Remittances, Inequality and Poverty: Evidence from Rural Mexico

Economic research has produced conflicting findings on the distributional impacts of migrant remittances, and there has been little research on the effects of changes in remittances on poverty. This paper utilizes new data from the Mexico National Rural Household Survey, together with inequality and poverty decomposition techniques, to explore the impacts of remittances on rural inequality and poverty. Our findings suggest that remittances from international migrants become more equalizing (or less unequalizing), as well as more effective at reducing poverty, as the prevalence of migration increases.Labor and Human Capital,

Quantifying selection in immune receptor repertoires

The efficient recognition of pathogens by the adaptive immune system relies on the diversity of receptors displayed at the surface of immune cells. T-cell receptor diversity results from an initial random DNA editing process, called VDJ recombination, followed by functional selection of cells according to the interaction of their surface receptors with self and foreign antigenic peptides. To quantify the effect of selection on the highly variable elements of the receptor, we apply a probabilistic maximum likelihood approach to the analysis of high-throughput sequence data from the $\beta$-chain of human T-cell receptors. We quantify selection factors for V and J gene choice, and for the length and amino-acid composition of the variable region. Our approach is necessary to disentangle the effects of selection from biases inherent in the recombination process. Inferred selection factors differ little between donors, or between naive and memory repertoires. The number of sequences shared between donors is well-predicted by the model, indicating a purely stochastic origin of such "public" sequences. We find a significant correlation between biases induced by VDJ recombination and our inferred selection factors, together with a reduction of diversity during selection. Both effects suggest that natural selection acting on the recombination process has anticipated the selection pressures experienced during somatic evolution

Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination

Despite the extreme diversity of T cell repertoires, many identical T-cell receptor (TCR) sequences are found in a large number of individual mice and humans. These widely-shared sequences, often referred to as `public', have been suggested to be over-represented due to their potential immune functionality or their ease of generation by V(D)J recombination. Here we show that even for large cohorts the observed degree of sharing of TCR sequences between individuals is well predicted by a model accounting for by the known quantitative statistical biases in the generation process, together with a simple model of thymic selection. Whether a sequence is shared by many individuals is predicted to depend on the number of queried individuals and the sampling depth, as well as on the sequence itself, in agreement with the data. We introduce the degree of publicness conditional on the queried cohort size and the size of the sampled repertoires. Based on these observations we propose a public/private sequence classifier, `PUBLIC' (Public Universal Binary Likelihood Inference Classifier), based on the generation probability, which performs very well even for small cohort sizes

Monitoring of offshore geological carbon storage integrity: Implications of natural variability in the marine system and the assessment of anomaly detection criteria

The design of efficient monitoring programmes required for the assurance of offshore geological storage requires an understanding of the variability and heterogeneity of marine carbonate chemistry. In the absence of sufficient observational data and for extrapolation both spatially and seasonally, models have a significant role to play. In this study a previously evaluated hydrodynamic-biogeochemical model is used to characterise carbonate chemistry, in particular pH heterogeneity in the vicinity of the sea floor. Using three contrasting regions, the seasonal and short term variability are analysed and criteria that could be considered as indicators of anomalous carbonate chemistry identified. These criteria are then tested by imposing a number of randomised DIC perturbations on the model data, representing a comprehensive range of leakage scenarios. In conclusion optimal criteria and general rules for developing monitoring strategies are identified. Detection criteria will be site specific and vary seasonally and monitoring may be more efficient at periods of low dynamics. Analysis suggests that by using high frequency, sub-hourly monitoring anomalies as small as 0.01 of a pH unit or less may be successfully discriminated from natural variability – thereby allowing detection of small leaks or at distance from a leakage source. Conversely assurance of no leakage would be profound. Detection at deeper sites is likely to be more efficient than at shallow sites where the near bed system is closely coupled to surface processes. Although this study is based on North Sea target sites for geological storage, the model and the general conclusions are relevant to the majority of offshore storage sites lying on the continental shelf

OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs

Motivation: High-throughput sequencing of large immune repertoires has enabled the development of methods to predict the probability of generation by V(D)J recombination of T- and B-cell receptors of any specific nucleotide sequence. These generation probabilities are very non-homogeneous, ranging over 20 orders of magnitude in real repertoires. Since the function of a receptor really depends on its protein sequence, it is important to be able to predict this probability of generation at the amino acid level. However, brute-force summation over all the nucleotide sequences with the correct amino acid translation is computationally intractable. The purpose of this paper is to present a solution to this problem. Results: We use dynamic programming to construct an efficient and flexible algorithm, called OLGA (Optimized Likelihood estimate of immunoGlobulin Amino-acid sequences), for calculating the probability of generating a given CDR3 amino acid sequence or motif, with or without V/J restriction, as a result of V(D)J recombination in B or T cells. We apply it to databases of epitope-specific T-cell receptors to evaluate the probability that a typical human subject will possess T cells responsive to specific disease-associated epitopes. The model prediction shows an excellent agreement with published data. We suggest that OLGA may be a useful tool to guide vaccine design. Availability: Source code is available at https://github.com/zsethna/OLG

A continuous rating method for preferential voting. The complete case

A method is given for quantitatively rating the social acceptance of different options which are the matter of a complete preferential vote. Completeness means that every voter expresses a comparison (a preference or a tie) about each pair of options. The proposed method is proved to have certain desirable properties, which include: the continuity of the rates with respect to the data, a decomposition property that characterizes certain situations opposite to a tie, the Condorcet-Smith principle, and a property of clone consistency. One can view this rating method as a complement for the ranking method introduced in 1997 by Markus Schulze. It is also related to certain methods of one-dimensional scaling or cluster analysis.Comment: This is part one of a revised version of arxiv:0810.2263. Version 3 is the result of certain modifications, both in the statement of the problem and in the concluding remarks, that enhance the results of the paper; the results themselves remain unchange

The molecular characterisation of Escherichia coli K1 isolated from neonatal nasogastric feeding tubes

Background: The most common cause of Gram-negative bacterial neonatal meningitis is E. coli K1. It has a mortality rate of 10–15%, and neurological sequelae in 30– 50% of cases. Infections can be attributable to nosocomial sources, however the pre-colonisation of enteral feeding tubes has not been considered as a specific risk factor. Methods: Thirty E. coli strains, which had been isolated in an earlier study, from the residual lumen liquid and biofilms of neonatal nasogastric feeding tubes were genotyped using pulsed-field gel electrophoresis, and 7-loci multilocus sequence typing. Potential pathogenicity and biofilm associated traits were determined using specific PCR probes, genome analysis, and in vitro tissue culture assays. Results: The E. coli strains clustered into five pulsotypes, which were genotyped as sequence types (ST) 95, 73, 127, 394 and 2076 (Achman scheme). The extra-intestinal pathogenic E. coli (ExPEC) phylogenetic group B2 ST95 serotype O1:K1:NM strains had been isolated over a 2 week period from 11 neonates who were on different feeding regimes. The E. coli K1 ST95 strains encoded for various virulence traits associated with neonatal meningitis and extracellular matrix formation. These strains attached and invaded intestinal, and both human and rat brain cell lines, and persisted for 48 h in U937 macrophages. E. coli STs 73, 394 and 2076 also persisted in macrophages and invaded Caco-2 and human brain cells, but only ST394 invaded rat brain cells. E. coli ST127 was notable as it did not invade any cell lines. Conclusions: Routes by which E. coli K1 can be disseminated within a neonatal intensive care unit are uncertain, however the colonisation of neonatal enteral feeding tubes may be one reservoir source which could constitute a serious health risk to neonates following ingestion