Pulmonary haemorrhage as a predominant cause of death in leptospirosis in Seychelles.

We examined the cause of death during a 12-month period (1995/96) in all consecutive patients admitted to hospital with leptospiral infection in Seychelles (Indian Ocean), where the disease is endemic. Leptospirosis was diagnosed by use of the microscopic agglutination test and a specific polymerase chain reaction assay on serum samples. Seventy-five cases were diagnosed and 6 patients died, a case fatality of 8%. All 6 patients died within 9 days of onset of symptoms and within 2 days of admission for 5 of them (5 days for the 6th). On autopsy, diffuse bilateral pulmonary haemorrhage (PH) was found in all fatalities. Renal, cardiac, digestive and cerebral haemorrhages were also found in 5, 3, 3 and 1 case(s), respectively. Incidentally, haemoptysis and lung infiltrate on chest radiographs, which suggest PH, were found in 8 of the 69 non-fatal cases. Dengue and hantavirus infections were ruled out. In conclusion, PH appeared to be a main cause of death in leptospirosis in this population, although haemorrhage in other organs may also have contributed to fatal outcomes. This cause of death contrasts with the findings generally reported in endemic settings

A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning

To achieve general intelligence, agents must learn how to interact with others in a shared environment: this is the challenge of multiagent reinforcement learning (MARL). The simplest form is independent reinforcement learning (InRL), where each agent treats its experience as part of its (non-stationary) environment. In this paper, we first observe that policies learned using InRL can overfit to the other agents’ policies during training, failing to sufficiently generalize duringn execution. We introduce a new metric, joint-policy correlation, to quantify this effect. We describe an algorithm for general MARL, based on approximate best responses to mixtures of policies generated using deep reinforcement learning, and empirical game-theoretic analysis to compute meta-strategies for policy selection. The algorithm generalizes previous ones such as InRL, iterated best response, double oracle, and fictitious play. Then, we present a scalable implementation which reduces the memory requirement using decoupled meta-solvers. Finally, we demonstrate the generality of the resulting policies in two partially observable settings: gridworld coordination games and poker

Comparison of Two Multilocus Sequence Based Genotyping Schemes for Leptospira Species

Two independent multilocus sequence based genotyping schemes (denoted here as 7L and 6L for schemes with 7 and 6 loci, respectively) are in use for Leptospira spp., which has led to uncertainty as to which should be adopted by the scientific community. The purpose of this study was to apply the two schemes to a single collection of pathogenic Leptospira, evaluate their performance, and describe the practical advantages and disadvantages of each scheme. We used a variety of phylogenetic approaches to compare the output data and found that the two schemes gave very similar results. 7L has the advantage that it is a conventional multi-locus sequencing typing (MLST) scheme based on housekeeping genes and is supported by a publically accessible database by which genotypes can be readily assigned as known or new sequence types by any investigator, but is currently only applicable to L. interrogans and L. kirschneri. Conversely, 6L can be applied to all pathogenic Leptospira spp., but is not a conventional MLST scheme by design and is not available online. 6L sequences from 271 strains have been released into the public domain, and phylogenetic analysis of new sequences using this scheme requires their download and offline analysis

Game Plan: What AI can do for Football, and What Football can do for AI

The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individual sports, including baseball, basketball, and tennis. More recently, AI techniques have been applied to football, due to a huge increase in data collection by professional teams, increased computational power, and advances in machine learning, with the goal of better addressing new scientific challenges involved in the analysis of both individual players’ and coordinated teams’ behaviors. The research challenges associated with predictive and prescriptive football analytics require new developments and progress at the intersection of statistical learning, game theory, and computer vision. In this paper, we provide an overarching perspective highlighting how the combination of these fields, in particular, forms a unique microcosm for AI research, while offering mutual benefits for professional teams, spectators, and broadcasters in the years to come. We illustrate that this duality makes football analytics a game changer of tremendous value, in terms of not only changing the game of football itself, but also in terms of what this domain can mean for the field of AI. We review the state-of-theart and exemplify the types of analysis enabled by combining the aforementioned fields, including illustrative examples of counterfactual analysis using predictive models, and the combination of game-theoretic analysis of penalty kicks with statistical learning of player attributes. We conclude by highlighting envisioned downstream impacts, including possibilities for extensions to other sports (real and virtual)

Genetic Affinities within a Large Global Collection of Pathogenic Leptospira: Implications for Strain Identification and Molecular Epidemiology

Leptospirosis is an important zoonosis with widespread human health implications. The non-availability of accurate identification methods for the individualization of different Leptospira for outbreak investigations poses bountiful problems in the disease control arena. We harnessed fluorescent amplified fragment length polymorphism analysis (FAFLP) for Leptospira and investigated its utility in establishing genetic relationships among 271 isolates in the context of species level assignments of our global collection of isolates and strains obtained from a diverse array of hosts. In addition, this method was compared to an in-house multilocus sequence typing (MLST) method based on polymorphisms in three housekeeping genes, the rrs locus and two envelope proteins. Phylogenetic relationships were deduced based on bifurcating Neighbor-joining trees as well as median joining network analyses integrating both the FAFLP data and MLST based haplotypes. The phylogenetic relationships were also reproduced through Bayesian analysis of the multilocus sequence polymorphisms. We found FAFLP to be an important method for outbreak investigation and for clustering of isolates based on their geographical descent rather than by genome species types. The FAFLP method was, however, not able to convey much taxonomical utility sufficient to replace the highly tedious serotyping procedures in vogue. MLST, on the other hand, was found to be highly robust and efficient in identifying ancestral relationships and segregating the outbreak associated strains or otherwise according to their genome species status and, therefore, could unambiguously be applied for investigating phylogenetics of Leptospira in the context of taxonomy as well as gene flow. For instance, MLST was more efficient, as compared to FAFLP method, in clustering strains from the Andaman island of India, with their counterparts from mainland India and Sri Lanka, implying that such strains share genetic relationships and that leptospiral strains might be frequently circulating between the islands and the mainland

Human Leptospirosis Caused by a New, Antigenically Unique Leptospira Associated with a Rattus Species Reservoir in the Peruvian Amazon

As part of a prospective study of leptospirosis and biodiversity of Leptospira in the Peruvian Amazon, a new Leptospira species was isolated from humans with acute febrile illness. Field trapping identified this leptospire in peridomestic rats (Rattus norvegicus, six isolates; R. rattus, two isolates) obtained in urban, peri-urban, and rural areas of the Iquitos region. Novelty of this species was proven by serological typing, 16S ribosomal RNA gene sequencing, pulsed-field gel electrophoresis, and DNA-DNA hybridization analysis. We have named this species “Leptospira licerasiae” serovar Varillal, and have determined that it is phylogenetically related to, but genetically distinct from, other intermediate Leptospira such as L. fainei and L. inadai. The type strain is serovar Varillal strain VAR 010T, which has been deposited into internationally accessible culture collections. By microscopic agglutination test, “Leptospira licerasiae” serovar Varillal was antigenically distinct from all known serogroups of Leptospira except for low level cross-reaction with rabbit anti–L. fainei serovar Hurstbridge at a titer of 1∶100. LipL32, although not detectable by PCR, was detectable in “Leptospira licerasiae” serovar Varillal by both Southern blot hybridization and Western immunoblot, although on immunoblot, the predicted protein was significantly smaller (27 kDa) than that of L. interrogans and L. kirschneri (32 kDa). Isolation was rare from humans (2/45 Leptospira isolates from 881 febrile patients sampled), but high titers of MAT antibodies against “Leptospira licerasiae” serovar Varillal were common (30%) among patients fulfilling serological criteria for acute leptospirosis in the Iquitos region, and uncommon (7%) elsewhere in Peru. This new leptospiral species reflects Amazonian biodiversity and has evolved to become an important cause of leptospirosis in the Peruvian Amazon

Conservation of the S10-spc-α Locus within Otherwise Highly Plastic Genomes Provides Phylogenetic Insight into the Genus Leptospira

S10-spc-α is a 17.5 kb cluster of 32 genes encoding ribosomal proteins. This locus has an unusual composition and organization in Leptospira interrogans. We demonstrate the highly conserved nature of this region among diverse Leptospira and show its utility as a phylogenetically informative region. Comparative analyses were performed by PCR using primer sets covering the whole locus. Correctly sized fragments were obtained by PCR from all L. interrogans strains tested for each primer set indicating that this locus is well conserved in this species. Few differences were detected in amplification profiles between different pathogenic species, indicating that the S10-spc-α locus is conserved among pathogenic Leptospira. In contrast, PCR analysis of this locus using DNA from saprophytic Leptospira species and species with an intermediate pathogenic capacity generated varied results. Sequence alignment of the S10-spc-α locus from two pathogenic species, L. interrogans and L. borgpetersenii, with the corresponding locus from the saprophyte L. biflexa serovar Patoc showed that genetic organization of this locus is well conserved within Leptospira. Multilocus sequence typing (MLST) of four conserved regions resulted in the construction of well-defined phylogenetic trees that help resolve questions about the interrelationships of pathogenic Leptospira. Based on the results of secY sequence analysis, we found that reliable species identification of pathogenic Leptospira is possible by comparative analysis of a 245 bp region commonly used as a target for diagnostic PCR for leptospirosis. Comparative analysis of Leptospira strains revealed that strain H6 previously classified as L. inadai actually belongs to the pathogenic species L. interrogans and that L. meyeri strain ICF phylogenetically co-localized with the pathogenic clusters. These findings demonstrate that the S10-spc-α locus is highly conserved throughout the genus and may be more useful in comparing evolution of the genus than loci studied previously

Genetic structure of the genus Leptospira by multilocus enzyme electrophoresis

Thirty strains from the 11 species of the genus Leptospira were studied by multilocus enzyme electrophoresis at 12 enzyme loci, all of which were polymorphic. The mean number of alleles per locus was 6.5. Twenty-five electrophoretic types were distinguished. Grouping of the strains by cluster analysis was in general agreement with species delineation as determined by DNA-DNA hybridization, except for the strains of Leptospira meyeri and Leptospira inadai, which were scattered throughout the genus, reflecting previously recognized taxonomic uncertainties. Analysis of the clonality within Leptospira interrogans sensu stricto indicated that this population was relatively heterogeneous and a lack of gene linkage disequilibrium could not be excluded. There was a genetic discrimination between the pathogenic species and the saprophytic ones. The phenotypically intermediate species (L. inadai and Leptospira fainei) were also genetically separated and were probably closer to the saprophytes than to the pathogens