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Abstract Taxanes, such as paclitaxel (PTX), stabilize microtubules and are used as a first-line therapy in multiple cancer types. Disruption of microtubule equilibrium, which plays an essential role in mitosis and cell homeostasis, ultimately results in cell death. Even though PTX is a very potent chemotherapy, its use is associated with major side effects and therapy resistance. Pelophen B (PPH), a synthetic analog of peloruside A, stabilizes microtubules through interaction with a non-taxoid binding site of β-tubulin. We evaluated the anticancer effect of PPH in a variety of tumor types by using established cell lines, early-passage cultures and ex vivo tumor-derived cultures that preserve the 3D architecture of the tumor microenvironment. PPH significantly blocks colony formation capacity, reduces viability and exerts additivity with PTX. Interestingly, PPH overcomes resistance to PTX. Mechanistically, PPH induces a G2/M cell cycle arrest and increases the presence of tubulin polymerization promoting protein (TPPP), inducing lysine 40 acetylation of α-tubulin. Although, results induced by paclitaxel or PPH are concordant, PPH’s unique microtubule binding mechanism enables PTX additivity and ensures overcoming PTX-induced resistance. In conclusion, PPH results in remarkable anti-cancer activity in a range of preclinical models supporting further clinical investigation of PPH as a therapeutic anticancer agent.

Objective: Subclinical hyperthyroidism (SCH) is common and associated with atrial fibrillation (AF) risk in the elderly. Current guidelines rely on a low level of evidence. Methods: Randomized clinical trial including patients 50 years and older, with thyroid-stimulating hormone (TSH) 65 years or TSH < 0.1mU/L. Of 94 patients treated using radioiodine, 25% developed hypothyroidism during follow-up. Conclusion: Due to recruitment difficulties, this study failed to demonstrate that SCH treatment can significantly reduce the incidence of AF in patients older than 50 years with thyroid autonomy even if all the patients who developed AF maintained TSH

Abstract Extranodal NK/T-cell lymphoma (ENKTCL) is an Epstein-Barr virus (EBV)-related neoplasm preferentially involving the upper aerodigestive tract. Here we show that NK-cell-specific Trp53 disruption in mice leads to the development of NK-cell lymphomas after long latency, which involve not only the hematopoietic system but also the salivary glands. Before tumor onset, Trp53 knockout causes extensive gene expression changes, resulting in immature NK-cell expansion, exclusively in the salivary glands. Both human and murine NK-cell lymphomas express tissue-resident markers, suggesting tissue-resident NK cells as their cell-of-origin. Murine NK-cell lymphomas show recurrent Myc amplifications and upregulation of MYC target gene signatures. EBV-encoded latent membrane protein 1 expression accelerates NK-cell lymphomagenesis and causes diverse microenvironmental changes, particularly myeloid propagation, through interferon-γ signaling. In turn, myeloid cells support tumor cells via CXCL16-CXCR6 signaling and its inhibition is effective against NK-cell tumors in vivo. Remarkably, KLRG1-expressing cells expand in the tumor and are capable of repopulating tumors in secondary recipients. Furthermore, targeting KLRG1 alone or combined with MYC inhibition using an eIF4 inhibitor is effective against NK-cell tumors. Therefore, our observations provide insights into the pathogenesis and highlight potential therapeutic targets, including CXCL16, KLRG1, and MYC, in ENKTCL, which can help improve its diagnostic and therapeutic strategies.

Abstract Background Pervasive translation is a widespread phenomenon that plays a critical role in the emergence of novel microproteins, but the diversity of translation patterns contributing to their generation remains unclear. Based on 54 ribosome profiling (Ribo-Seq) datasets, we investigated the yeast Ribo-Seq landscape using a representation framework that allows the comprehensive inventory and classification of the entire diversity of Ribo-Seq signals, including non-canonical ones. Results We show that if coding regions occupy specific areas of the Ribo-Seq landscape, noncoding regions encompass a wide diversity of Ribo-Seq signals and, conversely, populate the entire landscape. Our results show that pervasive translation can, nevertheless, be associated with high specificity, with 1055 noncoding ORFs exhibiting canonical Ribo-Seq signals. Using mass spectrometry under standard conditions or proteasome inhibition with an in-house analysis protocol, we report 239 microproteins originating from noncoding ORFs that display canonical but also non-canonical Ribo-Seq signals. Each condition yields dozens of additional microprotein candidates with comparable translation properties, suggesting a larger population of volatile microproteins that are challenging to detect. Our findings suggest that non-canonical translation signals may harbor valuable information and underscore the significance of considering them in proteogenomic studies. Finally, we show that the translation outcome of a noncoding ORF is primarily determined by the initiating codon and the codon distribution in its two alternative frames, rather than features indicative of functionality. Conclusion Our results enable us to propose a topology of a species’ Ribo-Seq landscape, opening the way to comparative analyses of this translation landscape under different conditions.

Aims Acute heart failure (AHF) is associated with end‐organ dysfunction. The effect of AHF on the pancreas has not been studied. We aim to evaluate serum markers of pancreatic damage during hospitalization for AHF. Methods and results In data from the Pragmatic Urinary Sodium‐based treatment algoritHm in Acute Heart Failure (PUSH‐AHF) study, amylase and lipase values were extracted from available serum samples at baseline, and at 24 and 72 h after hospitalization. The differences between pancreatic enzymes between timepoints were evaluated using the Friedman test. Associations with N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) were tested using linear regression analysis. The study population consisted of 274 patients. Mean age was 73 ± 11 years, and 117 (43%) were women. Mean left ventricular ejection fraction (LVEF) was 38 ± 14%; 53 (19%) patients had HF with a preserved LVEF (≥50%). At baseline, median amylase and lipase were within normal range (47 [33–63] U/L and 30 [21–44] U/L, respectively). Both enzymes significantly increased in the first 72 h (P‐value for trend

Abstract Genetic variants identified through genome-wide association studies (GWAS) are typically non-coding, exerting small regulatory effects on downstream genes. However, which downstream genes are ultimately impacted and how they confer risk remains mostly unclear. By contrast, variants that cause rare Mendelian diseases are often coding and have a more direct impact on disease development. Here we demonstrate that common and rare genetic diseases can be linked by studying how common disease-associated variants influence gene co-expression in 57 different tissues and cell types. We implemented this method in a framework called Downstreamer and applied it to 88 GWAS traits. We find that predicted downstream “genes” are enriched with Mendelian disease genes, e.g. key genes for height are enriched for genes that cause skeletal abnormalities and Ehlers–Danlos syndromes. 78% of these key genes are located outside of GWAS loci, suggesting that they result from complex trans regulation rather than being impacted by disease-associated variants in cis. Based on our findings, we discuss the challenges in reconstructing gene regulatory networks and provide a roadmap to improve the identification of these highly connected genes linked to common traits and diseases.

Abstract Adults and children with cholestatic liver disease are at risk for type C hepatic encephalopathy (HE) and may present lifelong neurocognitive impairment. While the underlying cellular and molecular mechanisms are still incompletely understood, ammonium and bile acids (BAs) seem to play a key role in this pathology, by crossing the blood-brain-barrier and modifying neuronal homeostasis and synaptic plasticity. This experimental study aimed to investigate the effects of ammonium and BAs on dendritic spines of rat hippocampal CA1 neurons. Taking advantage of the bile duct ligated (BDL) in vivo rat model and a hippocampal organotypic rat ex vivo slice model, we analyzed dendritic spine density in both models and spine turnover ex vivo. BDL rats showed decreased dendritic spine densities after 8 weeks, paralleled with increased concentrations of blood ammonium. In organotypic hippocampal slices, exposure to ammonium, tauro-α-muricholic and taurocholic acid induced a decrease in dendritic spine density during the first 3 days, followed by an increase in dendritic spinogenesis during days 4–5, resulting in an increased number of dendritic spines. These observations provide new insights into the effects of ammonium and BAs on dendritic spines and consequently synaptic plasticity in chronic cholestatic liver disease.

Abstract Augmenting the portfolio of therapeutics for type 2-driven diseases is crucial to address unmet clinical needs and to design personalized treatment schemes. An attractive therapy for such diseases would consist in targeting the recruitment of T helper 2 (Th2) lymphocytes to inflammatory sites. Herein, we show the degradation of filamins (FLN) a and b by the ASB2α E3 ubiquitin ligase as a mechanism sustaining Th2 lymphocyte functions. Low levels of FLNa and FLNb confer an elongated shape to Th2 lymphocytes associated with efficient αVβ3 integrin-dependent cell migration. Genes encoding the αVβ3 integrin and ASB2α belong to the core of Th2-specific genes. Using genetically modified mice, we find that increasing the levels of FLNa and FLNb in Th2 lymphocytes reduces airway inflammation through diminished Th2 lymphocyte recruitment in inflamed lungs. Collectively, our results highlight ASB2α and its substrates FLNa and FLNb to alter Th2 lymphocyte-mediated responses.

The intensification of crop management has resulted in a decline of biodiversity in the last decades, in particular through habitat loss, fragmentation and degradation. Semi-natural habitats within agricultural landscapes such as hedges, grasslands or herbaceous field margins, provide resources and refuge to beneficial arthropods. In vineyards, extensively used inter-row vegetation may be functionally equivalent to such semi-natural habitats, and sowing of plant species rich in floral resources may improve habitat functions. In this study, three types of vineyard inter-row vegetation treatments were compared in 15 vineyards of South-eastern France: (1) sowing a high-diversity seed mixture (HD) with a high number of nectariferous plant species, (2) spontaneous vegetation, and (3) tilled inter-rows. We monitored the inter-row vegetation including problematic weeds, the abundance of beneficial arthropods, and the predation of sentinel prey. The invasive weedy grass species Cynodon dactylon showed a lower cover in HD inter-rows than in spontaneous vegetation, whereas no differences were found for the invasive herb Erigeron sumatrensis. Both weed species were still best controlled in tilled inter-rows. Beneficial arthropods were less abundant in tilled than in spontaneously vegetated and sown inter-rows. Day predation was higher in HD inter-rows than in spontaneous vegetation although no significant differences were found for observed predators. Over all treatments, plant species richness, flower and grass cover had a positive influence on several beneficial arthropod groups. Our results highlight the positive effects of species-rich inter-row vegetation on weed control, beneficial arthropod abundance and predation but also showed that further research is needed to improve the efficiency beyond services already provided by spontaneous vegetation.

Abstract To circumvent reporting spurious correlations, species distribution models often explicitly account for spatial autocorrelation, for example by including spatially structured random effects. The validity of statistical inference derived from such models has been tested by simulations using null environmental predictors that do not have any causal dependency with the response. Such null environmental predictors can be obtained by permutations of the original predictors or by simulating spatial structures resembling the original predictors. In such approaches, it is important that the permuted or simulated predictors reflect the nature of spatial variation present in the original predictors. Here we present a novel approach for generating realistic null predictors by a shift‐&‐rotate (S&R) approach: we extract environmental variables after randomly translating and rotating the sampling area within a window of defined environmental layers. In this way, the null environmental variables have fully realistic spatial variation and covariation, but no relationship to the response variable. We implement the S&R approach to three main R‐functions and demonstrate with a simulation study how they can be used to untangle causal versus non‐causal relationships within species distribution modelling. These methods allow us to quantify the predictive power attributed within the models due to non‐causal correlations generated by the realistic structure of the environmental covariates. In our case study, we identify when a model incorrectly estimates parameter values, yet still has high predictive power due to the structured nature of the predictor variables. The use of null models is imperative in ecological modelling for testing the accuracy of statistical inference in complex ecological systems and the choice of these null models is far from trivial. Here we provide R functions for generating spatially realistic null models to use in species distribution modelling as well as other spatially explicit fields such as landscape genetics.

Abstract Understanding how ecological assemblages vary in space and time is essential for advancing our knowledge of biodiversity dynamics and ecosystem functioning. Metabarcoding of environmental DNA (eDNA) is an efficient method for documenting biodiversity changes in both marine and terrestrial ecosystems. However, current methods fail to detect and display the biodiversity structure within and between eDNA samples limiting ecological and biogeographical interpretations. We present a spatial matrix factorization method that identifies optimal eDNA sample assemblages—called pools—assuming that taxonomic unit composition is based on a fixed number of unknown sources. These sources, in turn, represent taxonomic units sharing similar habitat properties or characteristics. The method aims to reduce the multi‐taxa composition structure into a low number of dimensions defined by these sources. This method is inspired by admixture analysis in population genetics. Using a marine fish eDNA survey on 263 sampling stations detecting 2888 molecular operational taxonomic units (MOTUs), we apply this method to analyse the biogeography and mixing patterns of fish assemblages at regional and large scales. At large scale, our analysis reveals six primary pools of fish samples characterized by distinct biogeographic patterns, with some mixtures between these pools. We identify pools composed of unique sources, corresponding to distinct and more isolated regions such as the Mediterranean and Scotia Seas. We also identify pools composed of a greater mix of sources, corresponding to geographically connected areas, such as tropical regions. Additionally, we identify the taxa underpinning the formation of each pool. In the regional analysis of Mediterranean eDNA samples, our method successfully identifies different pools, allowing the detection of not only geographic gradients but also human‐induced gradients corresponding to protection levels. Spatial matrix factorization adds a new method in community ecology, where each sample is considered as a mixture of K unobserved sources, to assess the dissimilarity of ecological assemblages revealing environmental and human‐induced gradients. Beyond the study of fish eDNA samples, this method has the potential to shed new light on any biodiversity survey and provide new bioindicators of global change.

Chronic wasting disease (CWD) is an emerging disease in Europe. We report an increase in interspecies transmission capacity and zoonotic potential of a moose CWD isolate from Europe after passage in an ovine prion protein–expressing host. Those results indicated some CWD prions could acquire enhanced zoonotic properties following adaptation in an intermediate species.

Abstract To save saltmarshes and their valuable ecosystem services from sea level rise, it is crucial to understand their natural ability to gain elevation by sediment accretion. In that context, a widely accepted paradigm is that dense vegetation favors sediment accretion and hence saltmarsh resilience to sea level rise. Here, however, we reveal how dense vegetation can inhibit sediment accretion on saltmarsh platforms. Using a process‐based modeling approach to simulate biogeomorphic development of typical saltmarsh landscapes, we identify two key mechanisms by which vegetation hinders sediment transport from tidal channels toward saltmarsh interiors. First, vegetation concentrates tidal flow and sediment transport inside channels, reducing sediment supply to platforms. Second, vegetation enhances sediment deposition near channels, limiting sediment availability for platform interiors. Our findings suggest that the resilience of saltmarshes to sea level rise may be more limited than previously thought.

Abstract Marine microbes are strongly interrelated to trace metals in the ocean. How the availability of trace metals selects for prokaryotic taxa and the potential feedback of microbial processes on the trace metal distribution in the ocean remain poorly understood. We investigate here the potential reciprocal links between diverse prokaryotic taxa and iron (Fe), manganese (Mn), copper (Cu), and nickel (Ni) as well as apparent oxygen utilization (AOU) across 12 well‐defined water masses in the Southern Indian Ocean (SWINGS—South West Indian Ocean GEOTRACES GS02 Section cruise). Applying partial least square regression (PLSR) analysis, we show that the water masses are associated with particular latent vectors that are a combination of the spatial distribution of prokaryotic taxa, trace elements, and AOU. This approach provides novel insights on the potential interactions between prokaryotic taxa and trace metals in relation to organic matter remineralization in distinct water masses of the ocean.

Monoclonal antibodies (mAbs) hold significant potential as therapeutic agents and are invaluable tools in biomedical research. However, the lack of efficient high-throughput screening methods for single antibody-secreting cells (ASCs) has limited the diversity of available antibodies. Here, we introduce a novel, integrated workflow employing self-seeding microwells and an automated microscope-puncher system for the swift, high-throughput screening and isolation of single ASCs. The system allows for the individual screening and isolation of up to 6,400 cells within approximately one day, with the opportunity for parallelization and efficient upscaling. We successfully applied this workflow to both hybridomas and human patient-derived B cells, enabling subsequent clonal expansion or antibody sequence analysis through an optimized, single-cell nested reverse transcription-polymerase chain reaction (RT-PCR) procedure. By providing a time-efficient and more streamlined single ASC screening and isolation process, our workflow holds promise for driving forward progress in mAb development.

Background As the societal value of vaccines is increasingly recognized, there is a need to examine methodological approaches that could be used to integrate these various benefits in the economic evaluation of a vaccine.Research design and methods A literature review and two expert panel meetings explored methodologies to value herd immunity, health spillover effects (beyond herd immunity), impact on antimicrobial resistance, productivity, and equity implications of vaccines.Results The consideration of broader benefits of vaccines in economic evaluation is complicated and necessitates technical expertise. Whereas methodologies to account for herd immunity and work productivity are relatively well established, approaches to investigate equity implications are developing and less frequently applied. Modeling the potential impact on antimicrobial resistance not only depends on the multi-faceted causal relationship between vaccination and resistance but also on data availability.Conclusions Different methods are available to value the broad impact of vaccines, and it is important that analysts are aware of their strengths and limitations and justify their choice of method. In the future, we expect that an increasing number of economic evaluations will consider the broader benefits of vaccines as part of their base-case analysis or in sensitivity analyses.

Transcription is a major contributor to genomic instability. The ribosomal RNA (rDNA) gene locus consists of a head-to-tail repeat of the most actively transcribed genes in the genome. RNA polymerase I (RNAPI) is responsible for massive rRNA production, and nascent rRNA is co-transcriptionally assembled with early assembly factors in the yeast nucleolus. In Saccharomyces cerevisiae, a mutant form of RNAPI bearing a fusion of the transcription factor Rrn3 with RNAPI subunit Rpa43 (CARA-RNAPI) has been described previously. Here, we show that the CARA-RNAPI allele results in a novel type of rRNA processing defect, associated with rDNA genomic instability. A fraction of the 35S rRNA produced in CARA-RNAPI mutant escapes processing steps and accumulates. This accumulation is increased in mutants affecting exonucleolytic activities of the exosome complex. CARA-RNAPI is synthetic lethal with monopolin mutants that are known to affect the rDNA condensation. CARA-RNAPI strongly impacts rDNA organization and increases rDNA copy number variation. Reduced rDNA copy number suppresses lethality, suggesting that the chromosome segregation defect is caused by genomic rDNA instability. We conclude that a constitutive association of Rrn3 with transcribing RNAPI results in the accumulation of rRNAs that escape normal processing, impacting rDNA organization and affecting rDNA stability.

Permafrost landscapes are becoming increasingly susceptible to widespread thaw due to climate change. Collating historical and ongoing data are critical for assessing permafrost conditions and spatiotemporal changes. Electrical resistivity tomography (ERT) is a geophysical technique that has become standard practice for characterizing permafrost. However, resistivity data—particularly raw measurements—often go unpublished and unshared, resulting in missed opportunities for knowledge exchange and collaboration. To fill this gap, we created the Canadian Permafrost Electrical Resistivity Survey database and established clear guidelines for data archival and reuse. Here, we present the first release of the database, which currently houses 280 ERT datasets, including standardized metadata, collected between 2008 and 2022 in British Columbia, Labrador, Northwest Territories, Québec, Yukon, and Alaska. These data present unique opportunities to better understand spatial and temporal variability of permafrost conditions across North America.

The discovery of novel therapeutic targets, defined as proteins which drugs can interact with to induce therapeutic benefits, typically represent the first and most important step of drug discovery. One solution for target discovery is target repositioning, a strategy which relies on the repurposing of known targets for new diseases, leading to new treatments, less side effects and potential drug synergies. Biological networks have emerged as powerful tools for integrating heterogeneous data and facilitating the prediction of biological or therapeutic properties. Consequently, they are widely employed to predict new therapeutic targets by characterizing potential candidates, often based on their interactions within a Protein-Protein Interaction (PPI) network, and their proximity to genes associated with the disease. However, over-reliance on PPI networks and the assumption that potential targets are necessarily near known genes can introduce biases that may limit the effectiveness of these methods. This study addresses these limitations in two ways. First, by exploiting a multi-layer network which incorporates additional information such as gene regulation, metabolite interactions, metabolic pathways, and several disease signatures such as Differentially Expressed Genes, mutated genes, Copy Number Alteration, and structural variants. Second, by extracting relevant features from the network using several approaches including proximity to disease-associated genes, but also unbiased approaches such as propagation-based methods, topological metrics, and module detection algorithms. Using prostate cancer as a case study, the best features were identified and utilized to train machine learning algorithms to predict 5 novel promising therapeutic targets for prostate cancer: IGF2R, C5AR, RAB7, SETD2 and NPBWR1.

Through a case study of a popular French forum, this article aims to understand how speech moderation is received, criticized and countered by the cybercommunity, in particular by its most visible and virulent factions, largely influenced by and linked to the "fachosphere". The aim is to contribute to a critical reflection on the means and techniques of discourse regulation on social networking platforms, as well as the circumvention strategies implemented by a diversity of actors seeking to subvert the public spaces of "open societies" from within. First, I emphasize the victim ideology developed on the forum. Then I discuss several efficient circumvention strategies implemented by the forum’s far-right sub-community to circumvent censorship and how this helps cultivate a collective identity and a sense of belonging to the group. Finally, I show that censorship may lead participants to 'migrate' to other, more fringe spaces promoting almost total freedom of speech.

The use of alkylzinc bromides in the multicomponent Mannich reaction is described. Heteroleptic organozinc compounds were obtained in THF or 2-MeTHF by direct insertion of zinc dust into the C–Br bond of alkyl bromides. It was found that the presence of a stoichiometric amount of LiCl was essential for the efficiency of the subsequent three-component coupling with aldehydes and amines. A variety of primary, secondary, and tertiary organozinc reagents as well as secondary amines and aromatic aldehydes could be used for the straightforward preparation of α-branched amines. Interestingly, whereas previously reported work describing the preparation and reaction of organozinc iodides in acetonitrile showed higher reactivity of secondary organozinc reagents over primary ones, reactions in THF in the presence of LiCl led to opposite results, with higher reactivity of primary organozinc reagents.

Abstract Structural variants (SVs) are important contributors to human disease. Their characterization remains however difficult due to their size and association with repetitive regions. Long-read sequencing (LRS) and optical genome mapping (OGM) can aid as their molecules span multiple kilobases and capture SVs in full. In this study, we selected six individuals who presented with unresolved SVs. We applied LRS onto all individuals and OGM to a subset of three complex cases. LRS detected and fully resolved the interrogated SV in all samples. This enabled a precise molecular diagnosis in two individuals. Overall, LRS identified 100% of the junctions at single-basepair level, providing valuable insights into their formation mechanisms without need for additional data sources. Application of OGM added straightforward variant phasing, aiding in the unravelment of complex rearrangements. These results highlight the potential of LRS and OGM as follow-up molecular tests for complete SV characterization. We show that they can assess clinically relevant structural variation at unprecedented resolution. Additionally, they detect (complex) cryptic rearrangements missed by conventional methods. This ultimately leads to an increased diagnostic yield, emphasizing their added benefit in a diagnostic setting. To aid their rapid adoption, we provide detailed laboratory and bioinformatics workflows in this manuscript.

Abstract Deep phenotyping the right ventricle (RV) is essential for understanding the mechanisms of adaptive and maladaptive RV responses to pulmonary hypertension (PH). In this study, feature selection coupled with machine learning classification/ranking of specific cardiac magnetic resonance imaging (MRI) features from cine-MRI, flow-sensitized, and extracellular-volume techniques were used to assess RV remodelling in monocrotaline (MCT) and Sugen hypoxia (SuHx) PH rats. Early physiological changes associated with RV adaptation were detected along with prediction of RV maladaptive outcomes. Key adaptation features included haemodynamic alterations of pulmonary blood flow ejection and wave reflection, mild RV dilatation, progressive RV hypertrophy with subtle extracellular volume growth of RV wall. A dominant component of maladaptation was the extracellular matrix increase at RV insertion points and septum, observations compatible with histopathologic and RNA-sequencing results. The upregulation of mammalian target of rapamycin (mTOR) paralleled by AMP-activated protein kinase (AMPK) deactivation was seen at 4-week MCT and 8-week SuHx, along with reduced sarcoplasmic/endoplasmic reticulum Ca2+ATPase (SERCA2) expression, strongly associated with the RV systolic malfunction seen at this stage in vivo. The here established MRI features can serve as potential imaging biomarkers to evaluate PH treatment efficacy in preclinical studies and build up translational markers for the PH clinic.

Abstract Smart batteries, i.e., equipped with internal and external sensors, are emerging as promising solutions to enhance battery state of health and optimize operating conditions. However, for accurate correlations between the evolution of the cell parameters (e.g., temperature, strain) and physicochemical degradation mechanisms, it is crucial to know the reliability of sensors. To address this question, we perform a synchrotron operando X-ray diffraction experiment to investigate the local and global impact of the presence of internal sensors on a commercial prismatic Li-ion battery cell at various (dis)charge rates. We find that, while the overall electrochemical performance is unaffected, the sensors have a substantial impact on the local graphite lithiation kinetics, especially at high (dis)charge rates. These results show the importance of controlling local deformations induced by internal sensors and tailoring the dimensions of these sensors to obtain reliable battery performance indicators and optimize smart batteries.

Abstract Bubbles are ubiquitous in many research applications ranging from ultrasound imaging and drug delivery to the understanding of volcanic eruptions and water circulation in vascular plants. From an acoustic perspective, bubbles are resonant scatterers with remarkable properties, including a large scattering cross-section and strongly sub-wavelength dimensions. While it is known that the resonance properties of bubbles depend on their local environment, it remains challenging to probe this interaction at the single-bubble level due to the difficulty of manipulating a single resonating bubble in a liquid. Here, we confine a cubic bubble inside a cage using 3D printing technology, and we use this bubble as a local probe to perform scanning near-field acoustic microscopy—an acoustic analog of scanning near-field optical microscopy. By probing the acoustic interaction between a single resonating bubble and its local environment, we demonstrate near-field imaging of complex structures with a resolution that is two orders of magnitudes smaller than the wavelength of the acoustic field. As a potential application, our approach paves the way for the development of low-cost acoustic microscopes based on caged bubbles.

Abstract Background New onsets of chronic urticaria (CU) have been reported after repeated immunizations, mainly with the Moderna mRNA-1273 vaccine (Spikevax). This study aims to evaluate patients with CU after COVID-19 mRNA vaccination. The contribution of SARS-Cov2 infection, atopy and IgE against the vaccine was analyzed. Methods We monitored the features of patients who developed CU after vaccination through two surveys conducted in 2022 and 2023. Fifty individuals with CU underwent blood tests, and their results were compared with individuals without a history of urticaria (N = 135). The presence of anti-vaccine IgE was tested in 185 individuals with basophil activation tests (BAT). We assessed anti-SARS-Cov2 humoral response, and the presence of IgEs against common respiratory allergens (Phadiatop) as a surrogate for atopy. Results Post-vaccination CU occurs after a median interval of 10 days and significantly more after the Spikevax booster, affecting middle-aged individuals (median 41, 66% females). In 2023, CU was still active in 53% of the cases. Inducible forms of CU, primarily dermographism, are reported in 54% (2022) and 61% (2023) of the cases. BAT positivity is not specific to CU, anti-nucleocapsid positivity, or atopy but is significantly associated with higher anti-spike neutralizing activities and younger age. Four CU patients tolerate an additional dose of mRNA vaccine with no disease exacerbation/recurrence. Conclusions The spikevax booster induces anti-vaccine IgE independently of CU, the latter being not directly associated with COVID-19 infection nor atopy. The tolerance to a new booster in 4/4 patients suggests that the Spikevax vaccine indirectly triggers CU in predisposed individuals.

Abstract Using GPU-accelerated state-vector emulation, we propose to embed a quantum computing ansatz into density-functional theory via density-based basis-set corrections to obtain quantitative quantum-chemistry results on molecules that would otherwise require brute-force quantum calculations using hundreds of logical qubits. Indeed, accessing a quantitative description of chemical systems while minimizing quantum resources is an essential challenge given the limited qubit capabilities of current quantum processors. We provide a shortcut towards chemically accurate quantum computations by approaching the complete-basis-set limit through coupling the density-based basis-set corrections approach, applied to any given variational ansatz, to an on-the-fly crafting of basis sets specifically adapted to a given system and user-defined qubit budget. The resulting approach self-consistently accelerates the basis-set convergence, improving electronic densities, ground-state energies, and first-order properties (e.g. dipole moments), but can also serve as a classical, a posteriori, energy correction to quantum hardware calculations with expected applications in drug design and materials science.

Abstract Lung disease analysis in chest X-rays (CXR) using deep learning presents significant challenges due to the wide variation in lung appearance caused by disease progression and differing X-ray settings. While deep learning models have shown remarkable success in segmenting lungs from CXR images with normal or mildly abnormal findings, their performance declines when faced with complex structures, such as pulmonary opacifications. In this study, we propose AMRU++, an attention-based multi-residual UNet++ network designed for robust and accurate lung segmentation in CXR images with both normal and severe abnormalities. The model incorporates attention modules to capture relevant spatial information and multi-residual blocks to extract rich contextual and discriminative features of lung regions. To further enhance segmentation performance, we introduce a data augmentation technique that simulates the features and characteristics of CXR pathologies, addressing the issue of limited annotated data. Extensive experiments on public and private datasets comprising 350 cases of pneumoconiosis, COVID-19, and tuberculosis validate the effectiveness of our proposed framework and data augmentation technique.

Abstract Overcoming resistance to therapy is a major challenge in castration-resistant prostate cancer (CRPC). Lineage plasticity towards a neuroendocrine phenotype enables CRPC to adapt and survive targeted therapies. However, the molecular mechanisms of epigenetic reprogramming during this process are still poorly understood. Here we show that the protein kinase PKCλ/ι-mediated phosphorylation of enhancer of zeste homolog 2 (EZH2) regulates its proteasomal degradation and maintains EZH2 as part of the canonical polycomb repressive complex (PRC2). Loss of PKCλ/ι promotes a switch during enzalutamide treatment to a non-canonical EZH2 cistrome that triggers the transcriptional activation of the translational machinery to induce a transforming growth factor β (TGFβ) resistance program. The increased reliance on protein synthesis creates a synthetic vulnerability in PKCλ/ι-deficient CRPC.

Abstract Cancer cells in acidic tumor regions are aggressive and a key therapeutic target, but distinguishing between acid-exposed and hypoxic cells is challenging. Here, we use carbonic anhydrase 9 (CA9) antibodies to mark acidic areas in both hypoxic and respiring tumor areas, along with an HRE-GFP reporter for hypoxia, to isolate distinct cell populations from 3D tumor spheroids. Transcriptomic analysis of CA9-positive, hypoxia-negative cells highlights enriched fatty acid desaturase activity. Inhibiting or silencing stearoyl-CoA desaturase-1 (SCD1) induces ferroptosis in CA9-positive acidic cancer cells and delays mouse tumor growth, an effect enhanced by omega-3 fatty acid supplementation. Using acid-exposed cancer cells and patient-derived tumor organoids, we show that SCD1 inhibition increases acidic cancer cell reliance on external mono-unsaturated fatty acids, depriving hypoxic cells of essential resources. This bystander effect provides unbiased evidence for a lack of full overlap between hypoxic and acidic tumor compartments, highlighting a rationale for targeting desaturase activity in cancer.

Abstract Blockade of NKG2A/HLA-E interaction is a promising strategy to unleash the anti-tumor response. Yet the role of NKG2A+ CD8 T cells in the anti-tumor response and the regulation of NKG2A expression on human tumor-infiltrating T cells are still poorly understood. Here, by performing CITE-seq on T cells derived from head and neck squamous cell carcinoma and colorectal cancer, we show that NKG2A expression is induced on CD8 T cells differentiating into cytotoxic, CD39+CD103+ double positive (DP) cells, a phenotype associated with tumor-reactive T cells. This developmental trajectory leads to TCR repertoire overlap between the NKG2A– and NKG2A+ DP CD8 T cells, suggesting shared antigen specificities. Mechanistically, IL-12 is essential for the expression of NKG2A on CD8 T cells in a CD40/CD40L- dependent manner, in conjunction with TCR stimulation. Our study thus reveals that NKG2A is induced by IL-12 on human tumor-reactive CD8 T cells exposed to a TGF-β-rich environment, highlighting an underappreciated immuno-regulatory feedback loop dependent on IL-12 stimulation.

Abstract Liquid biopsies have the potential to revolutionize cancer care through non-invasive early detection of tumors. Developing a robust liquid biopsy test requires collecting high-dimensional data from a large number of blood samples across heterogeneous groups of patients. We propose that the generative capability of variational auto-encoders enables learning a robust and generalizable signature of blood-based biomarkers. In this study, we analyze orphan non-coding RNAs (oncRNAs) from serum samples of 1050 individuals diagnosed with non-small cell lung cancer (NSCLC) at various stages, as well as sex-, age-, and BMI-matched controls. We demonstrate that our multi-task generative AI model, Orion, surpasses commonly used methods in both overall performance and generalizability to held-out datasets. Orion achieves an overall sensitivity of 94% (95% CI: 87%–98%) at 87% (95% CI: 81%–93%) specificity for cancer detection across all stages, outperforming the sensitivity of other methods on held-out validation datasets by more than ~ 30%.

Abstract Introduction The COVID-19 pandemic generated overflow of healthcare systems in several countries. As the ethical debates focused on prioritisation for access to care with scarce medical resources, numerous recommendations were created. Late 2021, the emergence of the Omicron variant whose transmissibility was identified but whose vaccine sensitivity was still unknown, reactivated debates. Fears of the need to prioritise patients arose, particularly in France. Especially, a debate began about the role of vaccination status in the prioritisation strategy. Material and methods The Ethics Committee (EC) of the University Hospital of Bordeaux (UHB), France, identified prioritisation criteria in the literature (some recommended, such as being a healthcare worker (HCW) or having consented to research, while others were discouraged, such as age with a threshold effect or vaccination status). A survey was sent within the institution in January 2022 to explore frontline physicians' adherence to these prioritisation criteria. The decision making conditions were also surveyed. Results In 15 days, 78/165 (47.3%) frontline physicians responded, and more widely 1286/12946 (9.9%) professionals. A majority of frontline physicians were opposed to prioritising HCWs (54/75, 72%) and even more opposed to participating in research (69/76, 89.6%). Conversely, the results were very balanced for non-recommended criteria (respectively 39/77, 50.7% and 34/69 49.3% in favour for age with a threshold effect and for vaccination status). Decisions were considered to be multi-professional and multi-disciplinary for 65/76, 85.5% and 53/77, 68.8% of frontline physicians. Responders expressed opposition to extending decision-making to representatives of patients, civil society or HCWs not involved in care. Discussion Prioritisation recommendations in case of scarce medical resources were not necessarily approved by the frontline physicians, or by the other HCWs. This questions the way ethical recommendations should be communicated and discussed at a local scale, but it also questions these recommendations themselves. The article also reports the experience of seeking HCWs opinions on a sensitive ethical debate in a period of crisis.

Purpose: To determine 10 MV IMRT and VMAT based protocols with a daily bolus targeting a skin dose of 45 Gy in order to replace the 6 MV tangential fields with a 5 mm thick bolus on alternate days method for post-mastectomy radiotherapy. Method: We measured the mean surface dose along the chest wall PTV as a function of different bolus thicknesses for sliding window IMRT and VMAT plans. We analyzed surface dose profiles and dose homogeneities and compared them to our standard 6 MV strategy. All measurements were performed on a thorax phantom with Gafchromic films while dosimetric plans were computed using the Acuros XB algorithm (Varian). Results: We obtained the best compromise between measured surface dose (mean dose and homogeneity) and skin toxicity threshold obtained from the literature using a daily 3 mm thick bolus. Mean surface doses were 91.4 ± 2.8% [85.7% – 95.4%] and 92.2 ± 2.3% [85.6% – 95.2%] of the prescribed dose with IMRT and VMAT techniques, respectively. Our standard 6 MV alternate days 5 mm thick bolus leads to 89.0 ± 3.7% [83.6% – 95.5%]. Mean dose differences between measured and TPS results were < 3.2% for depths as low as 2 mm depth. Conclusion: 10 MV IMRT-based protocols with a daily 3 mm thick bolus produce a surface dose comparable to the standard 6 MV 5 mm thick bolus on alternate days method but with an improved surface dose homogeneity. This allows for a better control of skin toxicity and target volume coverage.

Abstract Background Bisphenol S (BPS) is the main substitute for bisphenol A (BPA), a well-known plasticiser and endocrine disruptor. BPS disrupts ovarian function in several species. Moreover, a few studies have reported that the effects of BPS might be modulated by the metabolic status, and none have characterised the granulosa cell (GC) proteome after chronic BPS exposure. Objectives This study aimed to decipher the mechanisms of action of chronic BPS exposure on the proteome of ewe GCs while considering the interaction between a deliberate contrasted metabolism and reproductive function. Methods Forty ewes were split into two groups with contrasted diets: restricted (R, n = 20) and well-fed (WF, n = 20). The R and WF ewes were subdivided according to the dose of BPS administered through the diet (0–50 µg/kg/day), forming four groups: R0, R50, WF0 and WF50. After 3-month BPS daily exposure, GCs were recovered during the pre-ovulatory stage and proteins were analysed by nano-liquid chromatography coupled with tandem mass spectrometry. Results Chronic exposure to BPS affected the GC proteome differently according to the ewe metabolic status. Fifty-nine out of 958 quantified proteins were differentially abundant between groups and are mainly involved in carbohydrate and lipid pathways. Unsupervised hierarchical clustering of differentially abundant proteins (DAPs) identified four clusters of 34, 6, 5 and 14 proteins according to the BPS exposure and diet interaction. Pairwise comparisons between groups also revealed a strong effect of BPS exposure and diet interaction. Functional analysis of DAPs highlighted that BPS upregulated β-glucuronidase (GUSB; p = 0.002), a protein especially able to deconjugate bisphenol glucuronides (BP-g). Moreover, among unexposed ewes, GUSB was detected only in well-fed ewes. Discussion Conjugation of glucuronides inhibits the oestrogenic activity of bisphenols. Upregulation of GUSB in ewes dosed with BPS would prolong the oestrogenic effects of BPS by deconjugating BPS-g into free BPS. In addition, literature has reported an up-regulation of GUSB in people suffering from obesity. Therefore, people suffering from obesity could be subjected to prolonged and aggravated exposure to BPS. These data highlighted the deleterious effects of BPS and its interaction with metabolic status.

Abstract The Ebola virus (EBOV) remains a major public health challenge due to its complex structure and the lack of appropriate and effective vaccines and therapies. This review characterizes the Ebola virus, its immune response, and its therapeutic challenges. Structural EBOV proteins include the envelope glycoprotein, nucleoprotein, RNA polymerase L, and viral proteins VP30, VP24, VP35, and VP40. The proteins play a role in the virus’s pathogenesis by evading the host's immune response. The immune system evasion mechanisms of EBOV are critical in its pathogenesis. Some vaccines, such as the recombinant vesicular stomatitis virus-Zaire Ebola virus (RVSV-ZEBOV), have proven to be very effective and have been approved by the Food and Drug Administration (FDA) additionally, four other vaccines have been approved including Gam Evac-Combi (licensed in Russia), ad5-EBOV (approved in China), Zabdeno and Mvabea (approved in Europe). However, some challenges remain in developing effective vaccines, such as the selection of immunogens, cross-protecting immunity, long-term protection, mechanism of protection, and rapid response vaccination. Despite the progress made, there is still a need for an effective vaccine that offers durable and broad protection against multiple strains of the Ebola virus. This will be achieved through the collaboration of various organizations and government and Non-Governmental Organization (NGO) agencies.

Abstract Cancer is a heterogeneous disease requiring costly genetic profiling for better understanding and management. Recent advances in deep learning have enabled cost-effective predictions of genetic alterations from whole slide images (WSIs). While transformers have driven significant progress in non-medical domains, their application to WSIs lags behind due to high model complexity and limited dataset sizes. Here, we introduce S E Q U O I A, a linearized transformer model that predicts cancer transcriptomic profiles from WSIs. S E Q U O I A is developed using 7584 tumor samples across 16 cancer types, with its generalization capacity validated on two independent cohorts comprising 1368 tumors. Accurately predicted genes are associated with key cancer processes, including inflammatory response, cell cycles and metabolism. Further, we demonstrate the value of S E Q U O I A in stratifying the risk of breast cancer recurrence and in resolving spatial gene expression at loco-regional levels. S E Q U O I A hence deciphers clinically relevant information from WSIs, opening avenues for personalized cancer management.

Abstract Oligodendrocytes are critical for CNS myelin formation and are involved in preterm-birth brain injury (PBI) and multiple sclerosis (MS), both of which lack effective treatments. We present a pharmacogenomic approach that identifies compounds with potent pro-oligodendrogenic activity, selected through a scoring strategy (OligoScore) based on their modulation of oligodendrogenic and (re)myelination-related transcriptional programs. Through in vitro neural and oligodendrocyte progenitor cell (OPC) cultures, ex vivo cerebellar explants, and in vivo mouse models of PBI and MS, we identify FDA-approved leucovorin and dyclonine as promising candidates. In a neonatal chronic hypoxia mouse model mimicking PBI, both compounds promote neural progenitor cell proliferation and oligodendroglial fate acquisition, with leucovorin further enhancing differentiation. In an adult MS model of focal de/remyelination, they improve lesion repair by promoting OPC differentiation while preserving the OPC pool. Additionally, they shift microglia from a pro-inflammatory to a pro-regenerative profile and enhance myelin debris clearance. These findings support the repurposing of leucovorin and dyclonine for clinical trials targeting myelin disorders, offering potential therapeutic avenues for PBI and MS.

Abstract Transition of cytosine to thymine in CpG dinucleotides is the most frequent type of mutation in cancer. This increased mutability is commonly attributed to the spontaneous deamination of 5-methylcytosine (5mC), which is normally repaired by the base-excision repair (BER) pathway. However, the contribution of 5mC deamination in the increasing diversity of cancer mutational signatures remains poorly explored. We integrate mutational signatures analysis in a large series of tumor whole genomes with lineage-specific epigenomic data to draw a detailed view of 5mC deamination in cancer. We uncover tumor type-specific patterns of 5mC deamination signatures in CpG and non-CpG contexts. We demonstrate that the BER glycosylase MBD4 preferentially binds to active chromatin and early replicating DNA, which correlates with lower mutational burden in these domains. We validate our findings by modeling BER deficiencies in isogenic cell models. Here, we establish MBD4 as the main actor responsible for 5mC deamination repair in humans.

Abstract Primary antiphospholipid syndrome (PAPS) is a life-threatening clotting disorder mediated by pathogenic autoantibodies. Here we dissect the origin of self-reactive B cells in human PAPS using peripheral blood and bone marrow of patients with triple-positive PAPS via combined single-cell RNA sequencing, B cell receptors (BCR) repertoire profiling, CITEseq analysis and single cell immortalization. We find that antiphospholipid (aPL)-specific B cells are present in the naive compartment, polyreactive, and derived from the natural repertoire. Furthermore, B cells with aPL specificities are not eliminated in patients with PAPS, persist until the memory and long-lived plasma cell stages, likely after defective germinal center selection, while becoming less polyreactive. Lastly, compared with the non-PAPS cells, PAPS B cells exhibit distinct IFN and APRIL signature as well as dysregulated mTORC1 and MYC pathways. Our findings may thus elucidate the survival mechanisms of these autoreactive B cells and suggest potential therapeutic targets for the treatment of PAPS.

Abstract Building reliable and robust quantitative structure–property relationship (QSPR) models is a challenging task. First, the experimental data needs to be obtained, analyzed and curated. Second, the number of available methods is continuously growing and evaluating different algorithms and methodologies can be arduous. Finally, the last hurdle that researchers face is to ensure the reproducibility of their models and facilitate their transferability into practice. In this work, we introduce QSPRpred, a toolkit for analysis of bioactivity data sets and QSPR modelling, which attempts to address the aforementioned challenges. QSPRpred’s modular Python API enables users to intuitively describe different parts of a modelling workflow using a plethora of pre-implemented components, but also integrates customized implementations in a “plug-and-play” manner. QSPRpred data sets and models are directly serializable, which means they can be readily reproduced and put into operation after training as the models are saved with all required data pre-processing steps to make predictions on new compounds directly from SMILES strings. The general-purpose character of QSPRpred is also demonstrated by inclusion of support for multi-task and proteochemometric modelling. The package is extensively documented and comes with a large collection of tutorials to help new users. In this paper, we describe all of QSPRpred’s functionalities and also conduct a small benchmarking case study to illustrate how different components can be leveraged to compare a diverse set of models. QSPRpred is fully open-source and available at https://github.com/CDDLeiden/QSPRpred . Scientific Contribution QSPRpred aims to provide a complex, but comprehensive Python API to conduct all tasks encountered in QSPR modelling from data preparation and analysis to model creation and model deployment. In contrast to similar packages, QSPRpred offers a wider and more exhaustive range of capabilities and integrations with many popular packages that also go beyond QSPR modelling. A significant contribution of QSPRpred is also in its automated and highly standardized serialization scheme, which significantly improves reproducibility and transferability of models.

Abstract The aim of the study was to examine various haemostasis values to identify the most relevant biological indicators for detecting significant haemorrhage, to determine the effectiveness of fresh frozen plasma (FFP) transfusion. Our findings suggest that a low prothrombin time, elevated Von Willebrand Antigen, increased plasma fibrinogen, and reduced Ca2 + levels are associated with challenges in achieving proper haemostasis. However, measurements of factors II, V, VII, VIII, IX, X, XI, XIII, protein C, and protein S do not appear to be linked to difficulties in achieving adequate haemostasis. Additionally, the administration of FFP appears to impact factors V, VII, X, and II. Trial registration EudraCT number: 2019-002898-64.

Abstract Energy flow within cellular elements of the brain is a well-orchestrated, tightly regulated process, however, details underlying these functions at the single-cell level are still poorly understood. Studying hypometabolism in aging and neurodegenerative diseases may benefit from experimentation on unicellular bioenergetics. Here, we examined energy status in neurons and astrocytes using mixed hippocampal cultures and PercevalHR, an ATP:ADP nanosensor. We assessed exposures of several compounds including KCl, glutamate, FCCP, insulin, and glucose. A mitochondrial stress test was performed, and PercevalHR’s fluorescence was corrected for pH using pHrodo. Results demonstrate that PercevalHR can reliably report on the energetic status of two cell types that communicate in a mixed-culture setting. While KCl, glutamate, and FCCP showed clear changes in PercevalHR fluorescence, insulin and glucose responses were found to be more subtle and sensitive to extracellular glucose. These results may highlight mechanisms that mediate insulin sensitivity in the brain.

Abstract Introduction Since the early 2000's, the appeal of certain operating room specialties has decreasedamong medical school graduate students. The recent reform of the second and third cycles of medical studies in France provides an opportunity to set up teaching programs around operating room specialties. We have organised a teaching unit which is part of the final year of medical studies. The main objectives are: (1) to examine whether a boot camp can modify students’ opinions and preconceived assumptions about a surgical and/or anaesthetist career (2) to determine whether these changes in perception, have an impact on students' interest in pursuing a surgical/anaesthetic career compared with the current situation. Materials and methods The “working in the operating theatre” boot camp (UETB) took place after the written exams of the sixth year of medical school, before students choose their future specialty for residency. This program included practical workshops, readings and time for exchanges surgeons and anaesthetists. At the beginning and at the end of the UETB, feedback forms were collected. Results The cohort included 59 students from the Toulouse medical school, academic year 2023–2024. After attending the UETB, there was a significant qualitative improvement in interest in a surgical and intensive care-anaesthesia career. Feedback on how the UETB influenced the choice of a future specialty was very positive, with statistically significant qualitive improvement., Additionally, the students’ perception of a work-life quality as a surgeon and/or anaesthetist improved significantly. Conclusion The outcome of this study makes a strong case for integrating additional exposure to the various surgical subspecialties into the graduate medical curriculum in France. By helping to dispel misperceptions of “a surgical/anaesthetist career” early on, opportunities such as the UETB program may enable addressing the attrition rate observed among surgical and anaesthetic residency applications.

Abstract Toxins of toxin-antitoxin systems use diverse mechanisms to inhibit bacterial growth. In this study, we characterize the translation inhibitor toxin MenT3 of Mycobacterium tuberculosis, the bacterium responsible for tuberculosis in humans. We show that MenT3 is a robust cytidine specific tRNA nucleotidyltransferase in vitro, capable of modifying the aminoacyl acceptor ends of most tRNA but with a marked preference for tRNASer, to which long stretches of cytidines are added. Furthermore, transcriptomic-wide analysis of MenT3 targets in M. tuberculosis identifies tRNASer as the sole target of MenT3 and reveals significant detoxification attempts by the essential CCA-adding enzyme PcnA in response to MenT3. Finally, under physiological conditions, only in the presence the native menAT3 operon, an active pool of endogenous MenT3 targeting tRNASer in M. tuberculosis is detected, likely reflecting the importance of MenT3 during infection.

Abstract Exsolution reactions enable the synthesis of oxide-supported metal nanoparticles, which are desirable as catalysts in green energy conversion technologies. It is crucial to precisely tailor the nanoparticle characteristics to optimize the catalysts’ functionality, and to maintain the catalytic performance under operation conditions. We use chemical (co)-doping to modify the defect chemistry of exsolution-active perovskite oxides and examine its influence on the mass transfer kinetics of Ni dopants towards the oxide surface and on the subsequent coalescence behavior of the exsolved nanoparticles during a continuous thermal reduction treatment. Nanoparticles that exsolve at the surface of the acceptor-type fast-oxygen-ion-conductor SrTi0.95Ni0.05O3−δ (STNi) show a high surface mobility leading to a very low thermal stability compared to nanoparticles that exsolve at the surface of donor-type SrTi0.9Nb0.05Ni0.05O3−δ (STNNi). Our analysis indicates that the low thermal stability of exsolved nanoparticles at the acceptor-doped perovskite surface is linked to a high oxygen vacancy concentration at the nanoparticle-oxide interface. For catalysts that require fast oxygen exchange kinetics, exsolution synthesis routes in dry hydrogen conditions may hence lead to accelerated degradation, while humid reaction conditions may mitigate this failure mechanism.

Abstract Despite their indisputable importance in neuroblastoma (NB) pathology, knowledge of the bases of NB plasticity and heterogeneity remains incomplete. They may be rooted in developmental trajectories of their lineage of origin, the sympatho-adrenal neural crest. We find that implanting human NB cells in the neural crest of the avian embryo allows recapitulating the metastatic sequence until bone marrow involvement. Using deep single cell RNA sequencing, we characterize transcriptome states of NB cells and their dynamics over time and space, and compare them to those of fetal sympatho-adrenal tissues and patient tumors and bone marrow samples. Here we report remarkable transcriptomic proximities restricted to an early sympathetic neuroblast branch that co-exist with phenotypical adaptations over disease progression and recapitulate intratumor and interpatient heterogeneity. Combining avian and patient datasets, we identify a list of genes upregulated during bone marrow involvement and associated with growth dependency, validating the relevance of our multimodal approach.

Abstract Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility in men. The non-synonymous KLK3 single nucleotide polymorphism (SNP), rs17632542 (c.536 T > C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity mediates prostate cancer pathogenesis. The ‘Thr’ PSA variant leads to small subcutaneous tumours, supporting reduced prostate cancer risk. However, ‘Thr’ PSA also displays higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterisation of this PSA variant demonstrates markedly reduced proteolytic activity that correlates with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele have reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes.