Integrated study of factors affecting fetal weight in singleton pregnancies. Nomogram and development of basic and advanced fetal growth customized models

We have performed a multivariate analysis to explore the influence on birth and ultrasound fetal weight estimation of traditional factors as biochemical data and maternal characteristics in combination with non- traditionally explored predictors as paternal height, Pregnancy-associated plasma protein A (PAPP-A), single umbilical artery or Free-beta Human Chorionic Gonadotropin (fß- HCG). The study was performed for a Spanish population (region of Aragon) in singleton pregnancies at term (37-42 weeks). Also, we have created a nomogram and in order to predict the occurrence of SGA (small for gestational age) and LGA (large for gestational age) cases we provide a multivariate predictive model of fetal weight that have been compared with other models in the prediction of ultrasound and birth weights. After study we have created a software application for automated calculation of percentile fetal weight, adjusting the variables when they were significant

Social media in cardiology: Reasons to learn how to use it

Social media has changed the way we learn, educate, and interact with our peers. The dynamic nature of social media and their immediate availability through our portable devices (smartphones, tablets, smartwatches, etc.) is quickly transforming the way we participate in society. The scope of these digital tools is broad as they deal with many different aspects: Teaching and learning, case discussion, congresses coverage, peer to peer interaction, research are examples worth mentioning. The scientific societies considered more innovative, are promoting these tools between their members. These new concepts need to be known by the cardiologists to stay updated, as countless information is moving rapidly through these channels. We summarize the main reasons why learning how to use these tools to be part of the conversation is essential for the cardiologist in training or fully stablished

23 Validation of PD-L1 dynamic expression on extracellular vesicles as a predictor of response to immune-checkpoint inhibitors and survival in non-small cell lung cancer patients

BackgroundImmune-checkpoint inhibitors (ICIs) revolutionized the treatment of advanced non-small cell lung cancer (NSCLC).1–3 To date, tissue PD-L1 immunohistochemistry is one of the leading biomarkers for prediction of ICIs response but has several limitations.4 5Extracellular vesicles (EVs) are cell-derived structures involved in cell communication and represent a potential minimally invasive alternative to predicting ICI response.6–9 Based on this and our preliminary results presented at SITC 2020,10 we hypothesize that EV PD-L1 predicts response to ICIs in NSCLC.MethodsThis study evaluates an exploratory cohort of advanced/metastatic NSCLC patients receiving ICIs (cohort A) and a validation cohort receiving Pembrolizumab+docetaxel or docetaxel alone (PROLUNG Phase 2 randomized trial) (cohort B).11 Plasma samples were collected pre-treatment (T1) and at 3 treatment cycles (T2) (figure 1A). Response was assessed by computed-tomography scan at 3 (cohort A) and 6–8 treatment cycles (cohort B) according to mono- or chemotherapy combination therapy. Patients were classified as responders (partial, stable, or complete response) or non-responders (progressive disease) by RECISTv1.1.12 EVs were isolated by serial ultracentrifugation and characterized following ISEV recommendations.13,14 Tissue PD-L1 expression was measured by standardized immunohistochemistry (SP263, 22C3, or 28–8 clones)5 and EV PD-L1 expression by immunoblot and its ratio was calculated as EV PD-L1 T2/T1. Cut-offs from the exploratory cohort were applied to the validation cohort, being EV PD-L1 ratio <0.85 = Low.ResultsPaired samples from 30 ICIs, 23 pembrolizumab+docetaxel, and 15 docetaxel treated patients were analyzed. In cohort A, non-responders showed higher EV PD-L1 ratio than responders (p=0.012) (figure 1B) with an area-under-the-curve (AUC) of 77.3%, 83.3% sensitivity, and 61.1% specificity, while the tissue PD-L1 was not predictive (AUC=50%). As a validation, pembrolizumab+docetaxel treated non-responders showed higher EV PD-L1 ratio (p=0.036) than responders with an AUC=69.3%, sensitivity=75%, and specificity=63.6%, outperforming the tissue PD-L1 (figure 1C). No statistically significant differences were observed in the docetaxel group (p=0.885). Moreover, ICIs patients with higher EV PD-L1 ratio showed shorter progression-free survival (PFS) (HR=0.30, p=0.066) and overall survival (OS) (HR=0.17, p=0.016) (figure 1D) which was also observed in the pembrolizumab+docetaxel cohort with shorter PFS (HR=0.12, p=0.004) and OS (HR=0.23, p=0.010) (figure 1E). EV PD-L1 ratio did not predict survival in docetaxel-treated patients.Abstract 23 Figure 1(A) Study design and methodology. (B) EV PD-L1 ratio predicts response to ICIs in 30 NSCLC patients from the discovery cohort A and outperforms tissue PD-L1. (C) EV PD-L1 ratio is predictive for response to pembrolizumab+docetaxel in 23 NSCLC patients but not in 15 patients receiving docetaxel alone from cohort B. (D) Higher EV PD-L1 ratio predicts shorter PFS and OS in 30 patients from the discovery cohort A treated with ICIs. (E) Higher EV PD-L1 ratio is associated with shorter PFS and OS in 23 patients treated with pembrolizumab+docetaxel but not in patients treated with docetaxel alone. Abbreviations: CT: Computed tomography, EV: Extracellular vesicle; HR: Hazard Ratio; ICIs: Immune-checkpoint Inhibitors; IHC: Immunohistochemistry; NR: Non-Responders; OS: Overall Survival; p: p-value; PFS: Progression-free survival; R: Responders [Created with BioRender].ConclusionsWe demonstrated that treatment-associated changes in EV PD-L1 levels are predictive of response and survival in advanced NSCLC patients treated with ICIs. This model, if confirmed in a large prospective cohort, could have important clinical implications, guiding treatment decisions and improving the outcome of patients receiving ICIs.AcknowledgementsWe would like to extend our gratitude to the all the patients that participated in the study.ReferencesBorghaei H, Paz-Ares L, Horn L, Spigel DR, Steins M, Ready NE, et al. Nivolumab versus Docetaxel in Advanced Nonsquamous Non–Small-Cell Lung Cancer. N Engl J Med 2015;373:1627–39.Herbst RS, Baas P, Kim DW, Felip E, Pérez-Gracia JL, Han JY, et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): A randomised controlled trial. Lancet 2016;387:1540–50.Ruiz-Patiño A, Arrieta O, Cardona AF, Martín C, Raez LE, Zatarain-Barrón ZL, et al. Immunotherapy at any line of treatment improves survival in patients with advanced metastatic non-small cell lung cancer (NSCLC) compared with chemotherapy (Quijote-CLICaP). Thorac Cancer 2020;11:353–61.Doroshow DB, Bhalla S, Beasley MB, Sholl LM, Kerr KM, Gnjatic S, et al. PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat Rev Clin Oncol 2021;18:345–362.Hirsch FR, McElhinny A, Stanforth D, Ranger-Moore J, Jansson M, Kulangara K, et al. PD-L1 immunohistochemistry assays for lung cancer: results from phase 1 of the blueprint PD-L1 IHC assay comparison project. J Thorac Oncol 2017;12:208–222.Poggio M, Hu T, Pai CC, Chu B, Belair CD, Chang A, et al. Suppression of exosomal PD-L1 induces systemic anti-tumor immunity and memory. Cell 2019;177:414–427.e13.Cordonnier M, Nardin C, Chanteloup G, Derangere V, Algros MP, Arnould L, et al. Tracking the evolution of circulating exosomal-PD-L1 to monitor melanoma patients. J Extracell Vesicles 2020;9:1710899.Del Re M, Cucchiara F, Rofi E, Fontanelli L, Petrini I, Gri N, et al. A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC. Cancer Immunol Immunother 2020;70:1667–1678.Chen G, Huang AC, Zhang W, Zhang G, Wu M, Xu W, et al. Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response. Nature. 2018;560:382–6.10 de Miguel Perez D, Russo A, Gunasekaran M, Cardona A, Lapidus R, Cooper B, et al. 31 Dynamic change of PD-L1 expression on extracellular vesicles predicts response to immune-checkpoint inhibitors in non-small cell lung cancer patients. 2020J Immunother Cancer;8(Suppl 3):A30–A30.Arrieta O, Barrón F, Ramírez-Tirado LA, Zatarain-Barrón ZL, Cardona AF, Díaz-García D, et al. Efficacy and safety of pembrolizumab plus docetaxel vs docetaxel alone in patients with previously treated advanced non–small cell lung cancer: the PROLUNG phase 2 randomized clinical trial. 2020JAMA Oncol;6:856–864.Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). 2009Eur J Cancer;45:228–47.Reclusa P, Verstraelen P, Taverna S, Gunasekaran M, Pucci M, Pintelon I, et al. Improving extracellular vesicles visualization: From static to motion. 2020Sci Rep;10:6494.Théry C, Witwer KW, Aikawa E, Alcaraz MJ, Anderson JD, Andriantsitohaina R, et al. Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines. 2018J Extracell Vesicles;7:1535750Ethics ApprovalPatients consented to Institutional Review Board–approved protocol, A.O. Pappardo, Messina, Italy for cohort A and Thoracic Oncology Unit, Instituto Nacional de Cancerología (INCan), México City, México in case of the cohort B. Biological material was transferred to the University of Maryland School of Medicine, Baltimore for EV analysis under signed MTA between institutions MTA/2020–13111 & MTA/2020–13113

Model comparisons for estimating carbon emissions from North American wildland fire

Research activities focused on estimating the direct emissions of carbon from wildland fires across North America are reviewed as part of the North American Carbon Program disturbance synthesis. A comparison of methods to estimate the loss of carbon from the terrestrial biosphere to the atmosphere from wildland fires is presented. Published studies on emissions from recent and historic time periods and five specific cases are summarized, and new emissions estimates are made using contemporary methods for a set of specific fire events. Results from as many as six terrestrial models are compared. We find that methods generally produce similar results within each case, but estimates vary based on site location, vegetation (fuel) type, and fire weather. Area normalized emissions range from 0.23 kg C m−2 for shrubland sites in southern California/NW Mexico to as high as 6.0 kg C m−2 in northern conifer forests. Total emissions range from 0.23 to 1.6 Tg C for a set of 2003 fires in chaparral-dominated landscapes of California to 3.9 to 6.2 Tg C in the dense conifer forests of western Oregon. While the results from models do not always agree, variations can be attributed to differences in model assumptions and methods, including the treatment of canopy consumption and methods to account for changes in fuel moisture, one of the main drivers of variability in fire emissions. From our review and synthesis, we identify key uncertainties and areas of improvement for understanding the magnitude and spatial-temporal patterns of pyrogenic carbon emissions across North America

La vesícula extracelular TGF-β basal es un biomarcador predictivo de la respuesta a los inhibidores del punto de control inmunitario y de la supervivencia en el cáncer de pulmón no microcítico

Antecedentes: Los inhibidores de los puntos de control inmunitarios (ICI) son una estrategia terapéutica eficaz que mejora la supervivencia de los pacientes con cáncer de pulmón en comparación con los tratamientos convencionales. terapéutica eficaz que mejora la supervivencia de los pacientes con cáncer de pulmón en comparación con los tratamientos convencionales. Sin embargo, se necesitan biomarcadores predictivos novedosos para estratificar qué pacientes obtienen un beneficio clínico, ya que el histológico PD-L1, actualmente utilizado y altamente heterogéneo, ha mostrado una baja precisión. La biopsia líquida es el análisis de biomarcadores en fluidos corporales y representa una herramienta mínimamente invasiva que puede utilizarse para monitorizar la evolución del tumor y los efectos del tratamiento, reduciendo potencialmente los sesgos asociados a la heterogeneidad tumoral asociada a las biopsias de tejidos. En este contexto citoquinas, como el factor de crecimiento transformante-β (TGF-β), pueden encontrarse libres en circulación en la sangre y empaquetadas en vesículas extracelulares (VE), que tienen un tropismo de administración específico y pueden afectar a la interacción entre el tumor y el sistema inmunitario. El TGF-β es una citocina inmunosupresora que desempeña un papel crucial en el escape inmunitario de los tumores, la resistencia al tratamiento y la metástasis. Así pues, nuestro objetivo era evaluar el valor predictivo predictivo del TGF-β circulante y EV en pacientes con cáncer de pulmón no microcítico que reciben ICI.Background: Immune‐checkpoint inhibitors (ICIs) are an effective therapeutic strategy, improving the survival of patients with lung cancer compared with conventional treatments. However, novel predictive biomarkers are needed to stratify which patients derive clinical benefit because the currently used and highly heterogenic histological PD‐L1 has shown low accuracy. Liquid biopsy is the analysis of biomarkers in body fluids and represents a minimally invasive tool that can be used to monitor tumor evolution and treatment effects, potentially reducing biases associated with tumor heterogeneity associated with tissue biopsies. In this context, cytokines, such as transforming growth factor‐β (TGF‐β), can be found free in circulation in the blood and packaged into extracellular vesicles (EVs), which have a specific delivery tropism and can affect in tumor/immune system interaction. TGF‐β is an immunosuppressive cytokine that plays a crucial role in tumor immune escape, treatment resistance, and metastasis. Thus, we aimed to evaluate the predictive value of circulating and EV TGF‐β in patients with non–small‐cell lung cancer receiving ICIs

Planck intermediate results. XXIX. All-sky dust modelling with Planck, IRAS, and WISE observations

We present all-sky modelling of the high resolution Planck, IRAS, and WISE infrared (IR) observations using the physical dust model presented by Draine and Li in 2007 (DL). We study the performance and results of this model, and discuss implications for future dust modelling. The present work extends the DL dust modelling carried out on nearby galaxies using Herschel and Spitzer data to Galactic dust emission. We employ the DL dust model to generate maps of the dust mass surface density, the optical extinction Av, and the starlight intensity parametrized by Umin. The DL model reproduces the observed spectral energy distribution (SED) satisfactorily over most of the sky, with small deviations in the inner Galactic disk and in low ecliptic latitude areas. We compare the DL optical extinction Av for the diffuse interstellar medium with optical estimates for 2 10^5 quasi-stellar objects (QSOs) observed in the Sloan digital sky survey. The DL Av estimates are larger than those determined towards QSOs by a factor of about 2, which depends on Umin. The DL fitting parameter Umin, effectively determined by the wavelength where the SED peaks, appears to trace variations in the far-IR opacity of the dust grains per unit Av, and not only in the starlight intensity. To circumvent the model deficiency, we propose an empirical renormalization of the DL Av estimate, dependent of Umin, which compensates for the systematic differences found with QSO observations. This renormalization also brings into agreement the DL Av estimates with those derived for molecular clouds from the near-IR colours of stars in the 2 micron all sky survey. The DL model and the QSOs data are used to compress the spectral information in the Planck and IRAS observations for the diffuse ISM to a family of 20 SEDs normalized per Av, parameterized by Umin, which may be used to test and empirically calibrate dust models.Comment: Final version that has appeared in A&

The miniJPAS survey : The role of group environment in quenching star formation

Peer reviewe