Graft Risk Index After Liver Transplant: Internal and External Validation of a New Spanish Indicator

OBJECTIVES: Scarcity of liver grafts has led to the use of marginal donors, consequently increasing the number of complications posttransplant. To prevent this situation, several indicators have been developed. However, important differences remain among countries. Here, we compared an early-risk liver transplant indicator based on the Spanish Liver Transplant Registry, called the Graft Risk Index, versus the US donor risk index and the Eurotransplant donor risk index. MATERIALS AND METHODS: The new indicator was based on prospectively collected data from 600 adult liver transplants performed in our center. We considered 2 events to compare the indexes: graft survival and rejection-free graft survival, with Cox proportional regression for analyses. Power to predict graft survival was evaluated by calculating the receiver operating characteristic area under the curve. RESULTS: We found no differences between the US and Eurotransplant donor risk indexes in prediction of patients with and without early graft failure. With regard to early survival, only the Graft Risk Index allowed better survival discrimination, in which survival progressively decreased with values = 3 (with probability of graft survival at 1 month of 68%; 95% confidence interval, 46.2-82.5). This increase in risk was significant compared with the standard group (hazard ratio of 10.15; 95% confidence interval, C 3.91- 26.32; P < .001). We calculated powers of prediction of 0.52 (95% confidence interval, 0.43-0.62), 0.54 (95% confidence interval, 0.45-0.65), and 0.69 (95% confidence interval, 0.61-0.77) for donor risk index, Eurotransplant donor risk index, and early Graft Risk Index, respectively. CONCLUSIONS: Neither the US donor risk index nor the Eurotransplant donor risk index was valid for our Spanish liver donation and transplant program. Therefore, an indicator to predict posttransplant graft survival that is adapted to our environment is necessary. This national Graft Risk Index can be a useful tool to optimize donor-recipient matchin

Long daytime napping is associated with increased adiposity and type 2 diabetes in an elderly population with metabolic syndrome

Research examining associations between objectively-measured napping time and type 2 diabetes (T2D) is lacking. This study aimed to evaluate daytime napping in relation to T2D and adiposity measures in elderly individuals from the Mediterranean region. A cross-sectional analysis of baseline data from 2190 elderly participants with overweight/obesity and metabolic syndrome, in the PREDIMED-Plus trial, was carried out. Accelerometer-derived napping was measured. Prevalence ratios (PR) and 95% confidence intervals (CI) for T2D were obtained using multivariable-adjusted Cox regression with constant time. Linear regression models were fitted to examine associations of napping with body mass index (BMI) and waist circumference (WC). Participants napping ≥90 min had a higher prevalence of T2D (PR 1.37 (1.06, 1.78)) compared with those napping 5 to <30 min per day. Significant positive associations with BMI and WC were found in those participants napping ≥30 min as compared to those napping 5 to <30 min per day. The findings of this study suggest that longer daytime napping is associated with higher T2D prevalence and greater adiposity measures in an elderly Spanish population at high cardiovascular risk

Influence of Winter North Atlantic Oscillation (NAO) on climate and snow accumulation in the Mediterranean mountains

This chapter shows the influence of the North Atlantic Oscillation (NAO) on droughts in the entire Mediterranean region between 1901 and 2006. The analysis has been based on identification of positive and negative NAO winters and also detection of the anomalies of drought severity by means of the Standardized Precipitation Evapotranspiration Index (SPEI). The analysis is focussed on the winter NAO. Nevertheless, given that the SPEI drought indicator can be obtained at different time-scales, the study shows how the effects of the winter NAO on droughts are propagated for the following months when long time scales are considered. In general, during the positive phases, the negative SPEI averages are recorded in Southern Europe (the Iberian Peninsula, Italy and the Balkans), areas of Turkey and northwest Africa. On the contrary, the SPEI averages are found positive in northeast Africa. The opposite configuration, but with some differences in the spatial patterns and the magnitude of the SPEI averages, is found during the negative NAO years. The findings of this study should be of great applicability in terms of developing early warning systems. The established relationships between NAO phases and drought indices seem appropriate for drought prediction over large areas of the Mediterranean basin

New immature hominin fossil from European Lower Pleistocene shows the earliest evidence of a modern human dental development pattern

Here we present data concerning the pattern of dental development derived from the microcomputed tomography (microCT) study of a recently discovered immature hominin mandible with a mixed dentition recovered from the TD6 level of the Gran Dolina Lower Pleistocene cave site in Sierra de Atapuerca, northern Spain. These data confirm our previous results that nearly 1 million years ago at least one European hominin species had a fully modern pattern of dental development with a clear slowdown in the development of the molar field regarding the anterior dental field. Furthermore, using available information about enamel formation times and root extension rates in chimpanzees, early hominins, and modern humans, we have estimated that the formation time of the upper and lower first molars of individual 5 (H5) from TD6, which had just erupted at the time of the death of this individual, ranges between 5.3 and 6.6 y. Therefore, the eruption time of the first permanent molars (M1) in the TD6 hominins was within the range of variation of modern human populations. Because the time of M1 eruption in primates is a robust marker of life history, we suggest, as a working hypothesis, that these hominins had a prolonged childhood in the range of the variation of modern humans. If this hypothesis is true, it implies that the appearance in Homo of this important developmental biological feature and an associated increase in brain size preceded the development of the neocortical areas leading to the cognitive capabilities that are thought to be exclusive to Homo sapiens

A toolbox of machine learning software to support microbiome analysis

The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This rapid development with a constant need for new developments and integration of new features require efforts into compile, catalog and classify these tools to create infrastructures and services with easy, transparent, and trustable standards. Here we review the state-of-the-art for ML tools applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on ML based software and framework resources currently available for the analysis of microbiome data in humans. The aim is to support microbiologists and biomedical scientists to go deeper into specialized resources that integrate ML techniques and facilitate future benchmarking to create standards for the analysis of microbiome data. The software resources are organized based on the type of analysis they were developed for and the ML techniques they implement. A description of each software with examples of usage is provided including comments about pitfalls and lacks in the usage of software based on ML methods in relation to microbiome data that need to be considered by developers and users. This review represents an extensive compilation to date, offering valuable insights and guidance for researchers interested in leveraging ML approaches for microbiome analysis

Measurements of triple-differential cross sections for inclusive isolated-photon+jet events in pp collisions at root s=8 TeV

Measurements are presented of the triple-differential cross section for inclusive isolated-photon+jet events in pp collisions at root s = 8 TeV as a function of photon transverse momentum (p(T)(gamma)), photon pseudorapidity (eta(gamma)), and jet pseudorapidity (eta(jet)). The data correspond to an integrated luminosity of 19.7 fb(-1) that probe a broad range of the available phase space, for vertical bar eta(gamma)vertical bar 25 GeV. The measurements are compared to next-to-leading order perturbative quantum chromodynamics calculations, which reproduce the data within uncertainties.Peer reviewe

Associations between dietary polyphenols and type 2 diabetes in a cross-sectional analysis of the PREDIMED-plus trial: Role of body mass index and sex

Overweight and obesity are important risk factors for type 2 diabetes (T2D). Moving towards healthier diets, namely, diets rich in bioactive compounds, could decrease the odds of suffering T2D. However, those individuals with high body mass index (BMI) may have altered absorption or metabolism of some nutrients and dietary components, including polyphenols. Therefore, we aimed to assess whether high intakes of some classes of polyphenols are associated with T2D in a population with metabolic syndrome and how these associations depend on BMI and sex. This baseline cross-sectional analysis includes 6633 participants from the PREDIMED-Plus trial. Polyphenol intakes were calculated from food frequency questionnaires (FFQ). Cox regression models with constant time at risk and robust variance estimators were used to estimate the prevalence ratios (PRs) for polyphenol intake and T2D prevalence using the lowest quartile as the reference group. Analyses were stratified by sex and BMI groups (overweight and obese) to evaluate potential effect modification. Catechins, proanthocyanidins, hydroxybenzoic acids, and lignans were inversely associated with T2D. Hydroxycinnamic acids were directly related in men. These associations were different depending on sex and BMI, that is, women and overweight obtained stronger inverse association