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Even when driven by the same stimulus, neuronal responses are well-known to exhibit a striking level of spiking variability. In-vivo electrophysiological recordings also reveal a surprisingly large degree of variability at the subthreshold level. In prior work, we considered biophysically relevant neuronal models to account for the observed magnitude of membrane voltage fluctuations. We found that accounting for these fluctuations requires weak but nonzero synchrony in the spiking activity, in amount that are consistent with experimentally measured spiking correlations. Here we investigate whether such synchrony can explain additional statistical features of the measured neural activity, including neuronal voltage covariability and voltage skewness. Addressing this question involves conducting a generalized moment analysis of conductance-based neurons in response to input drives modeled as correlated jump processes. Technically, we perform such an analysis using fixed-point techniques from queuing theory that are applicable in the stationary regime of activity. We found that weak but nonzero synchrony can consistently explain the experimentally reported voltage covariance and skewness. This confirms the role of synchrony as a primary driver of cortical variability and supports that physiological neural activity emerges as a population-level phenomenon, especially in the spontaneous regime. 

Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs.Wedemonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range. 

This study identified the LARP6 La Module from Tetrabaena socialis (T. socialis), a four-celled green algae, in an effort to better understand the evolution of LARP6 structure and RNA-binding activity in multicellular eukaryotes. Using a combination of sequence alignments, domain boundary screens, and structural modelling, we recombinantly expressed and isolated the TsLARP6 La Module to > 98% purity for in vitro biochemical characterization. The La Module is stably folded and exerts minimal RNA binding activity against single-stranded homopolymeric RNAs. Surprisingly, it exhibits low micromolar binding affinity for the vertebrate LARP6 cognate ligand, a bulged-stem loop found in the 5'UTR of collagen type I mRNA, but does not bind double-stranded RNAs of similar size. These result suggests that the TsLARP6 La Module may prefer structured RNA ligands. In contrast, however, the TsLARP6 La Module does not exhibit the RNA chaperone activity that is observed in vertebrate homologs. Therefore, we conclude that protist LARP6 may have both distinct RNA ligands and binding mechanisms from the previously characterized LARP6 proteins of animals and vascular plants, thus establishing a distinct third class of the LARP6 protein family.