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The overlap of two geosynthetic strips, located at the base of the granular load transfer platform and above rigid inclusions, is being studied on small-scale instrumented models using the moving tray device in the geotechnical centrifuge at the University Gustave Eiffel. The width of the cover (in the range between zero and the pile spacing, for 3 area ratios of reinforced pile embankment) influences the efficiency of the load transfer and the differential settlement at the surface.

The fluorescence index called the Transit Time index (TTi) is based on the fluorescence of natural organic matter in order to qualitatively assess the transit time of karst groundwater, using springs affected by human activities. This study aims to further evaluate the potential of fluorescent compounds as a natural tracer of transit time when applied to unsaturated zone flows with natural catchments, in contrast to the first study. For this purpose, a bi-monthly sampling of one year of monitoring for organic matter fluorescence, TOC, major elements and water-stable isotopes was performed. A conceptual model of the sources and fates of fluorescent compounds is built, emphasizing the allochthonous origin of humic-like C compounds, and the autochthonous production of humic-like M and protein-like compounds within the unsaturated zone. Fluorescent compound intensity interpretation according to this model reveals consistent relative transit times with flow behavior and also provides complementary information. The results also show the TTi’s ability to summarize fluorescent compounds, its consistency with relative transit time, and its higher sensitivity as compared to other natural tracers. However, prior to its use, a thorough assessment of soil organic matter, microbial activity, and potential anthropogenic contamination is required, encouraging interdisciplinary collaboration between hydrogeologists, microbiologists and soil scientists.

Background Despite widespread vaccination programs, pertussis continues circulating within populations and remains a life-threatening infection in infants. While several mortality risk factors have been described, a comprehensive synthesis is lacking. We conducted a meta-analysis of studies investigating mortality risk factors in Pertussis infections and validated those factors in a large cohort. Methods Observational studies published in English were systematically searched in PubMed, EMBASE, and LiSSa databases from 01/2000 to 06/2024. The search yielded 816 unique citations. The primary outcome was mortality before discharge from the Pediatric Intensive Care Unit (PICU). Two independent reviewers assessed the risk of bias and extracted data. A REML-random effect model was used to calculate pooled prevalence and conduct the analysis. The identified risk factors were subsequently evaluated in a monocentric cohort of patients admitted to a tertiary hospital’s PICU for severe pertussis between January 1996 and December 2020. Data analysis was conducted between June and August 2024. Results Seventeen studies, including 2,725 patients, met the inclusion criteria. The pooled prevalence of mechanical ventilation, continuous renal replacement therapy, and Extracorporeal Membrane Oxygenation support were 55% (95% CI: 40–70; I 2  = 98), 15% (95% CI: 3–27; I 2  = 95), and 8% (95% CI: 3–12; I 2  = 93), respectively. The pooled mortality incidence was 19% (95% CI:12–26; I 2  = 96). Identified mortality risk factors included elevated heart rate, presence of pulmonary hypertension, presence of seizures, and elevated white blood cell (WBC) count. Validation in an 83-patient cohort (median age: 45 days, IQR: 30–55) revealed a mortality rate of 12%. Risk factors identified in the meta-analysis were significantly associated with non-survival in the cohort. A mortality prediction score was developed incorporating age < 30 days, heart rate > 200/min, and WBC > 30 G/l, achieving an area under the curve of 0.92 (95% CI: 0.86–0.99). Conclusion This meta-analysis identified a simple yet effective score to assess the severity of pertussis infection in infants admitted to PICU. Accurate risk stratification may enable timely treatment of critically ill patients, potentially improving outcomes. Trial registration : The study protocol was registered on PROSPERO: CRD42024582057. Graphic abstract

Transit time can be estimated thanks to natural tracers, but few of them are usable in the 0-6-month range. The main purpose of this work is to analyze the potential of the ratio of heavy- to light-weight organic compounds (the humification index (HIX); Ohno, 2002; Zsolnay et al., 1999) as a natural tracer of short transit time (Blondel et al., 2012). Critical analysis of former studies shows that although the link between HIX and transit time seems consistent, the whole methodological approach needs to be consolidated. Natural organic matter fluorescence from 289 groundwater samples from four springs and 10 flow points located in the unsaturated zone of the Vaucluse karst system is characterized by parallel factor analysis (PARAFAC) thanks to the excitation-emission matrix (EEM), thus (i) allowing for the identification of main fluorescent compounds of sampled groundwater and (ii) evidencing the inadequacy of HIX 2D emission windows to characterize groundwater organic matter. We then propose a new humification index called the Transit Time index (TTi) based on the Ohno (2002) formula but using PARAFAC components of heavy and light organic matter from our samples instead of 2D windows. Finally, we evaluate TTi relevance as a transit time tracer by (i) performing a detailed analysis of its dynamics on a selected spring (Millet) and (ii) comparing its mean value over karst springs of the Vaucluse karst system. Principal component analysis (PCA) of TTi and other hydrochemical parameters monitored at Millet spring put in relief the different ranges of transit time associated with the different organic matter compounds. PCA results also provide evidence that TTi can detect a small proportion of fast infiltration water within a mix, while other natural tracers of transit time provide no or less sensitive information. TTi distributions at monitored karst springs are consistent with relative transit times expected for the small-scale, short average transit time systems. TTi thus appears as a relevant qualitative tracer of transit time in the 0-6-month range where existing tracers fail and may remain applicable, even in the case of anthropic contamination thanks to PARAFAC modeling. Transforming it into quantitative information is a challenging task which may be possible thanks to intensive studies of organic matter degradation kinetics in natural waters with the help of radiogenic isotope usage or an artificial tracer test.

Transit time can be estimated thanks to natural tracers, but few of them are usable in the 0–6-month range. The main purpose of this work is to analyze the potential of the ratio of heavy- to light-weight organic compounds (the humification index (HIX); Ohno, 2002; Zsolnay et al., 1999) as a natural tracer of short transit time (Blondel et al., 2012). Critical analysis of former studies shows that although the link between HIX and transit time seems consistent, the whole methodological approach needs to be consolidated. Natural organic matter fluorescence from 289 groundwater samples from four springs and 10 flow points located in the unsaturated zone of the Vaucluse karst system is characterized by parallel factor analysis (PARAFAC) thanks to the excitation–emission matrix (EEM), thus (i) allowing for the identification of main fluorescent compounds of sampled groundwater and (ii) evidencing the inadequacy of HIX 2D emission windows to characterize groundwater organic matter. We then propose a new humification index called the Transit Time index (TTi) based on the Ohno (2002) formula but using PARAFAC components of heavy and light organic matter from our samples instead of 2D windows. Finally, we evaluate TTi relevance as a transit time tracer by (i) performing a detailed analysis of its dynamics on a selected spring (Millet) and (ii) comparing its mean value over karst springs of the Vaucluse karst system. Principal component analysis (PCA) of TTi and other hydrochemical parameters monitored at Millet spring put in relief the different ranges of transit time associated with the different organic matter compounds. PCA results also provide evidence that TTi can detect a small proportion of fast infiltration water within a mix, while other natural tracers of transit time provide no or less sensitive information. TTi distributions at monitored karst springs are consistent with relative transit times expected for the small-scale, short average transit time systems. TTi thus appears as a relevant qualitative tracer of transit time in the 0–6-month range where existing tracers fail and may remain applicable, even in the case of anthropic contamination thanks to PARAFAC modeling. Transforming it into quantitative information is a challenging task which may be possible thanks to intensive studies of organic matter degradation kinetics in natural waters with the help of radiogenic isotope usage or an artificial tracer test.

Background Severe acute viral bronchiolitis is a common cause of admissions to pediatric intensive care units (PICUs), resulting in a significant organizational burden each winter. The recent introduction of generalized neonatal prophylactic therapies using Nirsevimab, a monoclonal antibody targeting the respiratory syncytial virus (RSV), has significantly reduced consultations and hospitalizations. However, its impact on the medico-economic aspects of the PICU remains poorly defined. Methods We analyzed all infants admitted to our unit for severe acute bronchiolitis over six consecutive epidemic periods (September to March) and examined the effect of Nirsevimab generalized prophylaxis on PICU admissions during the 2023–2024 period. Results Between 2018 and 2024, 572 out of, 3728 infants under 6 months of age were admitted to the PICU for severe acute bronchiolitis during six epidemic periods. The average percentage of infants with bronchiolitis admitted to the PICU was 15.3% (95% CI 14.2–16.5), with a net decrease during the 2023–2024 period (8.5%) compared to the 2022–2023 period (17.6%). Patients’ characteristics were similar, as were the supporting therapies. The causes of bronchiolitis were identical, with 83% and 77% secondary to RSV. PICU duration was significantly reduced during the last period from 4.4 days (95% CI 3.8–5.9) to 3.3 days (95% CI 2.6–4). The medico-economic impact was significant, with a cost reduction for acute severe viral bronchiolitis PICU total stays from €210,105 to €121,044 per annual epidemic without a change in the return on investment. Conclusions The introduction of generalized neonatal prophylaxis with Nirsevimab significantly impacts the burden of severe acute bronchiolitis in the PICU.

Prognostic factors of coronavirus disease 2019 (COVID-19) patients among European population are lacking. Our objective was to identify early prognostic factors upon admission to optimize the management of COVID-19 patients hospitalized in a medical ward. This French single-center prospective cohort study evaluated 152 patients with positive severe acute respiratory syndrome coronavirus 2 real-time reverse transcriptase-polymerase chain reaction assay, hospitalized in the Internal Medicine and Clinical Immunology Department, at Pitié-Salpêtrière's Hospital, in Paris, France, a tertiary care university hospital. Predictive factors of intensive care unit (ICU) transfer or death at day 14 (D14), of being discharge alive and severe status at D14 (remaining with ventilation, or death) were evaluated in multivariable logistic regression models; models' performances, including discrimination and calibration, were assessed (C-index, calibration curve, R2, Brier score). A validation was performed on an external sample of 132 patients hospitalized in a French hospital close to Paris, in Aulnay-sous-Bois, Île-de-France. The probability of ICU transfer or death was 32% (47/147) (95% CI 25-40). Older age (OR 2.61, 95% CI 0.96-7.10), poorer respiratory presentation (OR 4.04 per 1-point increment on World Health Organization (WHO) clinical scale, 95% CI 1.76-9.25), higher CRP-level (OR 1.63 per 100mg/L increment, 95% CI 0.98-2.71) and lower lymphocytes count (OR 0.36 per 1000/mm3 increment, 95% CI 0.13-0.99) were associated with an increased risk of ICU requirement or death. A 9-point ordinal scale scoring system defined low (score 0-2), moderate (score 3-5), and high (score 6-8) risk patients, with predicted respectively 2%, 25% and 81% risk of ICU transfer or death at D14. Therefore, in this prospective cohort study of laboratory-confirmed COVID-19 patients hospitalized in a medical ward in France, a simplified scoring system at admission predicted the outcome at D14.

Background Ovarian cancer is the first cause of death from gynecological malignancies mainly due to development of chemoresistance. Despite the emergence of PARP inhibitors, which have revolutionized the therapeutic management of some of these ovarian cancers, the 5-year overall survival rate remains around 45%. Therefore, it is crucial to develop new therapeutic strategies, to identify predictive biomarkers and to predict the response to treatments. In this context, functional assays based on patient-derived tumor models could constitute helpful and relevant tools for identifying efficient therapies or to guide clinical decision making. Method The OVAREX study is a single-center non-interventional study which aims at investigating the feasibility of establishing in vivo and ex vivo models and testing ex vivo models to predict clinical response of ovarian cancer patients. Patient-Derived Xenografts (PDX) will be established from tumor fragments engrafted subcutaneously into immunocompromised mice. Explants will be generated by slicing tumor tissues and Ascites-Derived Spheroids (ADS) will be isolated following filtration of ascites. Patient-derived tumor organoids (PDTO) will be established after dissociation of tumor tissues or ADS, cell embedding into extracellular matrix and culture in specific medium. Molecular and histological characterizations will be performed to compare tumor of origin and paired models. Response of ex vivo tumor-derived models to conventional chemotherapy and PARP inhibitors will be assessed and compared to results of companion diagnostic test and/or to the patient’s response to evaluate their predictive value. Discussion This clinical study aims at generating PDX and ex vivo models (PDTO, ADS, and explants) from tumors or ascites of ovarian cancer patients who will undergo surgical procedure or paracentesis. We aim at demonstrating the predictive value of ex vivo models for their potential use in routine clinical practice as part of precision medicine, as well as establishing a collection of relevant ovarian cancer models that will be useful for the evaluation of future innovative therapies. Trial registration The clinical trial has been validated by local research ethic committee on January 25th 2019 and registered at ClinicalTrials.gov with the identifier NCT03831230 on January 28th 2019, last amendment v4 accepted on July 18, 2023.

Background Increasing evidence supports the use of plasma biomarkers of amyloid, tau, neurodegeneration, and neuroinflammation for diagnosis of dementia. However, their performance for positive and differential diagnosis of dementia with Lewy bodies (DLB) in clinical settings is still uncertain. Methods We conducted a retrospective biomarker study in two tertiary memory centers, Paris Lariboisière and CM2RR Strasbourg, France, enrolling patients with DLB ( n  = 104), Alzheimer’s disease (AD, n  = 76), and neurological controls (NC, n  = 27). Measured biomarkers included plasma Aβ40/Aβ42 ratio, p-tau181, NfL, and GFAP using SIMOA and plasma YKL-40 and sTREM2 using ELISA. DLB patients with available CSF analysis ( n  = 90) were stratified according to their CSF Aβ profile. Results DLB patients displayed modified plasma Aβ ratio, p-tau181, and GFAP levels compared with NC and modified plasma Aβ ratio, p-tau181, GFAP, NfL, and sTREM2 levels compared with AD patients. Plasma p-tau181 best differentiated DLB from AD patients (ROC analysis, area under the curve [AUC] = 0.80) and NC (AUC = 0.78), and combining biomarkers did not improve diagnosis performance. Plasma p-tau181 was the best standalone biomarker to differentiate amyloid-positive from amyloid-negative DLB cases (AUC = 0.75) and was associated with cognitive status in the DLB group. Combining plasma Aβ ratio, p-tau181 and NfL increased performance to identify amyloid copathology (AUC = 0.79). Principal component analysis identified different segregation patterns of biomarkers in the DLB and AD groups. Conclusions Amyloid, tau, neurodegeneration and neuroinflammation plasma biomarkers are modified in DLB, albeit with moderate diagnosis performance. Plasma p-tau181 can contribute to identify Aβ copathology in DLB.