OPN/CD44v6 overexpression in laryngeal dysplasia and correlation with clinical outcome

Laryngeal dysplasia is a common clinical concern. Despite major advancements, a significant number of patients with this condition progress to invasive squamous cell carcinoma. Osteopontin (OPN) is a secreted glycoprotein, whose expression is markedly elevated in several types of cancers. We explored OPN as a candidate biomarker for laryngeal dysplasia. To this aim, we examined OPN expression in 82 cases of dysplasia and in hyperplastic and normal tissue samples. OPN expression was elevated in all severe dysplasia samples, but not hyperplastic samples, with respect to matched normal mucosa. OPN expression levels correlated positively with degree of dysplasia (P=0.0094) and negatively with disease-free survival (P<0.0001). OPN expression was paralleled by cell surface reactivity for CD44v6, an OPN functional receptor. CD44v6 expression correlated negatively with disease-free survival, as well (P=0.0007). Taken as a whole, our finding identify OPN and CD44v6 as predictive markers of recurrence or aggressiveness in laryngeal intraepithelial neoplasia, and overall, point out an important signalling complex in the evolution of laryngeal dysplasia

Genetic risk factors for cerebrovascular disease in children with sickle cell disease: design of a case-control association study and genomewide screen

BACKGROUND: The phenotypic heterogeneity of sickle cell disease is likely the result of multiple genetic factors and their interaction with the sickle mutation. High transcranial doppler (TCD) velocities define a subgroup of children with sickle cell disease who are at increased risk for developing ischemic stroke. The genetic factors leading to the development of a high TCD velocity (i.e. cerebrovascular disease) and ultimately to stroke are not well characterized. METHODS: We have designed a case-control association study to elucidate the role of genetic polymorphisms as risk factors for cerebrovascular disease as measured by a high TCD velocity in children with sickle cell disease. The study will consist of two parts: a candidate gene study and a genomewide screen and will be performed in 230 cases and 400 controls. Cases will include 130 patients (TCD ≥ 200 cm/s) randomized in the Stroke Prevention Trial in Sickle Cell Anemia (STOP) study as well as 100 other patients found to have high TCD in STOP II screening. Four hundred sickle cell disease patients with a normal TCD velocity (TCD < 170 cm/s) will be controls. The candidate gene study will involve the analysis of 28 genetic polymorphisms in 20 candidate genes. The polymorphisms include mutations in coagulation factor genes (Factor V, Prothrombin, Fibrinogen, Factor VII, Factor XIII, PAI-1), platelet activation/function (GpIIb/IIIa, GpIb IX-V, GpIa/IIa), vascular reactivity (ACE), endothelial cell function (MTHFR, thrombomodulin, VCAM-1, E-Selectin, L-Selectin, P-Selectin, ICAM-1), inflammation (TNFα), lipid metabolism (Apo A1, Apo E), and cell adhesion (VCAM-1, E-Selectin, L-Selectin, P-Selectin, ICAM-1). We will perform a genomewide screen of validated single nucleotide polymorphisms (SNPs) in pooled DNA samples from 230 cases and 400 controls to study the possible association of additional polymorphisms with the high-risk phenotype. High-throughput SNP genotyping will be performed through MALDI-TOF technology using Sequenom's MassARRAY™ system. DISCUSSION: It is expected that this study will yield important information on genetic risk factors for the cerebrovascular disease phenotype in sickle cell disease by clarifying the role of candidate genes in the development of high TCD. The genomewide screen for a large number of SNPs may uncover the association of novel polymorphisms with cerebrovascular disease and stroke in sickle cell disease

Economic evaluation of multiplex ligation-dependent probe amplification and karyotyping in prenatal diagnosis: a cost-minimization analysis

textabstractPurpose: To assess the cost-effectiveness of Multiplex Ligation-dependent Probe Amplification (MLPA, P095 kit) compared to karyotyping. Methods: A cost-minimization analysis alongside a nationwide prospective clinical study of 4,585 women undergoing amniocentesis on behalf of their age (≥36 years), an increased risk following first trimester prenatal screening or parental anxiety. Results: Diagnostic accuracy of MLPA (P095 kit) was comparable to karyotyping (1.0 95% CI 0.999-1.0). Health-related quality of life did not differ between the strategies (summary physical health: mean difference 0.31, p = 0.82; summary mental health: mean difference 1.91, p = 0.22). Short-term costs were lower for MLPA: mean difference €315.68 (bootstrap 95% CI €315.63-315.74; -44.4%). The long-term costs were slightly higher for MLPA: mean difference €76.42 (bootstrap 95% CI €71.32-81.52; +8.6%). Total costs were on average €240.13 (bootstrap 95% CI €235.02-245.23; -14.9%) lower in favor of MLPA. Cost differences were sensitive to proportion of terminated pregnancies, sample throughput, individual choice and performance of tests in one laboratory, but not to failure rate or the exclusion of polluted samples. Conclusion: From an economic perspective, MLPA is the preferred prenatal diagnostic strategy in women who undergo amniocentesis on behalf of their age, following prenatal screening or parental anxiety

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.A.G.-M. was supported by the SynBio3D project of the UK Engineering and Physical Sciences Research Council (EP/R019002/1) and the European CSA on biological standardization BIOROBOOST (EU grant number 820699). T.E.G. was supported by a Royal Society University Research Fellowship (grant UF160357) and BrisSynBio, a BBSRC/ EPSRC Synthetic Biology Research Centre (grant BB/L01386X/1). P.Z. was supported by the EPSRC Portabolomics project (grant EP/N031962/1). P.C. was supported by SynBioChem, a BBSRC/EPSRC Centre for Synthetic Biology of Fine and Specialty Chemicals (grant BB/M017702/1) and the ShikiFactory100 project of the European Union’s Horizon 2020 research and innovation programme under grant agreement 814408

Unifying syntactic theory and sentence processing difficulty through a connectionist minimalist parser

Syntactic theory provides a rich array of representational assumptions about linguistic knowledge and processes. Such detailed and independently motivated constraints on grammatical knowledge ought to play a role in sentence comprehension. However most grammar-based explanations of processing difficulty in the literature have attempted to use grammatical representations and processes per se to explain processing difficulty. They did not take into account that the description of higher cognition in mind and brain encompasses two levels: on the one hand, at the macrolevel, symbolic computation is performed, and on the other hand, at the microlevel, computation is achieved through processes within a dynamical system. One critical question is therefore how linguistic theory and dynamical systems can be unified to provide an explanation for processing effects. Here, we present such a unification for a particular account to syntactic theory: namely a parser for Stabler's Minimalist Grammars, in the framework of Smolensky's Integrated Connectionist/Symbolic architectures. In simulations we demonstrate that the connectionist minimalist parser produces predictions which mirror global empirical findings from psycholinguistic research

A dynamical systems perspective on the relationship between symbolic and non-symbolic computation

It has been claimed that connectionist (artificial neural network) models of language processing, which do not appear to employ “rules”, are doing something different in kind from classical symbol processing models, which treat “rules” as atoms (e.g., McClelland and Patterson in Trends Cogn Sci 6(11):465–472, 2002). This claim is hard to assess in the absence of careful, formal comparisons between the two approaches. This paper formally investigates the symbol-processing properties of simple dynamical systems called affine dynamical automata, which are close relatives of several recurrent connectionist models of language processing (e.g., Elman in Cogn Sci 14:179–211, 1990). In line with related work (Moore in Theor Comput Sci 201:99–136, 1998; Siegelmann in Neural networks and analog computation: beyond the Turing limit. Birkhäuser, Boston, 1999), the analysis shows that affine dynamical automata exhibit a range of symbol processing behaviors, some of which can be mirrored by various Turing machine devices, and others of which cannot be. On the assumption that the Turing machine framework is a good way to formalize the “computation” part of our understanding of classical symbol processing, this finding supports the view that there is a fundamental “incompatibility” between connectionist and classical models (see Fodor and Pylyshyn 1988; Smolensky in Behav Brain Sci 11(1):1–74, 1988; beim Graben in Mind Matter 2(2):29--51,2004b). Given the empirical successes of connectionist models, the more general, super-Turing framework is a preferable vantage point from which to consider cognitive phenomena. This vantage may give us insight into ill-formed as well as well-formed language behavior and shed light on important structural properties of learning processes