Empowering open science with reflexive and spatialised indicators

Bibliometrics have become commonplace and widely used by authors and journals to monitor, to evaluate and to identify their readership in an ever-increasingly publishing scientific world. This contribution introduces a multi-method corpus analysis tool, specifically conceived for scientific corpuses with spatialised content. We propose a dedicated interactive application that integrates three strategies for building semantic networks, using keywords (self-declared themes), citations (areas of research using the papers) and full-texts (themes derived from the words used in writing). The networks can be studied with respect to their temporal evolution as well as to their spatial expressions, by considering the countries studied in the papers under inquiry. The tool is applied as a proof-of-concept on the papers published in the online open access geography journal Cybergeo since its creation in 1996. Finally, we compare the three methods and conclude that their complementarity can help go beyond simple statistics to better understand the epistemological evolution of a scientific community and the readership target of the journal. Our tool can be applied by any journal on its own corpus, fostering thus open science and reflexivity

Variants in the 3'UTR of the ovine Acetyl-Coenzyme A Acyltransferase 2 gene are associated with dairy traits and exhibit differential allelic expression

The acetyl-CoA acyltransferase 2 (ACAA2) gene encodes an enzyme of the thiolase family that is involved in mitochondrial fatty acid elongation and degradation by catalyzing the last step of the respective β-oxidation pathway. The increased energy needs for gluconeogenesis and triglyceride synthesis during lactation are met primarily by increased fatty acid oxidation. Therefore, the ACAA2 enzyme plays an important role in the supply of energy and carbon substrates for lactation and may thus affect milk production traits. This study investigated the association of the ACAA2 gene with important sheep traits and the putative functional involvement of this gene in dairy traits. A single nucleotide substitution, a T to C transition located in the 3′ untranslated region of the ACAA2 gene, was used in mixed model association analysis with milk yield, milk protein yield and percentage, milk fat yield and percentage, and litter size at birth. The single nucleotide polymorphism was significantly associated with total lactation production and milk protein percentage, with respective additive effects of 6.81 ± 2.95 kg and −0.05 ± 0.02%. Additionally, a significant dominance effect of 0.46 ± 0.21 kg was detected for milk fat yield. Homozygous TT and heterozygous CT animals exhibited higher milk yield compared with homozygous CC animals, whereas the latter exhibited increased milk protein percentage. Expression analysis from age-, lactation-, and parity-matched female sheep showed that mRNA expression of the ACAA2 gene from TT animals was 2.8- and 11.8-fold higher in liver and mammary gland, respectively. In addition, by developing an allelic expression imbalance assay, it was estimated that the T allele was expressed at an average of 18% more compared with the C allele in the udder of randomly selected ewes. We demonstrated for the first time that the variants in the 3′ untranslated region of the ovine ACAA2 gene are differentially expressed in homozygous ewes of each allele and exhibit allelic expression imbalance within heterozygotes in a tissue-specific manner, supporting the existence of cis-regulatory DNA variation in the ovine ACAA2 gene. This is the first study reporting differential allelic imbalance expression of a candidate gene associated with milk production traits in dairy sheep

Automatic system for personalised exercise recommendation in breast cancer care using mobile technologies and machine learning

[ES] Aliviar las secuelas del cáncer en general, y en particular del cáncer de mama, es uno de los mayores retos de nuestros tiempos, y precisamente el ejercicio terapéutico se plantea como una solución para paliar los efectos secundarios del cáncer y su tratamiento a corto y largo plazo. No obstante, para que las intervenciones del ejercicio físico sean más efectivas estas deben estar adaptadas a cada paciente según sus capacidades y necesidades de entrenamiento específicas. Dicha adaptación al entrenamiento utilizando tecnologías de salud móvil (mSalud) ya se ha llevado a cabo con éxito en entornos deportivos, y en este trabajo se plantea una aproximación similar para pacientes con cáncer de mama, donde se pretende ajustar de forma individual las dosis de entrenamiento a las necesidades de cada paciente. Para ello, se ha diseñado y desarrollado un sistema completo de mSalud que ha permitido extraer un conjunto de datos longitudinal con mediciones de la carga del ejercicio de pacientes de cáncer de mama. A partir de dichos datos se están utilizando técnicas de ciencia de datos y aprendizaje automático para extraer los diferentes estados de recuperación de las pacientes a lo largo de una intervención en ejercicio físico, lo cual nos permitirá plantear un sistema de ayuda a la toma de decisiones para prescribir dosis individualizadas de ejercicio terapéutico.[EN] Alleviating the sequelae of cancer in general, and breast cancer in particular, is one of the greatest challenges of our times, and therapeutic exercise is precisely one solution to alleviate the side effects of cancer and its treatment in the short and long term. However, in order to make exercise interventions more effective, they must be adapted to each patient according to their specific training needs and abilities. Such adaptation to training using mobile health technologies (mHealth) has already been successfully carried out in sports settings, and this work proposes a similar approach for breast cancer patients, where the aim is to individually adjust the training doses to the needs of each patient. To this end, a complete mHealth system has been designed and developed to extract a longitudinal dataset of exercise load measurements from breast cancer patients. To leverage these data, data science and machine learning techniques are being used to extract the different states of recovery of patients throughout a physical exercise intervention, which will allow us to propose a decision support system to prescribe individualized doses of therapeutic exercise

Sedentary behavior-based user life-log monitoring for wellness services

© Springer International Publishing Switzerland 2016. Ubiquitous computing and smart gadgets have revolutionized the selfquantification in tracking and logging activities for improving daily life and inducing healthy behavior. Life-log monitoring is the process of monitoring the daily life routines of user in an efficient manner in terms of time and amount of activities. The effective utilization of life-log monitoring is to correctly identify and intimate user unhealthy activities in a timely manner. For monitoring lifelog, the knowledge of sedentary behavior first need to be formulated by the domain expert in the form of unhealthy situations, these situations are used as the monitoring unit. In this study we proposed a method for automatically monitoring users’ unhealthy situations in the domain of sedentary behavior with prolonged activities. The proposed method simultaneously filters out multiple sedentary activities of users simultaneously while ignoring the activities having no situations. The results depict that the monitoring method intimates the stakeholder with delay less than the monitoring interval cycle

Genomic markers associated with antibody response to Newcastle disease virus of Sasso chickens raised in Ethiopia

Newcastle disease virus (NDV) is one of the highly contagious avian pathogens that threatens poultry producers in endemic zones due to its epidemic potential. Selection for antibody (Ab) response can effectively improve disease resistance in chickens. However, the molecular basis of the variation in Ab response to NDV is unclear. This study aimed to detect genomic markers and genes modulating Ab response to NDV in chickens reared under tropical, outdoor conditions. A genome-wide association study (GWAS) was conducted on Sasso T451A chickens that were naturally exposed to infectious diseases from 56 to 112 days of age to identify regions associated with Ab response to NDV. Phenotypic immune data from 935 chickens, monitored in two batches, and genotyping data of these chickens based low-pass sequencing (2,676,181 single nucleotide polymorphisms, SNPs) were used. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of five SNPs (rs316795557 (FOXP2), chr 1; rs313761644 (CEP170B), chr 5; rs733628728, chr 13; and two unnamed SNPs, chr 30 and chr 33) were associated with the chicken antibody response to NDV at the suggestive significance level. These SNPs are located on chromosomes 1, 5, and 13 and are in genomic regions that contain several genes with roles in the regulation of the immune response. The results of this study pave the path for more investigation into the host immune response of chickens to NDV.</p

Current situations of animal data recording, dairy improvement infrastructure, human capacity and strategic issues affecting dairy production in sub-Saharan Africa

An online survey on the state of existing dairy data, dairy improvement infrastructure and human capacity in sub-Saharan Africa (SSA) was undertaken with the aim of assessing whether the state of existing animal recording, dairy improvement methods and key issues facing dairy production together with means of addressing the issues differ among countries and regions of SSA. Respondents comprised experts and practitioners in livestock production and genetic resources from research institutes, animal breeding companies, universities, non-governmental organisations and government agricultural ministries. The main dairy farming system in which the respondents were involved was mixed crop-livestock system (30.2%), and this was mainly practised in the private land tenure system (46.3%). Data were analysed using linear model and paired Student t test in R software package. Respondents identified key issues affecting dairy production as poor genetic assessment of imported exotic breeds and crosses in Africa (62.3%), fluctuations in milk prices within both the formal and informal markets (50.9%), no comprehensive sire ranking systems (39.6%), housing and health management regimes which adversely affect milk yield (32.1%), poor market networks for dairy products (25.5%), poor feeding (13.3%), inadequate genetic technologies (9.4%) and poor animal performance recording systems (9.4%). Respondents emphasised the need for updated breeding policies, sire ranking systems, adequate farm management systems, capacity building, across-country collaborations and joint genetic assessments of dairy breeds found in sub-Saharan Africa. The current situation of dairy production though similar for the different countries, differed in order of emphasis and magnitude across the countries and regions in sub-Saharan Africa.</p

Thermal, structural and optical properties of {CdS}-Na(86)X composites

Thermal, structural and optical properties of CdS superclusters grown in zeolite Na(86)X are reported. The interest in this work arose in the need to study CdS prepared in the zeolite host, at high concentrations (>19%), in order to observe porosyte behaviour and CdS aggregate properties. The semiconductor-zeolite composite was studied using X-ray diffraction analysis and photoacoustic technique (PAS). The properties of semiconductor CdS embedded in a zeolite matrix were analysed as a function of the CdS concentration by monitoring Cd concentration (atom%) by chemical analysis. The results show that as the concentration of CdS increases, the thermal diffusivity, capacity, conductivity and the band-gap increase up to a point where the zeolite lattice collapses. From this point on, all these thermal properties diminish and the band-gap is the same as for bulk CdS.92142651265