Generalizing the Wells-Riley Infection Probability: A Superstatistical Scheme for Indoor Infection Risk Estimation.

Recent evidence supports that air is the main transmission pathway of the recently identified SARS-CoV-2 coronavirus that causes COVID-19 disease. Estimating the infection risk associated with an indoor space remains an open problem due to insufficient data concerning COVID-19 outbreaks, as well as, methodological challenges arising from cases where environmental (i.e., out-of-host) and immunological (i.e., within-host) heterogeneities cannot be neglected. This work addresses these issues by introducing a generalization of the elementary Wells-Riley infection probability model. To this end, we adopted a superstatistical approach where the exposure rate parameter is gamma-distributed across subvolumes of the indoor space. This enabled us to construct a susceptible (S)-exposed (E)-infected (I) dynamics model where the Tsallis entropic index q quantifies the degree of departure from a well-mixed (i.e., homogeneous) indoor-air-environment state. A cumulative-dose mechanism is employed to describe infection activation in relation to a host's immunological profile. We corroborate that the six-foot rule cannot guarantee the biosafety of susceptible occupants, even for exposure times as short as 15 min. Overall, our work seeks to provide a minimal (in terms of the size of the parameter space) framework for more realistic indoor SEI dynamics explorations while highlighting their Tsallisian entropic origin and the crucial yet elusive role that the innate immune system can play in shaping them. This may be useful for scientists and decision makers interested in probing different indoor biosafety protocols more thoroughly and comprehensively, thus motivating the use of nonadditive entropies in the emerging field of indoor space epidemiology.

Non-extensitivity and criticality of atomic hydropathicity around a voltage-gated sodium channel's pore: a modeling study.

Voltage-gated sodium channels (NavChs) are pore-forming membrane proteins that regulate the transport of sodium ions through the cell membrane. Understanding the structure and function of NavChs is of major biophysical, as well as clinical, importance given their key role in cellular pathophysiology. In this work, we provide a computational framework for modeling system-size-dependent, i.e., cumulative, atomic properties around a NavCh's pore. We illustrate our methodologies on the bacterial NavAb channel captured in a closed-pore state where we demonstrate that the atomic environment around its pore exhibits a bi-phasic spatial organization dictated by the structural separation of the pore domains (PDs) from the voltage-sensing domains (VSDs). Accordingly, a mathematical model describing packing of atoms around NavAb's pore is constructed that allows-under certain conservation conditions-for a power-law approximation of the cumulative hydropathic dipole field effect acting along NavAb's pore. This verified the non-extensitivity hypothesis for the closed-pore NavAb channel and revealed a long-range hydropathic interactions law regulating atom-packing around the NavAb's selectivity filter. Our model predicts a PDs-VSDs coupling energy of [Formula: see text] kcal/mol corresponding to a global maximum of the atom-packing energy profile. Crucially, we demonstrate for the first time how critical phenomena can emerge in a single-channel structure as a consequence of the non-extensive character of its atomic porous environment.

Cumulative hydropathic topology of a voltage-gated sodium channel at atomic resolution.

Voltage-gated sodium channels (NavChs) are biological pores that control the flow of sodium ions through the cell membrane. In humans, mutations in genes encoding NavChs can disrupt physiological cellular activity thus leading to a wide spectrum of diseases. Here, we present a topological connection between the functional architecture of a NavAb bacterial channel and accumulation of atomic hydropathicity around its pore. This connection is established via a scaling analysis methodology that elucidates how intrachannel hydropathic density variations translate into hydropathic dipole field configurations along the pore. Our findings suggest the existence of a nonrandom cumulative hydropathic topology that is organized parallel to the membrane surface so that pore's stability, as well as, gating behavior are guaranteed. Given the biophysical significance of the hydropathic effect, our study seeks to provide a computational framework for studying cumulative hydropathic topological properties of NavChs and pore-forming proteins in general.

Targeted RNA-seq successfully identifies normal and pathogenic splicing events in breast/ovarian cancer susceptibility and Lynch syndrome genes.

A subset of genetic variants found through screening of patients with hereditary breast and ovarian cancer syndrome (HBOC) and Lynch syndrome impact RNA splicing. Through target enrichment of the transcriptome, it is possible to perform deep-sequencing and to identify the different and even rare mRNA isoforms. A targeted RNA-seq approach was used to analyse the naturally-occurring splicing events for a panel of 8 breast and/or ovarian cancer susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, PTEN, STK11, CDH1, TP53), 3 Lynch syndrome genes (MLH1, MSH2, MSH6) and the fanconi anaemia SLX4 gene, in which monoallelic mutations were found in non-BRCA families. For BRCA1, BRCA2, RAD51C and RAD51D the results were validated by capillary electrophoresis and were compared to a non-targeted RNA-seq approach. We also compared splicing events from lymphoblastoid cell-lines with those from breast and ovarian fimbriae tissues. The potential of targeted RNA-seq to detect pathogenic changes in RNA-splicing was validated by the inclusion of samples with previously well characterized BRCA1/2 genetic variants. In our study, we update the catalogue of normal splicing events for BRCA1/2, provide an extensive catalogue of normal RAD51C and RAD51D alternative splicing, and list splicing events found for eight other genes. Additionally, we show that our approach allowed the identification of aberrant splicing events due to the presence of BRCA1/2 genetic variants and distinguished between complete and partial splicing events. In conclusion, targeted-RNA-seq can be very useful to classify variants based on their putative pathogenic impact on splicing.

Network topology of NaV1.7 mutations in sodium channel-related painful disorders.

BACKGROUND: Gain-of-function mutations in SCN9A gene that encodes the voltage-gated sodium channel NaV1.7 have been associated with a wide spectrum of painful syndromes in humans including inherited erythromelalgia, paroxysmal extreme pain disorder and small fibre neuropathy. These mutations change the biophysical properties of NaV1.7 channels leading to hyperexcitability of dorsal root ganglion nociceptors and pain symptoms. There is a need for better understanding of how gain-of-function mutations alter the atomic structure of Nav1.7. RESULTS: We used homology modeling to build an atomic model of NaV1.7 and a network-based theoretical approach, which can predict interatomic interactions and connectivity arrangements, to investigate how pain-related NaV1.7 mutations may alter specific interatomic bonds and cause connectivity rearrangement, compared to benign variants and polymorphisms. For each amino acid substitution, we calculated the topological parameters betweenness centrality (B ct ), degree (D), clustering coefficient (CC ct ), closeness (C ct ), and eccentricity (E ct ), and calculated their variation (Δ value = mutant value -WT value ). Pathogenic NaV1.7 mutations showed significantly higher variation of |ΔB ct | compared to benign variants and polymorphisms. Using the cut-off value ±0.26 calculated by receiver operating curve analysis, we found that ΔB ct correctly differentiated pathogenic NaV1.7 mutations from variants not causing biophysical abnormalities (nABN) and homologous SNPs (hSNPs) with 76% sensitivity and 83% specificity. CONCLUSIONS: Our in-silico analyses predict that pain-related pathogenic NaV1.7 mutations may affect the network topological properties of the protein and suggest |ΔB ct | value as a potential in-silico marker.

The spacing principle for unlearning abnormal neuronal synchrony.

Desynchronizing stimulation techniques were developed to specifically counteract abnormal neuronal synchronization relevant to several neurological and psychiatric disorders. The goal of our approach is to achieve an anti-kindling, where the affected neural networks unlearn abnormal synaptic connectivity and, hence, abnormal neuronal synchrony, by means of desynchronizing stimulation, in particular, Coordinated Reset (CR) stimulation. As known from neuroscience, psychology and education, learning effects can be enhanced by means of the spacing principle, i.e. by delivering repeated stimuli spaced by pauses as opposed to delivering a massed stimulus (in a single long stimulation session). To illustrate that the spacing principle may boost the anti-kindling effect of CR neuromodulation, in this computational study we carry this approach to extremes. To this end, we deliver spaced CR neuromodulation at particularly weak intensities which render permanently delivered CR neuromodulation ineffective. Intriguingly, spaced CR neuromodulation at these particularly weak intensities effectively induces an anti-kindling. In fact, the spacing principle enables the neuronal population to successively hop from one attractor to another one, finally approaching attractors characterized by down-regulated synaptic connectivity and synchrony. Our computational results might open up novel opportunities to effectively induce sustained desynchronization at particularly weak stimulation intensities, thereby avoiding side effects, e.g., in the case of deep brain stimulation.