Bridging the GUI gap with reactive values and relations

There are at present two ways to write GUIs for functional code. One is to use standard GUI toolkits, with all the benefits they bring in terms of feature completeness, choice of platform, conformance to platform-specific look-and-feel, long-term viability, etc. However, such GUI APIs mandate an imperative programming style for the GUI and related parts of the application. Alternatively, we can use a functional GUI toolkit. The GUI can then be written in a functional style, but at the cost of foregoing many advantages of standard toolkits that often will be of critical importance. This paper introduces a light-weight framework structured around the notions of reactive values and reactive relations . It allows standard toolkits to be used from functional code written in a functional style. We thus bridge the gap between the two worlds, bringing the advantages of both to the developer. Our framework is available on Hackage and has been been validated through the development of non-trivial applications in a commercial context, and with different standard GUI toolkits

Cluster-induced crater formation

Using molecular-dynamics simulation, we study the crater volumes induced by energetic impacts ($v= 1- 250$ km/s) of projectiles containing up to N=1000 atoms. We find that for Lennard-Jones bonded material the crater volume depends solely on the total impact energy $E$. Above a threshold \Eth, the volume rises linearly with $E$. Similar results are obtained for metallic materials. By scaling the impact energy $E$ to the target cohesive energy $U$, the crater volumes become independent of the target material. To a first approximation, the crater volume increases in proportion with the available scaled energy, $V=aE/U$. The proportionality factor $a$ is termed the cratering efficiency and assumes values of around 0.5.Comment: 9 page

Oxaliplatin-Induced Leukocytoclastic Vasculitis under Adjuvant Chemotherapy for Colorectal Cancer: Two Cases of a Rare Adverse Event

Leukocytoclastic vasculitis is a multicausal systemic inflammatory disease of the small vessels, histologically characterized by inflammation and deposition of both nuclear debris and fibrin in dermal postcapillary venules. The clinical picture typically involves palpable purpura of the lower legs and may be associated with general symptoms such as fatigue, arthralgia and fever. Involvement of the internal organs, most notably the kidneys, the central nervous system or the eyes, is possible and determines the prognosis. Oxaliplatin-induced leukocytoclastic vasculitis is a very rare event that limits treatment options in affected patients. We report 2 patients who developed the condition under chemotherapy for advanced rectal and metastatic colon carcinoma, respectively; a termination of the therapy was therefore necessary. While current therapies for colorectal cancer include the combination of multimodal treatment with new and targeted agents, rare and unusual side effects elicited by established agents also need to be taken into account for the clinical management

García, Xavier (ed.) (2015). Joan Oliver-Joaquim Molas: Diàleg epistolar il·lustrat (1959-1982). Lleida: Pagès Editors, pp. 186

<p><i>Objectives</i>: Attention-deficit/hyperactivity disorder (ADHD) has been associated with spatial working memory as well as frontostriatal core deficits. However, it is still unclear how the link between these frontostriatal deficits and working memory function in ADHD differs in children and adults. This study examined spatial working memory in adults and children with ADHD, focussing on identifying regions demonstrating age-invariant or age-dependent abnormalities. <i>Methods</i>: We used functional magnetic resonance imaging to examine a group of 26 children and 35 adults to study load manipulated spatial working memory in patients and controls. <i>Results</i>: In comparison to healthy controls, patients demonstrated reduced positive parietal and frontostriatal load effects, i.e., less increase in brain activity from low to high load, despite similar task performance. In addition, younger patients showed negative load effects, i.e., a decrease in brain activity from low to high load, in medial prefrontal regions. Load effect differences between ADHD and controls that differed between age groups were found predominantly in prefrontal regions. Age-invariant load effect differences occurred predominantly in frontostriatal regions. <i>Conclusions</i>: The age-dependent deviations support the role of prefrontal maturation and compensation in ADHD, while the age-invariant alterations observed in frontostriatal regions provide further evidence that these regions reflect a core pathophysiology in ADHD.</p

Common clonal origin of conventional T cells and induced regulatory T cells in breast cancer patients

Regulatory CD4+ T cells (Treg) prevent tumor clearance by conventional T cells (Tconv) comprising a major obstacle of cancer immune-surveillance. Hitherto, the mechanisms of Treg repertoire formation in human cancers remain largely unclear. Here, we analyze Treg clonal origin in breast cancer patients using T-Cell Receptor and single-cell transcriptome sequencing. While Treg in peripheral blood and breast tumors are clonally distinct, Tconv clones, including tumor-antigen reactive effectors (Teff), are detected in both compartments. Tumor-infiltrating CD4+ cells accumulate into distinct transcriptome clusters, including early activated Tconv, uncommitted Teff, Th1 Teff, suppressive Treg and pro-tumorigenic Treg. Trajectory analysis suggests early activated Tconv differentiation either into Th1 Teff or into suppressive and pro-tumorigenic Treg. Importantly, Tconv, activated Tconv and Treg share highly-expanded clones contributing up to 65% of intratumoral Treg. Here we show that Treg in human breast cancer may considerably stem from antigen-experienced Tconv converting into secondary induced Treg through intratumoral activation

The poly-omics of ageing through individual-based metabolic modelling

Abstract Background Ageing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype. Results We propose a method based on poly-omic constraint-based models and machine learning in order to further the understanding of transcriptomic ageing. We use normalised CD4 T-cell gene expression data from peripheral blood mononuclear cells in 499 healthy individuals to create individual metabolic models. These models are then combined with a transcriptomic age predictor and chronological age to provide new insights into the differences between transcriptomic and chronological ageing. As a result, we propose a novel metabolic age predictor. Conclusions We show that our poly-omic predictors provide a more detailed analysis of transcriptomic ageing compared to gene-based approaches, and represent a basis for furthering our knowledge of the ageing mechanisms in human cells

Approximate Probabilistic Inference with Bounded Error for Hybrid Probabilistic Logic Programming

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