Does the history of food energy units suggest a solution to "Calorie confusion"?

The Calorie (kcal) of present U.S. food labels is similar to the original French definition of 1825. The original published source (now available on the internet) defined the Calorie as the quantity of heat needed to raise the temperature of 1 kg of water from 0 to 1°C. The Calorie originated in studies concerning fuel efficiency for the steam engine and had entered dictionaries by 1840. It was the only energy unit in English dictionaries available to W.O. Atwater in 1887 for his popular articles on food and tables of food composition. Therefore, the Calorie became the preferred unit of potential energy in nutrition science and dietetics, but was displaced when the joule, g-calorie and kcal were introduced. This article will explain the context in which Nicolas Clément-Desormes defined the original Calorie and the depth of his collaboration with Sadi Carnot. It will review the history of other energy units and show how the original Calorie was usurped during the period of international standardization. As a result, no form of the Calorie is recognized as an SI unit. It is untenable to continue to use the same word for different thermal units (g-calorie and kg-calorie) and to use different words for the same unit (Calorie and kcal). The only valid use of the Calorie is in common speech and public nutrition education. To avoid ongoing confusion, scientists should complete the transition to the joule and cease using kcal in any context

Health Centre Surveys as a Potential Tool for Monitoring Malaria Epidemiology by Area and over Time

BACKGROUND: Presently, many malaria control programmes use health facility data to evaluate the impact of their interventions. Facility-based malaria data, although useful, have problems with completeness, validity and representativeness and reliance on routinely collected health facility data might undermine demonstration of the magnitude of the impact of the recent scaleups of malaria interventions. To determine whether carefully conducted health centre surveys can be reliable means of monitoring area specific malaria epidemiology, we have compared malaria specific indices obtained from surveys in health centres with indices obtained from cross-sectional surveys conducted in their catchment communities. METHODS: A series of age stratified, seasonal, cross-sectional surveys were conducted during the peak malaria transmission season in 2008 and during the following dry season in 2009 in six ecologically diverse areas in The Gambia. Participants were patients who attended the health centres plus a representative sample from the catchment villages of these health facilities. Parasitaemia, anaemia, attributable proportion of fever and anti-MSP1-(19) antibody seroprevalence were compared in the health facility attendees and community participants. RESULTS: A total of 16,230 subjects completed the study; approximately half participated in the health centre surveys and half in the wet season surveys. Data from both the health centre and community surveys showed that malaria endemicity in The Gambia is now low, heterogeneous and seasonal. In the wet season, parasitaemia, seroprevalence and fever prevalence were higher in subjects seen in the health centres than in the community surveys. Age patterns of parasitaemia, attributable proportions of fever and seroprevalence rates were similar in subjects who participated in the community and health centre surveys. CONCLUSION: Health centre surveys have potential as a surveillance tool for evaluating area specific malaria control activities and for monitoring changes in local malaria epidemiology over time

Occurrence of Corynebacterium striatum as an emerging antibiotic-resistant nosocomial pathogen in a Tunisian hospital

Corynebacterium striatum is a nosocomial opportunistic pathogen increasingly associated with a wide range of human infections and is often resistant to several antibiotics. We investigated the susceptibility of 63 C. striatum isolated at the Farhat-Hached hospital, Sousse (Tunisia), during the period 2011?2014, to a panel of 16 compounds belonging to the main clinically relevant classes of antimicrobial agents. All strains were susceptible to vancomycin, linezolid, and daptomycin. Amikacin and gentamicin also showed good activity (MICs90 = 1 and 2 mg/L, respectively). High rates of resistance to penicillin (82.5%), clindamycin (79.4%), cefotaxime (60.3%), erythromycin (47.6%), ciprofloxacin (36.5%), moxifloxacin (34.9%), and rifampicin (25.4%) were observed. Fifty-nine (93.7%) out of the 63 isolates showed resistance to at least one compound and 31 (49.2%) were multidrug-resistant. Twenty-nine resistance profiles were distinguished among the 59 resistant C. striatum. Most of the strains resistant to fluoroquinolones showed a double mutation leading to an amino acid change in positions 87 and 91 in the quinolone resistance-determining region of the gyrA gene. The 52 strains resistant to penicillin were positive for the gene bla, encoding a class A ?-lactamase. Twenty-two PFGE patterns were identified among the 63 C. striatum, indicating that some clones have spread within the hospital

Evidence for Hitchhiking of Deleterious Mutations within the Human Genome

Deleterious mutations present a significant obstacle to adaptive evolution. Deleterious mutations can inhibit the spread of linked adaptive mutations through a population; conversely, adaptive substitutions can increase the frequency of linked deleterious mutations and even result in their fixation. To assess the impact of adaptive mutations on linked deleterious mutations, we examined the distribution of deleterious and neutral amino acid polymorphism in the human genome. Within genomic regions that show evidence of recent hitchhiking, we find fewer neutral but a similar number of deleterious SNPs compared to other genomic regions. The higher ratio of deleterious to neutral SNPs is consistent with simulated hitchhiking events and implies that positive selection eliminates some deleterious alleles and increases the frequency of others. The distribution of disease-associated alleles is also altered in hitchhiking regions. Disease alleles within hitchhiking regions have been associated with auto-immune disorders, metabolic diseases, cancers, and mental disorders. Our results suggest that positive selection has had a significant impact on deleterious polymorphism and may be partly responsible for the high frequency of certain human disease alleles

Diabetes-Specific Nutrition Algorithm: A Transcultural Program to Optimize Diabetes and Prediabetes Care

Type 2 diabetes (T2D) and prediabetes have a major global impact through high disease prevalence, significant downstream pathophysiologic effects, and enormous financial liabilities. To mitigate this disease burden, interventions of proven effectiveness must be used. Evidence shows that nutrition therapy improves glycemic control and reduces the risks of diabetes and its complications. Accordingly, diabetes-specific nutrition therapy should be incorporated into comprehensive patient management programs. Evidence-based recommendations for healthy lifestyles that include healthy eating can be found in clinical practice guidelines (CPGs) from professional medical organizations. To enable broad implementation of these guidelines, recommendations must be reconstructed to account for cultural differences in lifestyle, food availability, and genetic factors. To begin, published CPGs and relevant medical literature were reviewed and evidence ratings applied according to established protocols for guidelines. From this information, an algorithm for the nutritional management of people with T2D and prediabetes was created. Subsequently, algorithm nodes were populated with transcultural attributes to guide decisions. The resultant transcultural diabetes-specific nutrition algorithm (tDNA) was simplified and optimized for global implementation and validation according to current standards for CPG development and cultural adaptation. Thus, the tDNA is a tool to facilitate the delivery of nutrition therapy to patients with T2D and prediabetes in a variety of cultures and geographic locations. It is anticipated that this novel approach can reduce the burden of diabetes, improve quality of life, and save lives. The specific Southeast Asian and Asian Indian tDNA versions can be found in companion articles in this issue of Current Diabetes Reports

Search for large missing transverse momentum in association with one top-quark in proton-proton collisions at √s = 13 TeV with the ATLAS detector

This paper describes a search for events with one top-quark and large missing transverse momentum in the final state. Data collected during 2015 and 2016 by the ATLAS experiment from 13 TeV proton–proton collisions at the LHC corresponding to an integrated luminosity of 36.1 fb−1 are used. Two channels are considered, depending on the leptonic or the hadronic decays of the W boson from the top quark. The obtained results are interpreted in the context of simplified models for dark-matter production and for the single production of a vector-like T quark. In the absence of significant deviations from the Standard Model background expectation, 95% confidence-level upper limits on the corresponding production cross-sections are obtained and these limits are translated into constraints on the parameter space of the models considered

Correlated long-range mixed-harmonic fluctuations measured in pp, p+Pb and low-multiplicity Pb+Pb collisions with the ATLAS detector

For abstract see published article

Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC

The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s=13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb −1 for the tt ¯ and γ+jet and 36.7 fb −1 −1 for the dijet event topologies

In situ calibration of large-radius jet energy and mass in 13 TeV proton–proton collisions with the ATLAS detector

The response of the ATLAS detector to largeradius jets is measured in situ using 36.2 fb−1 of √s = 13 TeV proton–proton collisions provided by the LHC and recorded by the ATLAS experiment during 2015 and 2016. The jet energy scale is measured in events where the jet recoils against a reference object, which can be either a calibrated photon, a reconstructed Z boson, or a system of well-measured small-radius jets. The jet energy resolution and a calibration of forward jets are derived using dijet balance measurements. The jet mass response is measured with two methods: using mass peaks formed by W bosons and top quarks with large transverse momenta and by comparing the jet mass measured using the energy deposited in the calorimeter with that using the momenta of charged-particle tracks. The transversemomentum and mass responses in simulations are found to be about 2–3% higher than in data. This difference is adjusted for with a correction factor. The results of the different methods are combined to yield a calibration over a large range of transverse momenta (pT). The precision of the relative jet energy scale is 1–2% for 200 GeV < pT < 2 TeV, while that of the mass scale is 2–10%. The ratio of the energy resolutions in data and simulation is measured to a precision of 10–15% over the same pT range