Spatial Thinking in Practice: A Snapshot of teacher’s Spatial Activity Use in the Early Years’ Classroom

Spatial thinking predicts Science, Technology, Engineering, and Mathematics achievement, yet is often absent from educational policy. We provide benchmarks of teachers' usage and perceptions of spatial activities in practice in the reception classroom (first year of primary school). In this questionnaire study of educational professionals working in the reception classroom in England (N = 104), we found that spatial and numeracy activities were perceived as significantly less important, and were reportedly completed significantly less often, than literacy or life skills. Despite the lower perceived importance of spatial skills in curriculum guidance in England, rates of reported spatial activity use were encouragingly high and were broadly comparable to those of numeracy. Teachers had moderate anxiety levels for both spatial and mathematics domains. The findings highlight a need to elevate teachers' understanding of the importance of developing children's early spatial and numeracy skills, which may begin with efforts to reduce spatial and mathematics anxiety

Concert recording 2018-09-25

[Track 1]. The Holberg suite, op. 40. I. Praeludium (Allegro vivace) II. Sarabande (Andante) III. Gavotte (Allegretto) IV. Air (Andante religioso) V. Rigaudon (Allegro con brio) / Edvard Grieg -- [Track 2]. Serenade for strings in C major, op. 48. I. Pezzo in forma di sonatina (Andante non troppo - Allegro moderato) II. Valse (Moderato - Tempo di valse) III. Elegie (Larghetto elegiaco) IV. Finale (Tema russo) (Andante - Allegro con spirito) / Pyotr Tchaikovsky

An Environmental Science and Engineering Framework for Combating Antimicrobial Resistance

On June 20, 2017, members of the environmental engineering and science (EES) community convened at the Association of Environmental Engineering and Science Professors (AEESP) Biennial Conference for a workshop on antimicrobial resistance. With over 80 registered participants, discussion groups focused on the following topics: risk assessment, monitoring, wastewater treatment, agricultural systems, and synergies. In this study, we summarize the consensus among the workshop participants regarding the role of the EES community in understanding and mitigating the spread of antibiotic resistance via environmental pathways. Environmental scientists and engineers offer a unique and interdisciplinary perspective and expertise needed for engaging with other disciplines such as medicine, agriculture, and public health to effectively address important knowledge gaps with respect to the linkages between human activities, impacts to the environment, and human health risks. Recommendations that propose priorities for research within the EES community, as well as areas where interdisciplinary perspectives are needed, are highlighted. In particular, risk modeling and assessment, monitoring, and mass balance modeling can aid in the identification of “hot spots” for antibiotic resistance evolution and dissemination, and can help identify effective targets for mitigation. Such information will be essential for the development of an informed and effective policy aimed at preserving and protecting the efficacy of antibiotics for future generations

Critical-point scaling function for the specific heat of a Ginzburg-Landau superconductor

If the zero-field transition in high temperature superconductors such as YBa_2Cu_3O_7-\delta is a critical point in the universality class of the 3-dimensional XY model, then the general theory of critical phenomena predicts the existence of a critical region in which thermodynamic functions have a characteristic scaling form. We report the first attempt to calculate the universal scaling function associated with the specific heat, for which experimental data have become available in recent years. Scaling behaviour is extracted from a renormalization-group analysis, and the 1/N expansion is adopted as a means of approximation. The estimated scaling function is qualitatively similar to that observed experimentally, and also to the lowest-Landau-level scaling function used by some authors to provide an alternative interpretation of the same data. Unfortunately, the 1/N expansion is not sufficiently reliable at small values of N for a quantitative fit to be feasible.Comment: 20 pages; 4 figure

Poloxomer 188 Has a Deleterious Effect on Dystrophic Skeletal Muscle Function

Duchenne muscular dystrophy (DMD) is an X-linked, fatal muscle wasting disease for which there is currently no cure and limited palliative treatments. Poloxomer 188 (P188) is a tri-block copolymer that has been proposed as a potential treatment for cardiomyopathy in DMD patients. Despite the reported beneficial effects of P188 on dystrophic cardiac muscle function, the effects of P188 on dystrophic skeletal muscle function are relatively unknown. Mdx mice were injected intraperitoneally with 460 mg/kg or 30 mg/kg P188 dissolved in saline, or saline alone (control). The effect of single-dose and 2-week daily treatment was assessed using a muscle function test on the Tibialis Anterior (TA) muscle in situ in anaesthetised mice. The test comprises a warm up, measurement of the force-frequency relationship and a series of eccentric contractions with a 10% stretch that have previously been shown to cause a drop in maximum force in mdx mice. After 2 weeks of P188 treatment at either 30 or 460 mg/kg/day the drop in maximum force produced following eccentric contractions was significantly greater than that seen in saline treated control mice (P = 0.0001). Two week P188 treatment at either dose did not significantly change the force-frequency relationship or maximum isometric specific force produced by the TA muscle. In conclusion P188 treatment increases susceptibility to contraction-induced injury following eccentric contractions in dystrophic skeletal muscle and hence its suitability as a potential therapeutic for DMD should be reconsidered

A foundation model for generalizable disease detection from retinal images

Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders 1. However, the development of AI models requires substantial annotation and models are usually task-specific with limited generalizability to different clinical applications 2. Here, we present RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications. Specifically, RETFound is trained on 1.6 million unlabelled retinal images by means of self-supervised learning and then adapted to disease detection tasks with explicit labels. We show that adapted RETFound consistently outperforms several comparison models in the diagnosis and prognosis of sight-threatening eye diseases, as well as incident prediction of complex systemic disorders such as heart failure and myocardial infarction with fewer labelled data. RETFound provides a generalizable solution to improve model performance and alleviate the annotation workload of experts to enable broad clinical AI applications from retinal imaging.</p

Extinction of cue-evoked drug-seeking relies on degrading hierarchical instrumental expectancies

There has long been need for a behavioural intervention that attenuates cue-evoked drug-seeking, but the optimal method remains obscure. To address this, we report three approaches to extinguish cue-evoked drug-seeking measured in a Pavlovian to instrumental transfer design, in non-treatment seeking adult smokers and alcohol drinkers. The results showed that the ability of a drug stimulus to transfer control over a separately trained drug-seeking response was not affected by the stimulus undergoing Pavlovian extinction training in experiment 1, but was abolished by the stimulus undergoing discriminative extinction training in experiment 2, and was abolished by explicit verbal instructions stating that the stimulus did not signal a more effective response-drug contingency in experiment 3. These data suggest that cue-evoked drug-seeking is mediated by a propositional hierarchical instrumental expectancy that the drug-seeking response is more likely to be rewarded in that stimulus. Methods which degraded this hierarchical expectancy were effective in the laboratory, and so may have therapeutic potential

A foundation model for generalizable disease detection from retinal images

Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders1. However, the development of AI models requires substantial annotation and models are usually task-specific with limited generalizability to different clinical applications2. Here, we present RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications. Specifically, RETFound is trained on 1.6 million unlabelled retinal images by means of self-supervised learning and then adapted to disease detection tasks with explicit labels. We show that adapted RETFound consistently outperforms several comparison models in the diagnosis and prognosis of sight-threatening eye diseases, as well as incident prediction of complex systemic disorders such as heart failure and myocardial infarction with fewer labelled data. RETFound provides a generalizable solution to improve model performance and alleviate the annotation workload of experts to enable broad clinical AI applications from retinal imaging

Can FDG PET predict radiation treatment outcome in head and neck cancer? Results of a prospective study

Contains fulltext : 96692.pdf (publisher's version ) (Closed access)PURPOSE: In head and neck cancer (HNC) various treatment strategies have been developed to improve outcome, but selecting patients for these intensified treatments remains difficult. Therefore, identification of novel pretreatment assays to predict outcome is of interest. In HNC there are indications that pretreatment tumour (18)F-fluorodeoxyglucose (FDG) uptake may be an independent prognostic factor. The aim of this study was to assess the prognostic value of FDG uptake and CT-based and FDG PET-based primary tumour volume measurements in patients with HNC treated with (chemo)radiotherapy. METHODS: A total of 77 patients with stage II-IV HNC who were eligible for definitive (chemo)radiotherapy underwent coregistered pretreatment CT and FDG PET. The gross tumour volume of the primary tumour was determined on the CT (GTV(CT)) and FDG PET scans. Five PET segmentation methods were applied: interpreting FDG PET visually (PET(VIS)), applying an isocontour at a standardized uptake value (SUV) of 2.5 (PET(2.5)), using fixed thresholds of 40% and 50% (PET(40%), PET(50%)) of the maximum intratumoral FDG activity (SUV(MAX)) and applying an adaptive threshold based on the signal-to-background (PET(SBR)). Mean FDG uptake for each PET-based volume was recorded (SUV(mean)). Subsequently, to determine the metabolic volume, the integrated SUV was calculated as the product of PET-based volume and SUV(mean). All these variables were analysed as potential predictors of local control (LC), regional recurrence-free survival (RRFS), distant metastasis-free survival (DMFS), disease-free survival (DFS) and overall survival (OS). RESULTS: In oral cavity/oropharynx tumours PET(VIS) was the only volume-based method able to predict LC. Both PET(VIS) and GTV(CT) were able to predict DMFS, DFS and OS in these subsites. Integrated SUVs were associated with LC, DMFS, DFS and OS, while SUV(mean) and SUV(MAX) were not. In hypopharyngeal/laryngeal tumours none of the variables was associated with outcome. CONCLUSION: There is no role yet for pretreatment FDG PET as a predictor of (chemo)radiotherapy outcome in HNC in daily routine. However, this potential application needs further exploration, focusing both on FDG PET-based primary tumour volume, integrated SUV and SUV(MAX) of the primary tumour

Cancer Risk after Fat Transfer: A Multicenter Case-Cohort Study

Fat transfer is an increasingly popular method for refining post-mastectomy breast reconstructions. However, concern persists that fat transfer may promote disease recurrence. Adipocytes are derived from adipose-derived stem cells and express adipocytokines that can facilitate active breast cancer cells in laboratory models. We sough to evaluate the association between fat transfer to the reconstructed breast and cancer recurrence in patients diagnosed with local or regional invasive breast cancers