2,119 research outputs found
Shift invariant preduals of ℓ<sub>1</sub>(ℤ)
The Banach space ℓ<sub>1</sub>(ℤ) admits many non-isomorphic preduals, for
example, C(K) for any compact countable space K, along with many more
exotic Banach spaces. In this paper, we impose an extra condition: the predual
must make the bilateral shift on ℓ<sub>1</sub>(ℤ) weak<sup>*</sup>-continuous. This is
equivalent to making the natural convolution multiplication on ℓ<sub>1</sub>(ℤ)
separately weak*-continuous and so turning ℓ<sub>1</sub>(ℤ) into a dual Banach
algebra. We call such preduals <i>shift-invariant</i>. It is known that the
only shift-invariant predual arising from the standard duality between C<sub>0</sub>(K)
(for countable locally compact K) and ℓ<sub>1</sub>(ℤ) is c<sub>0</sub>(ℤ). We provide
an explicit construction of an uncountable family of distinct preduals which do
make the bilateral shift weak<sup>*</sup>-continuous. Using Szlenk index arguments, we
show that merely as Banach spaces, these are all isomorphic to c<sub>0</sub>. We then
build some theory to study such preduals, showing that they arise from certain
semigroup compactifications of ℤ. This allows us to produce a large number
of other examples, including non-isometric preduals, and preduals which are not
Banach space isomorphic to c<sub>0</sub>
Updated estimate of the duration of the meningo-encephalitic stage in gambiense human African trypanosomiasis
Background:
The duration of the stages of HAT is an important factor in epidemiological studies and intervention planning. Previously, we published estimates of the duration of the haemo-lymphatic stage 1 and meningo-encephalitic stage 2 of the gambiense form of human African trypanosomiasis (HAT), in the absence of treatment. Here we revise the estimate of stage 2 duration, computed based on data from Uganda and South Sudan, by adjusting observed infection prevalence for incomplete case detection coverage and diagnostic inaccuracy.
Findings:
The revised best estimate for the mean duration of stage 2 is 252 days (95% CI 171–399), about half of our initial best estimate, giving a total mean duration of untreated gambiense HAT infection of approximately 2 years and 2 months.
Conclusions:
Our new estimate provides improved information on the transmission dynamics of this neglected tropical disease in Uganda and South Sudan. We stress that there remains considerable variability around the estimated mean values, and that one must be cautious in applying these results to other foci
A fundamental test for stellar feedback recipes in galaxy simulations
Direct comparisons between galaxy simulations and observations that both
reach scales < 100 pc are strong tools to investigate the cloud-scale physics
of star formation and feedback in nearby galaxies. Here we carry out such a
comparison for hydrodynamical simulations of a Milky Way-like galaxy, including
stochastic star formation, HII region and supernova feedback, and chemical
post-processing at 8 pc resolution. Our simulation shows excellent agreement
with almost all kpc-scale and larger observables, including total star
formation rates, radial profiles of CO, HI, and star formation through the
galactic disc, mass ratios of the ISM components, both whole-galaxy and
resolved Kennicutt-Schmidt relations, and giant molecular cloud properties.
However, we find that our simulation does not reproduce the observed
de-correlation between tracers of gas and star formation on < 100 pc scales,
known as the star formation 'uncertainty principle', which indicates that
observed clouds undergo rapid evolutionary lifecycles. We conclude that the
discrepancy is driven by insufficiently-strong pre-supernova feedback in our
simulation, which does not disperse the surrounding gas completely, leaving
star formation tracer emission too strongly associated with molecular gas
tracer emission, inconsistent with observations. This result implies that the
cloud-scale de-correlation of gas and star formation is a fundamental test for
feedback prescriptions in galaxy simulations, one that can fail even in
simulations that reproduce all other macroscopic properties of star-forming
galaxies.Comment: 13 pages, 10 figures, accepted for publication in MNRA
The effects of subcurative praziquantel treatment on life-history traits and trade-offs in drug-resistant Schistosoma mansoni
Natural selection acts on all organisms, including parasites, to maximise reproductive fitness. Drug resistance traits are often associated with life-history costs in the absence of treatment. Schistosomiasis control programmes rely on mass drug administration to reduce human morbidity and mortality. Although hotspots of reduced drug efficacy have been reported, resistance is not widespread. Using Bayesian State-Space Models (SSMs) fitted to data from an in vivo laboratory system, we tested the hypothesis that the spread of resistant Schistosoma may be limited by life-history costs not present in susceptible counterparts. Schistosoma mansoni parasites from a praziquantel–susceptible (S), a praziquantel–resistant (R) or a mixed line of originally resistant and susceptible parasites (RS) were exposed to a range of praziquantel doses. Parasite numbers at each life stage were quantified in their molluscan intermediate and murine definitive hosts across four generations, and SSMs were used to estimate key life-history parameters for each experimental group over time. Model outputs illustrated that parasite adult survival and fecundity in the murine host decreased across all lines, including R, with increasing drug pressure. Trade-offs between adult survival and fecundity were observed in all untreated lines, and these remained strong in S with praziquantel pressure. In contrast, trade-offs between adult survival and fecundity were lost under praziquantel pressure in R. As expected, parasite life-history traits within the molluscan host were complex, but trade-offs were demonstrated between parasite establishment and cercarial output. The observed trade-offs between generations within hosts, which were modified by praziquantel treatment in the R line, could limit the spread of R parasites under praziquantel pressure. Whilst such complex life-history costs may be difficult to detect using standard empirical methods, we demonstrate that SSMs provide robust estimates of life history parameters, aiding our understanding of costs and trade-offs of resistant parasites within this system and beyond
Distinguishing low frequency mutations from RT-PCR and sequence errors in viral deep sequencing data
There is a high prevalence of coronary artery disease (CAD) in patients with left bundle branch block (LBBB); however there are many other causes for this electrocardiographic abnormality. Non-invasive assessment of these patients remains difficult, and all commonly used modalities exhibit several drawbacks. This often leads to these patients undergoing invasive coronary angiography which may not have been necessary. In this review, we examine the uses and limitations of commonly performed non-invasive tests for diagnosis of CAD in patients with LBBB
Plasticity in transmission strategies of the malaria parasite, Plasmodium chabaudi : environmental and genetic effects
Parasites may alter their behaviour to cope with changes in the within-host environment. In particular, investment in transmission may alter in response to the availability of parasite resources or host immune responses. However, experimental and theoretical studies have drawn conflicting conclusions regarding parasites' optimal (adaptive) responses to deterioration in habitat quality. We analyse data from acute infections with six genotypes of the rodent malaria species to quantify how investment in transmission (gametocytes) is influenced by the within-host environment. Using a minimum of modelling assumptions, we find that proportional investment in gametocytogenesis increases sharply with host anaemia and also increases at low parasite densities. Further, stronger dependence of investment on parasite density is associated with greater virulence of the parasite genotype. Our study provides a robust quantitative framework for studying parasites' responses to the host environment and whether these responses are adaptive, which is crucial for predicting the short-term and evolutionary impact of transmission-blocking treatments for parasitic diseases
The impact of mutation and gene conversion on the local diversification of antigen genes in African trypanosomes
Patterns of genetic diversity in parasite antigen gene families hold important information about their potential to generate antigenic variation within and between hosts. The evolution of such gene families is typically driven by gene duplication, followed by point mutation and gene conversion. There is great interest in estimating the rates of these processes from molecular sequences for understanding the evolution of the pathogen and its significance for infection processes. In this study, a series of models are constructed to investigate hypotheses about the nucleotide diversity patterns between closely related gene sequences from the antigen gene archive of the African trypanosome, the protozoan parasite causative of human sleeping sickness in Equatorial Africa. We use a hidden Markov model approach to identify two scales of diversification: clustering of sequence mismatches, a putative indicator of gene conversion events with other lower-identity donor genes in the archive, and at a sparser scale, isolated mismatches, likely arising from independent point mutations. In addition to quantifying the respective probabilities of occurrence of these two processes, our approach yields estimates for the gene conversion tract length distribution and the average diversity contributed locally by conversion events. Model fitting is conducted using a Bayesian framework. We find that diversifying gene conversion events with lower-identity partners occur at least five times less frequently than point mutations on variant surface glycoprotein (VSG) pairs, and the average imported conversion tract is between 14 and 25 nucleotides long. However, because of the high diversity introduced by gene conversion, the two processes have almost equal impact on the per-nucleotide rate of sequence diversification between VSG subfamily members. We are able to disentangle the most likely locations of point mutations and conversions on each aligned gene pair
Heterogeneity in the spread and control of infectious disease: consequences for the elimination of canine rabies
Understanding the factors influencing vaccination campaign effectiveness is vital in designing efficient disease elimination programmes. We investigated the importance of spatial heterogeneity in vaccination coverage and human-mediated dog movements for the elimination of endemic canine rabies by mass dog vaccination in Region VI of the Philippines (Western Visayas). Household survey data was used to parameterise a spatially-explicit rabies transmission model with realistic dog movement and vaccination coverage scenarios, assuming a basic reproduction number for rabies drawn from the literature. This showed that heterogeneous vaccination reduces elimination prospects relative to homogeneous vaccination at the same overall level. Had the three vaccination campaigns completed in Region VI in 2010–2012 been homogeneous, they would have eliminated rabies with high probability. However, given the observed heterogeneity, three further campaigns may be required to achieve elimination with probability 0.95. We recommend that heterogeneity be reduced in future campaigns through targeted efforts in low coverage areas, even at the expense of reduced coverage in previously high coverage areas. Reported human-mediated dog movements did not reduce elimination probability, so expending limited resources on restricting dog movements is unnecessary in this endemic setting. Enhanced surveillance will be necessary post-elimination, however, given the reintroduction risk from long-distance dog movements
Integrating serological and genetic data to quantify cross-species transmission: brucellosis as a case study
Epidemiological data are often fragmented, partial, and/or ambiguous and unable to yield the desired level of understanding
of infectious disease dynamics to adequately inform control measures. Here, we show how the information contained in
widely available serology data can be enhanced by integration with less common type-specific data, to improve the understanding
of the transmission dynamics of complex multi-species pathogens and host communities. Using brucellosis in
Northern Tanzania as a case-study, we developed a latent process model based on serology data obtained from the
field, to reconstruct Brucella transmission dynamics. We were able to identify sheep and goats as a more likely source
of human and animal infection than cattle; however, the highly cross-reactive nature of Brucella spp. meant that it was
not possible to determine which Brucella species (B. abortus or B. melitensis) is responsible for human infection. We
extended our model to integrate simulated serology and typing data, and show that although serology alone can identify
the host source of human infection under certain restrictive conditions, the integration of even small amounts (5%) of
typing data can improve understanding of complex epidemiological dynamics. We show that data integration will often
be essential when more than one pathogen is present and when the distinction between exposed and infectious individuals
is not clear from serology data. With increasing epidemiological complexity, serology data become less informative.
However, we show how this weakness can be mitigated by integrating such data with typing data, thereby enhancing
the inference from these data and improving understanding of the underlying dynamics
Driving improvements in emerging disease surveillance through locally-relevant capacity strengthening
Emerging infectious diseases (EIDs) threaten the health of people, animals, and crops globally, but our ability to predict their occurrence is limited. Current public health capacity and ability to detect and respond to EIDs is typically weakest in low- and middle-income countries (LMICs). Many known drivers of EID emergence also converge in LMICs. Strengthening capacity for surveillance of diseases of relevance to local populations can provide a mechanism for building the cross-cutting and flexible capacities needed to tackle both the burden of existing diseases and EID threats. A focus on locally relevant diseases in LMICs and the economic, social, and cultural contexts of surveillance can help address existing inequalities in health systems, improve the capacity to detect and contain EIDs, and contribute to broader global goals for development
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