The Cultural Context of the Aberdeen Candlemas Play

Among the lost plays of medieval Scotland the Aberdeen Candlemas play is one of the most intriguing. Our knowledge of its content derives principally from two lists, dating from 1442 and 1505, dividing the roles between the burgh’s various gilds, although the fact that there was some form of dramatic element rather than merely a procession appears to be confirmed by the discovery in the Dean of Guild’s accounts for 1470-71 of a payment of 16d. to “ye men ye maid scafald to ye candilmes play.” This paper focuses on the presence in the cast of The Three Kings of Cologne and of St .Helen and St. Bride. The first two point towards Aberdeen’s commercial connections with the Rhineland and the possible influence of John of Hildesheim’s Historia Trium Regum, while the inclusion of St. Bride brings a Celtic dimension, relating not only to Brigid’s Irish origins and the popularity of her cult in Scotland, but perhaps also to a tradition associating her (or a namesake) with the foundation of the church at Abernethy, and a further link with St. Duthac of Tain. The play therefore unites two aspects of late medieval Aberdeen, Celtic roots and Continental cultural perspectives

A Real-time Strategy Agent Framework and Strategy Classifier for Computer Generated Forces

This research effort is concerned with the advancement of computer generated forces AI for Department of Defense (DoD) military training and education. The vision of this work is agents capable of perceiving and intelligently responding to opponent strategies in real-time. Our research goal is to lay the foundations for such an agent. Six research objectives are defined: 1) Formulate a strategy definition schema effective in defining a range of RTS strategies. 2) Create eight strategy definitions via the schema. 3) Design a real-time agent framework that plays the game according to the given strategy definition. 4) Generate an RTS data set. 5) Create an accurate and fast executing strategy classifier. 6) Find the best counterstrategies for each strategy definition. The agent framework is used to play the eight strategies against each other and generate a data set of game observations. To classify the data, we first perform feature reduction using principal component analysis or linear discriminant analysis. Two classifier techniques are employed, k-means clustering with k-nearest neighbor and support vector machine. The resulting classifier is 94.1% accurate with an average classification execution speed of 7.14 us. Our research effort has successfully laid the foundations for a dynamic strategy agent

Synthetic Studies on Gibberellins

Based upon the serendipitous conversion of carbomethoxy-2-(p-methoxyphenyl)-cyclohexane-1-carboxylic acid into endo-2-(p-methoxyphenyl)-cyclohexane-cis-1,5-dicarboxylic acid anhydride, a stereospecific synthesis of 1,2,3,4,4a(betaH),9a(betaH)-hexahydro-7-methoxy-o-oxofluorene-2-carboxylic acid has been achieved in excellent yield, originating from the regiospecific and stereoselective Diels Alder cyclisation between acrylyl chloride and 5-(p-methoxyphenyl)-trans, trans-penta-2,4-dienoyl chloride. The Diels Alder reaction between related dienes and dienophiles was also investigated. A detailed investigation of the intramolecular Dieckmann cyclisation of methyl (1,2,3,4,4a(betaH),9a-hexahydro-2-carbomethoxy-7-methoxy-9-oxofluorenyl-9abeta)-acetate and of its 9-desoxy and 9alpha-hydroxy derivatives as a route to 3-methoxy-6,16-dioxo-9(betaH)-gibb-A-triene suggests that strain factors are the cause of failure of this cyclisation. 3-methoxy-16-oxogibba-1(10),2,4 ,9(11)-tetraene was obtained by acid catalysed cyclisation of the olefinic diazo ketone, 1,2,3,4,4a(betaH)-tetrahydro-Delta9,11-2-diazoacyl-7-methoxyfluorene. A keto-carbenoid C-H insertion reaction applied to the corresponding hexahydro and 9alpha-hydroxy-hexahydro derivatives failed to yield any tetracyclic material. An attempt to extend the Parham hydrofluorene synthesis failed at an early stage when 2-bromo-5-methoxybenzyl alcohol, or its 1-alkoxy-l-ethoxyethane acetal derivative failed to undergo electrophilic halogen exchange. A similar lack of success was experienced with the corresponding Grignard reagent

Phenotypic and genetic associations between anhedonia and brain structure in UK Biobank

Anhedonia is a core symptom of multiple psychiatric disorders and has been associated with alterations in brain structure. Genome-wide association studies suggest that anhedonia is heritable, with a polygenic architecture, but few studies have explored the association between genetic loading for anhedonia—indexed by polygenic risk scores for anhedonia (PRS-anhedonia)—and structural brain imaging phenotypes. Here, we investigated how anhedonia and PRS-anhedonia were associated with brain structure within the UK Biobank cohort. Brain measures (including total grey/white matter volumes, subcortical volumes, cortical thickness (CT) and white matter integrity) were analysed using linear mixed models in relation to anhedonia and PRS-anhedonia in 19,592 participants (9225 males; mean age = 62.6 years, SD = 7.44). We found that state anhedonia was significantly associated with reduced total grey matter volume (GMV); increased total white matter volume (WMV); smaller volumes in thalamus and nucleus accumbens; reduced CT within the paracentral cortex, the opercular part of inferior frontal gyrus, precentral cortex, insula and rostral anterior cingulate cortex; and poorer integrity of many white matter tracts. PRS-anhedonia was associated with reduced total GMV; increased total WMV; reduced white matter integrity; and reduced CT within the parahippocampal cortex, superior temporal gyrus and insula. Overall, both state anhedonia and PRS-anhedonia were associated with individual differences in multiple brain structures, including within reward-related circuits. These associations may represent vulnerability markers for psychopathology relevant to a range of psychiatric disorders

Polygenic Risk for Schizophrenia, Brain Structure, and Environmental Risk in UK Biobank

Schizophrenia is a heritable neurodevelopmental disorder characterized by neuroanatomical changes in the brain but exactly how increased genetic burden for schizophrenia influences brain structure is unknown. Similarly, the impact of environmental risk factors for schizophrenia on brain structure is not fully understood. We investigated how genetic burden for schizophrenia (indexed by a polygenic risk score, PRS-SCZ) was associated with cortical thickness (CT), cortical surface area (SA), cortical volume (CV) and multiple subcortical structures within 18,147 White British ancestry participants from UK Biobank. We also explored whether environmental risk factors for schizophrenia (cannabis use, childhood trauma, low birth weight and Townsend social deprivation index) exacerbated the impact of PRS-SCZ on brain structure. We found that PRS-SCZ was significantly associated with lower CT in the frontal lobe, insula lobe, lateral orbitofrontal cortex, medial orbitofrontal cortex, posterior cingulate cortex and inferior frontal cortex, as well as reduced SA and CV in the supramarginal cortex and superior temporal cortex, but not with differences in subcortical volumes. When models included environmental risk factors as covariates, PRS-SCZ was only associated with lower SA/CV within the supramarginal cortex, superior temporal cortex and inferior frontal cortex. Moreover, no interactions were observed between PRS-SCZ and each of the environmental risk factors on brain structure. Overall, we identified brain structural correlates of PRS-SCZ predominantly within frontal and temporal regions. Some of these associations were independent of environmental risk factors, suggesting that they may represent biomarkers of genetic risk for schizophrenia

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank

Background: Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes. Methods: Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC). Results: For MD vs. controls (n(MD) = 24,229; n(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67–0.69. Discrimination was reasonable for atypical vs. typical symptoms (n(atypical) = 958; n(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71–0.77) but poor for remaining models (AUCs 0.59–0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes. Limitations: Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary. Discussion: Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features

Changes in prescribing for bipolar disorder between 2009 and 2016: national-level data linkage study in Scotland

Background: People with bipolar disorder typically require long-term pharmacological treatment to prevent episodes of depression or mania. However, evidence-based guidelines are often not followed by prescribers and, in some countries, prescribing of lithium is in decline. Polypharmacy is also common in bipolar disorder. Aims: To employ a data linkage approach to describe and evaluate prescribing patterns in bipolar disorder in Scotland between 2009 and 2016. Method: By linking prescribing data to the electronic Scottish Morbidity Records, we identified a cohort of 23 135 patients with bipolar disorder who were prescribed psychotropic medication between 2009 and 2016. We examined trends in proportions of patients prescribed each of six drug categories. Random effects logistic models examined change in prescribing over years of interest. Results: The most common form of treatment was antidepressant monotherapy (24.96%), with only 5.90% of patients receiving lithium monotherapy. Prescribing of antipsychotics and anti-epileptics increased from 2009 to 2016 (antipsychotics: odds ratio 1.16, 95% CI 1.15–1.18; anti-epileptics: odds ratio 1.34, 95% CI 1.32–1.36), whereas prescribing of lithium decreased (odds ratio 0.83, 95% CI 0.82–0.85). Prescribing of valproate decreased from 2009–2016 in women, but increased in men (women: odds ratio 0.93, 95% CI 0.90–0.97; men: odds ratio 1.11, 95% CI 1.04–1.18). Conclusions: Antidepressant monotherapy was the most common form of treatment for bipolar disorder in Scotland and prescribing of lithium has declined between 2009 and 2016. The findings are concerning and represent a gap between treatment guidelines and clinical practice. Declaration of interest: None