A Cosmological Solution to the Doublet-Triplet Splitting Problem

International audienceWe propose a model that provides a simultaneous solution to the doublet-triplet splitting problem of grand unified theories, the electroweak hierarchy problem and the strong CP problem. The mechanism is based on the dynamics of two axion-like particles that would crunch the universe at the time of the QCD phase transition if triplets were light or had a VEV or if doublets were heavy or did not have a VEV. The only trace left at low energies are these two axion-like particles. They are weakly coupled to the Standard Model and could be detected at upcoming axion experiments or by a combination of neutron EDM measurements and the astrophysical detection of fuzzy dark matter

Transcriptomic response of the picoalga Pelagomonas calceolata to nitrogen availability: new insights into cyanate lyase function

International audienceAbstract. Cyanate (OCN − ) is an organic nitrogen compound found in aquatic environments potentially involved in phytoplankton growth. Given the prevalence and activity of cyanate lyase genes in eukaryotic microalgae, cyanate has been suggested as an alternative source of nitrogen in the environment. However, the conditions under which cyanate lyase is expressed and the actual capacity of microalgae to assimilate cyanate remain largely underexplored. Here, we studied the nitrogen metabolism in the cosmopolitan open-ocean picoalga Pelagomonas calceolata (Pelagophyceae and Stramenopiles) in environmental metatranscriptomes and transcriptomes from culture experiments under different nitrogen sources and concentrations. We observed that cyanate lyase is upregulated in nitrate-poor oceanic regions, suggesting that cyanate is an important molecule contributing to the persistence of P. calceolata in oligotrophic environments. Non-axenic cultures of P. calceolata were capable of growing on various nitrogen sources, including nitrate, urea, and cyanate, but not ammonium. RNA sequencing of these cultures revealed that cyanate lyase was downregulated in the presence of cyanate, indicating that this gene is not involved in the catabolism of extracellular cyanate to ammonia. Based on environmental data sets and laboratory experiments, we propose that cyanate lyase is important in nitrate-poor environments to generate ammonia from cyanate produced by endogenous nitrogenous compound recycling rather than being used to metabolize imported extracellular cyanate as an alternative nitrogen source.Importance. Vast oceanic regions are nutrient-poor, yet several microalgae thrive in these environments. While various acclimation strategies to these conditions have been discovered in a limited number of model microalgae, many important lineages remain understudied. Investigating nitrogen metabolism across different microalga lineages is crucial for understanding ecosystem functioning in low-nitrate areas, especially in the context of global ocean warming. This study describes the nitrogen metabolism of Pelagomonas calceolata , an abundant ochrophyte in temperate and tropical oceans. By utilizing both global scale in situ metatranscriptomes and laboratory-based transcriptomics, we uncover how P. calceolata adapts to low-nitrate conditions. Our findings reveal that P. calceolata can metabolize various nitrogenous compounds and relies on cyanate lyase to recycle endogenous nitrogen in low-nitrate conditions. This result paves the way for future investigations into the significance of cyanate metabolism within oceanic trophic webs

AGENT Guidelines for dataflow

The AGENT project aims at integrating data from different sources (genebanks, research institutes, international archives) and types (passport, phenotypic, genomic data). These guidelines have been developed to explain the data flow within the AGENT project and should be useful for other projects

Safety and efficacy of neoadjuvant immunotherapy with durvalumab (MEDI 4736) in combination with neoadjuvant chemotherapy (gemcitabine/cisplatin or carboplatin) in patients with operable high-risk upper tract urothelial carcinoma.

International audienceBackground: Most patients following radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC) face a poor prognosis. Combination of chemotherapy and immunotherapy in neoadjuvant setting have demonstrated survival improvement in several tumors. Additional systemic therapy in a neoadjuvant setting may prolong survival for UTUC patients, especially those after RNU who are ineligible to receive nephrotoxic chemotherapy. Methods: Phase 2 clinical trial (NCT04617756) was conducted in 10 French centers. Eligible patients had non metastatic, high-grade disease on ureteroscopic tumor biopsy or on urine cytology and infiltrative aspect of renal pelvis/ureteral wall on CT imaging. Subjects received a combination of: Durvalumab/Gemcitabine/Cisplatin (cohort 1) or Carboplatin (cohort 2) every 3 weeks for a total of 4 cycles based on glomerular filtration rate, prior to RNU. The primary objective was to assess the pathological complete response (ypT0) rate (pCR) of each combination. Results: A total of 50 patients were enrolledbetween 2021 and 2023 (31 in cohort 1 and 19 in cohort 2). Median age was 66 years old (range 38-79), 58% were males. 90% of patients (44) received 4 cycles of treatment, 3 patients 3 cycles and 2 patients received 2 cycles. Five patients switched for carboplatin during chemotherapy. We observed in cohort 1 : 20/31 (65%) patients with non infiltrative residual tumor; In cohort 2 : 9/19 (42%) patients (table). Secondary endpoint was safety, no immunotherapy-mediated AE was observed, 2 patients had Grade 3 neutropenia, 1 grade 4, 1 patient had grade 3 thrombopenia and 1 grade 3 anemia. Conclusions: Combination of durvalumab with platin-based chemotherapy, especially cisplatin, showed promising activity in UTUC, with the occurrence of complete responses and a high rate of non-infiltrative residual tumor. Safety profile was secure without increasing surgical risk. A randomized Phase 3 controlled study comparing neoadjuvant chemotherapy with chemotherapy combined with immunotherapy in patients with high-risk localized UTUC (iNDUCT-3) will open soon to validate these encouraging results. Clinical trial information: NCT04617756. Pathological response rate. ypT0 ypTIS /ypTa ypT1 ypT2 ypT3 ypT4 Missing data Withdrawal surgery Total Cis-Gem Durva 4 (13%) 5 (16%) 11 (36%) 1 (3%) 6 (19%) 1 (3%) 1 2 31 Carbo-Gem Durva 1 (5%) 6 (32%) 1 (5%) 3 (16%) 5 (26%) 1 (5%) 1 1 1

Co-occurrence drives horizontal gene transfer among marine prokaryotes

Understanding the drivers of horizontal gene transfer (HGT) is a key question in microbial evolution. While co-occurring taxa have long been appreciated to undergo HGT more often, this association is confounded with other factors, most notably their phylogenetic distance.To disentangle these factors, we analyzed 15,339 isolate and metagenome-assembled marine genomes. We identified HGT events across these genomes, and identified enrichments for functions previously shown to be prone to HGT. By mapping metagenomic reads from 1,862 ocean samples to these genomes, we also identified co-occurrence patterns and environmental associations. Although we observed an expected negative association between phylogenetic distance and HGT rates, we only detected the association between cooccurrence and phylogenetic distance when restricted to closely related taxa. This observation refines the previously reported trend to closely related taxa, rather than a consistent pattern across all taxonomic levels, at least within marine environments. In addition, we identified a significant association between co-occurrence and HGT, which remains even after controlling for phylogenetic distance and measured environmental variables. Overall, our findings demonstrate the significant influence of ecological associations in shaping marine bacterial evolution through HGT.</p

The DUNE Science Program

International audienceThe international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy for the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the previous European Strategy for Particle Physics. The construction of DUNE Phase I is well underway. DUNE Phase II consists of a third and fourth far detector module, an upgraded near detector complex, and an enhanced > 2 MW beam. The fourth FD module is conceived as a 'Module of Opportunity', aimed at supporting the core DUNE science program while also expanding the physics opportunities with more advanced technologies. The DUNE collaboration is submitting four main contributions to the 2026 Update of the European Strategy for Particle Physics process. This submission to the 'Neutrinos and cosmic messengers', 'BSM physics' and 'Dark matter and dark sector' streams focuses on the physics program of DUNE. Additional inputs related to DUNE detector technologies and R&D, DUNE software and computing, and European contributions to Fermilab accelerator upgrades and facilities for the DUNE experiment, are also being submitted to other streams

Exploiter l'incertitude lors de l'apprentissage par propagation d'équilibre dans les réseaux de neurones

8 pages, 5 figuresEquilibrium Propagation (EP) is a supervised learning algorithm that trains network parameters using local neuronal activity. This is in stark contrast to backpropagation, where updating the parameters of the network requires significant data shuffling. Avoiding data movement makes EP particularly compelling as a learning framework for energy-efficient training on neuromorphic systems. In this work, we assess the ability of EP to learn on hardware that contain physical uncertainties. This is particularly important for researchers concerned with hardware implementations of self-learning systems that utilize EP. Our results demonstrate that deep, multi-layer neural network architectures can be trained successfully using EP in the presence of finite uncertainties, up to a critical limit. This limit is independent of the training dataset, and can be scaled through sampling the network according to the central limit theorem. Additionally, we demonstrate improved model convergence and performance for finite levels of uncertainty on the MNIST, KMNIST and FashionMNIST datasets. Optimal performance is found for networks trained with uncertainties close to the critical limit. Our research supports future work to build self-learning hardware in situ with EP

Recent gains in global terrestrial carbon stocks are mostly stored in nonliving pools

International audienceTerrestrial sequestration of carbon has mitigated ≈30% of anthropogenic carbon emissions. However, its distribution across different pools, live or dead biomass and soil and sedimentary organic carbon, remains uncertain. Analyzing global observational datasets of changes in terrestrial carbon pools, we found that ≈35 ± 14 gigatons of carbon (GtC) have been sequestered on land between 1992 and 2019, whereas live biomass changed by ≈1 ± 7 GtC. Global vegetation models instead imply that sequestration has been mostly in live biomass. We identify key processes not included in most models that can explain this discrepancy. Most terrestrial carbon gains are sequestered as nonliving matter and thus are more persistent than previously appreciated, with a substantial fraction linked to human activities such as river damming, wood harvest, and garbage disposal in landfills

Generative T2*-weighted images as a substitute for true T2*-weighted images on brain MRI in patients with acute stroke

International audienceObjective: In centers that use MR as first-line diagnostic tool for acute stroke patients, the distinction between hemorrhagic and ischemic stroke relies on T2* sequence. We aimed to develop and validate a deep-learning algorithm generating a T2* from information embedded in Diffusion-weighted images (DWI) and compare its performance to real T2* for hemorrhage detection in acute stroke patients.Materials and methods: This monocentric retrospective study included DWI and T2* sequences obtained &lt;48h after symptom onset of consecutive (2002-2021) patients admitted for acute ischemic or hemorrhagic stroke. Datasets were split into training (60%), validation (20%), and test (20%) sets, with stratification on stroke type (hemorrhagic/ischemic). A generative adversarial network was trained to produce generative T2*, using DWI as input on the training set. Concordance of real and generative T2* for hemorrhage detection were independently evaluated by two readers as parenchymal hematoma (PH), hemorrhagic infarct (HI) or no hemorrhage (NoH), and discordances were solved in consensus.Results: 1491 MRI sets from 939 patients were included. In the test set (n=300), intra-observer reproducibility for hemorrhage classification (NoH, HI or PH) was excellent for real and generative T2* (weighted κ=0.97 [95%CI:0.95-0.99] and 0.95 [95%CI:0.92-0.97] respectively, p=0.27). Interobserver reproducibility for hemorrhage classification was excellent for real and generative T2* (κ=0.93 [95%CI:0.90-0.97] and 0.92 [95%CI:0.88-0.96] respectively, p=0.64). After consensus, concordance between real and generative T2* was excellent (κ=0.92 [95%CI: 0.91-0.96]).Conclusion: Generative T2* has similar diagnostic performances to real T2* for hemorrhage detection in acute stroke and may be used to shorten MRI protocols

Modulating the surface chemistry of gold nanoparticles produced via laser ablation in liquids by favored oxidative processes in the presence of Br anions

International audienceIn this study, we explore the influence of bromide anions concentration on the surface chemistry of colloidal gold nanoparticles synthesized via pulsed laser ablation in liquids (PLAL). Using X-ray photoelectron spectroscopy (XPS) in a controlled environment, by probing a beam of free-standing gold nanoparticles, we quantitatively characterize the surface composition of the nanoparticles, revealing that bromide adsorption significantly contributes to surface oxidation independently of counterion type and pH for alkaline solution. Additionally, our findings demonstrate the adjustability of halogen coverage post-synthesis, offering a versatile method for controlling nanoparticle properties