The influence of pharmaceutical industry (PI) on clinical practice and research in psychiatry has been considered a serious problem. Strict rules and guidelines were developed to regulate the interactions between doctors and PI. However, there is an ongoing debate whether these were thoroughly implemented in practice and internalized by physicians. The objective of our study was to assess the attitudes and behaviors of trainees in psychiatry and child & adolescent psychiatry toward PI across Europe. Methodologically, a validated questionnaire with additional items was administered to1444 trainees in 20 European countries. The minimum response rate was set at 60%. We found a high variation across countries in number of interactions between trainees and PI representatives; Portugal and Turkey had the highest number of interactions. The majority (59.76%) agreed that interactions with PI representatives have an impact on physicians’ prescribing behavior; whereas only 29.26% and 19.79% agreed interactions with PI representatives and gifts from PI have impact on their own prescribing behavior, respectively. Most of the gifts were considered appropriate by the majority, except tickets to vacation spot and social dinner at a restaurant. Of the sample, 70.76% think they have not been given sufficient training regarding how to interact with PI representatives. Only less than 20% indicated they have guidelines at institutional or national level. In conclusion, there is substantial interaction between trainees and PI across countries. The majority feel inadequately trained regarding professional interaction with PI, and believes they are immune to the influence of PI.

Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.

We studied trends in the incidence of health care-associated infections (HAIs) in LTCFs between 2009 and 2015 and determined the effect of participation in our network. Elder-care physicians reported weekly the number of cases of influenza-like illness, gastroenteritis, (probable) pneumonia, urinary tract infections (UTIs) and all-cause mortality. Trends in the incidence of infection and mortality in relation to LTCF characteristics were calculated using multilevel univariate and multivariate logistic regression. Thirty LTCF participated for 3 years or more, 16 for 2 years and the remaining 12 LTCF for 1 year. During the study period, the median number of beds decreased from 158 to 139, whereas the percentage of residents with private bedrooms increased from 14% to 87%. UTIs were the most frequently reported infections, followed by (probable) pneumonia and gastroenteritis. Adjusted for calendar year and season, we observed a statistically significant decrease in the incidence of influenza-like illness (odds ratio (OR) = 0.8, P < 0.01) and (probable) pneumonia (OR = 0.8, P < 0.01) for each extra year an LTCF participated. Although there are other likely contributors, such as more private rooms and enhanced infection control measures, the decreasing trend of HAI in LTCFs participating in surveillance implies that surveillance is a valuable addition to current strategies to optimise infection control.

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.

Static lattice energy calculations have been combined with cluster expansion formalism to predict pairwise ordering interactions in the pyrope–grossular solid solution. The ordering interactions, the Js, have been then used to calculate the activity-composition relations over a wide temperature range with the help of the Cluster Variation Method. It is shown that short-range ordering in the system is driven by size mismatch. The prediction of the right signs and magnitudes of the ordering interaction energies requires separation of the mixing enthalpy into the configuration-dependent (chemical) and the configuration-independent (elastic) components. The study predicts the existence of a miscibility gap below 500°C.

Delays in rotavirus vaccine schedule could improve performance in low- and middle-income countries (LMICs). However, delaying the first dose could be detrimental if infants experience severe rotavirus gastroenteritis (RVGE) early in life. Our objective was to describe the timing and predictors of severe RVGE in unvaccinated children in LMICs. We analysed the placebo arms from two clinical trials (cohort 1: NCT00241644; cohort 2: NCT00362648). We estimated the rate, cumulative incidence (per 1000 infants) and age distribution of severe RVGE episodes. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals (CI) for the association between baseline factors and severe RVGE. Cumulative incidence at 6 months of age was 23/1000 (95% CI 15–30) in cohort 1 and 6/1000 (95% CI 3–8) in cohort 2. Early antibiotic use (compared with no use) was associated with 2.03 (95% CI 1.18–3.48) and 1.41 (95% CI 0.80–2.51) times the rate of severe RVGE in cohorts 1 and 2, respectively. The cumulative incidence of severe RVGE was low at 6 months of age, suggesting that a 4-week delay in the vaccination schedule may not result in a large number of severe RVGE episodes prior to vaccine receipt.

Norovirus is detected in one in five diarrhoea episodes in children, yet little is known about environmental risk factors associated with this disease, especially in low-income settings. The objective of this study was to examine environmental risk factors, and spatial and seasonal patterns of norovirus diarrhoea episodes in children in León, Nicaragua. We followed a population-based cohort of children under age 5 years for norovirus diarrhoea over a 1-year period. At baseline, characteristics of each household were recorded. Households were geocoded and spatial locations of garbage dumps, rivers, and markets were collected. In bivariate analysis we observed younger children and those with animals in their households were more likely to have experienced norovirus episodes. In adjusted models, younger children remained at higher risk for norovirus episodes, but only modest associations were observed with family and environmental characteristics. We next identified symptomatic children living in the same household and within 500 m buffer zones around the household of another child infected with the same genotype. Norovirus diarrhoea episodes peaked early in the rainy season. These findings contribute to our understanding of environmental factors and norovirus infection.

A huge gap exists between the production of evidence and its take-up in clinical practice settings. To fill this gap, treatment guidelines, based on explicit assessments of the evidence base, are commonly employed in several fields of medicine, including schizophrenia and related psychotic disorders. It remains unclear, however, whether treatment guidelines have any impact on provider performance and patient outcomes, and how implementation should be conducted to maximise benefit.

Children with sickle cell anaemia (SCA) might carry hospital-associated bacterial lineages due to frequent hospital stays and antibiotic treatments. In this study we compared Staphylococcus aureus from SCA patients (n = 73) and healthy children (n = 143) in a cross-sectional study in Gabon. S. aureus carriage did not differ between children with SCA (n = 34, 46·6%) and controls matched for age, residence and sex (n = 67, 46·9%). Both groups shared similar S. aureus genotypes. This finding points towards a transmission of S. aureus between both groups in the community. We conclude that resistance rates from population-based studies with healthy participants could therefore also be used to guide treatment and prophylaxis of endogenous infections in children with SCA despite a different selection pressure.

Methicillin-resistant Staphylococcus aureus (MRSA) commonly causes infection in hospitalized patients. Resistance is due to the acquisition of mecA gene located on the chromosomal element SCCmec and to date 12 types have been identified. Specific epidemic clones of MRSA have emerged with enhanced ability to spread within and among hospitals and to cross national boundaries. We studied 30 isolates from patients with MRSA infections at two hospitals in Porto Alegre city from April to December, 2008 and determined their SCCmec type by PCR. Representative strains were typed by PFGE. Eighteen (60%) isolates carried SCCmec type III and had PFGE profiles clonally related to the previously characterized Brazilian epidemic clone, and 11 (36·7%) isolates with pulsotypes closely related to the Cordobes/Chilean clone harboured SCCmec type I. To the best of our knowledge, this is the first report of the appearance of Cordobes/Chilean clone involved in nosocomial infection in Brazil.

Strains of Staphylococcus aureus isolated from shrimp were examined for phage pattern and enterotoxin production; 63% of the strains isolated from North Sea shrimp were typable with the International and additional set of phages, as were 38% of the strains isolated from South-East Asian shrimp. Staphylococcal enterotoxin(s) (SE) were produced by 48% and 35% of strains isolated from North Sea and South-East Asian shrimp respectively. Growth and enterotoxin production by S. aureus in shrimp was examined in storage experiments at 22 °C. S. aureus increased by 1–2 log units in 24 h when the organism was only a minor part of the total microflora of shrimp. When S. aureus was an equivalent part of the total flora its numbers increased by 3–4 log units in 24 h. Enterotoxins A and B became detectable when the number of S. aureus exceeded 107 per g in aseptically peeled shrimp. Results indicate that S. aureus is able to produce enterotoxin in shrimp, but its production depends upon a number of factors, including the relationship between S. aureus and competitive micro-organisms. It is concluded that the presence of S. aureus on commercially produced shrimp represents a potential hazard to health.