Quality changes and shelf-life prediction of a fresh fruit and vegetables purple smoothie

The sensory, microbial and bioactive quality changes of untreated (CTRL) and mild heat−treated (HT; 90 ºC/45 s) smoothies were studied and modelled throughout storage (5, 15 and 25 ºC). The overall acceptability was better preserved in HT samples being highly correlated (hierarchical clustering) with the flavour. The sensory quality data estimated smoothie shelf−life (CTRL/HT) of 18/55 (at 5 ºC), 4.5/12 (at 15 ºC), 2.4/5.8 (at 25 ºC) days. The yeast and moulds growth rate was lower in HT compared to CTRL while a lag phase for mesophiles/psychrophiles was observed in HT−5/15 ºC. HT and 5 ºC−storage stabilized the phenolics content. FRAP reported the best correlation (R2=0.94) with the studied bioactive compounds, followed by ABTS (R2=0.81) while DPPH was the total antioxidant capacity method with the lowest adjustment (R2=0.49). Conclusively, modelling was used to estimate the shelf−life of a smoothie based on quality retention after a short time−high temperature heat treatment that better preserved microbial and nutritional quality during storage.The financial support of this research was provided by the Ministerio Español de Economía y Competitividad MINECO (Projects AGL2013−48830−C2−1−R and AGL2013−48993−C2−1−R) and by FEDER funds. G.A. González−Tejedor thanks to Panamá Government for the scholarship to carry out his PhD Thesis. A. Garre (BES−2014−070946) is grateful to the MINECO for awarding him a pre−doctoral grant. We are also grateful to E. Esposito and N. Castillejo for their skilful technical assistance

Systemic manifestations of primary Sjögren's syndrome out of the ESSDAI classification: prevalence and clinical relevance in a large international, multi-ethnic cohort of patients

OBJECTIVES: To analyse the frequency and characterise the systemic presentation of primary Sjögren’s syndrome (SS) out of the ESSDAI classification in a large international, multi-ethnic cohort of patients. // METHODS: The Big Data Sjögren Project Consortium is an international, multicentre registry based on world-wide data-sharing and cooperative merging of pre-existing clinical SS databases from leading centres in clinical research in SS from the five continents. A list of 26 organ-by-organ systemic features not currently included in the ESSDAI classification was defined according to previous studies; these features were retrospectively recorded. // RESULTS: Information about non-ESSDAI features was available in 6331 patients [5,917 female, mean age at diagnosis 52 years, mainly White (86.3%)]. A total of 1641 (26%) patients had at least one of the ESSDAI systemic features. Cardiovascular manifestations were the most frequent organ-specific group of non-ESSDAI features reported in our patients (17% of the total cohort), with Raynaud’s phenomenon being reported in 15%. Patients with systemic disease due to non-ESSDAI features had a lower frequency of dry mouth (90.7% vs. 94.1%, p<0.001) and positive minor salivary gland biopsy (86.7% vs. 89%, p=0.033), a higher frequency of anti-Ro/SSA (74.7% vs. 68.7%, p<0.001), anti-La/SSB antibodies (44.5% vs. 40.4%, p=0.004), ANA (82.7% vs. 79.5%, p=0.006), low C3 levels (17.4% vs. 9.7%, p<0.001), low C4 levels (14.4% vs. 9.6%, p<0.001), and positive serum cryoglobulins (8.6% vs. 5.5%, p=0.001). Systemic activity measured by the ESSDAI, clinESSDAI and DAS was higher in patients with systemic disease out of the ESSDAI in comparison with those without these features (p<0.001 for all comparisons). // CONCLUSIONS: More than a quarter of patients with primary SS may have systemic manifestations not currently included in the ESSDAI classification, with a wide variety of cardiovascular, digestive, pulmonary, neurological, ocular, ENT (ear, nose, and throat), cutaneous and urological features that increase the scope of the systemic phenotype of the disease. However, the individual frequency of each of these non-ESSDAI features was very low, except for Raynaud’s phenomenon

Mechanisms of Endothelial Dysfunction in Resistance Arteries from Patients with End-Stage Renal Disease

The study focuses on the mechanisms of endothelial dysfunction in the uremic milieu. Subcutaneous resistance arteries from 35 end-stage renal disease (ESRD) patients and 28 matched controls were studied ex-vivo. Basal and receptor-dependent effects of endothelium-derived factors, expression of endothelial NO synthase (eNOS), prerequisites for myoendothelial gap junctions (MEGJ), and associations between endothelium-dependent responses and plasma levels of endothelial dysfunction markers were assessed. The contribution of endothelium-derived hyperpolarizing factor (EDHF) to endothelium-dependent relaxation was impaired in uremic arteries after stimulation with bradykinin, but not acetylcholine, reflecting the agonist-specific differences. Diminished vasodilator influences of the endothelium on basal tone and enhanced plasma levels of asymmetrical dimethyl L-arginine (ADMA) suggest impairment in NO-mediated regulation of uremic arteries. eNOS expression and contribution of MEGJs to EDHF type responses were unaltered. Plasma levels of ADMA were negatively associated with endothelium-dependent responses in uremic arteries. Preserved responses of smooth muscle to pinacidil and NO-donor indicate alterations within the endothelium and tolerance of vasodilator mechanisms to the uremic retention products at the level of smooth muscle. We conclude that both EDHF and NO pathways that control resistance artery tone are impaired in the uremic milieu. For the first time, we validate the alterations in EDHF type responses linked to kinin receptors in ESRD patients. The association between plasma ADMA concentrations and endothelial function in uremic resistance vasculature may have diagnostic and future therapeutic implications

α-Synuclein Genetic Variants Predict Faster Motor Symptom Progression in Idiopathic Parkinson Disease

Currently, there are no reported genetic predictors of motor symptom progression in Parkinson’s disease (PD). In familial PD, disease severity is associated with higher α-synuclein (SNCA) expression levels, and in postmortem studies expression varies with SNCA genetic variants. Furthermore, SNCA is a well-known risk factor for PD occurrence. We recruited Parkinson’s patients from the communities of three central California counties to investigate the influence of SNCA genetic variants on motor symptom progression in idiopathic PD. We repeatedly assessed this cohort of patients over an average of 5.1 years for motor symptom changes employing the Unified Parkinson’s Disease Rating Scale (UPDRS). Of 363 population-based incident PD cases diagnosed less than 3 years from baseline assessment, 242 cases were successfully re-contacted and 233 were re-examined at least once. Of subjects lost to follow-up, 69% were due to death. Adjusting for covariates, risk of faster decline of motor function as measured by annual increase in motor UPDRS exam score was increased 4-fold in carriers of the REP1 263bp promoter variant (OR 4.03, 95%CI:1.57–10.4). Our data also suggest a contribution to increased risk by the G-allele for rs356165 (OR 1.66; 95%CI:0.96–2.88), and we observed a strong trend across categories when both genetic variants were considered (p for trend  = 0.002). Our population-based study has demonstrated that SNCA variants are strong predictors of faster motor decline in idiopathic PD. SNCA may be a promising target for therapies and may help identify patients who will benefit most from early interventions. This is the first study to link SNCA to motor symptom decline in a longitudinal progression study

Recording behaviour of indoor-housed farm animals automatically using machine vision technology: a systematic review

Large-scale phenotyping of animal behaviour traits is time consuming and has led to increased demand for technologies that can automate these procedures. Automated tracking of animals has been successful in controlled laboratory settings, but recording from animals in large groups in highly variable farm settings presents challenges. The aim of this review is to provide a systematic overview of the advances that have occurred in automated, high throughput image detection of farm animal behavioural traits with welfare and production implications. Peer-reviewed publications written in English were reviewed systematically following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After identification, screening, and assessment for eligibility, 108 publications met these specifications and were included for qualitative synthesis. Data collected from the papers included camera specifications, housing conditions, group size, algorithm details, procedures, and results. Most studies utilized standard digital colour video cameras for data collection, with increasing use of 3D cameras in papers published after 2013. Papers including pigs (across production stages) were the most common (n = 63). The most common behaviours recorded included activity level, area occupancy, aggression, gait scores, resource use, and posture. Our review revealed many overlaps in methods applied to analysing behaviour, and most studies started from scratch instead of building upon previous work. Training and validation sample sizes were generally small (mean±s.d. groups = 3.8±5.8) and in data collection and testing took place in relatively controlled environments. To advance our ability to automatically phenotype behaviour, future research should build upon existing knowledge and validate technology under commercial settings and publications should explicitly describe recording conditions in detail to allow studies to be reproduced

Urine metabolome profiling of immune-mediated inflammatory diseases

Background: Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn?s disease, and ulcerative colitis. Methods: Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls. Results: In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (PFDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (PFDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an overrepresentation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways. Conclusions: This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs

Signals in the Soil: An Introduction to Wireless Underground Communications

In this chapter, wireless underground (UG) communications are introduced. A detailed overview of WUC is given. A comprehensive review of research challenges in WUC is presented. The evolution of underground wireless is also discussed. Moreover, different component of UG communications is wireless. The WUC system architecture is explained with a detailed discussion of the anatomy of an underground mote. The examples of UG wireless communication systems are explored. Furthermore, the differences of UG wireless and over-the-air wireless are debated. Different types of wireless underground channel (e.g., In-Soil, Soil-to-Air, and Air-to-Soil) are reported as well

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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