Modelling the nucleon wave function from soft and hard processes

Current light-cone wave functions for the nucleon are unsatisfactory since they are in conflict with the data of the nucleon's Dirac form factor at large momentum transfer. Therefore, we attempt a determination of a new wave function respecting theoretical ideas on its parameterization and satisfying the following constraints: It should provide a soft Feynman contribution to the proton's form factor in agreement with data; it should be consistent with current parameterizations of the valence quark distribution functions and lastly it should provide an acceptable value for the \jp \to N \bar N decay width. The latter process is calculated within the modified perturbative approach to hard exclusive reactions. A simultaneous fit to the three sets of data leads to a wave function whose $x$-dependent part, the distribution amplitude, shows the same type of asymmetry as those distribution amplitudes constrained by QCD sum rules. The asymmetry is however much more moderate as in those amplitudes. Our distribution amplitude resembles the asymptotic one in shape but the position of the maximum is somewhat shifted.Comment: 32 pages RevTex + PS-file with 5 figures in uu-encoded, compressed fil

Familial history of diabetes and clinical characteristics in Greek subjects with type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>A lot of studies have showed an excess maternal transmission of type 2 diabetes (T2D). The aim, therefore, of the present study was to estimate the prevalence of familial history of T2D in Greek patients, and to evaluate its potential effect on the patient's metabolic control and the presence of diabetic complications.</p> <p>Methods</p> <p>A total of 1,473 T2D patients were recruited. Those with diabetic mothers, diabetic fathers, diabetic relatives other than parents and no known diabetic relatives, were considered separately.</p> <p>Results</p> <p>The prevalence of diabetes in the mother, the father and relatives other than parents, was 27.7, 11.0 and 10.7%, respectively. Patients with paternal diabetes had a higher prevalence of hypertension (64.8 vs. 57.1%, P = 0.05) and lower LDL-cholesterol levels (115.12 ± 39.76 vs. 127.13 ± 46.53 mg/dl, P = 0.006) than patients with diabetes in the mother. Patients with familial diabetes were significantly younger (P < 0.001), with lower age at diabetes diagnosis (P < 0.001) than those without diabetic relatives. Patients with a diabetic parent had higher body mass index (BMI) (31.22 ± 5.87 vs. 30.67 ± 5.35 Kg/m², P = 0.08), higher prevalence of dyslipidemia (49.8 vs. 44.6%, P = 0.06) and retinopathy (17.9 vs. 14.5%, P = 0.08) compared with patients with no diabetic relatives. No difference in the degree of metabolic control and the prevalence of chronic complications were observed.</p> <p>Conclusion</p> <p>The present study showed an excess maternal transmission of T2D in a sample of Greek diabetic patients. However, no different influence was found between maternal and paternal diabetes on the clinical characteristics of diabetic patients except for LDL-cholesterol levels and presence of hypertension. The presence of a family history of diabetes resulted to an early onset of the disease to the offspring.</p

Measuring macroscopic brain connections in vivo

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means

Prevalence, and associated risk factors, of self-reported diabetes mellitus in a sample of adult urban population in Greece: MEDICAL Exit Poll Research in Salamis (MEDICAL EXPRESS 2002)

BACKGROUND: The continuous monitoring and future prediction of the growing epidemic of diabetes mellitus worldwide presuppose consistent information about the extent of the problem. The aim of this study was to determine the prevalence of diagnosed diabetes and to identify associated risk factors in a sample of adult urban Greek population. METHODS: A cross-sectional population-based survey was conducted in municipality of Salamis, Greece, during an election day (2002). The study sample consisted of 2805 participants, aged 20–94 years. Data were collected using a standardized short questionnaire that was completed by a face-to-face interview. Multiple regression analyses were performed to evaluate the association of diabetes with potential risk factors. RESULTS: The overall prevalence of diagnosed diabetes was 8.7% (95% CI 7.7–9.8%). After age adjustment for the current adult population (2001 census) of Greece, the projection prevalence was calculated to 8.2%. Multivariate logistic regression analysis identified as independent risk factors: increasing age (odds ratio, OR = 1.07, 95% CI 1.06–1.08), male sex (OR = 1.43, 95% CI 1.04–1.95), overweight and obesity (OR = 1.97, 95% CI 1.29–3.01 and OR = 3.76, 95% CI 2.41–5.86, respectively), family history of diabetes (OR = 6.91, 95% CI 5.11–9.34), hypertension (OR = 2.19, 95% CI 1.60–2.99) and, among women, lower educational level (OR = 2.62, 95% CI 1.22–5.63). The prevalence of overweight and obesity, based on self-reported BMI, were 44.2% and 18.4%, respectively. Moreover, the odds for diabetes in obese subjects with family history were 25-fold higher than those with normal weight and without family history of diabetes, while the odds in overweight subjects with family history of diabetes were 15-fold higher. CONCLUSIONS: Our findings indicated that the prevalence of diabetes is high in Greek population. It is suggested that the main modifiable contributing factor is obesity, whose effect is extremely increased upon positive heredity presence

OptCircuit: An optimization based method for computational design of genetic circuits

<p>Abstract</p> <p>Background</p> <p>Recent years has witnessed an increasing number of studies on constructing simple synthetic genetic circuits that exhibit desired properties such as oscillatory behavior, inducer specific activation/repression, etc. It has been widely acknowledged that that task of building circuits to meet multiple inducer-specific requirements is a challenging one. This is because of the incomplete description of component interactions compounded by the fact that the number of ways in which one can chose and interconnect components, increases exponentially with the number of components.</p> <p>Results</p> <p>In this paper we introduce OptCircuit, an optimization based framework that automatically identifies the circuit components from a list and connectivity that brings about the desired functionality. Multiple literature sources are used to compile a comprehensive compilation of kinetic descriptions of promoter-protein pairs. The dynamics that govern the interactions between the elements of the genetic circuit are currently modeled using deterministic ordinary differential equations but the framework is general enough to accommodate stochastic simulations. The desired circuit response is abstracted as the maximization/minimization of an appropriately constructed objective function. Computational results for a toggle switch example demonstrate the ability of the framework to generate the complete list of circuit designs of varying complexity that exhibit the desired response. Designs identified for a genetic decoder highlight the ability of OptCircuit to suggest circuit configurations that go beyond the ones compatible with digital logic-based design principles. Finally, the results obtained from the concentration band detector example demonstrate the ability of OptCircuit to design circuits whose responses are contingent on the level of external inducer as well as pinpoint parameters for modification to rectify an existing (non-functional) biological circuit and restore functionality.</p> <p>Conclusion</p> <p>Our results demonstrate that OptCircuit framework can serve as a design platform to aid in the construction and finetuning of integrated biological circuits.</p

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments

Is there just one dyslexic reader? Evidence for the existence of distinct dyslexic sub-groups.

Purpose of Review. It is generally agreed that there are individual differences in the severity of the reading deficit in dyslexia. The purpose of this review is to discuss whether recent research strengthens claims that there are also qualitative differences in the type of reading impairment that individual dyslexic children experience. Recent Findings. Recent research suggests that surface dyslexia exists in larger numbers than has previously been assumed and that different subtypes of surface dyslexia exist in English as well as in Hebrew. Bilinguals with surface dyslexia in English also show the hallmarks of surface dyslexia when reading a more transparent orthography. The developmental reading impairments that have been observed in children with phonological dyslexia and in children with letter position dyslexia can also be found in several different orthographies and are quite distinct from those seen in surface dyslexia. Summary. Surface dyslexia, phonological dyslexia and letter position dyslexia represent qualitatively different types of developmental reading impairments and can all be seen in both opaque and more transparent alphabetic orthographies