Method for analyzing web space data

A method for analyzing data from the web that determine the importance that a chosen subject has in society, e.g., subject matter relating a concert, a scientific discovery, a football match, a person, a corporation, a brand, or a car, and analyze such data that can represent the entire society better than the known techniques. The method according to the invention can avoid malicious alterations and is able to measure and detect the temporal relations among all the web resources that talk about a particular topic or subject matter

SIWeb: understanding the Interests of the Society through Web data Analysis

The high availability of user-generated contents in the Web scenario represents a tremendous asset for understanding various social phenomena. Methods and commercial products that exploit the widespread use of the Web as a way of conveying personal opinions have been proposed, but a critical thinking is that these approaches may produce a partial, or distorted, understanding of the society, because most of them focus on definite scenarios, use specific platforms, base their analysis on the sole magnitude of data, or treat the different Web resources with the same importance. In this paper, we present SIWeb (Social Interests through Web Analysis), a novel mechanism designed to measure the interest the society has on a topic (e.g., a real world phenomenon, an event, a person, a thing). SIWeb is general purpose (it can be applied to any decision making process), cross platforms (it uses the entire Webspace, from social media to websites, from tags to reviews), and time effective (it measures the time correlatio between the Web resources). It uses fractal analysis to detect the temporal relations behind all the Web resources (e.g., Web pages, RSS, newsgroups, etc.) that talk about a topic and combines this number with the temporal relations to give an insight of the the interest the society has about a topic. The evaluation of the proposal shows that SIWeb might be helpful in decision making processes as it reflects the interests the society has on a specific topic

Early Steps in C-Type Inactivation of the hERG Potassium Channel

Fast C-type inactivation confers distinctive functional properties to the hERG potassium channel, and its association to inherited and acquired cardiac arrythmias makes the study of the inactivation mechanism of hERG at the atomic detail of paramount importance. At present, two models have been proposed to describe C-type inactivation in K+-channels. Experimental data and computational work on the bacterial KcsA channel support the hypothesis that C-type inactivation results from a closure of the selectivity filter that sterically impedes ion conduction. Alternatively, recent experimental structures of a mutated Shaker channel revealed a widening of the extracellular portion of the selectivity filter, which might diminish conductance by interfering with the mechanism of ion permeation. Here, we performed molecular dynamics simulations of the wild-type hERG, a non-inactivating mutant (hERG-N629D), and a mutant that inactivates faster than the wild-type channel (hERG-F627Y) to find out which and if any of the two reported C-type inactivation mechanisms applies to hERG. Closure events of the selectivity filter were not observed in any of the simulated trajectories but instead, the extracellular section of the selectivity filter deviated from the canonical conductive structure of potassium channels. The degree of widening of the potassium binding sites at the extracellular entrance of the channel was directly related to the degree of inactivation with hERG-F627Y > wild-type hERG > hERG-N629D. These findings support the hypothesis that C-type inactivation in hERG entails a widening of the extracellular entrance of the channel rather than a closure of the selectivity filter

Insights into the mechanisms of K+ permeation in K+-channels from computer simulations

Ion permeation, selectivity, and the behavior of the K+ channel selectivity filter have been studied intensively in the previous two decades. The agreement among multiple approaches used to study ion flux in K+ channels suggests a consensus mechanism of ion permeation across the selectivity that has been put to the test in recent years with the proposal of an alternative way by which ions can cross the selectivity filter of K+ channels via direct Coulomb repulsion between contacting cations. Past experimental work by Zhou and MacKinnon (J. Mol. Biol. 2004, 338, 839) showed that mutation of the site S4 reduces the total occupancy of the selectivity filter to less than two ions on average by lowering the occupancy of the S2-S4 configuration without changing the S1-S3 configuration much, and this reduction of occupancy means that ion configurations different from the ones involved in the canonical mechanism are likely to be involved. At that time, calculations using complicated kinetic networks to relate occupancy to conduction did not provide deeper insight into the conduction mechanism. Here, to help solve this enigma, umbrella sampling simulations have been performed to evaluate the potential of mean force of two KcsA mutant channels where the S4 site is substituted. Our new results provide insights into the significance of threonine in this position, revealing the effect of substitution on the alternate mechanisms of conduction proposed, involving either water or vacant sites

Effect of anionic lipids on ion permeation through the KcsA K+-channel

K+-channels are responsible for the efficient and selective conduction of K+ ions across the plasma membrane. The bacterial K+-channel KcsA has historically been used to characterize various aspects of K+ conduction via computational means. The energetic barriers associated with ion translocation across the KcsA selectivity filter have been computed in various studies, leading to the proposal of two alternate mechanisms of conduction, involving or neglecting the presence of water molecules in between the permeating ions. Here, the potential of mean force of K+ permeation is evaluated for KcsA in lipid bilayers containing anionic lipids, which is known to increase the open probability of the channel. In addition, the effect of the protonation/deprotonation of residue E71, which directly interacts with the selectivity filter sequence, is assessed. Both conduction mechanisms are considered throughout. The results obtained provide novel insights into the molecular functioning of K+-channels including the inactivation process

Rational design of modular circuits for gene transcription: A test of the bottom-up approach

<p>Abstract</p> <p>Background</p> <p>Most of synthetic circuits developed so far have been designed by an ad hoc approach, using a small number of components (i.e. LacI, TetR) and a trial and error strategy. We are at the point where an increasing number of modular, inter-changeable and well-characterized components is needed to expand the construction of synthetic devices and to allow a rational approach to the design.</p> <p>Results</p> <p>We used interchangeable modular biological parts to create a set of novel synthetic devices for controlling gene transcription, and we developed a mathematical model of the modular circuits. Model parameters were identified by experimental measurements from a subset of modular combinations. The model revealed an unexpected feature of the lactose repressor system, i.e. a residual binding affinity for the operator site by induced lactose repressor molecules. Once this residual affinity was taken into account, the model properly reproduced the experimental data from the training set. The parameters identified in the training set allowed the prediction of the behavior of networks not included in the identification procedure.</p> <p>Conclusions</p> <p>This study provides new quantitative evidences that the use of independent and well-characterized biological parts and mathematical modeling, what is called a bottom-up approach to the construction of gene networks, can allow the design of new and different devices re-using the same modular parts.</p

Ion-triggered selectivity in bacterial sodium channels

Since the availability of the first crystal structure of a bacterial Na+ channel in 2011, understanding selectivity across this family of membrane proteins has been the subject of intense research efforts. Initially, free energy calculations based on molecular dynamics simulations revealed that although sodium ions can easily permeate the channel with their first hydration shell almost intact, the selectivity filter is too narrow for efficient conduction of hydrated potassium ions. This steric view of selectivity was subsequently questioned by microsecond atomic trajectories, which proved that the selectivity filter appears to the permeating ions as a highly degenerate, liquid-like environment. Although this liquid-like environment looks optimal for rapid conduction of Na+, it seems incompatible with efficient discrimination between similar ion species, such as Na+ and K+, through steric effects. Here extensive molecular dynamics simulations, combined with Markov state model analyses, reveal that at positive membrane potentials, potassium ions trigger a conformational change of the selectivity toward a nonconductive metastable state. It is this transition of the selectivity filter, and not steric effects, that prevents the outward flux of K+ at positive membrane potentials. This description of selectivity, triggered by the nature of the permeating ions, might have implications on the current understanding of how ion channels, and in particular bacterial Na+ channels, operate at the atomic scale

Host genetic basis of COVID-19: from methodologies to genes

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is having a massive impact on public health, societies, and economies worldwide. Despite the ongoing vaccination program, treating COVID-19 remains a high priority; thus, a better understanding of the disease is urgently needed. Initially, susceptibility was associated with age, sex, and other prior existing comorbidities. However, as these conditions alone could not explain the highly variable clinical manifestations of SARS-CoV-2 infection, the attention was shifted toward the identification of the genetic basis of COVID-19. Thanks to international collaborations like The COVID-19 Host Genetics Initiative, it became possible the elucidation of numerous genetic markers that are not only likely to help in explaining the varied clinical outcomes of COVID-19 patients but can also guide the development of novel diagnostics and therapeutics. Within this framework, this review delineates GWAS and Burden test as traditional methodologies employed so far for the discovery of the human genetic basis of COVID-19, with particular attention to recently emerged predictive models such as the post-Mendelian model. A summary table with the main genome-wide significant genomic loci is provided. Besides, various common and rare variants identified in genes like TLR7, CFTR, ACE2, TMPRSS2, TLR3, and SELP are further described in detail to illustrate their association with disease severity

Rational design of modular circuits for gene transcription: A test of the bottom-up approach

BACKGROUND: Most of synthetic circuits developed so far have been designed by an ad hoc approach, using a small number of components (i.e. LacI, TetR) and a trial and error strategy. We are at the point where an increasing number of modular, inter-changeable and well-characterized components is needed to expand the construction of synthetic devices and to allow a rational approach to the design. RESULTS: We used interchangeable modular biological parts to create a set of novel synthetic devices for controlling gene transcription, and we developed a mathematical model of the modular circuits. Model parameters were identified by experimental measurements from a subset of modular combinations. The model revealed an unexpected feature of the lactose repressor system, i.e. a residual binding affinity for the operator site by induced lactose repressor molecules. Once this residual affinity was taken into account, the model properly reproduced the experimental data from the training set. The parameters identified in the training set allowed the prediction of the behavior of networks not included in the identification procedure. CONCLUSIONS: This study provides new quantitative evidences that the use of independent and well-characterized biological parts and mathematical modeling, what is called a bottom-up approach to the construction of gene networks, can allow the design of new and different devices re-using the same modular parts