Factors influencing the foliar elemental composition and stoichiometry in forest trees in Spain

Concentrations of nutrient elements in organisms and in the abiotic environment are key factors influencing ecosystem structure and function. We studied how concentrations and stoichiometries of nitrogen (N), phosphorus (P) and potassium (K) in leaves of forest trees are related to phylogeny and to environmental factors (mean annual precipitation, mean annual temperature, forest type, and nitrogen deposition). Using data for 4691 forest plots from across Spain, we tested the following hypotheses: (i) that foliar stoichiometries of forest trees are strongly influenced by phylogeny, (ii) that climate, as an important driver of plant uptake and nutrient use efficiency, affects foliar stoichiometry, (iii) that long-term loads of N influence N, P and K concentrations and ratios in natural vegetation, and (iv) that sympatric species are differentiated according to their foliar stoichiometry, thereby reducing the intensity of resource competition. Our analyses revealed that several factors contributed to interspecific variation in elemental composition and stoichiometry. These included phylogeny, forest type, climate, N deposition, and competitive neighborhood relationships (probably related to niche segregation effect). These findings support the notion that foliar elemental composition reflects adaptation both to regional factors such as climate and to local factors such as competition with co-occurring species

Association between long term exposure to particulate matter and incident hypertension in Spain

Exposure to air particulate matter has been linked with hypertension and blood pressure levels. The metabolic risks of air pollution could vary according to the specific characteristics of each area, and has not been sufficiently evaluated in Spain. We analyzed 1103 individuals, participants in a Spanish nationwide population based cohort study ([email protected]), who were free of hypertension at baseline (2008-2010) and completed a follow-up exam of the cohort (2016-2017). Cohort participants were assigned air pollution concentrations for particulate matter < 10 mu m (PM10) and < 2.5 mu m (PM2.5) during follow-up (2008-2016) obtained through modeling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). Mean and SD concentrations of PM10 and PM2.5 were 20.17 +/- 3.91 mu g/m(3) and 10.83 +/- 2.08 mu g/m(3) respectively. During follow-up 282 cases of incident hypertension were recorded. In the fully adjusted model, compared with the lowest quartile of PM10, the multivariate weighted ORs (95% CIs) for developing hypertension with increasing PM10 exposures were 0.82 (0.59-1.14), 1.28 (0.93-1.78) and 1.45 (1.05-2.01) in quartile 2, 3 and 4 respectively (p for a trend of 0.003). The corresponding weighted ORs according to PM2.5 exposures were 0.80 (0.57-1.13), 1.11 (0.80-1.53) and 1.48 (1.09-2.00) (p for trend 0.004). For each 5-mu g/m(3) increment in PM10 and PM2.5 concentrations, the odds for incident hypertension increased 1.22 (1.06-1.41) p = 0.007 and 1.39 (1.07-1.81) p = 0.02 respectively. In conclusion, our study contributes to assessing the impact of particulate pollution on the incidence of hypertension in Spain, reinforcing the need for improving air quality as much as possible in order to decrease the risk of cardiometabolic disease in the population

Association between exposure to air pollution and blood lipids in the general population of Spain.

Background and Aims: We aimed to assess the associations of exposure to air pollutants and standard and advanced lipoprotein measures, in a nationwide sample representative of the adult population of Spain.Methods: We included 4647 adults (>18 years), participants in the national, cross- sectional, population- based [email protected] study, conducted in 2008– 2010. Standard lipid measurements were analysed on an Architect C8000 Analyzer (Abbott Laboratories SA). Lipoprotein analysis was made by an advanced 1H- NMR lipoprotein test (Liposcale®). Participants were assigned air pollution con-centrations for particulate matter <10 μm (PM10), <2.5 μm (PM2.5) and nitrogen dioxide (NO2), corresponding to the health examination year, obtained by mod-elling combined with measurements taken at air quality stations (CHIMERE chemistry- transport model).Results: In multivariate linear regression models, each IQR increase in PM10, PM2.5 and NO2 was associated with 3.3%, 3.3% and 3% lower levels of HDL- c and 1.3%, 1.4% and 1.1% lower HDL particle (HDL- p) concentrations (p< .001 for all associations). In multivariate logistic regression, there was a significant associa-tion between PM10, PM2.5 and NO2 concentrations and the odds of presenting low HDL- c (<40 mg/dL), low HDL- p (<p25) and higher LDL particle (LDL- p) concentrations (≥p75). In subgroup analyses there were stronger associations be-tween PM10 and NO2 and low HDL- p in men (p for interaction .008 and .034), and between NO2 and low HDL- p in individuals with obesity (p for interaction .015).Conclusions: Our study shows an association between the exposure to air pol-lutants and blood lipids in the general population of Spain, suggesting a link to atherosclerosisFunding for open access charge: Universidad de Málaga / CBU

Ambient air pollution and thyroid function in Spanish adults. A nationwide population-based study ([email protected] study)

Background Recent reports have suggested that air pollution may impact thyroid function, although the evidence is still scarce and inconclusive. In this study we evaluated the association of exposure to air pollutants to thyroid function parameters in a nationwide sample representative of the adult population of Spain. Methods The [email protected] study is a national, cross-sectional, population-based survey which was conducted in 2008-2010 using a random cluster sampling of the Spanish population. The present analyses included 3859 individuals, without a previous thyroid disease diagnosis, and with negative thyroid peroxidase antibodies (TPO Abs) and thyroid-stimulating hormone (TSH) levels of 0.1-20 mIU/L. Participants were assigned air pollution concentrations for particulate matter <2.5 mu m (PM2.5) and Nitrogen Dioxide (NO2), corresponding to the health examination year, obtained by means of modeling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). TSH, free thyroxine (FT4), free triiodothyronine (FT3) and TPO Abs concentrations were analyzed using an electrochemiluminescence immunoassay (Modular Analytics E170 Roche). Results In multivariate linear regression models, there was a highly significant negative correlation between PM2.5 concentrations and both FT4 (p<0.001), and FT3 levels (p<0.001). In multivariate logistic regression, there was a significant association between PM2.5 concentrations and the odds of presenting high TSH [OR 1.24 (1.01-1.52) p=0.043], lower FT4 [OR 1.25 (1.02-1.54) p=0.032] and low FT3 levels [1.48 (1.19-1.84) p=<0.001] per each IQR increase in PM2.5 (4.86 mu g/m(3)). There was no association between NO2 concentrations and thyroid hormone levels. No significant heterogeneity was seen in the results between groups of men, pre-menopausal and post-menopausal women. Conclusions Exposures to PM2.5 in the general population were associated with mild alterations in thyroid function.CIBERDEM (Ministerio de Economia, Industria y Competitividad-ISCIII), Ministerio de Sanidad, Servicios Sociales e Igualdad-ISCIII, Instituto de Salud Carlos III (PI17/02136, PI20/01322), Consejeria de Salud y familias (PI-0144-2018), European Regional Development Fund (ERDF) "A way to build Europe". GRM belongs to the regional Nicolas Monardes research program of the Consejeria de Salud (RC-0006-2016; Junta de Andalucia, Spain). CMA is recipient of a "Rio Hortega" research contract (CM19/00186, Instituto de Salud Carlos III). VKDG is recipient of a "Rio Hortega" research contract (CM21/00214, Instituto de Salud Carlos III)

Tumor microenvironment gene expression profiles associated to complete pathological response and disease progression in resectable NSCLC patients treated with neoadjuvant chemoimmunotherapy

Background Neoadjuvant chemoimmunotherapy for non-small cell lung cancer (NSCLC) has improved pathological responses and survival rates compared with chemotherapy alone, leading to Food and Drug Administration (FDA) approval of nivolumab plus chemotherapy for resectable stage IB-IIIA NSCLC (AJCC 7th edition) without ALK or EGFR alterations. Unfortunately, a considerable percentage of tumors do not completely respond to therapy, which has been associated with early disease progression. So far, it is impossible to predict these events due to lack of knowledge. In this study, we characterized the gene expression profile of tumor samples to identify new biomarkers and mechanisms behind tumor responses to neoadjuvant chemoimmunotherapy and disease recurrence after surgery. Methods Tumor bulk RNA sequencing was performed in 16 pretreatment and 36 post-treatment tissue samples from 41 patients with resectable stage IIIA NSCLC treated with neoadjuvant chemoimmunotherapy from NADIM trial. A panel targeting 395 genes related to immunological processes was used. Tumors were classified as complete pathological response (CPR) and non-CPR, based on the total absence of viable tumor cells in tumor bed and lymph nodes tested at surgery. Differential-expressed genes between groups and pathway enrichment analysis were assessed using DESeq2 and gene set enrichment analysis. CIBERSORTx was used to estimate the proportions of immune cell subtypes. Results CPR tumors had a stronger pre-established immune infiltrate at baseline than non-CPR, characterized by higher levels of IFNG, GZMB, NKG7, and M1 macrophages, all with a significant area under the receiver operating characteristic curve (ROC) >0.9 for CPR prediction. A greater effect of neoadjuvant therapy was also seen in CPR tumors with a reduction of tumor markers and IFN gamma signaling after treatment. Additionally, the higher expression of several genes, including AKT1, BST2, OAS3, or CD8B; or higher dendritic cells and neutrophils proportions in post-treatment non-CPR samples, were associated with relapse after surgery. Also, high pretreatment PD-L1 and tumor mutational burden levels influenced the post-treatment immune landscape with the downregulation of proliferation markers and type I interferon signaling molecules in surgery samples. Conclusions Our results reinforce the differences between CPR and non-CPR responses, describing possible response and relapse immune mechanisms, opening the possibility of therapy personalization of immunotherapy-based regimens in the neoadjuvant setting of NSCLC

Stratification and therapeutic potential of PML in metastatic breast cancer.

Patient stratification has been instrumental for the success of targeted therapies in breast cancer. However, the molecular basis of metastatic breast cancer and its therapeutic vulnerabilities remain poorly understood. Here we show that PML is a novel target in aggressive breast cancer. The acquisition of aggressiveness and metastatic features in breast tumours is accompanied by the elevated PML expression and enhanced sensitivity to its inhibition. Interestingly, we find that STAT3 is responsible, at least in part, for the transcriptional upregulation of PML in breast cancer. Moreover, PML targeting hampers breast cancer initiation and metastatic seeding. Mechanistically, this biological activity relies on the regulation of the stem cell gene SOX9 through interaction of PML with its promoter region. Altogether, we identify a novel pathway sustaining breast cancer aggressiveness that can be therapeutically exploited in combination with PML-based stratification.The work of A.C. is supported by the Ramón y Cajal award, the Basque Department of Industry, Tourism and Trade (Etortek), Health (2012111086) and Education (PI2012-03), Marie Curie (277043), Movember Foundation (GAP1), ISCIII (PI10/01484, PI13/00031), FERO (VIII Fellowship) and ERC (336343). N.M.-M. and P.A. are supported by the Spanish Association Against Cancer (AECC), AECC JP Vizcaya and Guipuzcoa, respectively. J.U. and F.S. are Juan de la Cierva Researchers (MINECO). L.A., A.A.-A. and L.V.-J. are supported by the Basque Government of education. M.L.-M.C. acknowledges SAF2014-54658-R and Asociación Española contra el Cancer. R.B. acknowledges Spanish MINECO (BFU2014-52282-P, Consolider BFU2014-57703-REDC), the Departments of Education and Industry of the Basque Government (PI2012/42) and the Bizkaia County. M.S., V.S. and J.B. acknowledge Banco Bilbao Vizcaya Argentaria (BBVA) Foundation (Tumour Biomarker Research Program). M.S. and J.B. are supported by NIH grant P30 CA008748. M.dM.V. is supported by the Institute of Health Carlos III (PI11/02251, PI14/01328) and Basque Government, Health Department (2014111145). A.M. is supported by ISCIII (CP10/00539, PI13/02277) and Marie Curie CIG 2012/712404. V.S. is supported by the SCIII (PI13/01714, CP14/00228), the FERO Foundation and the Catalan Agency AGAUR (2014 SGR 1331). R.R.G. research support is provided by the Spanish Ministry of Science and Innovation grant SAF2013-46196, BBVA Foundation, the Generalitat de Catalunya (2014 SGR 535), Institució Catalana de Recerca i Estudis Avançats, the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds (SAF2013-46196).This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms1259

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Factors influencing the foliar elemental composition and stoichiometry in forest trees in Spain

Concentrations of nutrient elements in organisms and in the abiotic environment are key factors influencing ecosystem structure and function. We studied how concentrations and stoichiometries of nitrogen (N), phosphorus (P) and potassium (K) in leaves of forest trees are related to phylogeny and to environmental factors (mean annual precipitation, mean annual temperature, forest type, and nitrogen deposition). Using data for 4691 forest plots from across Spain, we tested the following hypotheses: (i) that foliar stoichiometries of forest trees are strongly influenced by phylogeny, (ii) that climate, as an important driver of plant uptake and nutrient use efficiency, affects foliar stoichiometry, (iii) that long-term loads of N influence N, P and K concentrations and ratios in natural vegetation, and (iv) that sympatric species are differentiated according to their foliar stoichiometry, thereby reducing the intensity of resource competition. Our analyses revealed that several factors contributed to interspecific variation in elemental composition and stoichiometry. These included phylogeny, forest type, climate, N deposition, and competitive neighborhood relationships (probably related to niche segregation effect). These findings support the notion that foliar elemental composition reflects adaptation both to regional factors such as climate and to local factors such as competition with co-occurring species

Trends of inorganic and organic aerosols and precursor gases in Europe: insights from the EURODELTA multi-model experiment over the 1990–2010 period

In the framework of the EURODELTA-Trends (EDT) modeling experiment, several chemical transport models (CTMs) were applied for the 1990–2010 period to investigate air quality changes in Europe as well as the capability of the models to reproduce observed long-term air quality trends. Five CTMs have provided modeled air quality data for 21 continuous years in Europe using emission scenarios prepared by the International Institute for Applied Systems Analysis/Greenhouse Gas – Air Pollution Interactions and Synergies (IIASA/GAINS) and corresponding year-by-year meteorology derived from ERA-Interim global reanalysis. For this study, long-term observations of particle sulfate (SO2−4 ), total nitrate (TNO3), total ammonium (TNHx) as well as sulfur dioxide (SO2) and nitrogen dioxide (NO2) for multiple sites in Europe were used to evaluate the model results. The trend analysis was performed for the full 21 years (referred to as PT) but also for two 11-year subperiods: 1990–2000 (referred to as P1) and 2000–2010 (referred to as P2). The experiment revealed that the models were able to reproduce the faster decline in observed SO2 concentrations during the first decade, i.e., 1990–2000, with a 64 %–76 % mean relative reduction in SO2 concentrations indicated by the EDT experiment (range of all the models) versus an 82 % mean relative reduction in observed concentrations. During the second decade (P2), the models estimated a mean relative reduction in SO2 concentrations of about 34 %–54 %, which was also in line with that observed (47 %). Comparisons of observed and modeled NO2 trends revealed a mean relative decrease of 25 % and between 19 % and 23 % (range of all the models) during the P1 period, and 12 % and between 22 % and 26 % (range of all the models) during the P2 period, respectively. Comparisons of observed and modeled trends in SO2−4 concentrations during the P1 period indicated that the models were able to reproduce the observed trends at most of the sites, with a 42 %–54 % mean relative reduction indicated by the EDT experiment (range of all models) versus a 57 % mean relative reduction in observed concentrations and with good performance also during the P2 and PT periods, even though all the models overpredicted the number of statistically significant decreasing trends during the P2 period. Moreover, especially during the P1 period, both modeled and observational data indicated smaller reductions in SO2−4 concentrations compared with their gas-phase precursor (i.e., SO2), which could be mainly attributed to increased oxidant levels and pH-dependent cloud chemistry. An analysis of the trends in TNO3 concentrations indicated a 28 %–39 % and 29 % mean relative reduction in TNO3 concentrations for the full period for model data (range of all the models) and observations, respectively. Further analysis of the trends in modeled HNO3 and particle nitrate (NO−3 ) concentrations revealed that the relative reduction in HNO3 was larger than that for NO−3 during the P1 period, which was mainly attributed to an increased availability of “free ammonia”. By contrast, trends in modeled HNO3 and NO−3 concentrations were more comparable during the P2 period. Also, trends of TNHx concentrations were, in general, underpredicted by all models, with worse performance for the P1 period than for P2. Trends in modeled anthropogenic and biogenic secondary organic aerosol (ASOA and BSOA) concentrations together with the trends in available emissions of biogenic volatile organic compounds (BVOCs) were also investigated. A strong decrease in ASOA was indicated by all the models, following the reduction in anthropogenic non-methane VOC (NMVOC) precursors. Biogenic emission data..