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Associations between abuse, neglect, and at-risk family interactions with adolescent psychiatric disorders
No full textInternational audienceBackgroundWhile maltreatment is a well-established risk factor for psychopathology, recent literature highlights the need to consider the role of broader family dynamics in shaping diagnostic outcomes.ObjectiveThis study adopts a framework that integrates both formal abuse/neglect and at-risk family interactions, aiming to identify diagnosis-specific adversity profiles.Participants and settingsThis cross-sectional analysis, conducted at a single site as part of the Family and Care study, includes hospitalized adolescents diagnosed with one or more conditions from nine diagnostic categories. Participants were recruited over a 4-year period in an 8-bed psychiatric unit within a university-affiliated psychiatric department.MethodData on abuse and neglect were collected through the European Child Abuse and Neglect dataset and the At-Risk Family Interactions and Levers (ARFIL) scale, a 30-item clinical tool, measured family interactions. We hypothesized that patterns of maltreatment and at-risk relationships would vary by diagnosis.ResultsAmong the 425 participants, emotional abuse prevalence was 46.1 %, physical abuse 21.4 %, sexual abuse 25.1 %, and neglect 70.5 %. Significant differences by age, gender, global assessment of functioning scores, and hospitalization duration were observed between diagnostic groups (p < .05). Personality, Oppositional Defiant, and Trauma and Stress-related Disorders showed higher ARFIL diversity and intensity scores compared to other diagnoses, highlighting the distinct influence of at-risk family dynamics in addition to formal abuse or neglect. All diagnoses exhibited a specific set of associations but mood and psychotic disorders.ConclusionsDistinct maltreatment and at-risk family interaction profiles were associated with specific diagnoses. Assessing both maltreatment and family dynamics enhances understanding of patient environments and provides targeted therapeutic insights
La dette publique : monétisation, notation et restructuration
No full textInternational audienceQu’est-ce que la dette publique ? Quelle est son origine ? Pourquoi certains États très endettés empruntent-ils sans difficulté apparente, tandis que d’autres font défaut avec des niveaux de dette bien plus faibles ? Quel est le rôle des agences de notation de crédit ?Cet ouvrage propose une lecture claire et rigoureuse de la dette publique et de ses composantes, suivie d’une présentation exhaustive des créanciers de l’État et des différentes formes de restructuration et de défaut, ainsi que du concept de monétisation — la version moderne de la planche à billets.Les auteurs proposent une analyse de la situation actuelle des pays surendettés, avec un focus sur la France, en se fondant sur l’histoire économique. Quand la dette devient insoutenable, deux options s’offrent à l’État : la monétisation, qui érode la valeur des créances par l’inflation, et la restructuration, qui impose des pertes aux prêteurs.Les auteurs analysent le rôle croissant des banques centrales, et l’influence des agences de notation sur l’accès aux marchés de la dette. Ils expliquent pourquoi l’endettement en devises étrangères constitue une vulnérabilité pour les pays en voie de développement et leur interdit d’obtenir des notes de crédit élevées
Resolving the Dusty Star-forming Galaxy GN20 at z = 4.055 with NOEMA and JWST: A Similar Distribution of Stars, Gas, and Dust Despite Distinct Apparent Profiles
No full textInternational audienceWe present high-resolution (0.″13–0.″23) NOEMA observations of the dust continuum emission at 1.1 mm (rest frame 220 μm) and JWST/NIRCam and MIRI imaging of the z = 4.055 starburst galaxy GN20. The sensitive NOEMA imaging at 1.6 kpc resolution reveals extended dust emission, ≈14 kpc in diameter (r ≈ 2.5 kpc, b/a = 0.5), which is centrally asymmetric and clumpy. The dust emission is as extended as the stellar emission and molecular gas traced by CO(2–1), with a common center, and is brightest in the strongly obscured nuclear part of the galaxy. Approximately one-third of the total dust emission emerges from the nucleus and the most prominent clump to the south, with (only) 60% from the central 3.5 × 1.5 kpc (0.″5–0.″2), implying that the starburst is very extended. The combined JWST and NOEMA morphology suggests GN20 experienced a recent interaction or merger, likely invigorating the starburst. The radial surface brightness profiles of the molecular gas and near-IR stellar emission are similar, while, in contrast, the dust emission appears significantly more concentrated. Through self-consistent radiative-transfer modeling of the integrated and resolved CO and dust emission, we derive Mmol=2.9−0.3+0.4×1011f M, with αCO=2.8−0.3+0.5. We find the extended dust implies a lower global dust optical depth than previously reported but a high dust mass of Mdust=5.7−0.6+0.8×109M and gas-to-dust ratio of ≈50. Furthermore, we show that the distinct apparent radial profiles of the gas and dust can be explained purely by radiative-transfer effects (differences in the radial optical depths and temperatures), and that the observations are consistent with the gas and dust masses being similarly distributed throughout the starburst. The latter highlights the importance of accounting for radiative-transfer effects when comparing molecular gas and dust distributions from different tracers
Plasma exchange as potential treatment of severe immune checkpoint inhibitor-induced hepatitis
No full textInternational audienceBackground & Aims: Immune checkpoint inhibitors (ICIs) improve cancer survival but can cause severe immune-related hepatitis. Standard therapy with corticosteroids and second-line agents such as mycophenolate mofetil fails in some cases. Therapeutic plasma exchange (TPE) has been suggested as rescue therapy, but supporting evidence is limited.Methods: We retrospectively analyzed French multicenter data (March 2021–April 2025) on patients with grade 4 ICI-induced hepatitis refractory to corticosteroids ± other immunosuppressants who underwent TPE.Results: Thirteen patients (median age 63 years; 54% male) were included. Eleven had acute hepatitis, including seven with acute liver injury, and two had steroid-refractory cholestatic hepatitis. TPE was initiated a median of 28 days after hepatitis onset (median MELD score 21) and administered in 2–8 sessions. Liver function improved in eight patients (61.5%), allowing resumption of anticancer therapy without ICI rechallenge in five. Three patients with cirrhosis and hepatocellular carcinoma died of liver failure, and three died from other causes. TPE-related adverse events were mild to moderate.Conclusion: TPE is feasible, safe, and may be effective for severe steroid- and immunosuppressant-refractory ICI-induced hepatitis. Early initiation could improve outcomes; prospective studies are needed to clarify optimal timing and patient selection.Impact and implications: Severe immune checkpoint inhibitor-induced hepatitis represents a rare but life-threatening complication for which therapeutic options are limited once corticosteroids and immunosuppressants fail. Our study provides the first multicenter evidence suggesting that therapeutic plasma exchange (TPE) is a feasible and safe approach that may improve hepatic outcomes in this setting. These findings are particularly relevant for oncologists, hepatologists, and intensivists facing refractory immune checkpoint inhibitor-induced liver injury, as TPE could offer a bridge to recovery when liver transplantation is not feasible. Early consideration of TPE, alongside careful patient selection, could optimize outcomes, although larger prospective studies are required to confirm efficacy and define the best timing and indications
Small in the heat, transparent in the bloom : copepod morphological responses in the California upwelling ecosystem
No full textInternational audienceCopepods are central to marine food webs as they link primary producers to higher trophic levels. This study used in situ images collected with an Underwater Vision Profiler during four cruises (2008, 2012, 2014 and 2016) in the California Current Ecosystem to investigate how copepod morphologies relate to environmental conditions. Consistent with Bergmann’s rule, our results indicate that smaller copepods were associated with warmer environments. Copepods with more complex body shapes, owing to extended appendages, were observed in waters with higher fluorescence and diatom concentrations. Finally, more transparent copepods were found in shallower waters with higher fluorescence, potentially suggesting predatory avoidance of darker copepods found deeper in the water column. These findings support the power of imaging-based functional trait-based approaches to link zooplankton morphological variability with environmental gradients, enhancing our understanding of zooplankton dynamics in productive upwelling systems
Distributionally Robust Geometric Joint Chance-Constrained Optimization: Neurodynamic Approaches
No full textThis paper proposes a two-time scale neurodynamic duplex approach to solve distributionally robust geometric joint chance-constrained optimizationproblems. The probability distributions of the row vectors are not known in advance and belong to a certain distributional uncertainty set. In our paper, we study three uncertainty sets for the unknown distributions. The neurodynamic duplex is designed based on three projection equations. The main contribution of our work is to propose a neural network-based method to solve distributionally robust joint chance-constrained optimization problems that converges in probability to the global optimum without the use of standard state-of-the-art solving methods. We show that neural networks can be used to solve multiple instances of a problem. In the numerical experiments, we apply the proposed approach to solve a problem of shape optimisation and a telecommunication problem
NeuroConText: Contrastive learning for neuroscience meta-analysis with rich text representation
No full textInternational audienceBrain meta-analysis is the common way to gather information about human brain function across the existing literature in order to formulate hypotheses and contextualize new findings. However, automated meta-analysis tools face challenges such as inconsistent terminology and difficulties in analyzing long texts and capturing semantic meaning because they still rely on bag-of-words approaches; furthermore, sparse coordinate reporting in articles distorts the activation distribution due to incomplete data. This paper introduces NeuroConText, a predictive text-to-brain modeling framework designed to support brain meta-analysis by bridging neuroscience text, brain location coordinates, and brain images within a shared latent space. This framework follows the predictive brain meta-analysis paradigm: it learns a regression from text descriptions to whole-brain activation maps and also enables the retrieval of relevant studies through contrastive learning, optimizing a multi-objective loss that combines retrieval and reconstruction objectives. Furthermore, NeuroConText supports second-level statistical synthesis by providing activation associated with top-K retrieved studies that can serve as input to coordinate-based meta-analysis (CBMA) methods. NeuroConText also leverages large language models (LLMs) to capture neuroscientific information from full-text articles, plus an LLM-based text augmentation strategy to handle short-text inputs. Quantitative and qualitative analyses demonstrate NeuroConText’s ability to enhance text-to-brain retrieval performance and reconstruct brain maps from neuroscience texts. We also show that predictive brain meta-analysis tools can infer brain activations in regions discussed in articles but absent in reported coordinates, potentially addressing the challenge of sparse coordinate reporting
De nouveaux alliés du bien-être des animaux confrontés aux défis des transitions agroécologiques et climatiques
No full textNational audienc
Hydrogen production by hydrolysis of ball milled and cold rolled activated magnesium wastes: case of MSR alloy wastes in NaCl solution
No full textInternational audienceThis study investigates the hydrolysis of MSR waste alloys, activated by ball milling and cold rolling, to produce hydrogen. MSR, a magnesium alloy with 2.4% Ag, 2.5% Nd, and 0.4% Zr, is used in applications requiring corrosion or mechanical resistance. The effects of feedstock type (powder vs. chips) and mechanical pre-treatments (ball milling, cold rolling) on hydrogen yield and hydrolysis mechanisms were analyzed through SEM and XRD. Mechanical treatments reduced crystallite size from 183 nm (powder) and 180 nm (chips) to 112 nm and 153 nm, respectively. Powder feedstock, cold rolled 10 times and ball milled for 3 hours, achieved an 89% hydrogen yield after 10 minutes (min) in NaCl solution, with fast kinetics due to defects introduced by the treatments. In contrast, chips with the same pre-treatment yielded 79% after 30 min. Cold rolling alone led to a 20% yield after 30 min. These findings suggest that various industrial waste feedstocks can be used for low-cost, scalable hydrogen production via hydrolysis with simple mechanical treatments.</p
From non-specific biomarker to targeted action: transdiagnostic and sex-specific drivers of high-CRP status in severe mental illness across the FondaMental Advanced Centers of Expertise (FACE) cohorts
No full textInternational audienceBackground and objectives: Low-grade systemic inflammation contributes to the pathophysiology of severe mental illness (SMI) in a substantial subset of patients, who often experience greater disease burden and poorer treatment response. Elevated C-reactive protein (CRP), defined as CRP ≥ 3 mg/L, has been proposed to identify this group, but its non-specificity limits the biomarker's ability to guide targeted intervention. We aimed to determine the most consistent drivers of high CRP across bipolar disorder (BD), schizophrenia (SZ) and major depressive disorder (MDD), and to translate these into clinically actionable intervention targets using robust data-driven methods.Methods: We pooled and harmonised data from three large French national SMI cohorts (n = 7149: 4797 bipolar disorder, 1958 schizophrenia and 394 resistant major depression) and classified participants by CRP ≥ 3 mg/L, as well as an alternative cut-off of 5 mg/L. We applied penalised logistic regression (PLR), random forests (RF) and unsupervised clustering, using 28 biopsychosocial variables to identify robust drivers of high-CRP status. We then grouped these into actionable targets and assessed relative dominance.Results: In total, 30.16% of participants had CRP ≥ 3 mg/L. PLR identified female sex (OR [95% CI]: 1.60 [1.27, 1.93]), higher BMI (OR: 1.09 [1.07, 1.13]), current nicotine dependence (OR: 1.05 [1.02, 1.09]), lower HDL cholesterol (OR: 0.57 [0.44, 0.73]) and smoking (ex-smoker status OR: 0.84 [0.66, 0.98]) as consistent drivers. RF highlighted a similar set of key drivers, also including waist circumference, triglycerides and cardiovascular comorbidities. Clustering of the high-CRP group was almost entirely driven by smoking status and nicotine dependence. When grouped into actionable targets, the identified drivers accounted for 16% of variance in CRP status, with obesity emerging as most dominant contributor. This pattern was most pronounced in females; in males it was more diffuse, with a more prominent role for smoking.Conclusions: We propose a decision tree framework where CRP can serve as a first-line screening marker for inflammation in SMI, with subsequent steps focusing on the main contributing factors to guide targeted interventions. Priority should be given to targeting obesity and metabolic dysregulation. Among females, hyperuricemia represents the next most appropriate target, whereas in males, smoking warrants greater attention. This stepwise approach provides a route from a nonspecific biomarker to targeted treatment strategies and should be validated in prospective studies