Three Bead Rotating Chain model shows universality in the stretching of proteins

We introduce a model of proteins in which all of the key atoms in the protein backbone are accounted for, thus extending the Freely Rotating Chain model. We use average bond lengths and average angles from the Protein Databank as input parameters, leaving the number of residues as a single variable. The model is used to study the stretching of proteins in the entropic regime. The results of our Monte Carlo simulations are found to agree well with experimental data, suggesting that the force extension plot is universal and does not depend on the side chains or primary structure of proteins

Scale-free networks with an exponent less than two

We study scale free simple graphs with an exponent of the degree distribution $\gamma$ less than two. Generically one expects such extremely skewed networks -- which occur very frequently in systems of virtually or logically connected units -- to have different properties than those of scale free networks with $\gamma>2$: The number of links grows faster than the number of nodes and they naturally posses the small world property, because the diameter increases by the logarithm of the size of the network and the clustering coefficient is finite. We discuss a simple prototype model of such networks, inspired by real world phenomena, which exhibits these properties and allows for a detailed analytical investigation

Major Thought Restructuring: The Roles of Different Prefrontal Cortical Regions

An important question for understanding the neural basis of problem solving is whether the regions of human prefrontal cortices play qualitatively different roles in the major cognitive restructuring required to solve difficult problems. However, investigating this question using neuroimaging faces a major dilemma: either the problems do not require major cognitive restructuring, or if they do, the restructuring typically happens once, rendering repeated measurements of the critical mental process impossible. To circumvent these problems, young adult participants were challenged with a one-dimensional Subtraction (or Nim) problem [Bouton, C. L. Nim, a game with a complete mathematical theory. The Annals of Mathematics, 3, 35-39, 1901] that can be tackled using two possible strategies. One, often used initially, is effortful, slow, and error-prone, whereas the abstract solution, once achieved, is easier, quicker, and more accurate. Behaviorally, success was strongly correlated with sex. Using voxel-based morphometry analysis controlling for sex, we found that participants who found the more abstract strategy (i.e., Solvers) had more gray matter volume in the anterior medial, ventrolateral prefrontal, and parietal cortices compared with those who never switched from the initial effortful strategy (i.e., Explorers). Removing the sex covariate showed higher gray matter volume in Solvers (vs. Explorers) in the right ventrolateral prefrontal and left parietal cortex

Continuum model for polymers with finite thickness

We consider the continuum limit of a recently-introduced model for discretized thick polymers, or tubes. We address both analytically and numerically how the polymer thickness influences the decay of tangent-tangent correlations and find how the persistence length scales with the thickness and the torsional rigidity of the tube centerline. At variance with the worm-like chain model, the phase diagram that we obtain for a continuous tube is richer; in particular, for a given polymer thickness there exists a threshold value for the centerline torsional rigidity separating a simple exponential decay of the tangent-tangent correlation from an oscillatory one.Comment: 8 pages, 4 figures. Accepted for publication in J. Phys.

Highly Designable Protein Structures and Inter Monomer Interactions

By exact computer enumeration and combinatorial methods, we have calculated the designability of proteins in a simple lattice H-P model for the protein folding problem. We show that if the strength of the non-additive part of the interaction potential becomes larger than a critical value, the degree of designability of structures will depend on the parameters of potential. We also show that the existence of a unique ground state is highly sensitive to mutation in certain sites.Comment: 14 pages, Latex file, 3 latex and 6 eps figures are include

Monotonicity, frustration, and ordered response: an analysis of the energy landscape of perturbed large-scale biological networks

<p>Abstract</p> <p>Background</p> <p>For large-scale biological networks represented as signed graphs, the index of frustration measures how far a network is from a monotone system, i.e., how incoherently the system responds to perturbations.</p> <p>Results</p> <p>In this paper we find that the frustration is systematically lower in transcriptional networks (modeled at functional level) than in signaling and metabolic networks (modeled at stoichiometric level). A possible interpretation of this result is in terms of energetic cost of an interaction: an erroneous or contradictory transcriptional action costs much more than a signaling/metabolic error, and therefore must be avoided as much as possible. Averaging over all possible perturbations, however, we also find that unlike for transcriptional networks, in the signaling/metabolic networks the probability of finding the system in its least frustrated configuration tends to be high also in correspondence of a moderate energetic regime, meaning that, in spite of the higher frustration, these networks can achieve a globally ordered response to perturbations even for moderate values of the strength of the interactions. Furthermore, an analysis of the energy landscape shows that signaling and metabolic networks lack energetic barriers around their global optima, a property also favouring global order.</p> <p>Conclusion</p> <p>In conclusion, transcriptional and signaling/metabolic networks appear to have systematic differences in both the index of frustration and the transition to global order. These differences are interpretable in terms of the different functions of the various classes of networks.</p

Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications

The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches and in applications to real-world problems. Complex networks have fared extremely well in both of these aspects, with their sound theoretical basis developed over the years and with a variety of applications. In this survey, we analyze the applications of complex networks to real-world problems and data, with emphasis in representation, analysis and modeling, after an introduction to the main concepts and models. A diversity of phenomena are surveyed, which may be classified into no less than 22 areas, providing a clear indication of the impact of the field of complex networks.Comment: 103 pages, 3 figures and 7 tables. A working manuscript, suggestions are welcome

More Than Smell—COVID-19 Is Associated With Severe Impairment of Smell, Taste, and Chemesthesis

Correction: Chemical Senses, Volume 46, 2021, bjab050, https://doi.org/10.1093/chemse/bjab050 Published: 08 December 2021Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments, such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, and generally lacked quantitative measurements. Here, we report the development, implementation, and initial results of a multilingual, international questionnaire to assess self-reported quantity and quality of perception in 3 distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, and 8 others, aged 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste, and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change +/- 100) revealed a mean reduction of smell (-79.7 +/- 28.7, mean +/- standard deviation), taste (-69.0 +/- 32.6), and chemesthetic (-37.3 +/- 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell but also affects taste and chemesthesis.The multimodal impact of COVID-19 and the lack of perceived nasal obstruction suggest that severe acute respiratory syndrome coronavirus strain 2 (SARS-CoV-2) infection may disrupt sensory-neural mechanisms.Peer reviewe

More than smell - COVID-19 is associated with severe impairment of smell, taste, and chemesthesis

Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments, such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, and generally lacked quantitative measurements. Here, we report the development, implementation, and initial results of a multilingual, international questionnaire to assess self-reported quantity and quality of perception in 3 distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, and 8 others, aged 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste, and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change ±100) revealed a mean reduction of smell (-79.7 ± 28.7, mean ± standard deviation), taste (-69.0 ± 32.6), and chemesthetic (-37.3 ± 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell but also affects taste and chemesthesis. The multimodal impact of COVID-19 and the lack of perceived nasal obstruction suggest that severe acute respiratory syndrome coronavirus strain 2 (SARS-CoV-2) infection may disrupt sensory-neural mechanisms. © 2020 The Author(s) 2020. Published by Oxford University Press. All rights reserved

Brain network dynamics during spontaneous strategy shifts and incremental task optimization

With practice, humans improve their performance in a task by either optimizing a known strategy or discovering a novel, potentially more fruitful strategy. We investigated the neural processes underlying these two fundamental abilities by applying fMRI in a task with two possible alternative strategies. For analysis we combined time-resolved network analysis with Coherence Density Peak Clustering (Allegra et al., 2017), univariate GLM, and multivariate pattern classification. Converging evidence showed that the posterior portion of the default network, i.e. the precuneus and the angular gyrus bilaterally, has a central role in the optimization of the current strategy. These regions encoded the relevant spatial information, increased the strength of local connectivity as well as the long-distance connectivity with other relevant regions in the brain (e.g., visual cortex, dorsal attention network). The connectivity increase was proportional to performance optimization. By contrast, the anterior portion of the default network (i.e. medial prefrontal cortex) and the rostral portion of the fronto-parietal network were associated with new strategy discovery: an early increase of local and long-range connectivity centered on these regions was only observed in the subjects who would later shift to a new strategy. Overall, our findings shed light on the dynamic interactions between regions related to attention and with cognitive control, underlying the balance between strategy exploration and exploitation. Results suggest that the default network, far from being “shut-down” during task performance, has a pivotal role in the background exploration and monitoring of potential alternative courses of action