguishing between healthy individuals.•Tissue specificity combined with high SNR may reveal new neurometabolic processes.
1H Magnetic Resonance Spectroscopy (MRS) is an important non-invasive tool for measuring brain metabolism, with numerous applications in the neuroscientific and clinical domains. In this work we present a new analysis pipeline (SLIPMAT), designed to extract high-quality, tissue-specific, spectral profiles from MR spectroscopic imaging data (MRSI). Spectral decomposition is combined with spatially dependant frequency and phase correction to yield high SNR white and grey matter spectra without partial-volume contamination. A subsequent series of spectral processing steps are applied to reduce unwanted spectral variation, such as baseline correction and linewidth matching, before direct spectral analysis with machine learning and traditional statistical methods. The method is validated using a 2D semi-LASER MRSI sequence, with a 5-minute duration, from data acquired in triplicate across 8 healthy participants. Reliable spectral profiles are confirmed with principal component analysis, revealing the importance of total-choline and scyllo-inositol levels in distinguishing between individuals – in good agreement with our previous work. Furthermore, since the method allows the simultaneous measurement of metabolites in grey and white matter, we show the strong discriminative value of these metabolites in both tissue types for the first time. In conclusion, we present a novel and time efficient MRSI acquisition and processing pipeline, capable of detecting reliable neuro-metabolic differences between healthy individuals, and suitable for the sensitive neurometabolic profiling of in-vivo brain tissue.
Journal Article
The mighty Thor. Vol. 3, The Asgard/Shi'ar war
\"Thor must deal with the escalating war of the Realms! To face Malekith, Loki and an all-new Kurse, she'll need a team of her own. Prepare for the triumphant return of the League of Realms! Far across the galaxy, though, another conflict is brewing--as the most powerful super-army in the cosmos prepares a surprise attack on the city of the gods! The Shi-ar Empire will lay siege to Asgardia--and their target is the Goddess of Thunder! But why? And what does the fate of Midgard have to do with it? And where the Shi'ar go, the Phoenix Force tends to follow--which is bad news for Thor! Maybe the returning Odinson could lend a hand--or perhaps the rebel X-Man known as Quentin Quire?!\" -- cover
Book
Evidence for distinct neuro-metabolic phenotypes in humans
Advances in magnetic resonance imaging have shown how individual differences in the structure and function of the human brain relate to health and cognition. The relationship between individual differences and the levels of neuro-metabolites, however, remains largely unexplored – despite the potential for the discovery of novel behavioural and disease phenotypes. In this study, we measured 14 metabolite levels, normalised as ratios to total-creatine, with 1H magnetic resonance spectroscopy (MRS) acquired from the bilateral anterior cingulate cortices of six healthy participants, repeatedly over a period of four months. ANOVA tests revealed statistically significant differences of 3 metabolites and 3 commonly used combinations (total-choline, glutamate + glutamine and total-N-acetylaspartate) between the participants, with scyllo-inositol (F=85, p=6e-26) and total-choline (F=39, p=1e-17) having the greatest discriminatory power. This was not attributable to structural differences. When predicting individuals from the repeated MRS measurements, a leave-one-out classification accuracy of 88% was achieved using a support vector machine based on scyllo-inositol and total-choline levels. Accuracy increased to 98% with the addition of total-N-acetylaspartate and myo-inositol – demonstrating the efficacy of combining MRS with machine learning and metabolomic methodology. These results provide evidence for the existence of neuro-metabolic phenotypes, which may be non-invasively measured using widely available 3 Tesla MRS. Establishing these phenotypes in a larger cohort and investigating their connection to brain health and function presents an important area for future study.
Journal Article
The impact of spectral basis set composition on estimated levels of cingulate glutamate and its associations with different personality traits
Background
1
H-MRS is increasingly used in basic and clinical research to explain brain function and alterations respectively. In psychosis research it is now one of the main tools to investigate imbalances in the glutamatergic system. Interestingly, however, the findings are extremely variable even within patients of similar disease states. One reason may be the variability in analysis strategies, despite suggestions for standardization. Therefore, our study aimed to investigate the extent to which the basis set configuration– which metabolites are included in the basis set used for analysis– would affect the spectral fit and estimated glutamate (Glu) concentrations in the anterior cingulate cortex (ACC), and whether any changes in levels of glutamate would be associated with psychotic-like experiences and autistic traits.
Methods
To ensure comparability, we utilized five different exemplar basis sets, used in research, and two different analysis tools, r-based spant applying the ABfit method and
Osprey
using the LCModel.
Results
Our findings revealed that the types of metabolites included in the basis set significantly affected the glutamate concentration. We observed that three basis sets led to more consistent results across different concentration types (i.e., absolute Glu in mol/kg, Glx (glutamate + glutamine), Glu/tCr), spectral fit and quality measurements. Interestingly, all three basis sets included phosphocreatine. Importantly, our findings also revealed that glutamate levels were differently associated with both schizotypal and autistic traits depending on basis set configuration and analysis tool, with the same three basis sets showing more consistent results.
Conclusions
Our study highlights that scientific results may be significantly altered depending on the choices of metabolites included in the basis set, and with that emphasizes the importance of carefully selecting the configuration of the basis set to ensure accurate and consistent results, when using MR spectroscopy. Overall, our study points out the need for standardized analysis pipelines and reporting.
Journal Article
A national data dashboard for neurology services
Across the UK evidence from the GIRFT report as well as data from comparable health economies across the world, show variable outcomes for patients with neurological conditions and highly variable access to neurology services in different regions.Information about the quality of neurology services across the UK, and access to them for patients, is sparse and often held in different places by different organisations, and not regularly updated.Access to such information in a user friendly and continuously updated format would be a powerful tool for service leads and commissioners to benchmark services, and facilitate quality improvement over time, as has been shown conclusively in other specialities eg SSNAP for stroke services.This will be particularly useful for Integrated Care Systems to whom responsibility for commissioning and delivering a large majority of neurology services will be delegated from national specialised commission- ing teams, from 2023 onwards.As part of NHSE’s neurosciences transformation programme and in collaboration with GIRFT, an online, updated, interactive dashboard has been developed to show key metrics and visualisations for neurology services within each ICS. We will present examples and screenshots to demonstrate the available metrics and functionality in this first version of the dashboard.
Journal Article
Association between increased anterior cingulate glutamate and psychotic-like experiences, but not autistic traits in healthy volunteers
Despite many differences, autism spectrum disorder and schizophrenia spectrum disorder share environmental risk factors, genetic predispositions as well as neuronal abnormalities, and show similar cognitive deficits in working memory, perspective taking, or response inhibition. These shared abnormalities are already present in subclinical traits of these disorders. The literature proposes that changes in the inhibitory GABAergic and the excitatory glutamatergic system could explain underlying neuronal commonalities and differences. Using magnetic resonance spectroscopy (
1
H-MRS), we investigated the associations between glutamate concentrations in the anterior cingulate cortex (ACC), the left/right putamen, and left/right dorsolateral prefrontal cortex and psychotic-like experiences (Schizotypal Personality Questionnaire) and autistic traits (Autism Spectrum Quotient) in 53 healthy individuals (26 women). To investigate the contributions of glutamate concentrations in different cortical regions to symptom expression and their interactions, we used linear regression analyses. We found that only glutamate concentration in the ACC predicted psychotic-like experiences, but not autistic traits. Supporting this finding, a binomial logistic regression predicting median-split high and low risk groups for psychotic-like experiences revealed ACC glutamate levels as a significant predictor for group membership. Taken together, this study provides evidence that glutamate levels in the ACC are specifically linked to the expression of psychotic-like experiences, and may be a potential candidate in identifying early risk individuals prone to developing psychotic-like experiences.
Journal Article
WED 017 Call on me: expanding the consultant advice line for gps
BackgroundThe Consultant Advice Line (CAL) is a service developed to provide telephone advice for GPs within our catchment. The hours of this service were extended in early 2017 to increase its capacity for GPs seeking guidance on neurological issues as part our Neuro Network Vanguard project.MethodologyData was routinely collected from calls received between 1 st March and 30th June 2017, and a sample of GPs completed an online survey after the call.ResultsVolume of calls has more than doubled since expansion, with calls spread evenly through the week and from all CCG’s in our region. Feedback from GP’s was overwhelmingly positive with an average ‘call usefulness’ score of 9.2/10, and 100% saying they would use the service again. 40% reported the advice had avoided an outpatient referral.DiscussionThe provision of equitable neurology services is challenging in the current climate. New models of care such as this help to break down barriers between primary and specialist care, reducing undesirable variation in access to acute neurology input and reducing unnecessary referrals to secondary and tertiary care.
Journal Article
Projecting demand for mineral-based critical materials in the energy transition for electricity
Several large scenario exercises in the last years present decarbonizing transitional energy pathways to 2050 and beyond. This changing energy landscape toward net zero is new territory to explore but is expected to be more intensive in mineral based materials than the current system. Mapping this territory and understanding the critical material needs to support the transition are essential for demanders and suppliers as well as policy makers seeking to orchestrate the transition. Our contribution is to provide such decision makers for electricity markets with a transparent tool that can be easily understood and modified as our transitional knowledge improves. In this tool, we take the International Energy Agency’s conservative Beyond Two Degrees scenario, which projects renewable energy penetration for 15 electricity technologies, supplemented by Bloomberg’s Electrical Vehicle Outlook. Coupling these electricity projections with estimates of material use per GW of new capacity, we estimate resulting needs for 33 materials through 2050. Assuming constant material intensities and recycle rates, our model finds dramatic increases in most included materials from 2021 to 2050. The total projected tonnage increases in materials used for the transition is 294% with a compounded average annual growth rate of 4.8%. However, there is wide heterogeneity across materials (from slightly negative for tungsten to nearly 1300% for lithium). Projected 2050 sales vary from less than 30 tonnes for hafnium and yttrium (with quantity demanded growth of − 4.8% from 2021 to 2050) to more than 17 million tonnes for steel (with growth of 291%) and aluminum (growth 419%). At 2021 prices, 2050 sales revenue varies from less than a million dollars for boron (growth of 164%) to more than $42 billion for aluminum (growth 419%), nickel (growth of 279%), and steel (growth of 291%).
Journal Article