<em>Rhodococcus indonesiensis</em> sp. nov. a new member of the <em>Rhodococcus ruber</em> lineage isolated from sediment of a neutral hot spring and reclassification of <em>Rhodococcus electrodiphilus</em> (Ramaprasad et al. 2018) as a later heterotypic synonym of <em>Rhodococcus ruber </em>(Kruse 1896) Goodfellow and Alderson 1977 (Approved Lists 1980)

\ua9 2024 The Authors.A polyphasic study was designed to determine the taxonomic status of isolate CSLK01-03T, which was recovered from an Indonesian neutral hot spring and provisionally assigned to the genus Rhodococcus. The isolate was found to have chemo-taxonomic, cultural and morphological properties typical of rhodococci. It has a rod–coccus lifecycle and grows from 10 to 39 \ub0C, from pH 6.5 to 8.0 and in the presence of 0–10% (w/v) sodium chloride. Whole-organism hydrolysates contain meso-diaminopimelic acid, arabinose and galactose, the predominant menaquinone is MK-8 (H2), the polar lipid pattern consists of diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol mannosides, phosphatidylmethylethanolamine and two unidentified components, it produces mycolic acids, and C16:0 is the major fatty acid. Whole-genome analyses show that the isolate and Rhodococcus electrodiphilus LMG 29881T (GenBank accession: JAULCK000000000) have genome sizes of 5.5 and 5.1 Mbp, respectively. These strains and Rhodococcus aetherivorans DSM 44752T and Rhodococcus ruber DSM 43338T form well-supported lineages in 16S rRNA and whole-genome trees that are close to sister lineages composed of the type strains of Rhodococcus rhodochrous and related Rhodococcus species. The isolate can be distinguished from its closest evolutionary neighbours using combinations of cultural and phenotypic features, and by low DNA–DNA hybridization values. Based on these data it is proposed that isolate CSLK01-03T (=CCMM B1310T=ICEBB-06T=NCIMB 15214T) be classified in the genus Rhodococcus as Rhodococcus indonesiensis sp. nov. The genomes of the isolate and its closest phylogenomic relatives are rich in biosynthetic gene clusters with the potential to synthesize new natural products, notably antibiotics. In addition, whole-genome-based taxonomy revealed that Rhodococ-cus electrodiphilus LMG 29881T and Rhodococcus ruber DSM 43338T belong to a single species. It is, therefore, proposed that R. electrodiphilus be recognized as a heterotypic synonym of R. ruber

The Relativistic Hopfield network: rigorous results

The relativistic Hopfield model constitutes a generalization of the standard Hopfield model that is derived by the formal analogy between the statistical-mechanic framework embedding neural networks and the Lagrangian mechanics describing a fictitious single-particle motion in the space of the tuneable parameters of the network itself. In this analogy the cost-function of the Hopfield model plays as the standard kinetic-energy term and its related Mattis overlap (naturally bounded by one) plays as the velocity. The Hamiltonian of the relativisitc model, once Taylor-expanded, results in a P-spin series with alternate signs: the attractive contributions enhance the information-storage capabilities of the network, while the repulsive contributions allow for an easier unlearning of spurious states, conferring overall more robustness to the system as a whole. Here we do not deepen the information processing skills of this generalized Hopfield network, rather we focus on its statistical mechanical foundation. In particular, relying on Guerra's interpolation techniques, we prove the existence of the infinite volume limit for the model free-energy and we give its explicit expression in terms of the Mattis overlaps. By extremizing the free energy over the latter we get the generalized self-consistent equations for these overlaps, as well as a picture of criticality that is further corroborated by a fluctuation analysis. These findings are in full agreement with the available previous results.Comment: 11 pages, 1 figur

Murine norovirus virulence factor 1 (VF1) protein contributes to viral fitness during persistent infection

Murine norovirus (MNV) is widely used as a model for studying norovirus biology. While MNV isolates vary in their pathogenesis, infection of immunocompetent mice mostly results in persistent infection. The ability of a virus to establish a persistent infection is dependent on its ability to subvert or avoid the host immune response. Previously, we described the identification and characterization of virulence factor 1 (VF1) in MNV, and demonstrated its role as an innate immune antagonist. Here, we explore the role of VF1 during persistent MNV infection in an immunocompetent host. Using reverse genetics, we generated MNV-3 viruses carrying a single or a triple termination codon inserted in the VF1 ORF. VF1-deleted MNV-3 replicated to comparable levels to the wildtype virus in tissue culture. Comparative studies between MNV-3 and an acute MNV-1 strain show that MNV-3 VF1 exerts the same functions as MNV-1 VF1, but with reduced potency. C57BL/6 mice infected with VF1-deleted MNV-3 showed significantly reduced replication kinetics during the acute phase of the infection, but viral loads rapidly reached the levels seen in mice infected with wildtype virus after phenotypic restoration of VF1 expression. Infection with an MNV-3 mutant that had three termination codons inserted into VF1, in which reversion was suppressed, resulted in consistently lower replication throughout a 3 month persistent infection in mice, suggesting a role for VF1 in viral fitness in vivo. Our results indicate that VF1 expressed by a persistent strain of MNV also functions to antagonize the innate response to infection. We found that VF1 is not essential for viral persistence, but instead contributes to viral fitness in mice. These data fit with the hypothesis that noroviruses utilize multiple mechanisms to avoid and/or control the host response to infection and that VF1 is just one component of this

The Case for Learned Index Structures

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of lookup keys and use this signal to effectively predict the position or existence of records. We theoretically analyze under which conditions learned indexes outperform traditional index structures and describe the main challenges in designing learned index structures. Our initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. More importantly though, we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs and that this work just provides a glimpse of what might be possible

A computational study of stimulus driven epileptic seizure abatement

This is the final version of the article. Available from Public Library of Science via the DOI in this record.Active brain stimulation to abate epileptic seizures has shown mixed success. In spike-wave (SW) seizures, where the seizure and background state were proposed to coexist, single-pulse stimulations have been suggested to be able to terminate the seizure prematurely. However, several factors can impact success in such a bistable setting. The factors contributing to this have not been fully investigated on a theoretical and mechanistic basis. Our aim is to elucidate mechanisms that influence the success of single-pulse stimulation in noise-induced SW seizures. In this work, we study a neural population model of SW seizures that allows the reconstruction of the basin of attraction of the background activity as a four dimensional geometric object. For the deterministic (noise-free) case, we show how the success of response to stimuli depends on the amplitude and phase of the SW cycle, in addition to the direction of the stimulus in state space. In the case of spontaneous noise-induced seizures, the basin becomes probabilistic introducing some degree of uncertainty to the stimulation outcome while maintaining qualitative features of the noise-free case. Additionally, due to the different time scales involved in SW generation, there is substantial variation between SW cycles, implying that there may not be a fixed set of optimal stimulation parameters for SW seizures. In contrast, the model suggests an adaptive approach to find optimal stimulation parameters patient-specifically, based on real-time estimation of the position in state space. We discuss how the modelling work can be exploited to rationally design a successful stimulation protocol for the abatement of SW seizures using real-time SW detection.This work was supported by the EPSRC (EP/K026992/1), the BBSRC, the DTC for Systems Biology (University of Manchester), and the Nanyang Technological University Singapore. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript