New Local, National and Regional Cereal Price Indices for Improved Identification of Food Insecurity

Large price increases over a short time period can be indicative of a deteriorating food security situation. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets. However, reporting by the United States Agency for International Development (USAID)'s Famine Early Warning Systems Network (FEWS NET) indicates that staple cereal prices in many markets of the developing world, especially in surplus-producing areas, often have a delayed and variable response to international export market price trends. Here we present new price indices compiled for improved food security monitoring and assessment, and specifically for monitoring conditions of food access across diverse food insecure regions. We found that cereal price indices constructed using market prices within a food insecure region showed significant differences from the international cereals price, and had a variable price dispersion across markets within each marketshed. Using satellite-derived remote sensing information that estimates local production and the FAO Cereals Index as predictors, we were able to forecast movements of the local or national price indices in the remote, arid and semi-arid countries of the 38 countries examined. This work supports the need for improved decision-making about targeted aid and humanitarian relief, by providing earlier early warning of food security crises

A matter of taste: the adverse effect of pollen compounds on the pre-ingestive gustatory experience of sugar solutions for honeybees

This is the final version. Available from the publisher via the DOI in this record.The online version of this article (https://doi.org/10.1007/s00359-019-01347-z) contains supplementary material, which is available to authorized users.In addition to sugars, nectar contains multiple nutrient compounds in varying concentrations yet little is known of their effect on the reward properties of nectar and the resulting implications for insect behaviour. We examined the pre-ingestive responses of honeybees to sucrose solutions containing a mix of pollen compounds, the amino acids proline or phenylalanine, or known distasteful substances, quinine and salt. We predicted that in taste and learning assays, bees would respond positively to the presence of nutrient compounds in a sucrose solution. However, bees’ proboscis extension responses decreased when their antennae were stimulated with pollen- or amino-acid supplemented sucrose solutions. Compared to pure sucrose, bees exhibited worse acquisition when conditioned to an odour with pollen-supplemented sucrose as the unconditioned stimulus. Such learning impairment was also observed with quinine-containing sucrose solutions. Our results suggest that bees can use their antennae to detect pollen compounds in floral nectars. Depending on the type and concentrations of compounds present, this may result in nectar being perceived as distasteful by bees, making it less effective in reinforcing the learning of floral cues. Such reward devaluation might be adaptive in cases where plants benefit from regulating the frequency of bee visitation.UKIERI (British Council)Biotechnology and Biological Sciences Research Council (BBSRC) (SWBiosciences DTP

Geometric representations for minimalist grammars

We reformulate minimalist grammars as partial functions on term algebras for strings and trees. Using filler/role bindings and tensor product representations, we construct homomorphisms for these data structures into geometric vector spaces. We prove that the structure-building functions as well as simple processors for minimalist languages can be realized by piecewise linear operators in representation space. We also propose harmony, i.e. the distance of an intermediate processing step from the final well-formed state in representation space, as a measure of processing complexity. Finally, we illustrate our findings by means of two particular arithmetic and fractal representations.Comment: 43 pages, 4 figure

Follicle-stimulating Hormone is Independently Associated with Lean Mass but not BMD in Younger Postmenopausal Women

PURPOSE: Increased follicle-stimulating hormone (FSH) has been associated with lower bone mineral density (BMD) in animal models and longitudinal studies of women, but a direct effect has not been demonstrated.METHODS: We tested associations between FSH, non-bone body composition measures and BMD in 94 younger (aged 50 to 64 years) postmenopausal women without current use of hormone therapy, adjusting for sex hormone concentrations and clinical risk factors for osteoporosis. Lean mass, fat mass and areal BMD (aBMD) at the spine, femoral neck and total hip were measured using dual energy X-ray absorptiometry (DXA). Volumetric BMD (vBMD) was measured at the distal radius using peripheral quantitative computed tomography (pQCT).RESULTS: FSH was inversely correlated with lean and fat mass, bioavailable estradiol, spine and hip aBMD, and vBMD at the ultradistal radius. In the multivariable analysis, FSH was independently associated with lean mass (β=-0.099, p=0.005) after adjustment for age, race, years since menopause, bioavailable estradiol, bioavailable testosterone, LH, PTH, SHBG and urine N-telopeptide. FSH showed no statistically significant association with aBMD at any site or pQCT measures at the distal radius in adjusted models. Race was independently associated with aBMD, and race and urine N-telopeptide were independently associated with bone area and vBMD.CONCLUSIONS: After adjustment for hormonal measures and osteoporosis risk factors, higher concentrations of FSH were independently associated with lower lean mass, but not with BMD. Previously reported correlations between FSH and BMD might have been due to indirect associations via lean mass or weight

Genomic and phenotypic analyses of recent Acinetobacter baumannii isolates from tertiary care hospitals in Thailand

Antibiotic resistant strains of Acinetobacter baumannii are responsible for a large and increasing burden of nosocomial infections in Thailand and other countries of Southeast Asia. New approaches to their control and treatment are urgently needed and we are actively seeking biological agents that remove the polysaccharide capsules that protect these pathogens from the host’s immune system. To examine phylogenetic relationships, distribution of capsule chemotypes, acquired antibiotic resistance determinants, susceptibility to complement and other traits associated with systemic infection, we sequenced 191 recent isolates from three tertiary referral hospitals in Thailand and used phenotypic assays to characterise key aspects of infectivity. Several distinct lineages were circulating in three hospitals and the majority belonged to global clonal group 2 (GC2). Very high levels of resistance to carbapenems and other front-line antibiotics were found, as were a number of widespread plasmid replicons. A high diversity of capsule genotypes were encountered with only three (KL6, KL10 and KL47) above 10% frequency. Almost 90% of GC2 isolates belonged to the most common capsule genotypes and were fully resistant to the bactericidal action of human serum complement; we attribute this trait to the presence of a substantial protective capsule and for this to represent a key determinant of virulence for systemic infection. We conclude that current Thai nosocomial isolates represent potential targets for therapeutic strategies designed to remove the polysaccharide capsule from extensively drug-resistant A. baumanii during the course of systemic infection

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

Type A behavior and risk of all-cause mortality, CAD, and CAD-related mortality, in a type 1 diabetes population: 22 years of follow-up in the Pittsburgh Epidemiology of Diabetes Complications Study

Objective To determine whether type A behavior predicts all cause mortality and incident coronary artery disease (CAD) in a type 1 diabetes population. Research Design and Methods Twenty-two year follow-up data from the Pittsburgh Epidemiology of Diabetes Complications (EDC) study of childhood onset type 1 diabetes were analyzed for the 506 participants who completed the Bortner Rating Scale (measuring type A myocardial infarction as determined by hospital records/ Q waves on ECG, CAD death behavior) and Beck’s Depression Inventory (BDI) at baseline (1986-1988). CAD comprised (determined by a mortality classification committee), angiographic stenosis, ischemic ECG and angina. Results There were 128 deaths (25.3%) during follow-up. Univariate analysis showed an inverse relationship between Bortner scores and all cause mortality (p=0.01) which remained significant after allowing for age, sex, duration, HbA1c, education, smoking, BMI, and physical activity (p=0.03). However, the addition of BDI scores attenuated the relationship (p=0.11) with a significant interaction (p=0.03) such that any protective effect against mortality was limited among individuals with lower BDI scores (bottom 3 quintiles) (p=0.07), while no effect was seen in those with higher BDI (p=0.97). Bortner scores showed only a borderline association with incident CAD (p=0.09). Conclusions Those with higher type A behavior have lower all-cause mortality in our type 1 diabetes population, an effect that interacts with depressive symptomatology such that it is only operative in those with low BDI scores. Further research should focus on understanding this interaction

Capturing the statewide incidence of neonatal abstinence syndrome in real time: the West Virginia experience

Background Neonatal abstinence syndrome (NAS) is one of the consequences at birth affecting the newborn after discontinuation of prenatal drug exposure to mainly opioids. The objective of this study was to determine the extent of the problem in the state of West Virginia (WV) using a real-time statewide surveillance system. Methods Project WATCH is a surveillance tool that since 1998 collects data on all infants born in the state of WV. NAS surveillance item was added to the tool in October 2016. This study examined all births (N = 23,667) in WV from October to December 2017. The data from six WV birthing facilities were audited for 1 month to evaluate how well this tool was capturing NAS data using κ-statistics. Results The 2017 annual incidence rate of NAS was 51.3 per 1000 live births per year for all births and 50.6 per 1000 live births per year for WV residents only. The κ-coefficient between the hospital medical records and Project WATCH data was 0.74 (95% confidence interval: 0.66–0.82) for NAS. Conclusion The study provides justification to develop effective systems of care for the mother–infant dyad affected by substance use, especially targeting pregnant women in rural communities