842 research outputs found
Conformal Radiotherapy Facilitates the Delivery of Concurrent Chemotherapy and Radiotherapy: A Case of Primitive Neuroectodermal Tumour of the Chest Wall
We illustrate the principle of conformal radiotherapy by discussing the case of a patient with a primitive neuroectodermal
tumour of the chest wall. Recent advances in radiotherapy planning enable precise localization of the planning target volume
(PTV) and normal organs at risk of irradiation. Customized blocks are subsequently designed to produce a treatment field
that ‘conforms’ to the PTV. The use of conformal radiotherapy (CRT) in this case facilitated the delivery of concurrent
chemotherapy and radiotherapy by significantly reducing the volume of red marrow irradiated.The lack of acute and late
toxicities was attributed to optimal exclusion of normal tissues from the treatment field, made possible by CRT
The Self Model and the Conception of Biological Identity in Immunology
The self/non-self model, first proposed by F.M. Burnet, has dominated immunology for sixty years now. According to this model, any foreign element will trigger an immune reaction in an organism, whereas endogenous elements will not, in normal circumstances, induce an immune reaction. In this paper we show that the self/non-self model is no longer an appropriate explanation of experimental data in immunology, and that this inadequacy may be rooted in an excessively strong metaphysical conception of biological identity. We suggest that another hypothesis, one based on the notion of continuity, gives a better account of immune phenomena. Finally, we underscore the mapping between this metaphysical deflation from self to continuity in immunology and the philosophical debate between substantialism and empiricism about identity
A statistical mechanics approach to autopoietic immune networks
The aim of this work is to try to bridge over theoretical immunology and
disordered statistical mechanics. Our long term hope is to contribute to the
development of a quantitative theoretical immunology from which practical
applications may stem. In order to make theoretical immunology appealing to the
statistical physicist audience we are going to work out a research article
which, from one side, may hopefully act as a benchmark for future improvements
and developments, from the other side, it is written in a very pedagogical way
both from a theoretical physics viewpoint as well as from the theoretical
immunology one.
Furthermore, we have chosen to test our model describing a wide range of
features of the adaptive immune response in only a paper: this has been
necessary in order to emphasize the benefit available when using disordered
statistical mechanics as a tool for the investigation. However, as a
consequence, each section is not at all exhaustive and would deserve deep
investigation: for the sake of completeness, we restricted details in the
analysis of each feature with the aim of introducing a self-consistent model.Comment: 22 pages, 14 figur
Randomly Evolving Idiotypic Networks: Structural Properties and Architecture
We consider a minimalistic dynamic model of the idiotypic network of
B-lymphocytes. A network node represents a population of B-lymphocytes of the
same specificity (idiotype), which is encoded by a bitstring. The links of the
network connect nodes with complementary and nearly complementary bitstrings,
allowing for a few mismatches. A node is occupied if a lymphocyte clone of the
corresponding idiotype exists, otherwise it is empty. There is a continuous
influx of new B-lymphocytes of random idiotype from the bone marrow.
B-lymphocytes are stimulated by cross-linking their receptors with
complementary structures. If there are too many complementary structures,
steric hindrance prevents cross-linking. Stimulated cells proliferate and
secrete antibodies of the same idiotype as their receptors, unstimulated
lymphocytes die.
Depending on few parameters, the autonomous system evolves randomly towards
patterns of highly organized architecture, where the nodes can be classified
into groups according to their statistical properties. We observe and describe
analytically the building principles of these patterns, which allow to
calculate number and size of the node groups and the number of links between
them. The architecture of all patterns observed so far in simulations can be
explained this way. A tool for real-time pattern identification is proposed.Comment: 19 pages, 15 figures, 4 table
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Size-dependent particle activation properties in fog during the ParisFog 2012/13 field campaign
Fog-induced visibility reduction is responsible for a variety of hazards in the transport sector. Therefore there is a large demand for an improved understanding of fog formation and thus improved forecasts. Improved fog forecasts require a better understanding of the numerous complex mechanisms during the fog life cycle. During winter 2012/13 a field campaign called ParisFog aiming at fog research took place at SIRTA (Instrumented Site for Atmospheric Remote Sensing Research). SIRTA is located about 20 km southwest of the Paris city center, France, in a semi-urban environment. In situ activation properties of the prevailing fog were investigated by measuring (1) total and interstitial (non-activated) dry particle number size distributions behind two different inlet systems; (2) interstitial hydrated aerosol and fog droplet size distributions at ambient conditions; and (3) cloud condensation nuclei (CCN) number concentration at different supersaturations (SS) with a CCN counter. The aerosol particles were characterized regarding their hygroscopic properties, fog droplet activation behavior and contribution to light scattering for 17 developed fog events. Low particle hygroscopicity with an overall median of the hygroscopicity parameter, κ, of 0.14 was found, likely caused by substantial influence from local traffic and wood burning emissions. Measurements of the aerosol size distribution at ambient RH revealed that the critical wet diameter, above which the hydrated aerosols activate to fog droplets, is rather large (with a median value of 2.6μm) and is highly variable (ranging from 1 to 5μm) between the different fog events. Thus, the number of activated fog droplets was very small and the non-activated hydrated particles were found to contribute significantly to the observed light scattering and thus to the reduction in visibility. Combining all experimental data, the effective peak supersaturation, SSpeak, a measure of the peak supersaturation during the fog formation, was determined. The median SSpeak value was estimated to be in the range from 0.031 to 0.046% (upper and lower limit estimations), which is in good agreement with previous experimental and modeling studies of fog
Galaxies and Cladistics
The Hubble tuning fork diagram, based on morphology and established in the
1930s, has always been the preferred scheme for classification of galaxies.
However, the current large amount of multiwavelength data, most often spectra,
for objects up to very high distances, asks for more sophisticated statistical
approaches. Interpreting formation and evolution of galaxies as a ?transmission
with modification' process, we have shown that the concepts and tools of
phylogenetic systematics can be heuristically transposed to the case of
galaxies. This approach, which we call ?astrocladistics', has successfully been
applied on several samples. Many difficulties still remain, some of them being
specific to the nature of both galaxies and their diversification processes,
some others being classical in cladistics, like the pertinence of the
descriptors in conveying any useful evolutionary information.Comment: Talk given at the "12th Evolutionary Biology Meeting" held in
Marseille, France, Sept. 24-26, 200
Hybrid metaheuristic for combinatorial optimization based on immune network for optimization and VNS
Metaheuristics for optimization based on the immune network theory are often highlighted by being able to maintain the diversity of candidate solutions present in the population, allowing a greater coverage of the search space. This work, however, shows that algorithms derived from the aiNET family for the solution of combinatorial problems may not present an adequate strategy for search space exploration, leading to premature convergence in local minimums. In order to solve this issue, a hybrid metaheuristic called VNS-aiNET is proposed, integrating aspects of the COPT-aiNET algorithm with characteristics of the trajectory metaheuristic Variable Neighborhood Search (VNS), as well as a new fitness function, which makes it possible to escape from local minima and enables it to a greater exploration of the search space. The proposed metaheuristic is evaluated using a scheduling problem widely studied in the literature. The performed experiments show that the proposed hybrid metaheuristic presents a convergence superior to two approaches of the aiNET family and to the reference algorithms of the literature. In contrast, the solutions present in the resulting immunological memory have less diversity when compared to the aiNET family approaches
Equilibrium statistical mechanics on correlated random graphs
Biological and social networks have recently attracted enormous attention
between physicists. Among several, two main aspects may be stressed: A non
trivial topology of the graph describing the mutual interactions between agents
exists and/or, typically, such interactions are essentially (weighted)
imitative. Despite such aspects are widely accepted and empirically confirmed,
the schemes currently exploited in order to generate the expected topology are
based on a-priori assumptions and in most cases still implement constant
intensities for links. Here we propose a simple shift in the definition of
patterns in an Hopfield model to convert frustration into dilution: By varying
the bias of the pattern distribution, the network topology -which is generated
by the reciprocal affinities among agents - crosses various well known regimes
(fully connected, linearly diverging connectivity, extreme dilution scenario,
no network), coupled with small world properties, which, in this context, are
emergent and no longer imposed a-priori. The model is investigated at first
focusing on these topological properties of the emergent network, then its
thermodynamics is analytically solved (at a replica symmetric level) by
extending the double stochastic stability technique, and presented together
with its fluctuation theory for a picture of criticality. At least at
equilibrium, dilution simply decreases the strength of the coupling felt by the
spins, but leaves the paramagnetic/ferromagnetic flavors unchanged. The main
difference with respect to previous investigations and a naive picture is that
within our approach replicas do not appear: instead of (multi)-overlaps as
order parameters, we introduce a class of magnetizations on all the possible
sub-graphs belonging to the main one investigated: As a consequence, for these
objects a closure for a self-consistent relation is achieved.Comment: 30 pages, 4 figure
The role of the microbiome in the neurobiology of social behaviour
Microbes colonise all multicellular life, and the gut microbiome has been shown to influence a range of host physiological and behavioural phenotypes. One of the most intriguing and least understood of these influences lies in the domain of the microbiome's interactions with host social behaviour, with new evidence revealing that the gut microbiome makes important contributions to animal sociality. However, little is known about the biological processes through which the microbiome might influence host social behaviour. Here, we synthesise evidence of the gut microbiome's interactions with various aspects of host sociality, including sociability, social cognition, social stress, and autism. We discuss evidence of microbial associations with the most likely physiological mediators of animal social interaction. These include the structure and function of regions of the 'social' brain (the amygdala, the prefrontal cortex, and the hippocampus) and the regulation of 'social' signalling molecules (glucocorticoids including corticosterone and cortisol, sex hormones including testosterone, oestrogens, and progestogens, neuropeptide hormones such as oxytocin and arginine vasopressin, and monoamine neurotransmitters such as serotonin and dopamine). We also discuss microbiome-associated host genetic and epigenetic processes relevant to social behaviour. We then review research on microbial interactions with olfaction in insects and mammals, which contribute to social signalling and communication. Following these discussions, we examine evidence of microbial associations with emotion and social behaviour in humans, focussing on psychobiotic studies, microbe-depression correlations, early human development, autism, and issues of statistical power, replication, and causality. We analyse how the putative physiological mediators of the microbiome-sociality connection may be investigated, and discuss issues relating to the interpretation of results. We also suggest that other candidate molecules should be studied, insofar as they exert effects on social behaviour and are known to interact with the microbiome. Finally, we consider different models of the sequence of microbial effects on host physiological development, and how these may contribute to host social behaviour.Peer reviewe
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