Are fairness metric scores enough to assess discrimination biases in machine learning?

This paper presents novel experiments shedding light on the shortcomings of current metrics for assessing biases of gender discrimination made by machine learning algorithms on textual data. We focus on the Bios dataset, and our learning task is to predict the occupation of individuals, based on their biography. Such prediction tasks are common in commercial Natural Language Processing (NLP) applications such as automatic job recommendations. We address an important limitation of theoretical discussions dealing with group-wise fairness metrics: they focus on large datasets, although the norm in many industrial NLP applications is to use small to reasonably large linguistic datasets for which the main practical constraint is to get a good prediction accuracy. We then question how reliable are different popular measures of bias when the size of the training set is simply sufficient to learn reasonably accurate predictions. Our experiments sample the Bios dataset and learn more than 200 models on different sample sizes. This allows us to statistically study our results and to confirm that common gender bias indices provide diverging and sometimes unreliable results when applied to relatively small training and test samples. This highlights the crucial importance of variance calculations for providing sound results in this field.Comment: Accepted for publication at Third Workshop on Trustworthy Natural Language Processing, ACL 202

IL-6 supports the generation of human long-lived plasma cells in combination with either APRIL or stromal cell-soluble factors.

International audienceThe recent understanding of plasma cell (PC) biology has been obtained mainly from murine models. The current concept is that plasmablasts home to the BM and further differentiate into long-lived PCs (LLPCs). These LLPCs survive for months in contact with a complex niche comprising stromal cells (SCs) and hematopoietic cells, both producing recruitment and survival factors. Using a multi-step culture system, we show here the possibility to differentiate human memory B cells into LLPCs surviving for at least 4 months in vitro and producing immunoglobulins continuously. A remarkable feature is that IL-6 is mandatory to generate LLPCs in vitro together with either APRIL or soluble factors produced by SCs, unrelated to APRIL/BAFF, SDF-1, or IGF-1. These LLPCs are out of the cell cycle, express highly PC transcription factors and surface markers. This model shows a remarkable robustness of human LLPCs, which can survive and produce highly immunoglobulins for months in vitro without the contact with niche cells, providing the presence of a minimal cocktail of growth factors and nutrients. This model should be useful to understand further normal PC biology and its deregulation in premalignant or malignant PC disorders

The ArT\'eMiS wide-field submillimeter camera: preliminary on-sky performances at 350 microns

ArTeMiS is a wide-field submillimeter camera operating at three wavelengths simultaneously (200, 350 and 450 microns). A preliminary version of the instrument equipped with the 350 microns focal plane, has been successfully installed and tested on APEX telescope in Chile during the 2013 and 2014 austral winters. This instrument is developed by CEA (Saclay and Grenoble, France), IAS (France) and University of Manchester (UK) in collaboration with ESO. We introduce the mechanical and optical design, as well as the cryogenics and electronics of the ArTeMiS camera. ArTeMiS detectors are similar to the ones developed for the Herschel PACS photometer but they are adapted to the high optical load encountered at APEX site. Ultimately, ArTeMiS will contain 4 sub-arrays at 200 microns and 2x8 sub-arrays at 350 and 450 microns. We show preliminary lab measurements like the responsivity of the instrument to hot and cold loads illumination and NEP calculation. Details on the on-sky commissioning runs made in 2013 and 2014 at APEX are shown. We used planets (Mars, Saturn, Uranus) to determine the flat-field and to get the flux calibration. A pointing model was established in the first days of the runs. The average relative pointing accuracy is 3 arcsec. The beam at 350 microns has been estimated to be 8.5 arcsec, which is in good agreement with the beam of the 12 m APEX dish. Several observing modes have been tested, like On-The-Fly for beam-maps or large maps, spirals or raster of spirals for compact sources. With this preliminary version of ArTeMiS, we concluded that the mapping speed is already more than 5 times better than the previous 350 microns instrument at APEX. The median NEFD at 350 microns is 600 mJy.s1/2, with best values at 300 mJy.s1/2. The complete instrument with 5760 pixels and optimized settings will be installed during the first half of 2015.Comment: 11 pages, 11 figures. Presented at SPIE Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy VII, June 24, 2014. To be published in Proceedings of SPIE Volume 915

The BLM helicase is a new therapeutic target in multiple myeloma involved in replication stress survival and drug resistance

Multiple myeloma (MM) is a hematologic cancer characterized by accumulation of malignant plasma cells in the bone marrow. To date, no definitive cure exists for MM and resistance to current treatments is one of the major challenges of this disease. The DNA helicase BLM, whose depletion or mutation causes the cancer-prone Bloom’s syndrome (BS), is a central factor of DNA damage repair by homologous recombination (HR) and genomic stability maintenance. Using independent cohorts of MM patients, we identified that high expression of BLM is associated with a poor outcome with a significant enrichment in replication stress signature. We provide evidence that chemical inhibition of BLM by the small molecule ML216 in HMCLs (human myeloma cell lines) leads to cell cycle arrest and increases apoptosis, likely by accumulation of DNA damage. BLM inhibition synergizes with the alkylating agent melphalan to efficiently inhibit growth and promote cell death in HMCLs. Moreover, ML216 treatment re-sensitizes melphalan-resistant cell lines to this conventional therapeutic agent. Altogether, these data suggest that inhibition of BLM in combination with DNA damaging agents could be of therapeutic interest in the treatment of MM, especially in those patients with high BLM expression and/or resistance to melphalan

Growth factors in multiple myeloma: a comprehensive analysis of their expression in tumor cells and bone marrow environment using Affymetrix microarrays

<p>Abstract</p> <p>Background</p> <p>Multiple myeloma (MM) is characterized by a strong dependence of the tumor cells on their microenvironment, which produces growth factors supporting survival and proliferation of myeloma cells (MMC). In the past few years, many myeloma growth factors (MGF) have been described in the literature. However, their relative importance and the nature of the cells producing MGF remain unidentified for many of them.</p> <p>Methods</p> <p>We have analysed the expression of 51 MGF and 36 MGF receptors (MGFR) using Affymetrix microarrays throughout normal plasma cell differentiation, in MMC and in cells from the bone marrow (BM) microenvironment (CD14, CD3, polymorphonuclear neutrophils, stromal cells and osteoclasts).</p> <p>Results</p> <p>4/51 MGF and 9/36 MGF-receptors genes were significantly overexpressed in plasmablasts (PPC) and BM plasma cell (BMPC) compared to B cells whereas 11 MGF and 11 MGFR genes were overexpressed in BMPC compared to PPC. 3 MGF genes (AREG, NRG3, Wnt5A) and none of the receptors were significantly overexpressed in MMC versus BMPC. Furthermore, 3/51 MGF genes were overexpressed in MMC compared to the the BM microenvironment whereas 22/51 MGF genes were overexpressed in one environment subpopulation compared to MMC.</p> <p>Conclusions</p> <p>Two major messages arise from this analysis 1) The majority of MGF genes is expressed by the bone marrow environment. 2) Several MGF and their receptors are overexpressed throughout normal plasma cell differentiation. This study provides an extensive and comparative analysis of MGF expression in plasma cell differentiation and in MM and gives new insights in the understanding of intercellular communication signals in MM.</p

Challenges and perspectives for naming lipids in the context of lipidomics

Introduction: Lipids are key compounds in the study of metabolism and are increasingly studied in biology projects. It is a very broad family that encompasses many compounds, and the name of the same compound may vary depending on the community where they are studied. Objectives: In addition, their structures are varied and complex, which complicates their analysis. Indeed, the structural resolution does not always allow a complete level of annotation so the actual compound analysed will vary from study to study and should be clearly stated. For all these reasons the identification and naming of lipids is complicated and very variable from one study to another, it needs to be harmonized. Methods & Results: In this position paper we will present and discuss the different way to name lipids (with chemoinformatic and semantic identifiers) and their importance to share lipidomic results. Conclusion: Homogenising this identification and adopting the same rules is essential to be able to share data within the community and to map data on functional networks