Caracterización de los procesos sísmicos y gravitacional sobre el deslizamiento de Maca (Colca)

El deslizamiento de Maca está ubicado en el poblado del mismo nombre, a orillas del río Colca en la región Arequipa al sur de Perú. En 1991, un sismo superficial (mb 5.4), con epicentro localizado a 8 km de la zona de estudio, reactivó el deslizamiento, provocando un hundimiento de la carretera, y causó la destrucción del sector oeste del pueblo. Los objetivos del estudio son evaluar los riesgos sísmicos y gravitacionales en el sector de Maca y alrededores. Para ello, se estudiará la respuesta del deslizamiento a los sismos y la interacción onda / estructura, para movimientos sísmicos moderados a fuertes. En este estudio presentamos medidas geodésicas y geofísicas que permitirán caracterizar el subsuelo y la cinemática del deslizamiento, mostrando las diferencias entre los sectores oeste y este. Especialmente, el subsuelo en la parte oeste del pueblo está conformado por material bien consolidado y saturado de agua. Las mediciones sugieren la influencia del subsuelo sobre los procesos sísmicos que sucedieron en 1991. Referente a la cinemática, los resultados de mediciones GPS muestran la influencia de la circulación del agua en la dinámica del deslizamiento, con desplazamientos en la parte oeste de 0.60 m/mes durante la época de lluvia, y de menos de 0.05 m/mes en época seca. La unión de las medidas geofísicas y geodésicas sugiere que la presencia de agua y del sismo es el origen del gran desplazamiento del deslizamiento durante el sismo de julio 1991, justo después la época de la lluvia

First-in-human study of JNJ-63709178, a CD123/CD3 targeting antibody, in relapsed/refractory acute myeloid leukemia

This study aimed to identify a recommended phase II dose and evaluate the safety, tolerability, pharmacokinetics/pharmacodynamics, and preliminary clinical activity of JNJ-63709178, a CD123/CD3 dual-targeting antibody, in patients with relapsed or refractory acute myeloid leukemia. Intravenous (i.v.) and subcutaneous (s.c.) administration of JNJ-63709178 were evaluated. The i.v. infusions were administered once every 2 weeks (cohorts 1-5 [n = 17]) or twice weekly (cohorts 6-11 [n = 36]). A twice-weekly s.c. dosing regimen with step-up dosing was also studied (s.c. cohorts 1-2 [n = 9]). Treatment-emergent adverse events (TEAEs) greater than or equal to grade 3 were observed in 11 (65%) patients in cohorts 1-5 and 33 (92%) patients in cohorts 6-11. At the highest i.v. dose (4.8 μg/kg), 5 (71%) patients discontinued treatment due to TEAEs. For s.c. administration (n = 9), eight (89%) patients experienced TEAEs greater than or equal to grade 3 and injection site reactions (≤ grade 3) emerged in all patients. At 4.8 μg/kg (i.v. and s.c.), the mean maximum serum concentrations were 30.3 and 3.59 ng/ml, respectively. Increases in multiple cytokines were observed following i.v. and s.c. administrations, and step-up dosing strategies did not mitigate cytokine production or improve the safety profile and led to limited duration of treatment. Minimal clinical activity was observed across all cohorts. The i.v. and s.c. dosing of JNJ-63709178 was associated with suboptimal drug exposure, unfavorable safety profiles, limited clinical activity, and inability to identify a recommended phase II dose.This work was supported by Janssen Research and Development, LLC.Peer reviewe

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Interest of air temperature modelling related to the need to define territorial vulnerabilities for a systemic understanding of the risk of heat waves in urban areas in Lyon and Tokyo

Le changement climatique est un phénomène contemporain majeur aux conséquences multiples. L’un de ses effets est l’augmentation de la fréquence et de l'intensité des vagues de chaleur. Celles-ci sont exacerbées en ville en raison de l'effet d'îlot de chaleur urbain et constituent ainsi une menace accrue pour la santé des populations. La connaissance des gradients thermiques urbains et de leurs déterminants dans une optique de réduction de la surchauffe urbaine est ainsi une priorité, tout comme l'identification des personnes les plus vulnérables, dans le but d’une gestion globale du risque aux fortes chaleurs afin de mettre en place des politiques publiques d’aménagement et de santé, ciblées et coordonnées. Ce travail de doctorat de géographie-aménagement porte ainsi sur les raisons de cette surchauffe urbaine et la modélisation des gradients thermiques associés sur les territoires de Lyon et de Tokyo. Ce travail est complété par une analyse des vulnérabilités socio-économiques et physiologiques aux fortes chaleurs afin de proposer des analyses de risque dans le but de fournir des pistes dans la construction d’une ville intelligente et durable. La méthodologie abordée dans ce manuscrit repose sur une approche pluridisciplinaire, au croisement de la géographie sociale et de la géographie physique, avec un traitement et une analyse spatiale et géostatistique d’une part, et une approche sociale dans la détermination des vulnérabilités territoriales. A ce titre, ce travail de recherche se fonde sur une littérature internationale, que ce soit pour la modélisation de la température de l’air ou encore pour la détermination des vulnérabilités physiologiques et socio-économiques. La première est déterminée grâce au recours de mesures mobiles, de mesures participatives et de données satellitaires et LiDAR. Par la suite, l’utilisation de modèles de régression et de machine learning permet de modéliser le microclimat urbain. D’une manière complémentaire, l’évaluation des vulnérabilités physiologiques et socio-économiques met l’accent sur l’utilisation de l’Analytic Hierarchy Process qui est une méthode d’aide à la décision et de prise en compte d’avis d’experts issus du monde médical et sur l’utilisation de l’analyse en composantes principales. Les résultats obtenus sur la modélisation de la température de l’air sont confrontés aux vulnérabilités, afin élaborer des cartes de risques liés à la surchauffe urbaine en proposant notamment deux indicateurs novateurs, le Heat Physiological Risk Index et le Heat Socio-economic Risk Index. Dans ce contexte de changement climatique, ces sorties analytiques peuvent contribuer à améliorer la conception de l’aménagement du territoire et des requalifications associées sur les deux zones d’étude en vue de limiter localement les surchauffes urbaines. Cette étude globale se veut ainsi être un véritable outil d’aide à la décision pour les professionnels de la ville.Climate change is a major contemporary phenomenon with multiple consequences. One of its effects is an increase in the frequency and intensity of heat waves. These are accentuated in cities due to the urban heat island effect and thus pose an increased threat to the health of the population. Knowledge of urban thermal gradients and their determinants with a view to reducing urban overheating is therefore a priority, as is the identification of the most vulnerable people, with the aim of global management of the risk of heat waves in order to put in place targeted and coordinated public planning and health policies. This PhD research in geography and planning thus focuses on the reasons for this urban overheating and the modelling of the associated thermal gradients on the areas of Lyon and Tokyo. This work is supplemented by an analysis of socio-economic and physiological vulnerabilities to high temperatures in order to propose risk analyses with the aim of providing guidelines for the construction of an intelligent and sustainable city. The methodology addressed in this manuscript is based on a multidisciplinary approach, at the interface of social and physical geography, with a spatial and geostatistical treatment and analysis on the one hand, and a social approach in the determination of territorial vulnerabilities on the other. In this respect, this research work is based on international literature, both for modelling air temperature and for determining physiological and socio-economic vulnerabilities. The first is determined through the use of mobile measurements, participatory measurements and satellite and LiDAR data. Subsequently, the use of regression models and machine learning enables the modelling of the urban microclimate. In a complementary approach, the assessment of physiological and socio-economic vulnerabilities emphasises the use of the Analytic Hierarchy Process, which is a method of decision support and taking into account the opinions of experts from the medical world, and the use of principal component analysis. The results obtained on air temperature modelling are faced with vulnerabilities, in order to elaborate risk maps related to urban overheating by proposing in particular two innovative indicators, the Heat Physiological Risk Index and the Heat Socio-economic Risk Index. In this context of climate change, these analytical outputs can contribute to improving the design of land use planning and associated requalifications in the two study areas with a view to limiting urban overheating

Impacts des principales requalifications urbaines lyonnaises sur l’Îlot de Chaleur Urbain de Surface

International audienc

Complementarity of temperature acquisition techniques in urban environment (Lyon, France): satellite data, participative measures and mental maps

International audienc

La combinaison de l’image satellitaire avec les données citoyennes pour la mesure de l’îlot de chaleur urbain

International audienc

Thermal comfort modeling in crowded and business areas in the city center of Lyon (France) by using thermal, optical and 3D data

International audienc

Integrating Satellite-Derived Data as Spatial Predictors in Multiple Regression Models to Enhance the Knowledge of Air Temperature Patterns

With the phenomenon of urban heat island and thermal discomfort felt in urban areas, exacerbated by climate change, it is necessary to best estimate the air temperature in every part of an area, especially in the context of the on-going rationalization weather stations network. In addition, the comprehension of air temperature patterns is essential for multiple applications in the fields of agriculture, hydrology, land development or public health. Thus, this study proposes to estimate the air temperature from 28 explanatory variables, using multiple linear regressions. The innovation of this study is to integrate variables from remote sensing into the model in addition to the variables traditionally used like the ones from the Land Use Land Cover. The contribution of spectral indices is significant and makes it possible to improve the quality of the prediction model. However, modeling errors are still present. Their locations and magnitudes are analyzed. However, although the results provided by modelling are of good quality in most cases, particularly thanks to the introduction of explanatory variables from remote sensing, this can never replace dense networks of ground-based measurements. Nevertheless, the methodology presented, applicable to any territory and not requiring specific computer resources, can be highly useful in many fields, particularly for urban planners