Maternal Expression Relaxes Constraint on Innovation of the Anterior Determinant, bicoid

The origin of evolutionary novelty is believed to involve both positive selection and relaxed developmental constraint. In flies, the redesign of anterior patterning during embryogenesis is a major developmental innovation and the rapidly evolving Hox gene, bicoid (bcd), plays a critical role. We report evidence for relaxation of selective constraint acting on bicoid as a result of its maternal pattern of gene expression. Evolutionary theory predicts 2-fold greater sequence diversity for maternal effect genes than for zygotically expressed genes, because natural selection is only half as effective acting on autosomal genes expressed in one sex as it is on genes expressed in both sexes. We sample an individual from ten populations of Drosophila melanogaster and nine populations of D. simulans for polymorphism in the tandem gene duplicates bcd, which is maternally expressed, and zerknüllt (zen), which is zygotically expressed. In both species, we find the ratio of bcd to zen nucleotide diversity to be two or more in the coding regions but one in the noncoding regions, providing the first quantitative support for the theoretical prediction of relaxed selective constraint on maternal-effect genes resulting from sex-limited expression. Our results suggest that the accelerated rate of evolution observed for bcd is owing, at least partly, to variation generated by relaxed selective constraint

How ions in solution can change the sign of the critical Casimir potential

We show that hydrophilic ions present in a confined, near-critical aqueous mixture can lead to an attraction between like charge surfaces with opposing preferential adsorption of the two species of the mixture, even though the corresponding Casimir potential in uncharged systems is repulsive. This prediction agrees with recent experiment [Nellen {\it{et al.}}, Soft Matter{\bf{80}}, 061143 (2011)]. We also show that oppositely charged hydrophobic surfaces can repel each other, although the Casimir potential between uncharged surfaces with like preferential adsorption (selectivity) is attractive. This behavior is expected when the electrostatic screening length is larger than the correlation length, and one of the confining surfaces is strongly selective and weakly charged, whereas the other confining surface is weakly selective and strongly charged. The Casimir potential can change sign because the hydrophilic ions near the weakly hydrophobic surface can overcompensate the effect of hydrophobicity, and this surface can act as a hydrophilic one. We also predict a more attractive interaction between hydrophilic surfaces and a more repulsive interaction between hydrophobic surfaces than given by the sum of the Casimir and Deby-H\"uckel potentials. Our theory is derived systematically from a microscopic approach, and combines the Landau-type and Debye-H\"uckel theories with an additional contribution of an entropic origin

Specificity quantification of biomolecular recognition and its implication for drug discovery

Highly efficient and specific biomolecular recognition requires both affinity and specificity. Previous quantitative descriptions of biomolecular recognition were mostly driven by improving the affinity prediction, but lack of quantification of specificity. We developed a novel method SPA (SPecificity and Affinity) based on our funneled energy landscape theory. The strategy is to simultaneously optimize the quantified specificity of the “native” protein-ligand complex discriminating against “non-native” binding modes and the affinity prediction. The benchmark testing of SPA shows the best performance against 16 other popular scoring functions in industry and academia on both prediction of binding affinity and “native” binding pose. For the target COX-2 of nonsteroidal anti-inflammatory drugs, SPA successfully discriminates the drugs from the diversity set, and the selective drugs from non-selective drugs. The remarkable performance demonstrates that SPA has significant potential applications in identifying lead compounds for drug discovery

The Fundamental Nature of the Log Loss Function

The standard loss functions used in the literature on probabilistic prediction are the log loss function, the Brier loss function, and the spherical loss function; however, any computable proper loss function can be used for comparison of prediction algorithms. This note shows that the log loss function is most selective in that any prediction algorithm that is optimal for a given data sequence (in the sense of the algorithmic theory of randomness) under the log loss function will be optimal under any computable proper mixable loss function; on the other hand, there is a data sequence and a prediction algorithm that is optimal for that sequence under either of the two other standard loss functions but not under the log loss function.Comment: 12 page

Beyond perceptual load and dilution: a review of the role of working memory in selective attention

The perceptual load and dilution models differ fundamentally in terms of the proposed mechanism underlying variation in distractibility during different perceptual conditions. However, both models predict that distracting information can be processed beyond perceptual processing under certain conditions, a prediction that is well-supported by the literature. Load theory proposes that in such cases, where perceptual task aspects do not allow for sufficient attentional selectivity, the maintenance of task-relevant processing depends on cognitive control mechanisms, including working memory. The key prediction is that working memory plays a role in keeping clear processing priorities in the face of potential distraction, and the evidence reviewed and evaluated in a meta-analysis here supports this claim, by showing that the processing of distracting information tends to be enhanced when load on a concurrent task of working memory is high. Low working memory capacity is similarly associated with greater distractor processing in selective attention, again suggesting that the unavailability of working memory during selective attention leads to an increase in distractibility. Together, these findings suggest that selective attention against distractors that are processed beyond perception depends on the availability of working memory. Possible mechanisms for the effects of working memory on selective attention are discussed

Predicting Thermal Adaptation by Looking Into Populations’ Genomic Past

Molecular evolution offers an insightful theory to interpret the genomic consequences of thermal adaptation to previous events of climate change beyond range shifts. However, disentangling often mixed footprints of selective and demographic processes from those due to lineage sorting, recombination rate variation, and genomic constrains is not trivial. Therefore, here we condense current and historical population genomic tools to study thermal adaptation and outline key developments (genomic prediction, machine learning) that might assist their utilization for improving forecasts of populations’ responses to thermal variation. We start by summarizing how recent thermal-driven selective and demographic responses can be inferred by coalescent methods and in turn how quantitative genetic theory offers suitable multi-trait predictions over a few generations via the breeder’s equation. We later assume that enough generations have passed as to display genomic signatures of divergent selection to thermal variation and describe how these footprints can be reconstructed using genome-wide association and selection scans or, alternatively, may be used for forward prediction over multiple generations under an infinitesimal genomic prediction model. Finally, we move deeper in time to comprehend the genomic consequences of thermal shifts at an evolutionary time scale by relying on phylogeographic approaches that allow for reticulate evolution and ecological parapatric speciation, and end by envisioning the potential of modern machine learning techniques to better inform long-term predictions. We conclude that foreseeing future thermal adaptive responses requires bridging the multiple spatial scales of historical and predictive environmental change research under modern cohesive approaches such as genomic prediction and machine learning frameworks

A Psychophysical Experiment to Test the Efficient Stereo Coding Theory

A theory of efficient stereo coding [2] predicts that, in a natural visual environment, where the ocular correlation of the input depends on stimulus orientations, the striate cortical cells are more likely binocular when selective to horizontal rather than vertical orientations. A psychophysical experiment was designed to test this prediction. The interocular transfers of simultaneous orientation contrast at near horizontal and vertical orientations were measured. This measure was used to access the binocularity of the underlying cells. It turned out that in the natural stereovisual environment, the transfers for horizontal orientations were larger than that for vertical case. And in the unnatural stereo experimental environment, where the binocular correlation is the same for vertical and horizontal orientations, the transfer for the horizontal orientation was almost equal to that in the corresponding vertical case. These results are consistent with the theoretical prediction