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A small-molecule inhibitor of the type III phosphatidylinositol 3-kinase, Vps34, binds the ATP binding pocket and prevents vesicle trafficking and autophagy. Vps34 is a phosphoinositide 3-kinase (PI3K) class III isoform that has attracted major attention over the recent years because of its role in autophagy. Herein we describe the biological characterization of SAR405, which is a low-molecular-mass kinase inhibitor of Vps34 ( K D 1.5 nM). This compound has an exquisite protein and lipid kinase selectivity profile that is explained by its unique binding mode and molecular interactions within the ATP binding cleft of human Vps34. To the best of our knowledge, this is the first potent and specific Vps34 inhibitor described so far. Our results demonstrate that inhibition of Vps34 kinase activity by SAR405 affects both late endosome-lysosome compartments and prevents autophagy. Moreover, we show that the concomitant inhibition of Vps34 and mTOR, with SAR405 and the US Food and Drug Administration–approved mTOR inhibitor everolimus, results in synergistic antiproliferative activity in renal tumor cell lines, indicating a potential clinical application in cancer.

Background: Up to 10% of patients with advanced non-small cell lung cancer (aNSCLC) have pre-existing interstitial lung disease (ILD). These patients are usually excluded from immunotherapy clinical trials. Consequently, knowledge on outcomes following nivolumab treatment in these patients remains limited. The primary objective of this study was to evaluate survival outcome following nivolumab treatment in ILD patients with pre-treated aNSCLC in the real-world setting. Patients and methods: The study included all patients with aNSCLC recorded in the French hospital database, starting nivolumab in 2015–2016. Patients were stratified by pre-existing ILD and three subgroups were studied [auto-immune or granulomatous (AI/G) ILD, other known causes ILD and idiopathic ILD]. Time to discontinuation of nivolumab treatment [time to treatment duration (TTD)] and overall survival (OS) were estimated using Kaplan–Meier survival analysis. Results: Of 10,452 aNSCLC patients initiating nivolumab, 148 (1.4%) had pre-existing ILD. Mean age at nivolumab initiation was 64.6 ± 9.4 years in ILD and 63.8 ± 9.6 years in non-ILD. Compared to non-ILD, patients in the ILD group were more frequently men (p < 0.05) and had more comorbidities (p < 0.001). There was no significant difference between ILD and non-ILD groups for median TTD (2.5 versus 2.8 months; p = 0.6) or median OS (9.6 versus 11.9 months; p = 0.1). Median OS in AI/G ILD (n = 14), other known causes ILD (n = 75), and idiopathic ILD (n = 59) were 8.6, 10.7, and 9.6 months, respectively. Conclusion: In this large cohort of aNSCLC patients with ILD, outcomes are similar to those obtained in the non-ILD population. Immunotherapy could be beneficial for these patients.

Mutations in genes involved in DNA methylation (DNAme; for example, TET2 and DNMT3A ) are frequently observed in hematological malignancies 1 – 3 and clonal hematopoiesis 4 , 5 . Applying single-cell sequencing to murine hematopoietic stem and progenitor cells, we observed that these mutations disrupt hematopoietic differentiation, causing opposite shifts in the frequencies of erythroid versus myelomonocytic progenitors following Tet2 or Dnmt3a loss. Notably, these shifts trace back to transcriptional priming skews in uncommitted hematopoietic stem cells. To reconcile genome-wide DNAme changes with specific erythroid versus myelomonocytic skews, we provide evidence in support of differential sensitivity of transcription factors due to biases in CpG enrichment in their binding motif. Single-cell transcriptomes with targeted genotyping showed similar skews in transcriptional priming of DNMT3A -mutated human clonal hematopoiesis bone marrow progenitors. These data show that DNAme shapes the topography of hematopoietic differentiation, and support a model in which genome-wide methylation changes are transduced to differentiation skews through biases in CpG enrichment of the transcription factor binding motif. Single-cell analysis of mouse hematopoietic stem cells shows that mutations in DNA methylation genes change the frequencies of erythroid versus myelomonocytic progenitors, owing to differential CpG enrichment in transcription factor binding motifs.

A large-scale survey was carried out in 336 French fields to investigate the influence of soil characteristics, climate conditions, the presence of wireworms and the identity of predominant species, agricultural practices, field history and local landscape features on the damage caused by wireworms in maize. Boosted regression trees, a statistical model originating from the field of machine learning, were fitted to survey data and then used to hierarchize and weigh the relative influence of a large set of variables on the observed damage. Our study confirmed the relevance of an early assessment of wireworm populations to forecast crop damage. Results have shown that climatic factors were also major determinants of wireworm damage, especially the soil temperature around the sowing date, with a strong decrease in damage when it exceeds 12 °C. Soil characteristics were ranked third in importance with a primary influence of pH, but also of organic matter content, and to a lesser extent of soil texture. Field history ranked next; in particular, our findings confirmed that a long-lasting meadow appeared favourable to wireworm damage. Finally, agriculture practices and landscape context (especially the presence of a meadow in the field vicinity) were also shown to influence wireworm damage but more marginally. Overall, the predicted damage appeared highly correlated with the observed one allowing us to produce the framework of a decision support system to forecast wireworm risk in maize crop.

Autoimmunity can occur when a checkpoint of self-tolerance fails. The study of familial autoimmune diseases can reveal pathophysiological mechanisms involved in more common autoimmune diseases. Here, by whole-exome/genome sequencing we identify heterozygous, autosomal-dominant, germline loss-of-function mutations in the SOCS1 gene in ten patients from five unrelated families with early onset autoimmune manifestations. The intracellular protein SOCS1 is known to downregulate cytokine signaling by inhibiting the JAK-STAT pathway. Accordingly, patient-derived lymphocytes exhibit increased STAT activation in vitro in response to interferon-γ, IL-2 and IL-4 that is reverted by the JAK1/JAK2 inhibitor ruxolitinib. This effect is associated with a series of in vitro and in vivo immune abnormalities consistent with lymphocyte hyperactivity. Hence, SOCS1 haploinsufficiency causes a dominantly inherited predisposition to early onset autoimmune diseases related to cytokine hypersensitivity of immune cells. SOCS1 is a potent suppressor of JAK-STAT signalling responses to IFNγ and γ-chain cytokines and thereby limits inflammation. Here the authors identify and characterize heterozygous SOCS1 mutations in 10 patients from 5 unrelated families with autoimmune diseases.

Characterizing tumor heterogeneity with textural indices extracted from 18F-fluorodeoxyglucose positron emission tomography (FDG PET/CT) is of growing interest in oncology. Several series showed promising results to predict survival in patients with head and neck squamous cell carcinoma (HNSCC), analyzing various tumor segmentation methods and textural indices. This preliminary study aimed at assessing the inter-observer and inter-segmentation method variability of textural indices in HNSCC pre-therapeutic FDG PET/CT. Consecutive patients with HNSCC referred in our department for a pre-therapeutic FDG PET/CT from January to March 2016 were retrospectively included. Two nuclear medicine physicians separately segmented all tumors using 3 different segmentation methods: a relative standardized uptake value (SUV) threshold (40%SUVmax), a signal-to-noise adaptive SUV threshold (DAISNE) and an image gradient-based method (PET-EDGE). SUV and metabolic tumor volume were recorded. Thirty-one textural indices were calculated using LIFEx software (www.lifexsoft.org). After correlation analysis, selected indices' inter-segmentation method and inter-observer variability were calculated. Forty-three patients (mean age 63.8±9.3y) were analyzed. Due to a too small segmented tumor volume of interest, textural analysis could not be performed in 6, 11 and 15 cases with respectively DAISNE, 40%SUVmax and PET-EDGE segmentation methods. Five independent textural indices were selected (Homogeneity, Correlation, Entropy, Busyness and LZLGE). There was a high inter-contouring method variability for Homogeneity, Correlation, Entropy and LZLGE (p<0.0001 for each index). The inter-observer reproducibility analysis revealed an excellent agreement for 3 indices (Homogeneity, Correlation and Entropy) with an intraclass correlation coefficient higher than 0.90 for the 3 methods. This preliminary study showed a high variability of 4 out of 5 textural indices (Homogeneity, Correlation, Entropy and LZLGE) extracted from pre-therapeutic FDG PET/CT in HNSCC using 3 different contouring methods. However, for each method, there was an excellent agreement between observers for 3 of these textural indices (Homogeneity, Correlation and Entropy).

Accurate fire spread modeling is essential for understanding and mitigating the impacts of wildfires. This study compares two fire spread models, FARSITE and FOREFIRE, by reconstructing the 2022 wildfire in El Pont de Vilomara, Spain. Both models use the Rothermel rate of spread (ROS) equation to model fire behavior, however, FOREFIRE employs a simplified fuel classification system, which may impact the accuracy of its predictions. Our analysis evaluates fire spread predictions in 0D (ROS), 2D (fire perimeter), and 3D (plume dynamics) simulations. Results show that FARSITE underestimates fire propagation, while FOREFIRE overestimates it, both requiring ROS adjustments to match observation. The coupled FOREFIRE-MesoNH require also ROS adjustment but better incorporates fire behavior representation.

To pursue the development and validation of coupled fire-atmosphere models, the wildland fire modeling community needs validation data sets with scenarios where fire-induced winds influence fire front behavior, and with high temporal and spatial resolution. Helicopter-borne infrared thermal cameras have the potential to monitor landscape-scale wildland fires at a high resolution during experimental burns. To extract valuable information from those observations, three-step image processing is required: (a) Orthorectification to warp raw images on a fixed coordinate system grid, (b) segmentation to delineate the fire front location out of the orthorectified images, and (c) computation of fire behavior metrics such as the rate of spread from the time-evolving fire front location. This work is dedicated to the first orthorectification step, and presents a series of algorithms that are designed to process handheld helicopter-borne thermal images collected during savannah experimental burns. The novelty in the approach lies on its recursive design, which does not require the presence of fixed ground control points, hence relaxing the constraint on field of view coverage and helping the acquisition of high-frequency observations. For four burns ranging from four to eight hectares, long-wave and mid infra red images were collected at 1 and 3 Hz, respectively, and orthorectified at a high spatial resolution (<1 m) with an absolute accuracy estimated to be lower than 4 m. Subsequent computation of fire radiative power is discussed with comparison to concurrent space-borne measurements.

Due to complex natural and anthropogenic interconnected forcings, the dynamics of suspended sediments within the ocean water column remains difficult to understand and monitor. Numerical models still lack capabilities to account for the variabilities depicted by in situ and satellite-derived datasets. Besides, the irregular space-time sampling associated with satellite sensors make crucial the development of efficient interpolation methods. Optimal Interpolation (OI) remains the state-of-the-art approach for most operational products. Due to the large increase of both in situ and satellite measurements more and more available information is coming from in situ and satellite measurements, as well as from simulation models. The emergence of data-driven schemes as possibly relevant alternatives with increased capabilities to recover finer-scale processes. In this study, we investigate and benchmark three state-of-the-art data-driven schemes, namely an EOF-based technique, an analog data assimilation scheme, and a neural network approach, with an OI scheme. We rely on an Observing System Simulation Experiment based on high-resolution numerical simulations and simulated satellite observations using real satellite sampling patterns. The neural network approach, which relies on variational data assimilation formulation for the interpolation problem, clearly outperforms both the OI and the other data-driven schemes, both in terms of reconstruction performance and of a greater ability to recover high-frequency events. We further discuss how these results could transfer to real data, as well as to other problems beyond interpolation issues, especially short-term forecasting problems from partial satellite observations.

Archaeological 3D digitization of skeletal elements is an essential aspect of the discipline. Objectives are various: archiving of data (especially before destructive sampling for biomolecular studies for example), study or for pedagogical purposes to allow their manipulation. As techniques are rapidly evolving, the question that arises is the use of appropriate methods to answer the different questions and guarantee sufficient quality of information. The combined use of different 3D technologies for the study of a single Mesolithic bone fragment from Brittany (France) is here an opportunity to compare different 3D digitization methods. This oldest human bone of Brittany, a clavicle constituted of two pieces, was dug up from the mesolithic shell midden of Beg-er-Vil in Quiberon and dated from ca. 8200 to 8000 years BP. They are bound to post-mortem processing, realized on fresh bone in order to remove the integuments, which it is necessary to better qualify. The clavicle was studied through a process that combines advanced 3D image acquisition, 3D processing, and 3D printing with the goal to provide relevant support for the experts involved in the work. The bones were first studied with a metallographic microscopy, scanned with a CT scan, and digitized with photogrammetry in order to get a high quality textured model. The CT scan appeared to be insufficient for a detailed analysis; the study was thus completed with a µ-CT providing a very accurate 3D model of the bone. Several 3D-printed copies of the collarbone were produced in order to support knowledge sharing between the experts involved in the study. The 3D models generated from µCT and photogrammetry were combined to provide an accurate and detailed 3D model. This model was used to study desquamation and the different cut marks, including their angle of attack. These cut marks were also studied with traditional binoculars and digital microscopy. This last technique allowed characterizing their type, revealing a probable meat cutting process with a flint tool. This work of crossed analyses allows us to document a fundamental patrimonial piece, and to ensure its preservation. Copies are also available for the regional museums.