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The aim of the study was to optimize the synthesis of diclofenac derivative with hydrazones structure in order to obtain higher yields and purity by variation of different parameters such as: ratio between reactants, solvent, catalyst, temperature, time of reaction and method used. The anti-inflammatory effects of diclofenac derivatives were evaluated using in vitro assays: albumin denaturation and erythrocyte membrane stability. The obtained results showed that the effect of the tested derivatives is increasing with the concentration, the best results being obtained at the concentration of 125 �g/mL (albumin denaturation assay), respectively 111.11 �g/mL (erythrocyte membrane stability assay). The most active compound was 4d which showed the highest inhibition effect on albumin denaturation and an appreciable effect on erythrocyte membrane stability, in comparation with diclofenac, used as drug reference.

Chromosomal diseases are heterogeneous conditions with complex phenotypes, which include also epileptic seizures. Each chromosomal syndrome has a range of specific characteristics regarding the type of seizures, EEG findings and specific response to antiepileptic drugs, significant in the context of the respective genetic etiology. Therefore, it is very important to know these particularities, in order to avoid an exacerbation of seizures or some side effects. In this paper we will present a review of the epileptic seizures and antiepileptic treatment in some of the most common chromosomal syndromes.

Combustion of hydrocarbons produces both particulate- and gas-phase emissions responsible for major impacts on atmospheric chemistry and human health. Ascertaining the impact of these emissions, especially on human health, is not straightforward because of our relatively poor knowledge of how chemical compounds are partitioned between the particle and gas phases. Accordingly, we propose coupling a two-filter sampling method with a multi-technique analytical approach to fully characterize the particulate- and gas-phase compositions of combustion by-products. The two-filter sampling method is designed to retain particulate matter (elemental carbon possibly covered in a surface layer of adsorbed molecules) on a first quartz fiber filter while letting the gas phase pass through and then trap the most volatile components on a second black-carbon-covered filter. All samples thus collected are subsequently subjected to a multi-technique analytical protocol involving two-step laser mass spectrometry (L2MS), secondary ion mass spectrometry (SIMS), and micro-Raman spectroscopy. Using the combination of this two-filter sampling–multi-technique approach in conjunction with advanced statistical methods, we are able to unravel distinct surface chemical compositions of aerosols generated with different set points of a miniCAST burner. Specifically, we successfully discriminate samples by their volatile, semi-volatile, and non-volatile polycyclic aromatic hydrocarbon (PAH) contents and reveal how subtle changes in combustion parameters affect particle surface chemistry.

Otoliths are a part of the fish inner ear involved in sound reception, balance perception and orientation. Saggital otoliths of teleost fish mainly consist of calcium carbonate in the form of aragonite. However, there are abnormal otoliths that contain other polymorphs, such as calcite, vaterite or their combinations. This preliminary study represents the first record and investigation of Lepidorhombus boscii otoliths including those irregularly shaped and characterized by surface deformations. These can arise due to stressful conditions, high population density, temperature fluctuations, disease or pollution, which can cause structural or physiological changes that affect the formation of otoliths. In addition to morphological features, polymorphs of calcium carbonate have an influence on the elemental composition of otoliths. The morphology and chemical composition of L. boscii saggital otolith were studied by scanning electron microscopy (SEM), X-ray diffraction (XRD) and by two step laser desorption ionization mass spectrometry (L2MS). L2MS was used to analyse the surface chemical composition of the otoliths, confirming the presence of inorganic and organic compounds in the otolith matrix. Tuning the desorption fluencies to maximize the metal containing components (K, Ca, Cu, Ag, Sr), shows an abundance of pure metallic, oxidized and hydroxidized species. XRD was used to analyse the crystal structure, while SEM was used to photograph the surfaces of normal and abnormal otoliths (aragonite and calcite) between males and females. This research provided a preliminary insight into the concentrations of chemical elements deposited on the otoliths of individuals of this species in the central Adriatic Sea. Although the number of analyzed samples is small, the results are promising. They represent a starting point for the future research, that should be based on a larger number of samples from more locations These results could be used to get a better insight into movement patterns and possibly for determination of the origin of this species.

This article introduces a compressive sensing (CS)-based approach for increasing bistatic synthetic aperture radar (SAR) imaging quality in the context of a multiaperture acquisition. The analyzed data were recorded over an opportunistic bistatic setup including a stationary ground-based-receiver opportunistic C-band bistatic SAR differential interferometry (COBIS) and Sentinel-1 C-band transmitter. Since the terrain observation by progressive scans (TOPS) mode is operated, the receiver can record synchronization pulses and echoed signals from the scene during many apertures. Hence, it is possible to improve the azimuth resolution by exploiting the multiaperture data. The recorded data are not contiguous and a naive integration of the chopped azimuth phase history would generate undesired grating lobes. The proposed processing scheme exploits the natural sparsity characterizing the illuminated scene. For azimuth profiles recovery greedy, convex, and nonconvex CS solvers are analyzed. The sparsifying basis/dictionary is constructed using the synthetically generated azimuth chirp derived considering Sentinel-1 orbital parameters and COBIS position. The chirped-based CS performance is further put in contrast with a Fourier-based CS method and an autoregressive model for signal reconstruction in terms of scene extent limitations and phase restoration efficiency. Furthermore, the analysis of different receiver-looking scenarios conducted to the insertion in the processing chain of a direct and an inverse Keystone transform for range cell migration (RCM) correction to cope with squinted geometries. We provide an extensive set of simulated and real-world results that prove the proposed workflow is efficient both in improving the azimuth resolution and in mitigating the sidelobes.

Les composés organiques volatils (COV) sont importants pour la production d'ozone et des précurseurs critiques des aérosols organiques secondaires dans l'atmosphère. Les activités agricoles telles que l'utilisation d'engrais minéraux, l'élevage et l'épandage de fumier animal contribuent à la pollution atmosphérique. L'épandage de fumier animal sur le sol est associé à divers polluants tels que les aérosols primaires, l'ammoniac et le sulfure d'hydrogène, ainsi qu'aux émissions de COV. Dans ce contexte, une étude expérimentale a été menée sur différents types de fumier (vache, cheval, brebis et chèvre) collectés à Grignon (Paris, France). Les échantillons ont été placés dans des chambres de simulation atmosphérique et les émissions en phase gazeuse de composés organiques volatils et leurs produits d'oxydation résultant de réactions d'ozonolyse ont été caractérisés par spectrométrie de masse. Plus de deux cents COV ont été détectés et quantifiés. Les familles de COV détectées comprenaient des composés oxygénés, azotés, soufrés, des composés azotées et oxygénées et des hydrocarbures. Les composés oxygénés se sont avérés être les COV dominants dans tous les échantillons. Lorsqu'ils sont exposés à l'ozone, seuls les échantillons de fumier de vache ont montré une réactivité due à la présence du scatole (C9H9N). Cependant, aucune formation de particules n'a été observée dans nos conditions expérimentales. Cela est principalement dû aux faibles émissions de SO2 des échantillons, car le SO2 et le scatole jouent un rôle clé dans la formation d'aérosols organiques secondaires. Les données expérimentales obtenues dans le cadre de cette étude aideront à améliorer les inventaires des émissions par les activités agricoles et fourniront des informations sur les COV d'origine agricole qui peuvent servir de précurseurs d'aérosols organiques secondaires en présence de photo-oxydants, comme l'ozone., Volatile organic compounds (VOCs) are significant to ozone production and critical precursors of secondary organic aerosols in the atmosphere. Agricultural activities such as the use of mineral fertilizers, livestock production and land application of animal manure contribute to atmospheric pollution. Land application of animal manure is associated with variety of pollutants such as primary aerosols, ammonia, and hydrogen sulfide as well as VOC emissions. In this context, an experimental study was carried out on different animal manures (e.g. cow, horse, sheep, and goat) taken from Grignon (Paris, France). The samples were placed in atmospheric simulation chambers and the gas phase emissions of VOCs and their oxidation products resulting from ozonolysis reactions were characterized using mass spectrometric tools. More than two hundred VOCs were detected and quantified. The detected VOCs families included oxygenated compounds, nitrogen-containing compounds, sulfur-containing compounds, nitrogen and oxygen containing compounds and hydrocarbons. Oxygenated compounds were found to be the dominating VOCs in all samples. When exposed to ozone, only cow manure samples showed reactivity due to skatole (C9H9N). However, no particle formation was observed in our experimental conditions. This is mainly explained by low SO2 emissions from the samples, as SO2 together with skatole play a key role in secondary organic aerosol formation. The experimental dataset obtained in this study will help to improve emission inventories for agricultural activities and provide deeper insights into potential VOCs that can serve as secondary organic aerosol precursors in the presence of photo-oxidants (e.g. ozone).

Attention network theory states that attention is not a unified construct but consists of three independent systems that are supported by separable distributed networks: an alerting network to deploy attentional resources in anticipation of upcoming events, an orienting network to direct attention to a cued location, and a control network to select relevant information at the expense of concurrently available information. Ample behavioral and neuroimaging evidence supports the dissociation of the three attention domains. The strong assumption that each attentional system is realized through a separable network, however, raises the question how these networks relate to the intrinsic network structure of the brain.Our understanding of brain networks has advanced majorly in the past years due to the increasing focus on brain connectivity. It is well established that the brain is intrinsically organized into several large-scale networks whose modular structure persists across task states. Existing proposals on how the presumed attention networks relate to intrinsic networks rely mostly on anecdotal and partly contradictory arguments. We addressed this issue by mapping different attention networks with highest spatial precision at the level of cifti-grayordinates. Resulting group maps were compared to the group-level topology of 23 intrinsic networks which we reconstructed from the same participants’ resting state fMRI data. We found that all attention domains recruited multiple and partly overlapping intrinsic networks and converged in the dorsal fronto-parietal and midcingulo-insular network. While we observed a preference of each attentional domain for its own set of intrinsic networks, implicated networks did not match well to those proposed in the literature. Our results indicate a necessary refinement of the attention network theory.

The role of polycyclic aromatic hydrocarbons (PAHs) in the formation of nascent soot particles in flames is well established and yet the detailed mechanisms are still not fully understood. Here we provide experimental evidence of the occurrence of dimerization of PAHs in the gas phase before soot formation in a laminar diffusion methane flame, supporting the hypothesis of stabilization of dimers through the formation of covalent bonds. The main findings of this work derive from the comparative chemical analysis of samples extracted from the gas to soot transition region of a laminar diffusion methane flame, and highlight two different groups of hydrocarbons that coexist in the same mass range, but show distinctly different behavior when processed with statistical analysis. In particular, the identified hydrocarbons are small-to-moderate size PAHs (first group) and their homo- and heterodimers stabilized by the formation of covalent bonds (second group). A comprehensive understanding of soot nucleation in flame combustion is still lacking. Here the authors identify homo- and heterodimers of small-to-moderate size polycyclic aromatic hydrocarbons in the gas to soot transition region of a laminar diffusion methane flame as viable intermediates in the soot nucleation process.

International audience; Aviation emissions are not limited to greenhouse gases like CO2 but include other gases as well, such as nitrogen oxides (NOx) or sulfur oxides (SOx) and volatile and non-volatile particulate matter (vPM and nvPM respectively). Sulfuric acid formed in the engine exhaust seems to be linked to the formation of vPM. However, the amount of sulfur present in the fuel converted to sulfuric acid in the exhaust is too small to explain the amount of vPM observed (Vancassel et al. 2004). Organic compounds emitted by the engine are among the most suitable candidates to explain the formation of vPM in the engine exhaust (Sorokin et al. 2001), but the molecular mechanisms behind this phenomenon are still unknown.

International audience; Aviation has been, before the sanitary crisis, one of the strongest growing transport sectors. Despite this crisis, this trend is predicted to continue (Neu 2020). One of the actual concerns of aviation industry is to reduce its impact on climate and air quality using for example Sustainable Aviation Fuels (SAF). As part of the UNREAL (Unveiling Nucleation mechanism in aiRcraft Engine exhAust and its Link with fuel composition) project, the objective of this work was to study and compare the chemical pattern, at a molecular level, of the gaseous and particulate phases of primary as well as secondary emissions from various aircraft fuels with distinct compositions.

In this paper are presented target displacement measurements using synthetic aperture radar interferometry, with the Pulson P440 radar module. The synthetic aperture is formed by automatically moving the radar with the help of a robotic arm. We show that by applying an appropriate interferometric phase correction, we can measure target displacement with the Pulson P440.

The influence of rare earth (RE = Dy, Gd, Yb) ion doping on the structural, magnetic and optical properties of cobalt ferrite thin films was studied. CoFe 2-x RE x O 4 (x = 0.01; 0.03; 0.05; 0.1; 0.2; 0.3) films were obtained by pulsed laser deposition on silicon substrates. The X-ray diffraction and Raman spectroscopy results on the bulk materials, which were used as targets during deposition, revealed the formation of residual phases as the concentration of RE dopant was increased. However, the annealed thin films presented diffraction lines and vibrational modes corresponding only to cobalt ferrite. A lower crystallinity of the deposited samples was observed when higher RE concentrations were used. Due to the substitution of Fe by RE elements which possess large ionic radii, the lattice parameter of the thin films presented a monotonous increase. The magnetic response of the nanostructures was correlated to the magnetic moment of the RE dopant and to the structural properties of the films. The optical bandgaps derived from the reflectance spectra presented an increasing trend as the Yb and Dy concentrations were augmented.

We investigate the oscillatory regimes of the Langmuir probe current recorded for the electrical characterization of femtosecond laser-produced plasma. The influence of metallic target biasing, which can perturb the ambipolar electric field generated through the charge separation at early stages of the expansion, is also studied. Two distinct behaviors are evidenced, and they point to the existence of two plasma structures: a fast one consisting in promptly ejected highly charged particles, and a slow “tail” of thermalized particles. Theoretically, a non-differentiable model which involves two scale resolutions is developed. Assuming the principle of scale resolution superposition, the current density at global scale is expressed as the sum of the current density at Coulomb and the thermal scale resolutions, in agreement with the experimental data. Interestingly, the theoretical estimation of oscillation frequencies shows a correspondence with the filling factor hierarchy in the fractional quantum Hall effect.

International audience; Time-of-flight secondary ion mass spectrometry (ToF-SIMS) and Raman spectroscopy are used to characterize samples extracted from a laboratory methane diffusion flame at different reaction times along the flame axis in order to gain information on the soot nucleation process. Experimental results from the comparison of these techniques allow the chemical characterization of the gas to soot particles phase transition and the quantification of the hydrogen content of the sampled matter. Before soot formation, no phase separation is observed on the samples, while after soot formation, a phase separation appears with two families of PAHs and a difference in the Raman signal.

International audience

The Mars organic molecular analyzer (MOMA) of the Rosalind Franklin rover (ExoMars project) will combine laser desorption-ionization mass spectrometry (LDI-MS) and gas-chromatography mass spectrometry (GC-MS) to assess the origin of organic matter on planet Mars. In order to further assess the type of molecular information that can be retrieved with the former technique, we applied high-resolution laser two-step mass spectrometry (L2MS) to fossil organic matter of sedimentary rock from the Jurassic deposit of Orbagnoux, France. Abundant sulfur-rich microbial organic matter has been thoroughly documented in this deposit [1]. This sample has been chosen following the detection of thiophenes at Gale Crater on Mars by the Sample analysis at Mars (SAM) instrument [2]. In our L2MS instrument [3], the samples are irradiated with a pulsed desorption laser (532 or 266 nm), which generates a plume of chemical species that can be further ionized with a second orthogonal laser beam (266 nm). A radiofrequency ion guide is used to carry the ions to an orthogonal time-of-flight mass spectrometer (oToF-MS system by Fasmatech), yielding high-resolution mass spectra (m/Δm ~10000 at 128 m/z). Focusing of the desorption laser using a reflective objective and automated micro-positioning of the sample were used to generate hyperspectral raster mappings. Subsamples included solvent-extracted molecules (bitumen and maltene fractions), insoluble macromolecular organic matter (kerogen), rock powder and a polished slice. Our analyses showed that we can extract chemical information with LDI-MS from both soluble and insoluble organic fractions of the Orbagnoux samples and that various chemical families can be distinguished even in mineralized samples. Carbon clusters, including sulfurated and hydrogenated species could be detected in all subsamples. With the exception of the rock slice, polyaromatic hydrocarbons could be detected in all samples. Oxygenated molecules and alkylbenzenes could only be detected in extracts, which generated rich and intense mass spectra. Various inorganic ions were also generated in all sample fractions. Using focused desorption beams, carbon clusters (including sulfurated clusters) and inorganic species could be detected and mapped in the polished slice with [1] Mongenot, T., Derenne, S., Largeau, C., Tribovillard, N.P., Lallier-Vergès, E., Dessort, D., Connan, J., 1999. Spectroscopic, kinetic and pyrolytic studies of kerogen from the dark parallel laminae facies of the sulphur-rich Orbagnoux deposit (Upper Kimmeridgian, Jura). Org. Geochem. 30, 39–56. [2] Eigenbrode, J.L., Summons, R.E., Steele, A., Freissinet, C., Millan, M., Navarro-González, R., Sutter, B., McAdam, A.C., Franz, H.B., Glavin, D.P., Archer, P.D., Mahaffy, P.R., Conrad, P.G., Hurowitz, J.A., Grotzinger, J.P., Gupta, S., Ming, D.W., Sumner, D.Y., Szopa, C., Malespin, C., Buch, A., Coll, P., 2018. Organic matter preserved in 3-billion-year-old mudstones at Gale crater, Mars. Science (80-. ). 360, 1096–1101. [3] A. Faccinetto, P. Desgroux, M. Ziskind, E. Therssen, C. Focsa, High-sensitivitydetection of polycyclic aromatic hydrocarbons adsorbed onto soot particles using laser desorption/laser ionization/time-of-flight mass spectrometry: An approach to studying the soot inception process in low-pressure flames, Combustion and Flame 158 (2011) 227–239.

Background :Formalin-fixation and paraffin-embedding (FFPE) is the worldwide gold standard for tissue preservation and routine pathology for general and cancer diagnostics. Despite robust histopathology methods, accurate diagnostic remains difficult for certain cases. Overall, the entire process is time-consuming, labor-intensive and doesn’t reach the right sensitivity and specificity. Lipids are central players in cancer, but they are not routinely used in diagnostics because of the sample processing which limits their detection, and lipid analysis directly from unprocessed FFPE tissues has never been reported. Methods :We present a new method for cancer diagnostics based on tissue-lipidomic signatures through rapid screening of FFPE without dewaxing using Water-Assisted Laser Desorption Ionization Mass Spectrometry (WALDI-MS) and deep-learning. Results :We show on a cohort of canine and human sarcoma tissues that classification for sarcoma sub-typing is possible and enables diagnosing blind samples in less than five minutes, with over 95% probability to discriminate specific subtypes. Conclusion: We have revealed the possibility to create a rapid diagnostic platform to screen clinical FFPE tissues with minimal sample preparation for molecular pathology.

International audience; Emissions from aircraft engines impact climate and air quality in and around airports (Airbus GMF 2018, Vorster et al. 2013). There are different options available to reduce aircraft emissions, based notably on the development of sustainable fuels. The evaluation of the physicochemical characteristics of the particulate emissions from such fuels in real conditions is difficult to achieve and very expensive. The mini-CAST burner, suitable for the combustion of liquid fuel (Jing 2003), is an interesting alternative to obtain soot emissions comparable to those from aircraft engine. The design of the liquid CAST is based on the conventional propane model but here, the propane flame is used to vaporize the fuel in the combustion chamber to further generate a flame. A quenching flow of nitrogen stops the combustion reactions and a flow of dilution air accelerates emissions in the measurement line and avoids soot agglomeration. This work aimed to characterize CAST emissions for aircraft fuels of different chemical compositions and to study their stability and reproducibility.

Les aérosols organiques secondaires représentent une des principales sources d'incertitudes dans la compréhension actuelle du climat. Il est bien connu maintenant que l'agriculture contribue aux émissions d'aérosols primaires dans l'atmosphère, mais il n'existe pas d'estimation sur la formation d'aérosols organiques secondaires. Ce travail montre que les produits résiduaires organiques, et notamment les boues d'épuration, représentent une source non comptabilisée de précurseurs d'aérosols organiques secondaires par ses émissions de scatole, C9H9N. Les taux d'émission et de nucléation du scatole dus à la réactivité de l'ozone ont été déterminés en laboratoire. Nos résultats montrent que le SO2 joue un rôle clé dans l'oxydation du scatole et entraîne la formation de nouvelles particules. Les résultats présentés ici apportent de nouvelles connaissances sur un nouveau mécanisme de nucléation à partir du recyclage des produits résiduaires organiques., Secondary organic aerosols (SOA) are one of the main uncertainty sources in the current understanding of the Earth's Climate. It is known that agriculture contributes to primary aerosols emissions but there is no estimate for the secondary organic aerosol formation from precursor gas phase. Organic waste products like sewage sludge are applied to cropland as fertilizers. In this work we show that sewage sludge is an unaccounted source of nucleation precursors (skatole, C9H9N). The skatole emission and nucleation rates due to ozone reactivity were determined in the laboratory. Based on our results, SO2 plays a key role in the oxidation of skatole and leads to new particle formation. The results presented here provide new insights into this novel nucleation mechanism and aid our understanding of the organic waste agricultural recycling contribution to the aerosol balance in the atmosphere.

Cette étude vise à mettre en évidence l'impact d'un lit catalytique sur les caractéristiques physico-chimiques des particules émises par combustion d'un carburant aéronautique, c'est-à-dire leur concentration en nombre et en masse, leur distribution en taille ou leur composition chimique. En détruisant les composés organiques présents en phase volatile mais également à la surface des particules non volatiles, le catalyseur a pour effet de réduire la taille des particules ainsi que leur concentration en nombre et en masse. La caractérisation chimique a également montré son rôle dans la destruction des composés soufrés., This study aims to highlight the impact of a catalytic stripper on the physical and chemical characteristics of particles emitted by aeronautic fuel combustion, i.e. their mass and number concentration, size distribution or chemical composition. It has been shown that by destroying the organic compounds present in the volatile phase but also on the surface of non-volatile particles, the catalytic stripper has the effect of reducing the size of the particles as well as their mass and number concentration. Chemical characterization has also shown its role in the destruction of sulfur compounds.

Les émissions issues des moteurs aéronautiques ont un impact sur le climat et la qualité de l'air, dans et autour des aéroports. Il existe différentes options pour réduire les émissions des aéronefs, basées notamment sur le développement de nouveaux carburants alternatifs. Un brûleur mini-CAST, adapté à la combustion de carburants liquides, est utilisé comme source représentative et reproductible pour la production de suies similaires à celles des émissions des moteurs d'avions. Ce travail vise à caractériser physiquement et chimiquement les émissions du CAST et à étudier sa stabilité afin de pouvoir en faire usage sur des bancs d'essais et lors de futures campagnes nécessitant une source de combustion fiable., Emissions from aircraft engines impact climate and air quality in and around airports. There are different options available to reduce aircraft emissions, based in particular on the development of new sustainable fuels. A mini-CAST burner suitable for the combustion of liquid fuel is used as a representative and a reproducible source in soot production similar to aircraft engine emissions. This work aims for physico-chemical characterization of the CAST and for studying its stability in view of use on test benches.

Background: Due to sizeable batch effect challenges, published scRNA datasets remain siloed, with no tools or packages yet demonstrating an ability to integrate more than a handful of datasets into a unified atlas. This has precluded generation of a large-unified Atlas akin to The Cancer Genome Atlas (TCGA) for scRNA, despite massive demand for such a resource. Methods: We built the first training scRNA dataset that we know of that relies on using cell-type labels from published studies as a ground-truth metric. Using this dataset, we evaluated and trained a variety of models specifically for the task of integrating disparate data into a unified space. Further we developed a specific framework for evaluating how well unsupervised models perform at the task of integrating disparate data, using a new approach reliant on leave-one out validation of ‘unseen’ datasets. Using deep-learning models, that performed best on the training dataset, we scaled integration of over 50 public datasets focused on solid cancers, that collectively contain over 1000 patient samples worth of data covering over 20 indications. Results: The pan-cancer scRNA atlas produced by the above workflow is an order of magnitude larger than previous scRNA datasets and the first to span many indications alongside adjacent and separate normal tissue data. Analysis of this atlas reveals novel axes of variation in the tumor microenvironment linked to Cancer Associated Fibroblast (CAF) biology. For example: (a) We find CAF high samples vs. cancer high samples are enriched for T-cells in a naïve state; (b) Cancer vs. CAF rich samples result in variation in M2 like macrophage signatures; this compartmentalization is also seen in spatial RNA data; (c) A spectrum of CAF, perivascular, and endothelial like states is also observed indicating potential cell-type plasticity. Collectively, these observations identify novel biology and variation in the tumor microenvironment that will likely apply to many ongoing experimental projects and therapeutic programs. Conclusions: We’ve used deep-learning to build one of the largest scRNA atlases to date, and potentially the first that will progressively release models and data as an open-source package to benefit the wider community. We anticipate the ability to resolve target expression at the single cell level will greatly enhance our understanding of the tumor microenvironment, as it aids our own efforts to drug CAF biology and the tumor stroma. Citation Format: Javier Díaz-Mejía, Swechha X, Dylan Mendonca, Octavian Focsa, Chris Harvey, Mike Briskin, Sam Cooper. Unification of over 50 published single-cell RNA datasets covering over a 1000 patient samples with deep-learning reveals novel axes of tumor microenvironment variation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3813.