Quantification of short and long asbestos fibers to assess asbestos exposure: a review of fiber size toxicity.

International audienceThe fibrogenicity and carcinogenicity of asbestos fibers are dependent on several fiber parameters including fiber dimensions. Based on the WHO (World Health Organization) definition, the current regulations focalise on long asbestos fibers (LAF) (Length: L ≥ 5 μm, Diameter: D  3). However air samples contain short asbestos fibers (SAF) (L < 5 μm). In a recent study we found that several air samples collected in buildings with asbestos containing materials (ACM) were composed only of SAF, sometimes in a concentration of ≥10 fibers.L-1. This exhaustive review focuses on available information from peer-review publications on the size-dependent pathogenetic effects of asbestos fibers reported in experimental in vivo and in vitro studies. In the literature, the findings that SAF are less pathogenic than LAF are based on experiments where a cut-off of 5 μm was generally made to differentiate short from long asbestos fibers. Nevertheless, the value of 5 μm as the limit for length is not based on scientific evidence, but is a limit for comparative analyses. From this review, it is clear that the pathogenicity of SAF cannot be completely ruled out, especially in high exposure situations. Therefore, the presence of SAF in air samples appears as an indicator of the degradation of ACM and inclusion of their systematic search should be considered in the regulation. Measurement of these fibers in air samples will then make it possible to identify pollution and anticipate health risk

Impairment of NO-Dependent Relaxation in Intralobar Pulmonary Arteries: Comparison of Urban Particulate Matter and Manufactured Nanoparticles

International audienceBACKGROUND AND OBJECTIVES: Because pulmonary circulation is the primary vascular target of inhaled particulate matter (PM), and nitric oxide is a major vasculoprotective agent, in this study we investigated the effect of various particles on the NO-cyclic guanosine monophosphate (cGMP) pathway in pulmonary arteries. METHODS: We used intrapulmonary arteries and/or endothelial cells, either exposed in vitro to particles or removed from PM-instilled animals for assessment of vasomotricity, cGMP and reactive oxygen species (ROS) levels, and cytokine/chemokine release. RESULTS: Endothelial NO-dependent relaxation and cGMP accumulation induced by acetylcholine (ACh) were both decreased after 24 hr exposure of rat intrapulmonary arteries to standard reference material 1648 (SRM1648; urban PM). Relaxation due to NO donors was also decreased by SRM1648, whereas responsiveness to cGMP analogue remained unaffected. Unlike SRM1648, ultrafine carbon black and ultrafine and fine titanium dioxide (TiO2) manufactured particles did not impair NO-mediated relaxation. SRM1648-induced decrease in relaxation response to ACh was prevented by dexamethasone (an anti-inflammatory agent) but not by antioxidants. Accordingly, SRM1648 increased the release of proinflammatory mediators (tumor necrosis factor-alpha, interleukin-8) from intrapulmonary arteries or pulmonary artery endothelial cells, but did not elevate ROS levels within intrapulmonary arteries. Decreased relaxation in response to ACh was also evidenced in intrapulmonary arteries removed from rats intratracheally instilled with SRM1648, but not with fine TiO2. CONCLUSION: In contrast to manufactured particles (including nanoparticles), urban PM impairs NO but not cGMP responsiveness in intrapulmonary arteries. We attribute this effect to oxidative-stress-independent inflammatory response, resulting in decreased guanylyl cyclase activation by NO. Such impairment of the NO pathway may contribute to urban-PM-induced cardiovascular dysfunction

Interstitial Lung Abnormalities Detected by CT in Asbestos-Exposed Subjects Are More Likely Associated to Age

OBJECTIVE: the aim of this study was to evaluate the association between interstitial lung abnormalities, asbestos exposure and age in a population of retired workers previously occupationally exposed to asbestos. METHODS: previously occupationally exposed former workers to asbestos eligible for a survey conducted between 2003 and 2005 in four regions of France, underwent chest CT examinations and pulmonary function testing. Industrial hygienists evaluated asbestos exposure and calculated for each subject a cumulative exposure index (CEI) to asbestos. Smoking status information was also collected in this second round of screening. Expert radiologists performed blinded independent double reading of chest CT-scans and classified interstitial lung abnormalities into: no abnormality, minor interstitial findings, interstitial findings inconsistent with UIP, possible or definite UIP. In addition, emphysema was assessed visually (none, minor: emphysema 50% of the lung). Logistic regression models adjusted for age and smoking were used to assess the relationship between interstitial lung abnormalities and occupational asbestos exposure. RESULTS: the study population consisted of 2157 male subjects. Interstitial lung abnormalities were present in 365 (16.7%) and emphysema in 444 (20.4%). Significant positive association was found between definite or possible UIP pattern and age (OR adjusted =1.08 (95% CI: 1.02-1.13)). No association was found between interstitial abnormalities and CEI or the level of asbestos exposure. CONCLUSION: presence of interstitial abnormalities at HRCT was associated to aging but not to cumulative exposure index in this cohort of former workers previously occupationally exposed to asbestos

Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects

OBJECTIVE: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos. METHODS: CT scans of former workers previously occupationally exposed to asbestos who participated in the multicenter APEXS (Asbestos PostExposure Survey) study were collected retrospectively between 2010 and 2017 during the second and the third rounds of the survey. A hundred and forty-one participants with pleural plaques identified by expert radiologists at the 2nd and the 3rd CT screenings were included. Maximum Intensity Projection (MIP) with 5 mm thickness was used to reduce the number of CT slices for manual delineation. A Deep Learning AI algorithm using 2D-convolutional neural networks was trained with 8280 images from 138 CT scans of 69 participants for the semantic labeling of Pleural Plaques (PP). In all, 2160 CT images from 36 CT scans of 18 participants were used for AI testing versus ground-truth labels (GT). The clinical validity of the method was evaluated longitudinally in 54 participants with pleural plaques. RESULTS: The concordance correlation coefficient (CCC) between AI-driven and GT was almost perfect (>0.98) for the volume extent of both PP and calcified PP. The 2D pixel similarity overlap of AI versus GT was good (DICE = 0.63) for PP, whether they were calcified or not, and very good (DICE = 0.82) for calcified PP. A longitudinal comparison of the volumetric extent of PP showed a significant increase in PP volumes (p < 0.001) between the 2nd and the 3rd CT screenings with an average delay of 5 years. CONCLUSIONS: AI allows a fully automated volumetric quantification of pleural plaques showing volumetric progression of PP over a five-year period. The reproducible PP volume evaluation may enable further investigations for the comprehension of the unclear relationships between pleural plaques and both respiratory function and occurrence of thoracic malignancy

Development of a Questionnaire for the Search for Occupational Causes in Patients with Non-Hodgkin Lymphoma: The RHELYPRO Study

Non-Hodgkin lymphoma (NHL), multiple myeloma and chronic lymphocytic leukemia are possibly related to environmental and/or occupational exposure. The primary objective of this study was to develop a questionnaire for screening patients with these blood disorders who might benefit from a specialized consultation for possible recognition of the disease as an occupational disease. The study included 205 subjects (male gender, 67.3%; mean age, 60 years; NHL, 78.5%). The questionnaire performed very satisfactorily in identifying the exposures most frequently retained by experts for their potential involvement in the occurrence of NHL. Its sensitivity and specificity in relation to the final expertise were 96% and 96% for trichloroethylene, 85% and 82% for benzene, 78% and 87% for solvents other than trichloroethylene and dichloromethane, 87% and 95% for pesticides, respectively. Overall, 15% of the subjects were invited to ask National Social Insurance for compensation as occupational disease. These declarations concerned exposure to pesticides (64%), solvents (trichloroethylene: 29%; benzene: 18%; other than chlorinated solvents: 18%) and sometimes multiple exposures. In conclusion, this questionnaire appears as a useful tool to identify NHL patients for a specialized consultation, in order to ask for compensation for occupational disease

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Rest of authors: Decky Junaedi, Robert R. Junker, Eric Justes, Richard Kabzems, Jeffrey Kane, Zdenek Kaplan, Teja Kattenborn, Lyudmila Kavelenova, Elizabeth Kearsley, Anne Kempel, Tanaka Kenzo, Andrew Kerkhoff, Mohammed I. Khalil, Nicole L. Kinlock, Wilm Daniel Kissling, Kaoru Kitajima, Thomas Kitzberger, Rasmus Kjøller, Tamir Klein, Michael Kleyer, Jitka Klimešová, Joice Klipel, Brian Kloeppel, Stefan Klotz, Johannes M. H. Knops, Takashi Kohyama, Fumito Koike, Johannes Kollmann, Benjamin Komac, Kimberly Komatsu, Christian König, Nathan J. B. Kraft, Koen Kramer, Holger Kreft, Ingolf Kühn, Dushan Kumarathunge, Jonas Kuppler, Hiroko Kurokawa, Yoko Kurosawa, Shem Kuyah, Jean-Paul Laclau, Benoit Lafleur, Erik Lallai, Eric Lamb, Andrea Lamprecht, Daniel J. Larkin, Daniel Laughlin, Yoann Le Bagousse-Pinguet, Guerric le Maire, Peter C. le Roux, Elizabeth le Roux, Tali Lee, Frederic Lens, Simon L. Lewis, Barbara Lhotsky, Yuanzhi Li, Xine Li, Jeremy W. Lichstein, Mario Liebergesell, Jun Ying Lim, Yan-Shih Lin, Juan Carlos Linares, Chunjiang Liu, Daijun Liu, Udayangani Liu, Stuart Livingstone, Joan Llusià, Madelon Lohbeck, Álvaro López-García, Gabriela Lopez-Gonzalez, Zdeňka Lososová, Frédérique Louault, Balázs A. Lukács, Petr Lukeš, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki Mäkelä, Harri Mäkinen, Ana Claudia Mendes Malhado, Azim Mallik, Peter Manning, Stefano Manzoni, Zuleica Marchetti, Luca Marchino, Vinicius Marcilio-Silva, Eric Marcon, Michela Marignani, Lars Markesteijn, Adam Martin, Cristina Martínez-Garza, Jordi Martínez-Vilalta, Tereza Mašková, Kelly Mason, Norman Mason, Tara Joy Massad, Jacynthe Masse, Itay Mayrose, James McCarthy, M. Luke McCormack, Katherine McCulloh, Ian R. McFadden, Brian J. McGill, Mara Y. McPartland, Juliana S. Medeiros, Belinda Medlyn, Pierre Meerts, Zia Mehrabi, Patrick Meir, Felipe P. L. Melo, Maurizio Mencuccini, Céline Meredieu, Julie Messier, Ilona Mészáros, Juha Metsaranta, Sean T. Michaletz, Chrysanthi Michelaki, Svetlana Migalina, Ruben Milla, Jesse E. D. Miller, Vanessa Minden, Ray Ming, Karel Mokany, Angela T. Moles, Attila Molnár V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka Moravcová, Alvaro Moreno-Martínez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina Müller, François Munoz, Isla H. Myers-Smith, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Ayyappan Narayanan, Balachandran Natesan, Luka Negoita, Andrew S. Nelson, Eike Lena Neuschulz, Jian Ni, Georg Niedrist, Jhon Nieto, Ülo Niinemets, Rachael Nolan, Henning Nottebrock, Yann Nouvellon, Alexander Novakovskiy, The Nutrient Network, Kristin Odden Nystuen, Anthony O'Grady, Kevin O'Hara, Andrew O'Reilly-Nugent, Simon Oakley, Walter Oberhuber, Toshiyuki Ohtsuka, Ricardo Oliveira, Kinga Öllerer, Mark E. Olson, Vladimir Onipchenko, Yusuke Onoda, Renske E. Onstein, Jenny C. Ordonez, Noriyuki Osada, Ivika Ostonen, Gianluigi Ottaviani, Sarah Otto, Gerhard E. Overbeck, Wim A. Ozinga, Anna T. Pahl, C. E. Timothy Paine, Robin J. Pakeman, Aristotelis C. Papageorgiou, Evgeniya Parfionova, Meelis Pärtel, Marco Patacca, Susana Paula, Juraj Paule, Harald Pauli, Juli G. Pausas, Begoña Peco, Josep Penuelas, Antonio Perea, Pablo Luis Peri, Ana Carolina Petisco-Souza, Alessandro Petraglia, Any Mary Petritan, Oliver L. Phillips, Simon Pierce, Valério D. Pillar, Jan Pisek, Alexandr Pomogaybin, Hendrik Poorter, Angelika Portsmuth, Peter Poschlod, Catherine Potvin, Devon Pounds, A. Shafer Powell, Sally A. Power, Andreas Prinzing, Giacomo Puglielli, Petr Pyšek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime Réjou-Méchain, Victor Resco de Dios, Sabina Ribeiro, Sarah Richardson, Kersti Riibak, Matthias C. Rillig, Fiamma Riviera, Elisabeth M. R. Robert, Scott Roberts, Bjorn Robroek, Adam Roddy, Arthur Vinicius Rodrigues, Alistair Rogers, Emily Rollinson, Victor Rolo, Christine Römermann, Dina Ronzhina, Christiane Roscher, Julieta A. Rosell, Milena Fermina Rosenfield, Christian Rossi, David B. Roy, Samuel Royer-Tardif, Nadja Rüger, Ricardo Ruiz-Peinado, Sabine B. Rumpf, Graciela M. Rusch, Masahiro Ryo, Lawren Sack, Angela Saldaña, Beatriz Salgado-Negret, Roberto Salguero-Gomez, Ignacio Santa-Regina, Ana Carolina Santacruz-García, Joaquim Santos, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Matthias Schleuning, Bernhard Schmid, Marco Schmidt, Sylvain Schmitt, Julio V. Schneider, Simon D. Schowanek, Julian Schrader, Franziska Schrodt, Bernhard Schuldt, Frank Schurr, Galia Selaya Garvizu, Marina Semchenko, Colleen Seymour, Julia C. Sfair, Joanne M. Sharpe, Christine S. Sheppard, Serge Sheremetiev, Satomi Shiodera, Bill Shipley, Tanvir Ahmed Shovon, Alrun Siebenkäs, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, Grégory Sonnier, Mia Vedel Sørensen, Enio Egon Sosinski Jr, Nadejda A. Soudzilovskaia, Alexandre F. Souza, Marko Spasojevic, Marta Gaia Sperandii, Amanda B. Stan, James Stegen, Klaus Steinbauer, Jörg G. Stephan, Frank Sterck, Dejan B. Stojanovic, Tanya Strydom, Maria Laura Suarez, Jens-Christian Svenning, Ivana Svitková, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, Rubén Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, Lubomír Tichý, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, Péter Török, Tonantzin Tarin, José M. Torres-Ruiz, Béla Tóthmérész, Martina Treurnicht, Valeria Trivellone, Franck Trolliet, Volodymyr Trotsiuk, James L. Tsakalos, Ioannis Tsiripidis, Niklas Tysklind, Toru Umehara, Vladimir Usoltsev, Matthew Vadeboncoeur, Jamil Vaezi, Fernando Valladares, Jana Vamosi, Peter M. van Bodegom, Michiel van Breugel, Elisa Van Cleemput, Martine van de Weg, Stephni van der Merwe, Fons van der Plas, Masha T. van der Sande, Mark van Kleunen, Koenraad Van Meerbeek, Mark Vanderwel, Kim André Vanselow, Angelica Vårhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime Villacís, Cyrille Violle, Pandi Vivek, Katrin Wagner, Matthew Waldram, Anthony Waldron, Anthony P. Walker, Martyn Waller, Gabriel Walther, Han Wang, Feng Wang, Weiqi Wang, Harry Watkins, James Watkins, Ulrich Weber, James T. Weedon, Liping Wei, Patrick Weigelt, Evan Weiher, Aidan W. Wells, Camilla Wellstein, Elizabeth Wenk, Mark Westoby, Alana Westwood, Philip John White, Mark Whitten, Mathew Williams, Daniel E. Winkler, Klaus Winter, Chevonne Womack, Ian J. Wright, S. Joseph Wright, Justin Wright, Bruno X. Pinho, Fabiano Ximenes, Toshihiro Yamada, Keiko Yamaji, Ruth Yanai, Nikolay Yankov, Benjamin Yguel, Kátia Janaina Zanini, Amy E. Zanne, David Zelený, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia Ziemińska, Chad R. Zirbel, Georg Zizka, Irié Casimir Zo-Bi, Gerhard Zotz, Christian Wirth.Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); GIS ‘Climat, Environnement et Société'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc

Altérations génétiques des tumeurs respiratoires humaines et murines après exposition à des fibres minérales

L’objectif était de mieux définir les relations entre l’exposition à certaines fibres minérales et les anomalies génétiques somatiques associées à la transformation tumorale de cellules de l’appareil respiratoire. Deux études indépendantes ont été conduites à partir du modèle murin Nf2+/- de mésothéliome malin (MM) développé dans le laboratoire, exposé par inoculation intrapéritonéale à des fibres d’amiante crocidolite (souris abs-Nf2+/- et abs-Nf2+/+) et à des fibres céramiques réfractaires (FCR) (souris ceram-Nf2+/-).Ce choix a été fondé selon une stratégie raisonnée à partir de la connaissance des anomalies génétiques observées dans le MM. La validité de ce modèle a été vérifiée en comparant les MM murins et humains. Des MM ont été induits par le crocidolite chez des souris abs-Nf2+/- et abs-Nf2+/+. Les souris abs-Nf2+/- ont significativement développé plus de MM que les souris abs-Nf2+/+. Les caractéristiques histologiques des MM murins sont analogues aux MM humains, avec des altérations génétiques similaires, en terme de fréquence et de mécanismes d’inactivation (mutations ponctuelles pour le gène TP53, délétions pour les gènes NF2 et P16/CDKN2A). Ce modèle murin a été ensuite utilisé pour évaluer la toxicité de FCR. Les souris ceram-Nf2+/- ont développé des MM similaires aux MM humains du point de vue histologique et moléculaire. Ainsi, le profil des altérations génétiques des MM murins ceram-Nf2+/- est semblable à celui des MM murins abs-Nf2+/- et abs-Nf2+/+, et humains. Les cellules mésotheliales des souris exposées aux FCR et à l’amiante semblent suivre les mêmes voies de transformation néoplasique. Une étude à la recherche d’altérations génétiques de ces 3 gènes et des gènes Ki-ras et EGFr fréquemment mutés dans le cancer broncho-pulmonaire (CBP) a été conduite à partir de cas de CBP sélectionnés (50 sujets exposés à l’amiante (E+) et 50 sujets non exposés (E-) appariés sur l’âge, le sexe, le type histologique et le tabagisme) provenant d’une série de cas opérés. A l’instar du MM, l’analyse du gène P16/CDKN2A suggère que le mécanisme d’inactivation pourrait être différent chez les sujets E+ (par délétion) par rapport aux sujets E- (par hyperméthylation du promoteur), indépendamment de l’âge et du tabagisme. Deux SNP (rs12947788 et rs12951053) du gène TP53 sont plus fréquemment retrouvés chez les sujets E+. En revanche, aucune différence significative n’est retrouvée pour les autres gènes entre ces 2 groupes. Ainsi, les mutations du gène NF2 dans le MM seraient plus liées à une spécificité cellulaire et à une fonction particulière de la protéine nf2 dans ces cellulesRésumé en anglais non communiqu

Les BPCO ou bronchopneumopathies chroniques obstructives

National audienceIl existe d’après le rapport Diricq en 2011180, un contraste très important entre le nombre annuel de cas incidents de BPCO professionnelles, estimé entre 75.000 et 112.500 cas en France et le nombre très faible de cas reconnus en maladie professionnelle, susceptibles de bénéficier d'une retraite anticipée (quelque dizaine de cas par an, tous régimes de protection sociale confondus). Une meilleure évaluation de la pénibilité liée à l’exposition à des aérocontaminants dans le cadre réglementaire de la pénibilité aux agents chimiques dangereux est donc nécessaire

Cancer de vessie et expositions professionnelles (étude cas-témoins multicentrique en Ile de France)

PARIS6-Bibl.Pitié-Salpêtrie (751132101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF