Using sulfur stable isotope ratios (δ34 S) for animal geolocation: Estimating the delay mechanisms between diet ingestion and isotope incorporation in tail hair.

RATIONALE: Metabolism and diet quality play an important role in determining delay mechanisms between an animal ingesting an element and depositing the associated isotope signal in tissue. While many isotope mixing models assume instantaneous reflection of diet in an animal- tissue, this is rarely the case. Here we use data from wildebeest to measure the lag time between ingestion of 34 S and its detection in tail hair. METHODS: We use time-lagged regression analysis of δ34 S data from GPS-collared blue wildebeest from the Serengeti ecosystem in combination with δ34 S isoscape data to estimate the lag time between an animal ingesting and depositing 34 S in tail hair. RESULTS: The best fitting regression model of δ34 S in tail hair and an individual- position on the δ34 S isoscape is generated assuming an average time delay of 78 days between ingestion and detection in tail hair. This suggests that sulfur may undergo multiple metabolic transitions before being deposited in tissue. CONCLUSION: Our findings help to unravel the underlying complexities associated with sulfur metabolism and are broadly consistent with results from other species. These findings will help to inform research aiming to apply the variation of δ34 S in inert biological material for geolocation or understanding dietary changes, especially for fast moving migratory ungulates such as wildebeest.

Nutritional, biochemical, and clinical determinants of hyperuricemia in systemic lupus erythematosus patients: Relationship with clinical and renal disease activity.

Systemic lupus erythematosus (SLE) is the prototypical autoimmune disease considered as an independent risk factor for mortality by cardiovascular disease. Currently, uric acid is described as a novel biomarker associated with cardiometabolic risk. However, nutritional and serum determinants that influence hyperuricemia development in autoimmune diseases have not been fully elucidated. This study aimed to assess the nutritional, biochemical, and cardiometabolic determinants of hyperuricemia and its relationship with clinical variables in SLE patients. A cross-sectional study was conducted in 167 SLE patients and 195 control subjects (CS). Nutrient intake, anthropometry, biochemical, and cardiometabolic indexes were evaluated. In SLE patients, adequate protein (OR = 0.4; p = 0.04) and carbohydrate (OR = 0.2; p = 0.01) intakes were associated with a lower risk of hyperuricemia. SLE patients with hyperuricemia presented a higher risk of clinical (OR = 2.2; p = 0.03) and renal activity (OR = 3.4; p < 0.01), as well as triglycerides ≥150 mg/dL (OR = 3.6; p < 0.01), hs-CRP ≥1 mg/L (OR = 3.1; p < 0.01), Kannel score ≥3 (OR = 2.5; p = 0.02), and BMI ≥25 kg/m2 (OR = 2.2; p = 0.02). Oppositely, serum levels of HDL-C ≥40 mg/dL (OR = 0.2; p < 0.01) were associated with a lower risk of hyperuricemia. According to the pharmacotherapy administered, prednisone treatment was associated with a high risk of hyperuricemia (OR = 4.7; p < 0.001). In contrast, the hydroxychloroquine treatment was associated with a lower risk of hyperuricemia (OR = 0.4; p = 0.02). In conclusion, SLE patients with hyperuricemia presented a high risk of clinical and renal activity as well as worse cardiometabolic status. Notably, an adequate intake of protein, carbohydrates, healthy HDL-C serum levels, and hydroxychloroquine treatment could be determinants of lower risk of hyperuricemia.

Frugivory Specialization in Birds and Fruit Chemistry Structure Mutualistic Networks across the Neotropics.

AbstractThe interaction between fruit chemistry and the physiological traits of frugivores is expected to shape the structure of mutualistic seed dispersal networks, but it has been understudied compared with the role of morphological trait matching in structuring interaction patterns. For instance, highly frugivorous birds (i.e., birds that have fruits as the main component of their diets), which characteristically have fast gut passage times, are expected to avoid feeding on lipid-rich fruits because of the long gut retention times associated with lipid digestion. Here, we compiled data from 84 studies conducted in the Neotropics that used focal plant methods to record 35,815 feeding visits made by 317 bird species (155 genera in 28 families) to 165 plant species (82 genera in 48 families). We investigated the relationship between the degree of frugivory of birds (i.e., how much of their diet is composed of fruit) at the genus level and their visits to plant genera that vary in fruit lipid content. We used a hierarchical modeling of species communities approach that accounted for the effects of differences in body size, bird and plant phylogeny, and spatial location of study sites. We found that birds with a low degree of frugivory (e.g., predominantly insectivores) tend to have the highest increase in visitation rates as fruits become more lipid rich, while birds that are more frugivorous tend to increase visits at a lower rate or even decrease visitation rates as lipids increase in fruits. This balance between degree of frugivory and visitation rates to lipid-poor and lipid-rich fruits provides a mechanism to explain specialized dispersal systems and the occurrence of certain physiological nutritional filters, ultimately helping us to understand community-wide interaction patterns between birds and plants.

Association of BCAT2 and BCKDH polymorphisms with clinical, anthropometric and biochemical parameters in young adults.

BACKGROUND AND AIM: Circulating amino acids are modified by sex, body mass index (BMI) and insulin resistance (IR). However, whether the presence of genetic variants in branched-chain amino acid (BCAA) catabolic enzymes modifies circulating amino acids is still unknown. Thus, we determined the frequency of two genetic variants, one in the branched-chain aminotransferase 2 (BCAT2) gene (rs11548193), and one in the branched-chain ketoacid dehydrogenase (BCKDH) gene (rs45500792), and elucidated their impact on circulating amino acid levels together with clinical, anthropometric and biochemical parameters. METHODS AND RESULTS: We performed a cross-sectional comparative study in which we recruited 1612 young adults (749 women and 863 men) aged 19.7 ± 2.1 years and with a BMI of 24.9 ± 4.7 kg/m2. Participants underwent clinical evaluation and provided blood samples for DNA extraction and biochemical analysis. The single nucleotide polymorphisms (SNPs) were determined by allelic discrimination using real-time polymerase chain reaction (PCR). The frequencies of the less common alleles were 15.2 % for BCAT2 and 9.83 % for BCKDH. The subjects with either the BCAT2 or BCKDH SNPs displayed no differences in the evaluated parameters compared with subjects homozygotes for the most common allele at each SNP. However, subjects with both SNPs had higher body weight, BMI, blood pressure, glucose, and circulating levels of aspartate, isoleucine, methionine, and proline than the subjects homozygotes for the most common allele (P < 0.05, One-way ANOVA). CONCLUSION: Our findings suggest that the joint presence of both the BCAT2 rs11548193 and BCKDH rs45500792 SNPs induces metabolic alterations that are not observed in subjects without either SNP.

Can network metrics predict vulnerability and species roles in bird-dispersed plant communities? Not without behaviour.

Network metrics are widely used to infer the roles of mutualistic animals in plant communities and to predict the effect of species' loss. However, their empirical validation is scarce. Here we parameterized a joint species model of frugivory and seed dispersal with bird movement and foraging data from tropical and temperate communities. With this model, we investigate the effect of frugivore loss on seed rain, and compare our predictions to those of standard coextinction models and network metrics. Topological coextinction models underestimated species loss after the removal of highly linked frugivores with unique foraging behaviours. Network metrics informed about changes in seed rain quantity after frugivore loss. However, changes in seed rain composition were only predicted by partner diversity. Nestedness, closeness, and d' specialisation could not anticipate the effects of rearrangements in plant-frugivore communities following species loss. Accounting for behavioural differences among mutualists is critical to improve predictions from network models.

Running on empty: recharge dynamics from animal movement data.

Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population-level characteristics are tied with individual-level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous-time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion (Puma concolor; in Colorado, USA) and African buffalo (Syncerus caffer; in Kruger National Park, South Africa) recharge dynamics.

The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality.

Globally, agriculture increasingly depends on pollinators to produce many seed and fruit crops. However, what constitutes optimal pollination service for pollinator-dependent crops remains unanswered. We developed a simulation model to identify the optimal pollination service that maximizes fruit quality in crops. The model depicts the pollination (i.e., autonomous self-fertilization, pollen deposition) and post-pollination (i.e., pollen germination, and time from germination to ovule fertilization) processes leading to fruit and seed set and allows for negative flower-pollinator interactions, specifically pistil damage. We parameterized and validated the model based on empirical observations of commercial raspberry in western Argentina. To assess the effects of pollination intensity for fruit production, we conducted simulations over a range of visit number per flower by the two primary managed pollinators worldwide, Apis mellifera and Bombus terrestris. Simulations identified that ~15-35 visits per flower by A. mellifera or ~10-20 visits by B. terrestris provide adequate pollination and maximize raspberry fruit quality (i.e., estimated as the proportion of ovules that develop into drupelets). Visits in excess of these optima reduce simulated fruit quality, and flowers receiving >670 honey bee visits or >470 bumble bee visits would produce fruits of poorer quality than those receiving no bee visits. The simulations generated consistent, unbiased predictions of fruit quality for 12 raspberry fields. This model could be adapted easily to other animal-pollinated crops and used to guide efficient pollinator management in any agro-ecosystem.

Generalist birds promote tropical forest regeneration and increase plant diversity via rare-biased seed dispersal.

Regenerated forests now compose over half of the world's tropical forest cover and are increasingly important as providers of ecosystem services, freshwater, and biodiversity conservation. Much of the value and functionality of regenerating forests depends on the plant diversity they contain. Tropical forest diversity is strongly shaped by mutualistic interactions between plants and fruit-eating animals (frugivores) that disperse seeds. Here we show how seed dispersal by birds can influence the speed and diversity of early successional forests in Puerto Rico. For two years, we monitored the monthly fruit production of bird-dispersed plants on a fragmented landscape, and measured seed dispersal activity of birds and plant establishment in experimental plots located in deforested areas. Two predominantly omnivorous bird species, the Northern Mockingbird (Mimus polyglottos) and the Gray Kingbird (Tyrannus dominicensis), proved critical for speeding up the establishment of woody plants and increasing the species richness and diversity of the seed rain in deforested areas. Seed dispersal by these generalists increased the odds for rare plant species to disperse and establish in experimental forest-regeneration plots. Results indicate that birds that mix fruit and insects in their diets and actively forage across open and forested habitats can play keystone roles in the regeneration of mutualistic plant-animal communities. Furthermore, our analyses reveal that rare-biased (antiapostatic) frugivory and seed dispersal is the mechanism responsible for increasing plant diversity in the early-regenerating community.

Statistical ecology comes of age.

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

Water temperature and microenvironmental factors predict the presence and detection of the snail host of Fasciola hepatica in Andean Patagonia.

The transmission of Fasciola hepatica occurs only where there are -or recently were- aquatic or amphibious snails of the Lymnaeidae family, the intermediate host of this parasite. Direct detection of these snails is time-consuming and imprecise, hindering accurate and detailed mapping of transmission risk. To identify which microenvironmental factors could be used as proxies for the occurrence of the lymnaeid snail Galba viator, a major intermediate host in South America, a total of 183 1-m2 quadrants across diverse water bodies in an endemic area in Andean Patagonia were manually timed-searched for snails and microenvironmental variables were registered. Data was analyzed using a Bayesian hierarchical occupancy model that assessed the effects of the microenvironmental variables on the presence of snails while considering imperfect snail detection. The model estimated that G. viator predominantly inhabits shallow aquatic environments, in the presence of grasses, where snails of the genus Biomphalaria are also detected, and with scarce tree canopy cover. Physical factors affecting occupancy presumably act as proxies for the average water temperature, while the temperature at the time of sampling was found to affect snail detectability. The identified variables are easy, fast, and inexpensive to measure, and can complement management decisions and risk maps based on coarser remote-sensing data, particularly relevant in a context of growing resistance to anthelminthic drugs.

miR-21, miR-221, miR-29 and miR-34 are distinguishable molecular features of a metabolically unhealthy phenotype in young adults.

Discrepancies between the measurement of body mass index (BMI) and metabolic health status have been described for the onset of metabolic diseases. Studying novel biomarkers, some of which are associated with metabolic syndrome, can help us to understand the differences between metabolic health (MetH) and BMI. A group of 1469 young adults with pre-specified anthropometric and blood biochemical parameters were selected. Of these, 80 subjects were included in the downstream analysis that considered their BMI and MetH parameters for selection as follows: norm weight metabolically healthy (MHNW) or metabolically unhealthy (MUNW); overweight/obese metabolically healthy (MHOW) or metabolically unhealthy (MUOW). Our results showed for the first time the differences when the MetH status and the BMI are considered as global MetH statures. First, all the evaluated miRNAs presented a higher expression in the metabolically unhealthy group than the metabolically healthy group. The higher levels of leptin, IL-1b, IL-8, IL-17A, miR-221, miR-21, and miR-29 are directly associated with metabolic unhealthy and OW/OB phenotypes (MUOW group). In contrast, high levels of miR34 were detected only in the MUNW group. We found differences in the SIRT1-PGC1α pathway with increased levels of SIRT1+ cells and diminished mRNA levels of PGCa in the metabolically unhealthy compared to metabolically healthy subjects. Our results demonstrate that even when metabolic diseases are not apparent in young adult populations, MetH and BMI have a distinguishable phenotype print that signals the potential to develop major metabolic diseases.

Negative density dependence characterizes mutualistic interactions between birds and fruiting plants across latitudes.

Negative density dependence (NDD) in biotic interactions of interference such as plant-plant competition, granivory and herbivory are well-documented mechanisms that promote species' coexistence in diverse plant communities worldwide. Here, we investigated the generality of a novel type of NDD mechanism that operates through the mutualistic interactions of frugivory and seed dispersal among fruit-eating birds and plants. By sampling community-wide frugivory interactions at high spatial and temporal resolution in Pennsylvania, Puerto Rico, Peru, Brazil and Argentina, we evaluated whether interaction frequencies between birds and fruit resources occurred more often (selection), as expected, or below expectations (under-utilization) set by the relative fruit abundance of the fruit resources of each plant species. Our models considered the influence of temporal scales of fruit availability and bird phylogeny and diets, revealing that NDD characterizes frugivory across communities. Irrespective of taxa or dietary guild, birds tended to select fruits of plant species that were proportionally rare in their communities, or that became rare following phenological fluctuations, while they mostly under-utilized abundant fruit resources. Our results demonstrate that negative density-dependence in frugivore-plant interactions provides a strong equalizing mechanism for the dispersal processes of fleshy-fruited plant species in temperate and tropical communities, likely contributing to building and sustaining plant diversity. This article is part of the theme issue 'Diversitydependence of dispersal: interspecific interactions determine spatial dynamics'.

Genetic risk score for insulin resistance based on gene variants associated to amino acid metabolism in young adults.

Circulating concentration of arginine, alanine, aspartate, isoleucine, leucine, phenylalanine, proline, tyrosine, taurine and valine are increased in subjects with insulin resistance, which could in part be attributed to the presence of single nucleotide polymorphisms (SNPs) within genes associated with amino acid metabolism. Thus, the aim of this work was to develop a Genetic Risk Score (GRS) for insulin resistance in young adults based on SNPs present in genes related to amino acid metabolism. We performed a cross-sectional study that included 452 subjects over 18 years of age. Anthropometric, clinical, and biochemical parameters were assessed including measurement of serum amino acids by high performance liquid chromatography. Eighteen SNPs were genotyped by allelic discrimination. Of these, ten were found to be in Hardy-Weinberg equilibrium, and only four were used to construct the GRS through multiple linear regression modeling. The GRS was calculated using the number of risk alleles of the SNPs in HGD, PRODH, DLD and SLC7A9 genes. Subjects with high GRS (≥ 0.836) had higher levels of glucose, insulin, homeostatic model assessment- insulin resistance (HOMA-IR), total cholesterol and triglycerides, and lower levels of arginine than subjects with low GRS (p < 0.05). The application of a GRS based on variants within genes associated to amino acid metabolism may be useful for the early identification of subjects at increased risk of insulin resistance.

Where do seeds go when they go far? Distance and directionality of avian seed dispersal in heterogeneous landscapes.

Seed dispersal at large scales strongly influences plant population dynamics. Still, ecologists have rarely measured seed dispersal at relevant scales, and the role of habitat types in affecting seed dispersal at long distances remains unexplored. We studied seed dispersal of Ilex aquifolium and Crataegus monogyna in northern Spain, hypothesizing that seeds would be recovered at higher rates and at longer distances (LDD) at habitats with fleshy-fruited trees, compared to habitats with other tree types or at open habitats. We tracked seeds in eight landscapes by enriching trees with 15N isotopes at the center of landscapes, and then detected 15N-marked seeds by sampling at distances of up to 700 m. We found that seeds arrive in greater densities and at longer distances in habitats with trees, particularly fleshy-fruited types, producing different LDD probabilities for each habitat. Results also show a disproportional arrival of seeds in habitats similar to those of mother plants, which should affect seed establishment and the genetic diversity of plant neighborhoods. Findings reveal the strong dependence of seed dispersal on the existing templates that guide the movements of avian dispersers in heterogeneous landscapes and also suggest that LDD above tree lines and beyond hard habitat edges can be difficult.

Inferring the interaction rules of complex systems with graph neural networks and approximate Bayesian computation.

Inferring the underlying processes that drive collective behaviour in biological and social systems is a significant statistical and computational challenge. While simulation models have been successful in qualitatively capturing many of the phenomena observed in these systems in a variety of domains, formally fitting these models to data remains intractable. Recently, approximate Bayesian computation (ABC) has been shown to be an effective approach to inference if the likelihood function for a model is unavailable. However, a key difficulty in successfully implementing ABC lies with the design, selection and weighting of appropriate summary statistics, a challenge that is especially acute when modelling high dimensional complex systems. In this work, we combine a Gaussian process accelerated ABC method with the automatic learning of summary statistics via graph neural networks. Our approach bypasses the need to design a model-specific set of summary statistics for inference. Instead, we encode relational inductive biases into a neural network using a graph embedding and then extract summary statistics automatically from simulation data. To evaluate our framework, we use a model of collective animal movement as a test bed and compare our method to a standard summary statistics approach and a linear regression-based algorithm.

Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions.

We discuss hidden Markov-type models for fitting a variety of multistate random walks to wildlife movement data. Discrete-time hidden Markov models (HMMs) achieve considerable computational gains by focusing on observations that are regularly spaced in time, and for which the measurement error is negligible. These conditions are often met, in particular for data related to terrestrial animals, so that a likelihood-based HMM approach is feasible. We describe a number of extensions of HMMs for animal movement modeling, including more flexible state transition models and individual random effects (fitted in a non-Bayesian framework). In particular we consider so-called hidden semi-Markov models, which may substantially improve the goodness of fit and provide important insights into the behavioral state switching dynamics. To showcase the expediency of these methods, we consider an application of a hierarchical hidden semi-Markov model to multiple bison movement paths.

Integration of mark-recapture and acoustic detections for unbiased population estimation in animal communities.

Abundance estimation methods that combine several types of data are becoming increasingly common because they yield more accurate and precise parameter estimates and predictions than are possible from a single data source. These beneficial effects result from increasing sample size (through data pooling) and complementarity between different data types. Here, we test whether integrating mark-recapture data with passive acoustic detections into a joint likelihood improves estimates of population size in a multi-guild community. We compared the integrated model to a mark-recapture-only model using simulated data first and then using a data set of mist-net captures and acoustic recordings from an Afrotropical agroforest bird community. The integrated model with simulated data improved accuracy and precision of estimated population size and detection parameters. When applied to field data, the integrated model was able to produce, for each bird guild, ecologically plausible estimates of population size and detection parameters, with more precision compared with the mark-recapture model. Overall, our results show that adding acoustic data to mark-recapture analyses improves estimates of population size. With the increasing availability of acoustic recording devices, this data collection technique could readily be added to routine field protocols, leading to a cost-efficient improvement of traditional mark-recapture population estimation.

A preliminary study on health impacts of Mexican mercury mining workers in a context of precarious employment.

Mercury mining is one of the main sources of mercury (Hg) release into the environment, causing serious impacts on human health and the environment. Workers in these mines are employed informally and precariously and therefore lack labor rights such as social security. The objective of the study is to make visible the exposure to environmental contaminants and the health of workers in mercury mines. An environmental assessment was conducted to determine workers' exposure to contaminants; urine samples were obtained to measure exposure to mercury and arsenic, and blood samples were obtained for lead and cadmium. Clinical parameters were also evaluated. Concentrations of Hg, As and Pb were determined in soil, 279.4 mg/kg (24.4-788.5), 14.7 mg/kg (9.5-20.3) and 1.4 mg/kg (1-2.8), respectively. The exposure results for mercury were 551 µg/g creatinine, for arsenic 50 µg/L and for lead 4.7 µg/dL. Cd-B was not found. In addition, 17.6 % of the workers had diabetes and 17.6 % had renal disorders. Principal Component Regression was performed obtaining an r2 of 0.86 for glomerular filtration rate and 0.54 for albumin creatinine ratio using clinical, occupational, and metal exposure variables. Exposure to Hg in this type of mine is not exclusive, so there is a cumulative risk of chronic exposure to different environmental pollutants directly impacting the health of workers. It is necessary to implement health strategies and different work opportunities for these workers.

Stability of pollination services decreases with isolation from natural areas despite honey bee visits.

Sustainable agricultural landscapes by definition provide high magnitude and stability of ecosystem services, biodiversity and crop productivity. However, few studies have considered landscape effects on the stability of ecosystem services. We tested whether isolation from florally diverse natural and semi-natural areas reduces the spatial and temporal stability of flower-visitor richness and pollination services in crop fields. We synthesised data from 29 studies with contrasting biomes, crop species and pollinator communities. Stability of flower-visitor richness, visitation rate (all insects except honey bees) and fruit set all decreased with distance from natural areas. At 1 km from adjacent natural areas, spatial stability decreased by 25, 16 and 9% for richness, visitation and fruit set, respectively, while temporal stability decreased by 39% for richness and 13% for visitation. Mean richness, visitation and fruit set also decreased with isolation, by 34, 27 and 16% at 1 km respectively. In contrast, honey bee visitation did not change with isolation and represented > 25% of crop visits in 21 studies. Therefore, wild pollinators are relevant for crop productivity and stability even when honey bees are abundant. Policies to preserve and restore natural areas in agricultural landscapes should enhance levels and reliability of pollination services.

Expression and function of P2X(7) receptor and CD39/Entpd1 in patients with type 2 diabetes and their association with biochemical parameters.

Chronic inflammation is an important contributor to the insulin resistance observed in type 2 diabetes (T2D). We evaluated the expression and function of the P2X(7) receptor and CD39/Entpd1, molecules involved in the cellular regulation of inflammation, in peripheral blood mononuclear cells from T2D patients, and their correlation with the concentration of HbA1c in blood. T2D patients with deficient metabolic control (DC) showed increased proportion of P2X(7)(+) cells compared with healthy individuals; T2D-DC subjects also displayed higher proportion of CD14(+), CD4(+) and CD19(+) subpopulations of P2X(7)(+) cells when compared with T2D patients with acceptable metabolic control. A significant association was observed between the proportion of P2X(7)(+)CD14(+) cells and blood concentration of LDL-c. In addition, the percentages of CD39(+) cells and CD39(+)CD19(+) cells were significantly associated with HbA1c and fasting plasma glucose levels. No changes were observed in the function of P2X(7)(+) cells from T2D patients; however, enhanced CD39/Entpd1 enzyme activity and low serum levels of IL-17 were detected. Therefore, CD39(+) cells could have a balancing regulatory role in the inflammatory process observed in patients with T2D.