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Metabolic acidosis causes a Fanconi-like syndrome with intracellular trafficking defects and proximal tubule dysfunction
No full textInternational audiencePatients suffering from distal renal tubular acidosis (dRTA) are sometimes diagnosed with proximal tubule dysfunction with leaks of phosphate, uric acid, amino acids, and low–molecular weight proteins, a condition also known as Fanconi-like syndrome. The underlying molecular basis is largely elusive. We previously reported on ATPase H + transporting V0 subunit a4 ( Atp6v0a4 ) knockout (KO) mice, which exhibit severe metabolic acidosis in combination with proximal tubule dysfunction as evidenced by phosphaturia and proteinuria. Here, we show that ras analog in brain 7 (Rab7), a key regulator of endolysosomal trafficking and lysosomal biogenesis, was diminished, and the number of abnormal lysosomal-associated membrane protein 1 (Lamp1)–positive vesicles labeled for increased sodium tolerance 1 (Ist1) was increased in proximal tubules of Atp6v0a4 KO mice. This was accompanied by the accumulation of autophagosomes, autolysosomes, and autophagic substrates. Correction of metabolic acidosis with bicarbonate therapy resolved proximal tubule dysfunction and trafficking defects in Atp6v0a4 KO mice. After 28 days of acid challenge, wild-type mice showed comparable trafficking defects to Rab7 down-regulation and an increase in Ist1-labeled Lamp1-positive vesicles and proximal tubule damage. Acidosis-induced decreases in RAB7-labeled particles and increased numbers of IST1-labeled LAMP1-positive particles also occurred in proximal tubule correlates of human kidney organoids derived from the widely used induced pluripotent stem cell line KOLF2.1J. Together, our data provide insight into why patients suffering from severe dRTA can develop a Fanconi-like syndrome, which may contribute to the progression of chronic kidney failure
A contemporary picture of bacterial infections in patients with hereditary hemorrhagic telangiectasia: A nationwide cohort study
No full textInternational audienceObjectives: Patients with hereditary hemorrhagic telangiectasia (HHT) present increased risk of severe infections. Studies focusing on infections in HHT population are scarce. We aimed to assess characteristics and outcomes of infections in patients with HHT.Methods: A retrospective study was conducted in a nationwide cohort of 4502 HHT patients. Patients with HHT hospitalized for infection across 16 referral centers in France between 2010 and 2024 were identified, and data were collected through a standardized questionnaire.Results: We included 163 HHT patients (median age, 60 years [49-69], 52% male), who experienced a total of 249 bacterial infections. One third (n=53/163) experienced recurrent infections requiring hospitalization. Infections caused by Staphylococcus aureus were reported in 80 patients representing 107 episodes of infection. Brain abscesses were reported in 43 patients representing 51 episodes, often despite prior pulmonary arteriovenous malformations embolization (n=17/43). In multivariable analysis, factors associated with 1-year mortality (n=27/163, 17%) were age (aHR=1.06, 95%CI:1.01-1.16) and infective endocarditis (aHR=2.88, 95%CI:1.10-7.87).Conclusions: In this HHT cohort, severe infections were predominantly due to S. aureus, far ahead of brain abscesses caused by oral bacteria. Considering the high rate of recurrent infections, further studies focusing on prophylaxis strategies in HHT patients are needed
Histidine Rich Protein 2-Based Malaria Rapid Diagnostic Testing in Sentinel Sites of Gabon: Impact of Epidemiological Context and Microscopy Capacity
No full textInternational audienceIntroduction: Rapid diagnostic tests (RDTs) that detect the histidine-rich protein 2 (HRP2) antigen are fundamental to malaria diagnosis in sub-Saharan Africa. However, their diagnostic performance can vary depending on the epidemiological context, local operational conditions, including laboratory capacity, personnel expertise and quality assurance. This study aimed to evaluate the performance of HRP2-based RDTs in sentinel sites across Gabon, and to identify factors associated with positive test results. Methods: A cross-sectional study was conducted among 447 patients recruited from multiple sentinel sites. Light microscopy of Giemsa-stained thick blood films was used as the reference standard. Malaria prevalence, diagnostic performance indicators (sensitivity, specificity, positive and negative predictive values, and overall accuracy) and discrepancies between diagnostic methods were estimated. Univariate and multivariable logistic regression analyses were performed to identify factors independently associated with HRP2-RDT positivity. Results: Malaria prevalence was 32.2 % according to microscopy and 43.4 % according to the HRP2-RDT. The overall sensitivity of the RDT was 84 %, with substantial variability between sites, ranging from 66% in Melen to 100% in Mouila. Specificity also varied substantially, reaching 95% in Melen and decreasing to 58 % in Oyem. The positive and negative predictive values were 66% and 89 %, respectively, giving an overall diagnostic accuracy of 79%. Among patients with a negative HRP2-RDT result, 10.7 % had a malaria infection confirmed by microscopy. The overall discordance rate between the two diagnostic methods was 21 %, primarily observed in Oyem and Moanda. Multivariable analysis revealed that patients attending health facilities in Mouila, Oyem and Bitam had a significantly higher likelihood of testing positive by HRP2-RDT than those in Melen. Conclusion: The diagnostic performance of HRP2-based RDTs varied significantly across sentinel sites, with an overall rate of discordance of 21.0 %. These findings highlight the need for cautious interpretation of RDT results and for strengthening diagnostic capacities, particularly microscopy, within malaria surveillance systems in Gabon
Achieving Optimal Locomotion using Self-Generated Waves
No full textInternational audienceAn oscillating body floating at the water surface produces a wave-field of self-generated waves. When the oscillation induces a difference in fore-aft wave amplitude squared, these self-generated waves can be used as a mechanism to propel the body horizontally across the surface (Longuet-Higgins and Stewart 1964). The optimisation of this wave-driven propulsion (WDP) is the interest of this work. To study the conditions necessary to produce optimal thrust we will utilise a shallow water set-up where a periodically oscillating pressure source acts as the body. In this framework, an expression for the thrust is derived by relation to the aforementioned difference in fore-aft amplitude squared. The conditions on the source for maximal thrust are explored both analytically and numerically in two optimal control problems. The first case is where a bound is imposed on the norm of the control function to regularise it. Secondly, a more physically motivated case is studied where the power injected by the source is bounded. The body is permitted to have a drift velocity . When scaled with the wave speed , the dimensionless velocity divides the study into subcritical, critical and supercritical regimes and the optimal conditions are presented for each. The result in the bounded power case is then used to demonstrate how the modulation of power injected can slowly change the cruising velocity from rest to supercritical velocities
Historias del ecologismo, influencias y trayectorias en España (1950-2024)
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Marine plastic debris as a reservoir and vector of antibiotic-resistant pathogens: evidence of transmission to sea turtles in the Southwest Indian Ocean
No full textInternational audienceMarine plastic debris provides a novel substrate for microbial colonization, potentially facilitating the spread of pathogens in marine environments. At Reunion Island (Southwest Indian Ocean), injured sea turtles undergoing rehabilitation at the K´elonia center were found to harbor antibiotic-resistant pathogenic bacteria. We hypoth- esized that these bacteria were originated from plastic debris present in the seawater pumping system. To investigate this, we isolated and characterized culturable bacteria from plastic fragments, seawater, and turtles. Bacterial identification was performed using 16S rDNA sanger sequencing, and multilocus phylogenetic analyses were conducted to assess genetic relatedness among isolates. Antimicrobial susceptibility testing (AST) was also carried out. Plastic debris, primarily composed of polypropylene and polyethylene, supported dense bacterial communities (105–107 CFU/g), in contrast to seawater which contained significantly lower loads (up to 103 CFU/ ml). Among the potentially pathogenic bacteria, Enterococcus (22 %), Vibrio (16 %), Bacillus (16 %), Staphylo- coccus (9 %), and Citrobacter (6 %) were the most prevalent. Phylogenetic analyses revealed close relationships between strains from plastics and turtles, particularly for Bacillus, Citrobacter, and Enterococcus. Notably, Vibrio strains were undetected from seawater but detected on plastics and in turtles, suggesting a possible transmission route. Phenotypic antibiotic resistances, mainly to β-lactams, were detected in 30 % of plastic-associated strains and 14 % of turtle strains. Our results suggest that plastic debris serve as a reservoir and vector for antimicrobial- resistant pathogens, potentially compromising turtle rehabilitation efforts. This potential transmission pathway may hinder the treatment of infected or injured turtles, posing a significant challenge to the conservation of these endangered species
Equivalence of relaxation time distribution in spectral induced polarization
No full textInternational audienceDecomposing spectral responses in induced polarization on the basis of elementary Debye relaxation kernels with a distribution of time constants (Relaxation Time Distribution) is a powerful tool for analysing observations in this low-frequency electromagnetic method. Notably, it enables the estimation of the sizes of polarization sites, particularly in the presence of metallic particles, as well as facilitating environmental studies. These decompositions generalize a plethora of historical models, some of which can be considered equivalent to each other in the sense of mathematical equivalence classes. Here, we explicit several types of these equivalence relations, which we recall in their definition in relation to a common property, the elements of a given class belong to a given set. For example, we present a class of models that fall under the same differential equation, meaning this is the class of models that belong to the set of distributions that verify the differential equation. We also exhibit another class of models where we can pass from one to the other by an elementary calculation. Among all the possibilities, a particular class often interests us in IP: RTD classes such as spectra are practically indistinguishable as they are so close according to a defined criterion. In this particular case, we study here the equivalence (or non-equivalence) of certain classical models. We confirm that two models play major roles: the lognormal distribution (because it is the most natural) and the Cole–Cole distribution, which is empirical but also often used for its simplicity (and the associated RTD is analytical, unlike that of the lognormal which requires numerical evaluations). It turns out that these two distributions are equivalent in terms of their quasi-equal spectra, a fact known since Cole and Cole, but whose scope is extended here by an in-depth study of the objective function which separates them in the least squares sense
Unraveling pyroclastic density current dynamics with multiparameter geophysical sensing
No full textInternational audienceDetecting, locating, and characterising the dynamics of destabilised volcanic material is critical for assessing the extreme hazards posed by volcanic mass flows, such as pyroclastic density currents. Geophysical measurements of these events may offer information otherwise hardly observable at close range. Here we investigate pyroclastic density current dynamics using a multiparameter approach that combines seismic, distributed acoustic sensing, and infrasound data with thermal and visible imagery, supported by numerical simulations. We focus on two events at Stromboli volcano, Italy, that occurred in October and December 2022. By comparing visible imagery with seismic energy and applying array processing techniques, we identify different flow volumes ( ~23.5 ± 9.5 × 10 3 m 3 and ~80 ± 9 × 10 3 m 3 , respectively) and velocities (33-42 m/s and 54-59 m/s, respectively). Simulations reveal that reproducing these velocities requires volume-dependent empirical friction angles ( ~27°a nd 21°), consistent with dry granular flow behaviour and friction weakening. These findings offer new insights into the use of distributed acoustic sensing for volcanic monitoring and underscore the value of integrating multiparameter data with modeling to better understand complex volcanic processes
Fine-Tuning Language Models for Structured Botanical Trait Extraction and Species Comparison
No full textInternational audienceAs artificial intelligence (AI) becomes central to biodiversity research, transforming morphological descriptions of species into structured data remains a challenge, particularly in botany, where species descriptions are rich in detail but lack formal structure. Despite the progress brought by transformer architectures (Vaswani et al. 2017) and their multilingual variants such as CamemBERT (Martin et al. 2020), most large language models (LLMs) are trained on general-domain English corpora, limiting their effectiveness for non-English biodiversity applications. We present a two-stage information extraction pipeline that fine-tunes LLaMA (Large Language Model Meta AI)- based LLMs (Touvron et al. 2023) to extract botanical traits from French floristic texts and enable species-level comparison at scale. Trained on a curated corpus of legacy botanical descriptions and expert-validated French question-answer pairs, the system demonstrates how domain-specific fine-tuning can bridge the gap between narrative botanical knowledge and structured trait data (Fig. 1). At the user-interface layer, we add a third stage that automatically converts the trait-value pairs generated by the question-answering module into a structured CSV table for downstream use. Our approach unifies question generation and trait extraction within a single information extraction workflow. First, predefined botanical traits (e.g., leaf shape, flower color) are reformulated as natural-language questions tailored to each species description. Then, using these questions as prompts, the model identifies and extracts the corresponding trait values: for example, extracting "lanceolate" as the standardized leaf shape from "lanceolate leaves." This converts unstructured text into consistent character-state pairs aligned with botanical ontologies. A proof-of-concept showing the input species descriptions processed by the pipeline is shown in Fig. 2. The LLaMA model was fine-tuned via Low-Rank Adaptation (LoRA) (Hu et al. 2021) on ~17,000 manually verified French question-answer pairs derived from floristic descriptions across multiple French-language flora, including: Flore de Nouvelle-Calédonie and Flore du Cameroun . Building on FloraNER (Named Entity Recognition) (Nainia et al. 2024a) and earlier CamemBERT-based pipelines (Nainia et al. 2024b), the current system, F-LoRA-QA (Nainia et al. 2025b), substantially improves structured trait generation from domain-specific descriptions. In evaluation, F-LoRA-QA outperformed an untuned LLaMA baseline with ~4× higher BLEU score (Bilingual Evaluation Understudy), a 16% gain in semantic similarity, and exact-match accuracy rising from 2% to 24%. Expert botanists further validated trait accuracy, completeness, fluency, and terminology, supporting critiques of over-reliance on automatic metrics for domain question answering (Nainia et al. 2025a). A key application is the enrichment of descriptor-based systems like Xper³ (Kerner et al. 2025), which rely on structured trait matrices to describe and differentiate taxa. Fig. 3 and Fig. 4 illustrate trait discovery, value extraction, and a comparison matrix with evidence links, supporting descriptor systems and interoperable biodiversity databases
Study of Methylene Blue from Water Solution Adsorption onto Mesoporous Silica (SiO₂) Synthesised from Clay via a Mineral Sol
No full textInternational audienceBackground: Methylene blue (BM), whose toxic effects are not immediately apparent, can, in the long term, cause damage to the cardiovascular, central nervous, dermatological, gastrointestinal, genitourinary, and haematological systems in humans. It is therefore essential to eliminate this dye from wastewater. Aims: The present study aims to investigate the elimination of methylene blue from water solution by adsorption on mesoporous silica.Study Design: This study was conducted using a batch method for the treatment of aqueous methylene blue solution through the adsorption technique.Place and Duration of Study: Département de Chimie, Université de N’Djamena, from August 2025 to October 2025.Methodology: This study aims to remove a synthetic dye, specifically methylene blue, using mesoporous silica (nanometer-sized amorphous silica) synthesised via a colloidal route. The adsorption technique is implemented by examining the influence of pH, temperature, and dye concentration under various experimental conditions. During the experiments, a fixed mass of adsorbent was introduced into different beakers containing 50 mL of the colored solution and then subjected to continuous stirring for 180 minutes at 25 °C. The effects of the experimental parameters on the adsorption process were also investigated in this work.Results: Synthesised SiO2 has a pHpzc of 7,57. An optimal pH of 8 was determined at 25 °C, resulting in 99.079% dye removal. Equilibrium was reached after 10 minutes of contact with a removal rate of 99.63%. With a mass of 40 mg of the adsorbent, 99.65% of the dye was removed. The Langmuir isotherm accurately describes the experimental data, while the pseudo-second-order kinetic model more precisely describes the adsorption behaviour.Conclusion: This mesoporous silica (SiO2) synthesised via a Mineral Sol is a promising candidate for the remediation of wastewater pollution