Genetic correlations greatly increase mutational robustness and can both reduce and enhance evolvability

Mutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps—a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure—to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so increase evolvability

Deep learning generalizes because the parameter-function map is biased towards simple functions

This is the final version. Available from ICLR via the link in this recordDeep neural networks (DNNs) generalize remarkably well without explicit regularization even in the strongly over-parametrized regime where classical learning theory would instead predict that they would severely overfit. While many proposals for some kind of implicit regularization have been made to rationalise this success, there is no consensus for the fundamental reason why DNNs do not strongly overfit. In this paper, we provide a new explanation. By applying a very general probability-complexity bound recently derived from algorithmic information theory (AIT), we argue that the parameter-function map of many DNNs should be exponentially biased towards simple functions. We then provide clear evidence for this strong bias in a model DNN for Boolean functions, as well as in much larger fully conected and convolutional networks trained on CIFAR10 and MNIST. As the target functions in many real problems are expected to be highly structured, this intrinsic simplicity bias helps explain why deep networks generalize well on real world problems. This picture also facilitates a novel PAC-Bayes approach where the prior is taken over the DNN input-output function space, rather than the more conventional prior over parameter space. If we assume that the training algorithm samples parameters close to uniformly within the zero-error region then the PAC-Bayes theorem can be used to guarantee good expected generalization for target functions producing high-likelihood training sets. By exploiting recently discovered connections between DNNs and Gaussian processes to estimate the marginal likelihood, we produce relatively tight generalization PAC-Bayes error bounds which correlate well with the true error on realistic datasets such as MNIST and CIFAR10and for architectures including convolutional and fully connected networks

Input–output maps are strongly biased towards simple outputs

This is the final version. Available from Nature Research via the DOI in this record. The data sets generated during and/or analysed during the current study are available from the corresponding authors on reasonable request.Many systems in nature can be described using discrete input–output maps. Without knowing details about a map, there may seem to be no a priori reason to expect that a randomly chosen input would be more likely to generate one output over another. Here, by extending fundamental results from algorithmic information theory, we show instead that for many real-world maps, the a priori probability P(x) that randomly sampled inputs generate a particular output x decays exponentially with the approximate Kolmogorov complexity K(x) of that output. These input–output maps are biased towards simplicity. We derive an upper bound P(x) ≲ 2^−aK(x)−b, which is tight for most inputs. The constants a and b, as well as many properties of P(x), can be predicted with minimal knowledge of the map. We explore this strong bias towards simple outputs in systems ranging from the folding of RNA secondary structures to systems of coupled ordinary differential equations to a stochastic financial trading model.Engineering and Physical Sciences Research Council (EPSRC)Clarendon Fun

Characterizing the bending and flexibility induced by bulges in DNA duplexes

Advances in DNA nanotechnology have stimulated the search for simple motifs that can be used to control the properties of DNA nanostructures. One such motif, which has been used extensively in structures such as polyhedral cages, two-dimensional arrays, and ribbons, is a bulged duplex, that is, two helical segments that connect at a bulge loop. We use a coarse-grained model of DNA to characterize such bulged duplexes. We find that this motif can adopt structures belonging to two main classes: one where the stacking of the helices at the center of the system is preserved, the geometry is roughly straight, and the bulge is on one side of the duplex and the other where the stacking at the center is broken, thus allowing this junction to act as a hinge and increasing flexibility. Small loops favor states where stacking at the center of the duplex is preserved, with loop bases either flipped out or incorporated into the duplex. Duplexes with longer loops show more of a tendency to unstack at the bulge and adopt an open structure. The unstacking probability, however, is highest for loops of intermediate lengths, when the rigidity of single-stranded DNA is significant and the loop resists compression. The properties of this basic structural motif clearly correlate with the structural behavior of certain nano-scale objects, where the enhanced flexibility associated with larger bulges has been used to tune the self-assembly product as well as the detailed geometry of the resulting nanostructures. We further demonstrate the role of bulges in determining the structure of a "Z-tile," a basic building block for nanostructures

High levels of dietary stearate promote adiposity and deteriorate hepatic insulin sensitivity

<p>Abstract</p> <p>Background</p> <p>Relatively little is known about the role of specific saturated fatty acids in the development of high fat diet induced obesity and insulin resistance. Here, we have studied the effect of stearate in high fat diets (45% energy as fat) on whole body energy metabolism and tissue specific insulin sensitivity.</p> <p>Methods</p> <p>C57Bl/6 mice were fed a low stearate diet based on palm oil or one of two stearate rich diets, one diet based on lard and one diet based on palm oil supplemented with tristearin (to the stearate level of the lard based diet), for a period of 5 weeks. <it>Ad libitum </it>fed Oxidative metabolism was assessed by indirect calorimetry at week 5. Changes in body mass and composition was assessed by DEXA scan analysis. Tissue specific insulin sensitivity was assessed by hyperinsulinemic-euglycemic clamp analysis and Western blot at the end of week 5.</p> <p>Results</p> <p>Indirect calorimetry analysis revealed that high levels of dietary stearate resulted in lower caloric energy expenditure characterized by lower oxidation of fatty acids. In agreement with this metabolic phenotype, mice on the stearate rich diets gained more adipose tissue mass. Whole body and tissue specific insulin sensitivity was assessed by hyperinsulinemic-euglycemic clamp and analysis of insulin induced PKB^ser473phosphorylation. Whole body insulin sensitivity was decreased by all high fat diets. However, while insulin-stimulated glucose uptake by peripheral tissues was impaired by all high fat diets, hepatic insulin sensitivity was affected only by the stearate rich diets. This tissue-specific pattern of reduced insulin sensitivity was confirmed by similar impairment in insulin-induced phosphorylation of PKB^ser473in both liver and skeletal muscle.</p> <p>Conclusion</p> <p>In C57Bl/6 mice, 5 weeks of a high fat diet rich in stearate induces a metabolic state favoring low oxidative metabolism, increased adiposity and whole body insulin resistance characterized by severe hepatic insulin resistance. These results indicate that dietary fatty acid composition <it>per sé </it>rather than dietary fat content determines insulin sensitivity in liver of high fat fed C57Bl/6 mice.</p

Cognitive phenotype of juvenile absence epilepsy: An investigation of patients and unaffected siblings

Objective: The cognitive profile of juvenile absence epilepsy (JAE) remains largely uncharacterized. This study aimed to: (1) elucidate the neuropsychological profile of JAE; (2) identify familial cognitive traits by investigating unaffected JAE siblings; (3) establish the clinical meaningfulness of JAE-associated cognitive traits; (4) determine whether cognitive traits across the idiopathic generalized epilepsy (IGE) spectrum are shared or syndrome-specific, by comparing JAE to juvenile myoclonic epilepsy (JME); and (5) identify relationships between cognitive abilities and clinical characteristics. Methods: We investigated 123 participants—23 patients with JAE, 16 unaffected siblings of JAE patients, 45 healthy controls, and 39 patients with JME—who underwent a comprehensive neuropsychological test battery including measures within four cognitive domains: attention/psychomotor speed, language, memory, and executive function. We correlated clinical measures with cognitive performance data to decode effects of age at onset and duration of epilepsy. Results: Cognitive performance in individuals with JAE was reduced compared to controls across attention/psychomotor speed, language, and executive function domains; those with ongoing seizures additionally showed lower memory scores. Patients with JAE and their unaffected siblings had similar language impairment compared to controls. Individuals with JME had worse response inhibition than those with JAE. Across all patients, those with older age at onset had better attention/psychomotor speed performance. Significance: JAE is associated with wide-ranging cognitive difficulties that encompass domains reliant on frontal lobe processing, including language, attention, and executive function. JAE siblings share impairment with patients on linguistic measures, indicative of a familial trait. Executive function subdomains may be differentially affected across the IGE spectrum. Cognitive abilities are detrimentally modulated by an early age at seizure onset

Measurement of the antineutrino neutral-current elastic differential cross section

arXiv:1309.7257v1 [hep-ex

Motor performance in five-year-old extracorporeal membrane oxygenation survivors: a population-based study

Contains fulltext : 79690.pdf (publisher's version ) (Open Access)INTRODUCTION: Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a cardio-pulmonary bypass technique to provide life support in acute reversible cardio-respiratory failure when conventional management is not successful. Most neonates receiving ECMO suffer from meconium aspiration syndrome (MAS), congenital diaphragmatic hernia (CDH), sepsis or persistent pulmonary hypertension (PPH). In five-year-old children who underwent VA-ECMO therapy as neonates, we assessed motor performance related to growth, intelligence and behaviour, and the association with the primary diagnosis. METHODS: In a prospective population-based study (n = 224) 174 five-year-old survivors born between 1993 and 2000 and treated in the two designated ECMO centres in the Netherlands (Radboud University Medical Centre Nijmegen and Sophia Children's Hospital, Erasmus MC - University Medical Center Rotterdam) were invited to undergo follow-up assessment including a paediatric assessment, the movement assessment battery for children (MABC), the revised Amsterdam intelligence test (RAKIT) and the child behaviour checklist (CBCL). RESULTS: Twenty-two percent of the children died before the age of five, 86% (n = 149) of the survivors were assessed. Normal development in all domains was found in 49% of children. Severe disabilities were present in 13%, and another 9% had impaired motor development combined with cognitive and/or behavioural problems. Chi-squared tests showed adverse outcome in MABC scores (P < 0.001) compared with the reference population in children with CDH, sepsis and PPH, but not in children with MAS. Compared with the Dutch population height, body mass index (BMI) and weight for height were lower in the CDH group (P < 0.001). RAKIT and CBCL scores did not differ from the reference population. Total MABC scores, socio-economic status, growth and CBCL scores were not related to each other, but negative motor outcome was related to lower intelligence quotient (IQ) scores (r = 0.48, P < 0.001). CONCLUSIONS: The ECMO population is highly at risk for developmental problems, most prominently in the motor domain. Adverse outcome differs between the primary diagnosis groups. Objective evaluation of long-term developmental problems associated with this highly invasive technology is necessary to determine best evidence-based practice. The ideal follow-up programme requires an interdisciplinary team, the use of normal-referenced tests and an international consensus on timing and actual outcome measurements

Motor performance in five-year-old extracorporeal membrane oxygenation survivors: a population-based study

Contains fulltext : 79690.pdf (publisher's version ) (Open Access)INTRODUCTION: Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a cardio-pulmonary bypass technique to provide life support in acute reversible cardio-respiratory failure when conventional management is not successful. Most neonates receiving ECMO suffer from meconium aspiration syndrome (MAS), congenital diaphragmatic hernia (CDH), sepsis or persistent pulmonary hypertension (PPH). In five-year-old children who underwent VA-ECMO therapy as neonates, we assessed motor performance related to growth, intelligence and behaviour, and the association with the primary diagnosis. METHODS: In a prospective population-based study (n = 224) 174 five-year-old survivors born between 1993 and 2000 and treated in the two designated ECMO centres in the Netherlands (Radboud University Medical Centre Nijmegen and Sophia Children's Hospital, Erasmus MC - University Medical Center Rotterdam) were invited to undergo follow-up assessment including a paediatric assessment, the movement assessment battery for children (MABC), the revised Amsterdam intelligence test (RAKIT) and the child behaviour checklist (CBCL). RESULTS: Twenty-two percent of the children died before the age of five, 86% (n = 149) of the survivors were assessed. Normal development in all domains was found in 49% of children. Severe disabilities were present in 13%, and another 9% had impaired motor development combined with cognitive and/or behavioural problems. Chi-squared tests showed adverse outcome in MABC scores (P < 0.001) compared with the reference population in children with CDH, sepsis and PPH, but not in children with MAS. Compared with the Dutch population height, body mass index (BMI) and weight for height were lower in the CDH group (P < 0.001). RAKIT and CBCL scores did not differ from the reference population. Total MABC scores, socio-economic status, growth and CBCL scores were not related to each other, but negative motor outcome was related to lower intelligence quotient (IQ) scores (r = 0.48, P < 0.001). CONCLUSIONS: The ECMO population is highly at risk for developmental problems, most prominently in the motor domain. Adverse outcome differs between the primary diagnosis groups. Objective evaluation of long-term developmental problems associated with this highly invasive technology is necessary to determine best evidence-based practice. The ideal follow-up programme requires an interdisciplinary team, the use of normal-referenced tests and an international consensus on timing and actual outcome measurements