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Background\udNeonatal sepsis is a primary cause of neonatal mortality and is an urgent global health concern, especially within low-income and middle-income countries (LMICs), where 99% of global neonatal mortality occurs. The aims of this study were to determine the incidence and associations with neonatal sepsis and all-cause mortality in facility-born neonates in LMICs.\udMethods\udThe Burden of Antibiotic Resistance in Neonates from Developing Societies (BARNARDS) study recruited mothers and their neonates into a prospective observational cohort study across 12 clinical sites from Bangladesh, Ethiopia, India, Pakistan, Nigeria, Rwanda, and South Africa. Data for sepsis-associated factors in the four domains of health care, maternal, birth and neonatal, and living environment were collected for all mothers and neonates enrolled. Primary outcomes were clinically suspected sepsis, laboratory-confirmed sepsis, and all-cause mortality in neonates during the first 60 days of life. Incidence proportion of livebirths for clinically suspected sepsis and laboratory-confirmed sepsis and incidence rate per 1000 neonate-days for all-cause mortality were calculated. Modified Poisson regression was used to investigate factors associated with neonatal sepsis and parametric survival models for factors associated with all-cause mortality.\udFindings\udBetween Nov 12, 2015 and Feb 1, 2018, 29 483 mothers and 30 557 neonates were enrolled. The incidence of clinically suspected sepsis was 166·0 (95% CI 97·69–234·24) per 1000 livebirths, laboratory-confirmed sepsis was 46·9 (19·04–74·79) per 1000 livebirths, and all-cause mortality was 0·83 (0·37–2·00) per 1000 neonate-days. Maternal hypertension, previous maternal hospitalisation within 12 months, average or higher monthly household income, ward size (>11 beds), ward type (neonatal), living in a rural environment, preterm birth, perinatal asphyxia, and multiple births were associated with an increased risk of clinically suspected sepsis, laboratory-confirmed sepsis, and all-cause mortality. The majority (881 [72·5%] of 1215) of laboratory-confirmed sepsis cases occurred within the first 3 days of life.\udInterpretation\udFindings from this study highlight the substantial proportion of neonates who develop neonatal sepsis, and the high mortality rates among neonates with sepsis in LMICs. More efficient and effective identification of neonatal sepsis is needed to target interventions to reduce its incidence and subsequent mortality in LMICs.\udFunding\udBill & Melinda Gates Foundation.

Antimicrobial resistance in neonatal sepsis is rising, yet mechanisms of resistance that often spread between species via mobile genetic elements, ultimately limiting treatments in low- and middle-income countries (LMICs), are poorly characterized. The Burden of Antibiotic Resistance in Neonates from Developing Societies (BARNARDS) network was initiated to characterize the cause and burden of antimicrobial resistance in neonatal sepsis for seven LMICs in Africa and South Asia. A total of 36,285 neonates were enrolled in the BARNARDS study between November 2015 and December 2017, of whom 2,483 were diagnosed with culture-confirmed sepsis. Klebsiella pneumoniae (n = 258) was the main cause of neonatal sepsis, with Serratia marcescens (n = 151), Klebsiella michiganensis (n = 117), Escherichia coli (n = 75) and Enterobacter cloacae complex (n = 57) also detected. We present whole-genome sequencing, antimicrobial susceptibility and clinical data for 916 out of 1,038 neonatal sepsis isolates (97 isolates were not recovered from initial isolation at local sites). Enterobacterales (K. pneumoniae, E. coli and E. cloacae) harboured multiple cephalosporin and carbapenem resistance genes. All isolated pathogens were resistant to multiple antibiotic classes, including those used to treat neonatal sepsis. Intraspecies diversity of K. pneumoniae and E. coli indicated that multiple antibiotic-resistant lineages cause neonatal sepsis. Our results will underpin research towards better treatments for neonatal sepsis in LMICs., Genomic and clinical analysis of 916 bacterial isolates from neonates with sepsis in seven low- and middle-income countries (the BARNARDS study) reveals that the main species present were antimicrobial-resistant Klebsiella, Escherichia coli and Enterobacter.

Candida albicans typically resides in the human gastrointestinal tract and mucosal membranes as a commensal organism. To adapt and cope with the host immune system, it has evolved a variety of mechanisms of adaptation such as stress-induced mutagenesis and epigenetic regulation. Niche-specific patterns of gene expression also allow the fungus to fine-tune its response to specific microenvironments in the host and switch from harmless commensal to invasive pathogen. Proteome plasticity produced by CUG ambiguity, on the other hand is emerging as a new layer of complexity in C. albicans adaptation, pathogenesis, and drug resistance. Such proteome plasticity is the result of a genetic code alteration where the leucine CUG codon is translated mainly as serine (97%), but maintains some level of leucine (3%) assignment. In this review, we dissect the link between C. albicans non-standard CUG translation, proteome plasticity, host adaptation and pathogenesis. We discuss published work showing how this pathogen uses the fidelity of protein synthesis to spawn novel virulence traits., Candida albicans uses the fidelity of protein synthesis to spawn novel virulence traits.

Introduction Newborn sepsis accounts for more than a third of neonatal deaths globally and one in five neonatal deaths in Ethiopia. The first-line treatment recommended by WHO is the combination of gentamicin with ampicillin or benzylpenicillin. Gram-negative bacteria (GNB) are increasingly resistant to previously effective antibiotics. Objectives Our goal was to estimate the prevalence of antibiotic-resistant gram-negative bacteremia and identify risk factors for antibiotic resistance, among newborns with GNB sepsis. Methods At a tertiary hospital in Ethiopia, we enrolled a cohort pregnant women and their newborns, between March and December 2017. Newborns who were followed up until 60 days of life for clinical signs of sepsis. Among the newborns with clinical signs of sepsis, blood samples were cultured; bacterial species were identified and tested for antibiotic susceptibility. We described the prevalence of antibiotic resistance, identified newborn, maternal, and environmental factors associated with multidrug resistance (MDR), and combined resistance to ampicillin and gentamicin (AmpGen), using multivariable regression. Results Of the 119 newborns with gram-negative bacteremia, 80 (67%) were born preterm and 82 (70%) had early-onset sepsis. The most prevalent gram-negative species were Klebsiella pneumoniae 94 (79%) followed by Escherichia coli 10 (8%). Ampicillin resistance was found in 113 cases (95%), cefotaxime 104 (87%), gentamicin 101 (85%), AmpGen 101 (85%), piperacillin-tazobactam 47 (39%), amikacin 10 (8.4%), and Imipenem 1 (0.8%). Prevalence of MDR was 88% (n = 105). Low birthweight and late-onset sepsis (LOS) were associated with higher risks of AmpGen-resistant infections. All-cause mortality was higher among newborns treated with ineffective antibiotics. Conclusion There was significant resistance to current first-line antibiotics and cephalosporins. Additional data are needed from primary care and community settings. Amikacin and piperacillin-tazobactam had lower rates of resistance; however, context-specific assessments of their potential adverse effects, their local availability, and cost-effectiveness would be necessary before selecting a new first-line regimen to help guide clinical decision-making.

Background Sepsis is a major contributor to neonatal mortality, particularly in low-income and middle-income countries (LMICs). WHO advocates ampicillin–gentamicin as first-line therapy for the management of neonatal sepsis. In the BARNARDS observational cohort study of neonatal sepsis and antimicrobial resistance in LMICs, common sepsis pathogens were characterised via whole genome sequencing (WGS) and antimicrobial resistance profiles. In this substudy of BARNARDS, we aimed to assess the use and efficacy of empirical antibiotic therapies commonly used in LMICs for neonatal sepsis. Methods In BARNARDS, consenting mother–neonates aged 0–60 days dyads were enrolled on delivery or neonatal presentation with suspected sepsis at 12 BARNARDS clinical sites in Bangladesh, Ethiopia, India, Pakistan, Nigeria, Rwanda, and South Africa. Stillborn babies were excluded from the study. Blood samples were collected from neonates presenting with clinical signs of sepsis, and WGS and minimum inhibitory concentrations for antibiotic treatment were determined for bacterial isolates from culture-confirmed sepsis. Neonatal outcome data were collected following enrolment until 60 days of life. Antibiotic usage and neonatal outcome data were assessed. Survival analyses were adjusted to take into account potential clinical confounding variables related to the birth and pathogen. Additionally, resistance profiles, pharmacokinetic–pharmacodynamic probability of target attainment, and frequency of resistance (ie, resistance defined by in-vitro growth of isolates when challenged by antibiotics) were assessed. Questionnaires on health structures and antibiotic costs evaluated accessibility and affordability. Findings Between Nov 12, 2015, and Feb 1, 2018, 36 285 neonates were enrolled into the main BARNARDS study, of whom 9874 had clinically diagnosed sepsis and 5749 had available antibiotic data. The four most commonly prescribed antibiotic combinations given to 4451 neonates (77·42%) of 5749 were ampicillin–gentamicin, ceftazidime–amikacin, piperacillin–tazobactam–amikacin, and amoxicillin clavulanate–amikacin. This dataset assessed 476 prescriptions for 442 neonates treated with one of these antibiotic combinations with WGS data (all BARNARDS countries were represented in this subset except India). Multiple pathogens were isolated, totalling 457 isolates. Reported mortality was lower for neonates treated with ceftazidime–amikacin than for neonates treated with ampicillin–gentamicin (hazard ratio [adjusted for clinical variables considered potential confounders to outcomes] 0·32, 95% CI 0·14–0·72; p=0·0060). Of 390 Gram-negative isolates, 379 (97·2%) were resistant to ampicillin and 274 (70·3%) were resistant to gentamicin. Susceptibility of Gram-negative isolates to at least one antibiotic in a treatment combination was noted in 111 (28·5%) to ampicillin–gentamicin; 286 (73·3%) to amoxicillin clavulanate–amikacin; 301 (77·2%) to ceftazidime–amikacin; and 312 (80·0%) to piperacillin–tazobactam–amikacin. A probability of target attainment of 80% or more was noted in 26 neonates (33·7% [SD 0·59]) of 78 with ampicillin–gentamicin; 15 (68·0% [3·84]) of 27 with amoxicillin clavulanate–amikacin; 93 (92·7% [0·24]) of 109 with ceftazidime–amikacin; and 70 (85·3% [0·47]) of 76 with piperacillin–tazobactam–amikacin. However, antibiotic and country effects could not be distinguished. Frequency of resistance was recorded most frequently with fosfomycin (in 78 isolates [68·4%] of 114), followed by colistin (55 isolates [57·3%] of 96), and gentamicin (62 isolates [53·0%] of 117). Sites in six of the seven countries (excluding South Africa) stated that the cost of antibiotics would influence treatment of neonatal sepsis. Interpretation Our data raise questions about the empirical use of combined ampicillin–gentamicin for neonatal sepsis in LMICs because of its high resistance and high rates of frequency of resistance and low probability of target attainment. Accessibility and affordability need to be considered when advocating antibiotic treatments with variance in economic health structures across LMICs. Funding The Bill & Melinda Gates Foundation.

Ana C. Pereira acknowledges Agencia Regional para o Desenvolvimento da Investigacao Tecnologia e Inovacao (ARDITI) for financial support through her grant, M1420-09-5369-FSE- 000001.

Background\ud Low-income and middle-income countries (LMICs) are under-represented in reports on the burden of antimicrobial resistance. We aimed to quantify the clinical effect of carbapenem resistance on mortality and length of hospital stay among inpatients in LMICs with a bloodstream infection due to Enterobacteriaceae.\ud \ud Methods\ud The PANORAMA study was a multinational prospective cohort study at tertiary hospitals in Bangladesh, Colombia, Egypt, Ghana, India, Lebanon, Nepal, Nigeria, Pakistan, and Vietnam, recruiting consecutively diagnosed patients with carbapenem-susceptible Enterobacteriaceae (CSE) and carbapenem-resistant Entero-bacteriaceae (CRE) bloodstream infections. We excluded patients who had previously been enrolled in the study and those not treated with curative intent at the time of bloodstream infection onset. There were no age restrictions. Central laboratories in India and the UK did confirmatory testing and molecular characterisation, including strain typing. We applied proportional subdistribution hazard models with inverse probability weighting to estimate the effect of carbapenem resistance on probability of discharge alive and in-hospital death, and multistate modelling for excess length of stay in hospital. All patients were included in the analysis.\ud \ud Findings\ud Between Aug 1, 2014, and June 30, 2015, we recruited 297 patients from 16 sites in ten countries: 174 with CSE bloodstream infection and 123 with CRE bloodstream infection. Median age was 46 years (IQR 15–61). Crude mortality was 20% (35 of 174 patients) for patients with CSE bloodstream infection and 35% (43 of 123 patients) for patients with CRE bloodstream infection. Carbapenem resistance was associated with an increased length of hospital stay (3·7 days, 95% CI 0·3–6·9), increased probability of in-hospital mortality (adjusted subdistribution hazard ratio 1·75, 95% CI 1·04–2·94), and decreased probability of discharge alive (0·61, 0·45–0·83). Multilocus sequence typing showed various clades, with marginal overlap between strains in the CRE and CSE clades.\ud \ud Interpretation\ud Carbapenem resistance is associated with increased length of hospital stay and mortality in patients with bloodstream infections in LMICs. These data will inform global estimates of the burden of antimicrobial resistance and reinforce the need for better strategies to prevent, diagnose, and treat CRE infections in LMICs.

A high resolution atmospheric modelling study was done for a 20-year recent historical period. The dynamic downscaling approach adopted used the Max Planck Institute Earth System Model (MPI-ESM) to drive the WRF running in climate mode. Three online nested domains were used covering part of the North Atlantic and Europe, with a resolution 81 km, and reaching 9 km in the innermost domain which covers the Iberian Peninsula. This paper presents the validation of the WRF configuration, which is based on historic simulations between 1986 and 2005 and observational datasets of near surface temperature and precipitation for the same period. The validation was done in terms of comparison of probability distributions between model results and observations, as daily climatologies, spatially averaged inside subdomains obtained with cluster analysis of the observations, for each of the four seasons. In addition, Taylor diagrams are presented for each of the seasons and subdomains. This validation approach was repeated with the results of a new WRF simulation with the same parameterisations but forced by the ERA-Interim reanalysis. The capacity of the MPI-ESM driven WRF configuration to compare with observations and in a manner similar to the ERA-Interim driven WRF, ensures the capacity of the configuration for climate and climate change studies. Considering the difficulty to simulate extremes in long term simulations, the results showed a comfortable comparison of both models (forced by climate model and reanalysis results) with observations. This provides us confidence on the continuity of using the MPI-ESM driven WRF configuration for climate studies.

In order to study climate change on a regional scale using Earth System Models, it is useful to partition the spatial domain into regions according to their climate changes. The aim of this work is to divide the European domain into regions of similar projected climate changes using a simulation of daily total precipitation, minimum and maximum temperatures for the recent-past (1986–2005) and long-term future (2081–2100) provided by the Coupled Model Intercomparison Project (CMIP5). The difference between the long-term future and recent-past daily climatologies of these three variables is determined. Aiming to objectively identify the grid points with coherent climate changes, a K -Mean Cluster Analysis is applied to these differences. This method is performed for each variable independently (univariate version) and for the aggregation of the three variables (multivariate version). A mathematical approach to determine the optimal number of clusters is pursued. However, due to the method characteristics, a sensitivity test to the number of clusters is performed by analysing the consistency of the results. This is a novel method, allowing for the determination of regions based on the climate change of multiple variables. Results from the univariate application of this method are in accordance with results found in the literature, showing overall similar regions of changes. The regions obtained for the multivariate version are mainly defined by latitude over European land, with some features of land-sea interaction. Furthermore, all regions have statistically different distributions of at least one of the variables, providing confidence to the regions obtained.

Climate change and extreme climate events have a significant impact on societies and ecosystems. As a result, climate change projections, especially related with extreme temperature events, have gained increasing importance due to their impacts on the well-being of the population and ecosystems. However, most studies in the field are based on coarse global climate models (GCMs). In this study, we perform a high resolution downscaling simulation to evaluate recent trends of extreme temperature indices. The model used was Weather Research and Forecast (WRF) forced by MPI-ESM-LR, which has been shown to be one of the more robust models to simulate European climate. The domain used in the simulations includes the Iberian Peninsula and the simulation covers the 1986–2005 period (i.e. recent past). In order to study extreme temperature events, trends were computed using the Theil-Sen method for a set of temperature indexes defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this, daily values of minimum and maximum temperatures were used. The trends of the indexes were computed for annual and seasonal values and the Mann-Kendall Trend test was used to evaluate their statistical significance. In order to validate the results, a second simulation, in which WRF was forced by ERA-Interim, was performed. The results suggest an increase in the number of warm days and warm nights, especially during summer and negative trends for cold nights and cold days for the summer and spring. For the winter, contrary to the expected, the results suggest an increase in cold days and cold nights (warming hiatus). This behavior is supported by the WRF simulation forced by ERA-Interim for the autumn days, pointing to an extension of the warming hiatus phenomenon to the remaining seasons. These results should be used with caution since the period used to calculate the trends may not be long enough for this purpose. However, the general sign of trends are similar for both simulations despite some differences in their magnitudes.

Spatial and temporal distributions of the trends of extreme precipitation indices were analysed between 1986 and 2005, over the Iberian Peninsula (IP). The knowledge of the patterns of extreme precipitation is important for impacts assessment, development of adaptation and mitigation strategies. As such, there is a growing need for a more detailed knowledge of precipitation climate change. This analysis was performed for Portuguese and Spanish observational datasets and results performed by the Weather Research and Forecast (WRF) model forced by the ERA-Interim reanalysis. Extreme precipitation indices recommended by the Expert Team for Climate Change Detection Monitoring and Indices were computed, by year and season. Then, annual and seasonal trends of the indices were estimated by Theil-Sen method and their significance was tested by the Mann-Kendal test. Additionally, a second simulation forced by the Max Planck Institute Earth System Model (MPI-ESM), was considered. This second modelling configuration was created in order to assess its performance when simulating extremes of precipitation. The annual trends estimated for the 1986–2005, from the observational datasets and from the ERA-driven simulation reveal: 1) negative statistically significant trends of the CWD index in the Galicia and in the centre of the IP; 2) positive statistically significant trends of the CDD index over the south of the IP and negative statistically significant trends in Galicia, north and centre of Portugal; 3) positive statistically significant trends of the R75p index in some regions of the north of the IP; 4) positive statistically significant trends in the R95pTOT index in the Central Mountains Chain, Leon Mountains and in the north of Portugal. Seasonally, negative statistically significant trends of the CWD index were found in Galicia, in winter and in the south of the IP, in summer. Positive statistically significant trends of the CWD index were identified in the Leon Mountains, in spring, and in Galicia, in autumn. For the CDD index, negative statistically significant trends were seen in Valencia, in the spring, and, in Galicia and Portugal (north and centre), in summer. Positive statistically significant trends of the CDD index were found: in the east of the IP, in the winter; in the Cantabrian Mountain, in the spring; and, in the south of the IP, in summer. Regarding to the R75p index, negative statistically significant trends were found in Galicia, in winter and positive statistically significant trends in the north of Portugal, in spring and in the Central Mountains Chain and north of Portugal, in autumn. For the R95pTOT index, negative statistically significant trends were found over the Sierra Cuenca and Sierra Cazorla, in winter and positive statistically significant trends were found over the Sierra Cebollera, in winter and in Castile-la Mancha region, in spring. The results of the annual and seasonal trends of the extreme precipitation indices performed for observational datasets and the simulation forced by ERA-Interim, are similar. The results obtained for the simulation forced by MPI-ESM are not satisfactory, and can be a source of criticism for the use of simulation forced by MPI-ESM in this type of climate change studies. Even for the relatively short period used, the WRF model, when properly forced is a useful tool due to the similar results of Portuguese and Spanish observational datasets and the simulation forced by ERA-Interim.

Blueberries have a well-deserved reputation as a potential functional food, supported by studies which have identified and quantified various nutrients and bioactive phytochemicals with known benefits for human diet and health. Wild blueberries have attracted particular attention due to the levels and concentrations of those phytonutrients. This study aims to evaluate for the first time the chemical composition of Madeira Island's endemic Vaccinium padifolium Sm wild berry. Results show that this fruit contains high values of total soluble phenolic content (around 4 g GAE kgThis study is in line with the efforts of the scientific community to identify new sources of phytonutrients that are beneficial to human health, characterizing the wild Madeira blueberry in terms of phytonutrients that suggest there may be health benefits associated with its consumption. The findings of this research are very important for both the commercial and agricultural sectors that produce this fruit, and for consumers who seek phytonutrient-rich foods.

The polymixin colistin is a “last line” antibiotic against extensively-resistant Gram-negative bacteria. Recently, the mcr-1 gene was identified as a plasmid-mediated resistance mechanism in human and animal Enterobacteriaceae, with a wide geographical distribution and many producer strains resistant to multiple other antibiotics. mcr-1 encodes a membrane-bound enzyme catalysing phosphoethanolamine transfer onto bacterial lipid A. Here we present crystal structures revealing the MCR-1 periplasmic, catalytic domain to be a zinc metalloprotein with an alkaline phosphatase/sulphatase fold containing three disulphide bonds. One structure captures a phosphorylated form representing the first intermediate in the transfer reaction. Mutation of residues implicated in zinc or phosphoethanolamine binding, or catalytic activity, restores colistin susceptibility of recombinant E. coli. Zinc deprivation reduces colistin MICs in MCR-1-producing laboratory, environmental, animal and human E. coli. Conversely, over-expression of the disulphide isomerase DsbA increases the colistin MIC of laboratory E. coli. Preliminary density functional theory calculations on cluster models suggest a single zinc ion may be sufficient to support phosphoethanolamine transfer. These data demonstrate the importance of zinc and disulphide bonds to MCR-1 activity, suggest that assays under zinc-limiting conditions represent a route to phenotypic identification of MCR-1 producing E. coli, and identify key features of the likely catalytic mechanism.

The advances in satellite technology in recent years have made feasible the acquisition of high-resolution information on the Earth's surface. Examples of such information include elevation and land use, which have become more detailed. Including this information in numerical atmospheric models can improve their results in simulating lower boundary forced events, by providing detailed information on their characteristics. Consequently, this work aims to study the sensitivity of the weather research and forecast (WRF) model to different topography as well as land-use simulations in an extreme precipitation event. The test case focused on a topographically driven precipitation event over the island of Madeira, which triggered flash floods and mudslides in the southern parts of the island. Difference fields between simulations were computed, showing that the change in the data sets produced statistically significant changes to the flow, the planetary boundary layer structure and precipitation patterns. Moreover, model results show an improvement in model skill in the windward region for precipitation and in the leeward region for wind, in spite of the non-significant enhancement in the overall results with higher-resolution data sets of topography and land use.

This study aimed to determine if aerobic fitness assessed by 6MWD is able to predict resting cardiovascular function and cardiovascular disease risk factors (CVDRF). One hundred and five old individuals were analyzed: aerobic fitness (6MWD), body composition (DXA), blood pressure (BP), resting heart rate (HRrest) and rate-pressure product (RPPrest) were evaluated. Pearson correlation analysis was used to assess the relationship between 6MWD, resting cardiovascular function and CVDRF. To examine the shared variance between 6MWD, cardiac function, and CVDRF, linear regression analyses were employed. Inverse associations were observed between 6MWD and age (r=-0.405; p0.001), percent body fat (%BF) (r=-0.472; p0.001), trunk fat (r=-0.234; p=0.020), systolic blood pressure (SBP) (r=-0.307; p=0.002), HRrest (r=-0.248; p=0.013), and RPPrest (r=-0.400; p0.001). In simple linear regressions, except the diastolic blood pressure (DBP), the 6MWD correlated (0.001≥p≤0.020) with all investigated parameters. When models were adjusted (for age and sex), the 6MWD remained associated with %BF (p0.001), SBP (0.002≥p≤0.009) and RPPrest (0.001≥p≤0.002). Our study reinforces the idea that a worse cardiovascular profile is related with lower fitness. Furthermore, it supports the potential of 6MWD to identify adverse outcomes such as %BF, increased SBP and higher RPPrest in older adults.

The bla NDM-1 gene is associated with extensive drug resistance in Gram-negative bacteria. This probably spread to Enterobacteriaceae from Acinetobacter spp., and we characterized plasmids associated with bla NDM-1 in Acinetobacter spp. to gain insight into their role in this dissemination. Four clinical NDM-1-producing Acinetobacter species strains from India and Pakistan were investigated. A plasmid harboring bla NDM-1 , pNDM-40-1, was characterized by whole-genome sequencing of Acinetobacter bereziniae CHI-40-1 and comparison with related plasmids. The presence of similar plasmids in strains from Pakistan was sought by PCR and sequencing of amplicons. Conjugation frequency was tested and stability of pNDM-40-1 investigated by real-time PCR of isolates passaged with and without antimicrobial selection pressure. A. bereziniae and Acinetobacter haemolyticus strains contained plasmids similar to the pNDM-BJ01-like plasmids identified in Acinetobacter spp. in China. The backbone of pNDM-40-1 was almost identical to that of pNDM-BJ01-like plasmids, but the transposon harboring bla NDM-1 , Tn 125 , contained two short deletions. Escherichia coli and Acinetobacter pittii transconjugants were readily obtained. Transconjugants retained pNDM-40-1 after a 14-day passage experiment, although stability was greater with meropenem selection. Fragments of pNDM-BJ01-like plasmid backbones are found near bla NDM-1 in some genetic contexts from Enterobacteriaceae , suggesting that cross-genus transfer has occurred. pNDM-BJ01-like plasmids have been described in isolates originating from a wide geographical region in southern Asia. In vitro data on plasmid transfer and stability suggest that these plasmids could have contributed to the spread of bla NDM-1 into Enterobacteriaceae .

The present study aims to analyse the evolution of colour and browning of fortified wines submitted to oak and accelerated ageing induced by temperature, both traditional ageing processes of Madeira wines. These wines were followed during the first 2 years of ageing and were simultaneously compared to aged reference samples, in order to disclose if accelerated ageing favours the wine evolution. The data analysis approaches followed two strategies: the first one was based on the monitoring of wine colour parameters based on CIELab methodology, while the second strategy adopted an untargeted approach, taking advantage of all wine information comprised on the UV-vis spectrum. CIELab results indicated that the greatest variation (up to 92 %) occurs during the vinification, since it was observed that wines produced from the same grape variety (Tinta Negra) acquired different characteristics already on the vinification processes. All wines tend to approach the reference samples during ageing, with the lowest ΔE* value obtained for Malvasia submitted to canteiro at 2 years of ageing (3.29 units). Sweet Tinta Negra wines, previously submitted to estufagem, presented the most pronounced colour change associated with ageing. The multivariate principal component analysis (PCA) model was built with aged reference samples to evaluate how young wines acquire the reference wine’s characteristics and revealed that accelerated ageing increases colour evolution and favours the homogeneity of Malvasia wines.

Sexual function, psychosocial status and quality of life (QoL) are important dimensions, often underestimated, in dialysis treatment schedules.The aim of this study was to evaluate the prevalence of sexual dysfunction and its associations, among peritoneal dialysis (PD) patients.The Index of Female Sexual Function (IFSF), the International Index of Erectile Function (IIEF), the Hospital Anxiety and Depression Scale (HADS) and the Quality of Life EQ5D questionnaires were applied to a prevalent PD population of 57 enrolled patients. Multivariate analysis was conducted to investigate clinical independent risk factors for sexual dysfunction.Sexual dysfunction was diagnosed in 67.9% of women and 44.8% of men. In females, serum albumin, creatinine and phosphorus levels and EQ5D positively correlated with IFSF score. For males, there was a significant negative correlation between serum calcium levels and the IIEF score. On multivariate analysis, nutritional parameters remained independently associated with sexual dysfunction in women; in males, increase in calcium concentration and decrease of testosterone were main determinants. On logistic regression analysis, the risk of sexual dysfunction in global population was associated with lower values of albumin (OR=6.94) and with a lower QoL score EQ5D (OR=6.93).Sexual dysfunction is highly prevalent and strongly associated with impaired QoL of PD patients. Different clinical variables were related to sexual dysfunction in each gender, justifying an individualized preventive and therapeutic approaches.

Peritoneal dialysis (PD) patients seem to maintain a better nutrition status than do hemodialysis patients, and some develop overweight. The clinical relevance of overweight in PD is uncertain. We assessed nutrition status and evaluated the prevalence of overweight in PD patients, and we explored the association of overweight with demographic, clinical, and dialysis factors. The study group included 57 patients (31.5% men; 12.3% with diabetes; mean age: 49.5 +/- 14.9 years) on PD for 2.9 +/- 2.7 years. Nutrition status was assessed by subjective global assessment (SGA), body mass index (BMI), and a nutrition status score (NSS) based on biochemical and anthropometric measurements. By SGA, 70.2% of patients were classified as having a normal nutrition status; none had severe malnutrition. Based on the NSS, only 4 patients were identified as mildly-to-moderately malnourished. By BMI, 50.9% of the patients were overweight (BMIor = 25 kg/m2). No relationship was found for BMI or NSS with dialysis time, Kt/V, residual renal function, or peritoneal transport. Similar results were obtained considering only overweight patients. Overweight patients had higher levels of serum albumin (p = 0.014), homocysteine (p = 0.003), and total-to-high-density lipoprotein cholesterol ratio (p = 0.048). Instead of malnutrition, overweight was highly prevalent in our PD patients. Overweight was not associated with demographic- or modality-related factors, nor with fast transport or markers of systemic inflammation.

Preservation of residual renal function (RRF) is an important goal in peritoneal dialysis (PD). The present study explored the factors conditioning RRF decline in a PD population. We studied 148 consecutive patients. Age, sex, diabetes, previous renal replacement therapy time and modality [hemodialysis (HD), renal transplantation (RT), or PD first], peritoneal transport, PD prescription [automated (APD) or continuous ambulatory], and peritonitis were investigated as possible determinants of RRF decline. In 22 patients (15%), PD was started after RT. Residual renal function was not significantly different between patients who started PD as their first option and those who started after RT, either at baseline or after 1 year on PD. Baseline dialysate-to-plasma creatinine was also similar between those groups. Transfer from HD was the single significant predictor of baseline anuria [odds ratio (OR): 6.3; p0.001). After the start of PD, diabetes was the only predictor of anuria (OR: 2.5; p = 0.02). Age, sex, reason for PD, PD after graft failure, peritonitis, use of APD, and fast transport were not predictors of anuria. Despite slow tapering of immunosuppression, peritonitis-free survival was not shortened in patients who started PD after RT. Diabetes was a determinant of the time course of RRF decline in PD. Peritoneal dialysis after RT failure offered short-term RRF protection that was similar to that seen in PD-first patients.