The Epitheliome: agent-based modelling of the social behaviour of cells

We have developed a new computational modelling paradigm for predicting the emergent behaviour resulting from the interaction of cells in epithelial tissue. As proof-of-concept, an agent-based model, in which there is a one-to-one correspondence between biological cells and software agents, has been coupled to a simple physical model. Behaviour of the computational model is compared with the growth characteristics of epithelial cells in monolayer culture, using growth media with low and physiological calcium concentrations. Results show a qualitative fit between the growth characteristics produced by the simulation and the in vitro cell models

Grid simulation services for the medical community

The first part of this paper presents a selection of medical simulation applications, including image reconstruction, near real-time registration for neuro-surgery, enhanced dose distribution calculation for radio-therapy, inhaled drug delivery prediction, plastic surgery planning and cardio-vascular system simulation. The latter two topics are discussed in some detail. In the second part, we show how such services can be made available to the clinical practitioner using Grid technology. We discuss the developments and experience made during the EU project GEMSS, which provides reliable, efficient, secure and lawful medical Grid services

Plasmodium yoelii infection of BALB/c mice results in expansion rather than induction of CD4+ Foxp3+ regulatory T cells

Recently, we demonstrated elevated numbers of CD4(+) Foxp3(+) regulatory T (Treg) cells in Plasmodium yoelii‐infected mice contributing to the regulation of anti‐malarial immune response. However, it remains unclear whether this increase in Treg cells is due to thymus‐derived Treg cell expansion or induction of Treg cells in the periphery. Here, we show that the frequency of Foxp3(+) Treg cells expressing neuropilin‐1 (Nrp‐1) decreased at early time‐points during P. yoelii infection, whereas percentages of Helios(+) Foxp3(+) Treg cells remained unchanged. Both Foxp3(+) Nrp‐1(+) and Foxp3(+) Nrp‐1(−) Treg cells from P. yoelii‐infected mice exhibited a similar T‐cell receptor Vβ chain usage and methylation pattern in the Treg‐specific demethylation region within the foxp3 locus. Strikingly, we did not observe induction of Foxp3 expression in Foxp3(−) T cells adoptively transferred to P. yoelii‐infected mice. Hence, our results suggest that P. yoelii infection triggered expansion of naturally occurring Treg cells rather than de novo induction of Foxp3(+) Treg cells

Autonomous multi-dimensional slicing for large-scale distributed systems

Slicing is a distributed systems primitive that allows to autonomously partition a large set of nodes based on node-local attributes. Slicing is decisive for automatically provisioning system resources for different services, based on their requirements or importance. One of the main limitations of existing slicing protocols is that only single dimension attributes are considered for partitioning. In practical settings, it is often necessary to consider best compromises for an ensemble of metrics. In this paper we propose an extension of the slicing primitive that allows multi-attribute distributed systems slicing. Our protocol employs a gossip-based approach that does not require centralized knowledge and allows self-organization. It leverages the notion of domination between nodes, forming a partial order between multi-dimensional points, in a similar way to SkyLine queries for databases. We evaluate and demonstrate the interest of our approach using large-scale simulations.This work received support from the Portuguese Foundation for Science and Technology under grant SFRH/BD/71476/2010

Machine Learning with Physicochemical Relationships: Solubility Prediction in Organic Solvents and Water

Solubility prediction remains a critical challenge in drug development, synthetic route and chemical process design, extraction and crystallisation. Here we report a successful approach to solubility prediction in organic solvents and water using a combination of machine learning (ANN, SVM, RF, ExtraTrees, Bagging and GP) and computational chemistry. Rational interpretation of dissolution process into a numerical problem led to a small set of selected descriptors and subsequent predictions which are independent of the applied machine learning method. These models gave significantly more accurate predictions compared to benchmarked open-access and commercial tools, achieving accuracy close to the expected level of noise in training data (LogS ± 0.7). Finally, they reproduced physicochemical relationship between solubility and molecular properties in different solvents, which led to rational approaches to improve the accuracy of each models

Review of biorthogonal coupled cluster representations for electronic excitation

Single reference coupled-cluster (CC) methods for electronic excitation are based on a biorthogonal representation (bCC) of the (shifted) Hamiltonian in terms of excited CC states, also referred to as correlated excited (CE) states, and an associated set of states biorthogonal to the CE states, the latter being essentially configuration interaction (CI) configurations. The bCC representation generates a non-hermitian secular matrix, the eigenvalues representing excitation energies, while the corresponding spectral intensities are to be derived from both the left and right eigenvectors. Using the perspective of the bCC representation, a systematic and comprehensive analysis of the excited-state CC methods is given, extending and generalizing previous such studies. Here, the essential topics are the truncation error characteristics and the separability properties, the latter being crucial for designing size-consistent approximation schemes. Based on the general order relations for the bCC secular matrix and the (left and right) eigenvector matrices, formulas for the perturbation-theoretical (PT) order of the truncation errors (TEO) are derived for energies, transition moments, and property matrix elements of arbitrary excitation classes and truncation levels. In the analysis of the separability properties of the transition moments, the decisive role of the so-called dual ground state is revealed. Due to the use of CE states the bCC approach can be compared to so-called intermediate state representation (ISR) methods based exclusively on suitably orthonormalized CE states. As the present analysis shows, the bCC approach has decisive advantages over the conventional CI treatment, but also distinctly weaker TEO and separability properties in comparison with a full (and hermitian) ISR method

Perceived benefits and barriers to exercise for recently treated patients with multiple myeloma: a qualitative study

AbstractBackground: Understanding the physical activity experiences of patients with multiple myeloma (MM) is essential to inform the development of evidence-based interventions and to quantify the benefits of physical activity. The aim of this study was to gain an in-depth understanding of the physical activity experiences and perceived benefits and barriers to physical activity for patients with MM.Methods: This was a qualitative study that used a grounded theory approach. Semi-structured interviews were conducted in Victoria, Australia by telephone from December 2011-February 2012 with patients who had been treated for MM within the preceding 2 &ndash; 12 months. Interviews were transcribed and analysed using the constant comparison coding method to reduce the data to themes. Gender differences and differences between treatment groups were explored.Results: Twenty-four interviews were completed. The sample comprised 13 females (54%), with a mean age of 62 years (SD = 8.8). Sixteen (67%) participants had received an autologous stem cell transplant (ASCT). All participants currently engaged in a range of light to moderate intensity physical activity; walking and gardening were the most common activities. Recovery from the symptoms of MM and side effects of therapy, psychological benefits, social factors and enjoyment were important benefits of physical activity. Barriers to physical activity predominately related to the symptoms of MM and side effects of therapy, including pain, fatigue, and fear of infection. Low self- motivation was also a barrier. Women participated in a more diverse range of physical activities than men and there were gender differences in preferred type of physical activity. Women were more likely to report psychological and social benefits; whereas men reported physical activity as a way to keep busy and self- motivation was a barrier. Patients treated with an ASCT more often reported affective benefits of participation in physical activity and fatigue as a barrier. Patients treated with other therapies (e.g., chemotherapy, radiotherapy) were more likely to report pain as a barrier.Conclusions: Patients with MM experience debilitating effects of their condition and therapy, which influences their level and intensity of physical activity participation. Physical activity programs should be individualised; take into consideration gender differences and the impact of different types of therapy on physical activity; and focus on meeting the psychological, coping and recovery needs of patients.<br /

Dose Response of a Novel Exogenous Ketone Supplement on Physiological, Perceptual and Performance Parameters

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A Geological Itinerary Through the Southern Apennine Thrust-Belt (Basilicata—Southern Italy)

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