Analyzing international airtime top-up transfers for migration and mobility.

International airtime top-up transfers enable prepaid mobile phone users to send top-ups and data bundles to users in other countries, as well as make payments, in real time. These are heavily used by migrants to financially assist their families in their home countries and consequently could be a valuable source of information for migration and mobility analysis. However, top-up transfers are understudied as a form of money remittance in migration. In this paper, we explore the determinants and the potential of top-up transactions to complement remittance and migration statistics. Our results show that such data can provide insights into migrant groups, particularly for irregular migration and for estimating the real-time distribution of migrant groups for a given country.

Glycaemic control in intensive care: Everything in moderation.

INTRODUCTION: Glycaemic control is an important predictor of mortality in sepsis. Various international organizations including the Surviving Sepsis campaign recommend glycaemic control in critical illness with a glucose target between 6.1-10 mmol/L. The NICE-SUGAR Trial in 2009 was a landmark in the debate over tight versus liberal glycaemic control in the critically ill and subsequent guidelines have been adjusted to reflect a move towards moderate glycaemic control. METHODS: We conducted a nation-wide study comparing glucose targets used in intensive care units in the United Kingdom in 2007 with those used in 2014 to 2015 to see the impact of the NICE-SUGAR study and subsequent guideline changes. RESULTS: We received a combined response from 81% of intensive care units in the UK. There was an increase in the average median glucose target in 2014/2015 compared with 2007 (7.8 versus 7.2; p < 0.01). However, there is still much variability in glucose targets used in critical care in the UK. CONCLUSIONS: There is an overall trend towards using a more moderate glucose target in critical care in the UK reflecting changes in international guidelines. However, it is likely that controversies, which still exist in the literature, are reflected in the variability of glycaemic control targets. It is possible that the advent of closed-loop or continuous glucose monitoring may have a further impact on this.

Imputation-based population genetics analysis of Plasmodium falciparum malaria parasites.

Whole-genome sequencing technologies are being increasingly applied to Plasmodium falciparum clinical isolates to identify genetic determinants of malaria pathogenesis. However, genome-wide discovery methods, such as haplotype scans for signatures of natural selection, are hindered by missing genotypes in sequence data. Poor correlation between single nucleotide polymorphisms (SNPs) in the P. falciparum genome complicates efforts to apply established missing-genotype imputation methods that leverage off patterns of linkage disequilibrium (LD). The accuracy of state-of-the-art, LD-based imputation methods (IMPUTE, Beagle) was assessed by measuring allelic r2 for 459 P. falciparum samples from malaria patients in 4 countries: Thailand, Cambodia, Gambia, and Malawi. In restricting our analysis to 86 k high-quality SNPs across the populations, we found that the complete-case analysis was restricted to 21k SNPs (24.5%), despite no single SNP having more than 10% missing genotypes. The accuracy of Beagle in filling in missing genotypes was consistently high across all populations (allelic r2, 0.87-0.96), but the performance of IMPUTE was mixed (allelic r2, 0.34-0.99) depending on reference haplotypes and population. Positive selection analysis using Beagle-imputed haplotypes identified loci involved in resistance to chloroquine (crt) in Thailand, Cambodia, and Gambia, sulfadoxine-pyrimethamine (dhfr, dhps) in Cambodia, and artemisinin (kelch13) in Cambodia. Tajima's D-based analysis identified genes under balancing selection that encode well-characterized vaccine candidates: apical merozoite antigen 1 (ama1) and merozoite surface protein 1 (msp1). In contrast, the complete-case analysis failed to identify any well-validated drug resistance or candidate vaccine loci, except kelch13. In a setting of low LD and modest levels of missing genotypes, using Beagle to impute P. falciparum genotypes is a viable strategy for conducting accurate large-scale population genetics and association analyses, and supporting global surveillance for drug resistance markers and candidate vaccine antigens.

T3SEdb: data warehousing of virulence effectors secreted by the bacterial Type III Secretion System.

BACKGROUND: Effectors of Type III Secretion System (T3SS) play a pivotal role in establishing and maintaining pathogenicity in the host and therefore the identification of these effectors is important in understanding virulence. However, the effectors display high level of sequence diversity, therefore making the identification a difficult process. There is a need to collate and annotate existing effector sequences in public databases to enable systematic analyses of these sequences for development of models for screening and selection of putative novel effectors from bacterial genomes that can be validated by a smaller number of key experiments. RESULTS: Herein, we present T3SEdb http://effectors.bic.nus.edu.sg/T3SEdb, a specialized database of annotated T3SS effector (T3SE) sequences containing 1089 records from 46 bacterial species compiled from the literature and public protein databases. Procedures have been defined for i) comprehensive annotation of experimental status of effectors, ii) submission and curation review of records by users of the database, and iii) the regular update of T3SEdb existing and new records. Keyword fielded and sequence searches (BLAST, regular expression) are supported for both experimentally verified and hypothetical T3SEs. More than 171 clusters of T3SEs were detected based on sequence identity comparisons (intra-cluster difference up to ~60%). Owing to this high level of sequence diversity of T3SEs, the T3SEdb provides a large number of experimentally known effector sequences with wide species representation for creation of effector predictors. We created a reliable effector prediction tool, integrated into the database, to demonstrate the application of the database for such endeavours. CONCLUSIONS: T3SEdb is the first specialised database reported for T3SS effectors, enriched with manual annotations that facilitated systematic construction of a reliable prediction model for identification of novel effectors. The T3SEdb represents a platform for inclusion of additional annotations of metadata for future developments of sophisticated effector prediction models for screening and selection of putative novel effectors from bacterial genomes/proteomes that can be validated by a small number of key experiments.