Délégation Provence et Corse

Animal movement underpins critical ecological processes and shapes ecosystem resilience. In marine systems, understanding the spatial ecology and connectivity of exploited species is essential for informing conservation and sustainable fisheries management. Despite their ecological and economic importance, the spatio-temporal movement of gilthead seabream (Sparus aurata) in the Mediterranean Sea remains poorly understood. We leveraged the largest acoustic telemetry dataset ever collected in the Mediterranean as part of the project CONNECT-MED and RESMED, tracking 222 tagged seabream over three years (2019–2022). Using an array of more than 180 strategically positioned acoustic receivers across the Gulf of Lion in both lagoons and the sea, we analysed over 700,000 detections spanning a longitudinal gradient of 200 km. Using individual-based spatial network analysis, we quantified movement dynamics, space use, and connectivity. Seabream showed strong seasonal migrations, with wide (> 180 km for some individuals) spatial dispersal during spawning (October–March) and localized movements whilst foraging (April–September). Eastward and southward migration linked lagoon nurseries/foraging areas to offshore spawning areas. The Marseille area (Calanques National Park and Côte Bleue Marine Park) was identified as a major spawning region used by fish across the Gulf of Lion. Movement varied with fish size, with larger fish having more complex and dynamic networks. Autumn saw synchronous lagoon emigration and aggregation at spawning sites, with multi-year site fidelity. Our findings demonstrate size-dependent movement strategies in gilthead seabream and reveal structured connectivity linking lagoon foraging areas to offshore spawning grounds. The concentration of spawning activity near Marseille identifies a key regional hotspot of ecological and management importance. Incorporating these connectivity patterns, ontogenetic shifts, and spatial behaviours into fisheries management will be essential for sustaining seabream populations across the northwestern Mediterranean.

Abstract. Prediction of shallow landslides at the regional scale generally relies on statistical analyses of landslide inventories. Rainfall-duration thresholds and susceptibility maps are among the most common approaches to anticipate future landslide occurrences. However, the outputs and reliability of these approaches can be strongly affected by the representativeness of the landslides included in the inventory. This study specifically investigates the impact of landslides triggered by an extreme rainfall event on the determination of rainfall-duration thresholds and susceptibility maps. We consider the case of Storm Alex, a millennial return period rainfall event, which hit the Alpes-Maritimes region (France) on October 2, 2020. The analysis is based on an inventory of 5,383 shallow landslides, including 1,656 landslides triggered by Storm Alex. The CTRL-T algorithm was used to compute statistical rainfall-duration thresholds with and without the inclusion of Storm Alex landslides. A Random Forest approach was used to produce and compare susceptibility maps under the same two configurations. Results show that: (a) rainfall-duration thresholds derived from datasets including Storm Alex landslides are significantly higher; (b) the exceptional rainfall intensity triggered landslides in areas having an initial lower susceptibility; and (c) including these events in susceptibility modeling alters the spatial distribution of susceptibility values. This study provides a quantitative analysis of the impact of landslides triggered by extreme rainfall events on statistical prediction models.

Bumetanide, a specific NKCC1 co-transporter inhibitor, restores deficient GABAergic inhibition implicated in various brain disorders, including Autism Spectrum Disorders (ASD). In keeping with this mechanism, nine successful phase 2 clinical trials, conducted by seven independent teams using an identical protocol, have shown significant improvements in ASD symptoms among individuals treated with Bumetanide. Despite these promising results, two large phase 3 clinical trials (over 400 children recruited in approximately 50 centers and covering age groups 2-6 and 7-17 years) failed with no significant difference between patients treated by placebo or Bumetanide. This failure may stem from the substantial heterogeneity of ASD symptom profiles across the study population, potentially diluting the overall observed treatment effect. To address this, we reanalyzed the phase 3 data using Q-Finder, a supervised machine learning algorithm, aiming to identify subgroups of patients who responded to the treatment. This analysis was based on clinical parameters collected at the baseline of trial and used the same standard endpoints and success criteria defined in the original phase 3 protocol. It enabled the identification of responder subgroups showing a statistically significant difference between placebo and Bumetanide treatment arms. We report detailed descriptions and statistical evaluations of these subgroups. The discovered responder subgroups, representing up to 40% of participants, were cross validated between the two study populations. These findings suggest that meaningful treatment responses can be uncovered within negative phase 3 trials, highlighting the limitations of a one-size-fits-all approach for heterogeneous conditions such as ASD. Machine learning appears to be a promising tool to support this precision medicine strategy.

Abstract The ability to detect sensory regularities and their violations (i.e. deviance) is fundamental for learning and the orientation of attention across the lifespan. This starts from the prenatal period, where the environment is rich in regular patterns and deviations of auditory stimulation which likely provides the basis for the emergence of early learning capacities. Following birth, EEG recordings of brain activity have demonstrated that neonates detect violations of regularity and show a robust mismatch response to deviant auditory stimuli. However, it is unknown how this processing is integrated across wider regions within emergent brain networks. To gain comprehensive insight into both the temporal and spatial properties of the processing underlying sensory deviance detection in the neonatal brain, we acquired simultaneous EEG and fMRI data in sleeping neonates during an auditory oddball paradigm. A mismatch response was identified with EEG when a deviant sound appeared after a sequence of identical sounds but not when a sound was omitted, suggesting encoding of deviances that violated local sequence regularity, but not global sequence structure. Simultaneous fMRI demonstrated engagement of distributed cortical networks during sound sequence processing, encompassing temporal, sensori-motor, and inferior frontal cortices, as well as subcortical regions including the thalamus and hippocampus. Deviance detection was associated with activity in the superior and ventromedial (hippocampus and parahippocampus) parts of the temporal lobe, and the precentral gyrus. Together, these findings suggest that neonatal brain detects deviance in sound sequences through the encoding of local regularities, supported by distinct processing pathways within sensory and limbic systems. These insights help advance our understanding of early auditory learning mechanisms, with implications for understanding how atypical developmental trajectories may emerge in these substrates.

A recent publication (Cui et al., 2025) presents an inversion method to extract temperature from multiwavelength radiation measurements that is claimed to be accurate despite the absence of any information on emissivity. This Comment recalls that when no information on emissivity is available, we are faced with an unsolvable problem because it has a continuous infinity of physically acceptable solutions, among which the true solution is indistinguishable from the others. It is therefore impossible to extract reliably the true temperature. No inversion or optimization method can be successful, except by chance. However, in Cui et al. (2025), the validation tests showed systematic success, which can then only be explained by the fact that the “true” solution was known in advance. When this is not the case, the inversion method cannot be better than a random draw. Blind tests of multiwavelength thermometry methods allegedly not requiring emissivity information were recently organized. The results confirmed, if proof were needed, that this approach is a dead end.

<bold>Background:</bold> Depemokimab is the first ultra-long-acting biologic with enhanced IL-5 binding affinity, high potency, and extended half-life, enabling twice-yearly dosing in patients with asthma. Previously approved biologics are recommended as add-on treatment to high-dose ICS. In SWIFT-1/2, depemokimab significantly reduced exacerbations, with sustained suppression of inflammation as assessed by blood eosinophil count in patients with type 2 asthma. <bold>Aims:</bold> Assess depemokimab efficacy in SWIFT-1/2 patients by medium- and high-dose ICS subgroup. <bold>Methods:</bold> Patients randomised 2:1 (stratified by medium-/high-dose ICS) with any ACQ-5 score were studied for 52 weeks and received depemokimab 100 mg subcutaneous or placebo at Week 0 and 26, plus standard of care. Pre-specified analyses examined exacerbation rate and change from baseline in St George’s Respiratory Questionnaire (SGRQ) score by baseline ICS dose. <bold>Results:</bold> Depemokimab reduced exacerbations vs placebo by 61% and 49% in patients on medium- and high-dose ICS, respectively (Figure). There was a greater SGRQ improvement for depemokimab vs placebo in patients on medium- vs high-dose ICS (Figure). <bold>Conclusions:</bold> Depemokimab reduces exacerbations in patients with asthma across baseline ICS dose subgroups, supporting potential initiation prior to ICS escalation. <bold>Funding:</bold> GSK (206713/213744; <ext-link>NCT04719832</ext-link>/NCT04718103). <fig><object-id>erj;66/suppl_69/PA2469/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig>

We performed deep next-generation sequencing using a 55-gene panel in 590 affected tissue samples from 549 patients referred for various cutaneous birthmarks, mostly vascular anomalies. We confirm that double variants in tissue from vascular anomalies are a rare event. We report the clinical features of eight patients with double variants and discuss their clinical significance and impact on treatment options.

ObjectiveThe consortium ALT‐SPF performed an international round robin test to characterize non‐invasive methods as alternatives to the erythema‐based testing of sun protection factor (SPF) according to ISO 24444:2019.MethodsHybrid diffuse reflectance spectroscopy (HDRS) based on a multi‐lambda LED light source uses in vivo reflectance spectra on skin to determine sunscreens in vivo absorbance spectra, which are fused with respective in vitro absorbance spectra measured as thin films transmission as described in ISO 24443:2019. As a part of the ALT‐SPF consortium initiative, a blinded study on 64 samples was performed in four European laboratories. After further improvements of the method, a blinded re‐evaluation based on 16 samples was performed. Five statistical acceptance criteria for new methods were assessed by an independent statistical institute to compare the obtained results to the reference methods for SPF and UVA‐PF.ResultsThe initial ALT‐SPF study 1 showed that the bias criterion was acceptable, while the reproducibility and interlaboratory variability needed further improvement. The re‐evaluation study 2 showed that the reproducibility and interlaboratory variability could be considerably improved. Using only n = 10 volunteers and a bias correction based on the initial ALT‐SPF study 1 data, the SPF results of the re‐evaluation study 2 were close to the acceptance criteria of the ALT‐SPF study with criterion 1 (reproducibility) and only 11% over the limit defined by the performance of the gold standard. The UVA‐PF results were within the acceptance limits for the acceptance criteria, except criterion 3 being in the ‘almost met’ range. The re‐evaluation study indicates that the method has a comparable precision to the gold standard methods ISO 24444 and ISO 24443.ConclusionThis study showed that the LED‐HDRS method is capable of providing reasonable non‐invasive SPF and UVA‐PF results and that the performance shows close alignment to the reference method. Thus, it can be proposed as an alternative method to the current standards ISO 24444 and ISO 24443.

COVID affects around 400 million individuals today with a strong economic impact on the global economy. The list of long COVID symptoms is extremely broad because it is derived from neurological, cardiovascular, respiratory, immune, and renal dysfunctions and damages. We review here these pathophysiological manifestations and the predictors of this multi-organ pathology like the persistence of the virus, altered endothelial function, unrepaired tissue damage, immune dysregulation, and gut dysbiosis. We also discuss the similarities between long COVID and vaccine side effects together with possible common immuno-inflammatory pathways. Since the spike protein is present in SARS-CoV-2 (and its variants) but also produced by the COVID vaccines, its toxicity may also apply to all mRNA or adenoviral DNA vaccines as they are based on the production of a very similar spike protein to the virus. After COVID infection or vaccination, the spike protein can last for months in the body and may interact with ACE2 receptors and mannan-binding lectin (MBL)/mannan-binding lectin serine protease 2 (MASP-2), which are present almost everywhere in the organism. As a result, the spike protein may be able to trigger inflammation in a lot of organs and systems similar to COVID infection. We suggest that three immuno-inflammatory pathways are particularly key and responsible for long COVID and COVID vaccine side effects, as it has been shown for COVID, which may explain in large part their strong similarities: the renin–angiotensin–aldosterone system (RAAS), the kininogen–kinin–kallikrein system (KKS), and the lectin complement pathway. We propose that therapeutic studies should focus on these pathways to propose better cures for both long COVID as well as for COVID vaccine side effects.