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Comparaison des troubles de la cognition sociale dans les maladies neurodégénératives : Une revue de la littérature
No full textInternational audiencePoster : Social cognition impairments, including difficulties in understanding emotions and social interactions, are common in neurodegenerative diseases. This literature review compares social cognitive deficits in Alzheimer’s disease (AD), Huntington’s disease (HD), and Amyotrophic Lateral Sclerosis (ALS). Although each condition presents a specific profile, common alterations are reported, particularly in emotion recognition and theory of mind. HD is characterized by early and severe impairments in emotional recognition. In AD, the main deficits concern theory of mind and emotion recognition. ALS is associated with more subtle difficulties, especially in interpreting others' emotions and intentions. These impairments, which vary across diseases, are likely to affect patients’ social interactions. A better understanding of their specific features would help refine assessment tools and adapt care strategies. This analysis highlights the importance of social cognition in patient follow-up and the optimization of therapeutic interventions
Analysis of infectious complications in paediatric autoimmune neutropenia: a French nationwide retrospective cohort study
No full textInternational audienceBackground: Autoimmune neutropenia (AIN) is the main cause of chronic neutropenia in children, but its infectious consequences remain poorly studied. The primary objective of this study was to evaluate infectious events leading to emergency department or hospital admissions during the first 2 years following the diagnosis of AIN in children.Methods: We performed a retrospective, multicentre analysis of medical records from 21 French university hospitals of patients aged under 18 years diagnosed with AIN with positive antineutrophils autoantibodies. We collected data on emergency room visits and hospitalisations in the 2 years following diagnosis, causes of these events, microbiology results, management and outcome.Results: One hundred and sixty-eight patients were enrolled. Median age at diagnosis of AIN was 13 months. AIN was predominantly diagnosed during an infectious episode (n=120, 71%). In the 2 years of follow-up after diagnosis, 248 events of emergency room visits and/or hospitalisations were reported (0.77 per patient-year). The most frequent diagnoses were common childhood viral or bacterial infections. The incidence rate of severe infections was 0.003 per patient-year. Despite the predominance of viral infections, 177 episodes (71%) led to hospitalisation and 166 (68%) to the initiation of antibiotic therapy, for a median duration of 7 days (IQR 3-10).Conclusion: The risk of severe infections in children with AIN is low. During follow-up, we suggest being attentive to signs of severity during fever, particularly in children over 3 years of age and/or with other immunological comorbidities but not proposing systematic hospitalisation or additional antibiotic therapy
Model Variability in Assessment of Human Exposure to Radiofrequency Fields
No full textInternational audienceThe recent advances in computational dosimetry for electromagnetics and thermodynamics are reviewed to assess human exposure to electromagnetic fields in the MHz-to-terahertz range. This review emphasizes model variability in computational dosimetry. Apart from computational electromagnetic methods and their usage, the developments in anatomical phantoms and tissue dielectric properties characterization are also surveyed. In addition, the rationale for dosimetric quantities prescribed in international exposure guidelines, such as the specific absorption rate (SAR) and absorbed power density, is revisited in relation to their correlation with local and core temperature rises in various tissues and populations. A heating factor, which is defined as a steady-state temperature rise per SAR, for the brain, eye lens, skin, and body core is evaluated to estimate heating resulting from exposure to electromagnetic fields. The transition of a physical quantity in the guidelines at 6 GHz, from SAR to the absorbed power density, is discussed along with the optimal spatial averaging volume and areas. Computational evaluations of product compliance, 5G devices, and wireless power transfer systems are also reviewed. This review aims to synthesize the current knowledge, identify key sources of computational model variability and uncertainty, and outline further research needs for setting exposure guidelines and compliance assessment
Marine protected areas as living labs ? Lessons learned & future perspectives
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Lernen, im Geschichtsunterricht zu recherchieren, um in Krisenzeiten aktuelle Medienberichte zu kritisieren
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Large B-cell lymphoma: The LYSA pragmatic guidelines
No full textInternational audienceThe management of large B-cell lymphomas (LBCL) has undergone major changes over the last 5 years. These changes reflect the availability of new therapies (immunotherapies, cell therapies, targeted molecules), but also a better compartmentalization of the entities and their specific clinical characteristics. Numerous first-, second- and third-line therapeutic strategies are available, and each practitioner is committed to selecting the treatment that offers the best balance between efficacy and toxicity. Advances in the understanding of LBCL biology, coupled with improvements in diagnostic and monitoring tools and therapeutic approaches, have significantly enhanced patient outcomes in recent years. In this article, we present a set of pragmatic guidelines developed by the LYSA (Lymphoma Study Association) for the management of LBCL. These guidelines address key aspects of diagnosis, staging, response evaluation, and treatment, integrating the latest evidence from clinical trials, expert consensus, and real-world practice. They aim to provide clinicians with a clear, practical framework to optimize care for patients with LBCL, ensuring that the best available evidence is translated into clinical practice
Effects of composition and process on the performance of thermopressed materials prepared from model and real-life biomass
No full textInternational audienceThere is growing interest in turning the by-products of agricultural processes into biobased and biodegradable materials. The complexity of composition and structure of biomass makes it difficult to understand the mechanisms involved in its transformation into materials, requiring model systems. In this study, solid materials were obtained from model cellulosic fibers (modulus of 5.5-5.8 GPa) and biomass from brewery co-products (modulus of 2.2-2.6 GPa) using uniaxial compression. Their properties were comparable to or exceeded those reported for conventional binderless cellulosic materials processed at higher temperatures (~200 • C), thus highlighting the efficiency of our low-temperature process. The effect of the fiber size and composition, of the processing temperature on the resulting samples mechanical properties was assessed. We show that longer initial fibers, with higher aspect ratio, led to improved flexural modulus and strength due to a higher degree of fiber entanglement, which translated into better performance for the less transformed biomass. While purely cellulosic samples displayed better mechanical properties than those prepared from biomass at a pressing temperature of 100 • C, the increase to 140 • C closed the gap between the two biomasses particularly in terms of water resistance due to a reduced porosity. Finally, model cellulosic polymers improved the water resistance of the cellulosic samples due to the formation of water tight matrix. This low temperature, binder-free method is promising for the green transformation of biomass coproducts
A clustering based on the dynamics of DSM-5 criteria for gambling disorder: a 5-year follow-up of gamblers with and without gambling disorder
No full textInternational audienceBackground and aims: Gambling disorder (GD) follows a non-linear progression over time. Beyond shifts between disordered and non-disordered gambling statuses, the presence of each DSM-5 diagnostic criteria for GD may fluctuate throughout a gambler's trajectory. This study aimed to identify clusters of gamblers based on the evolution of the nine GD diagnostic criteria over time and to characterize these clusters using clinical variables. Methods: Data were drawn from the JEU cohort (NCT01207674), a multicenter study of adult gamblers with and without GD, featuring a five-year follow-up. Participants completed structured clinical interviews and self-report questionnaires at baseline and annually. The analysis included only individuals who completed at least one follow-up assessment and met at least one GD diagnostic criterion during the study period (n 5 209). A mixture model was applied to estimate the probability of meeting each GD criterion over time. Results: Four distinct clusters emerged, characterized by a gradient of GD severity and specific criterion-based evolutions. Some criteria fluctuated alongside overall GD severity, while others, particularly "loss of control", persisted even when severity decreased. Additionally, three criteria ("lying", "jeopardization" and "bailout") were more likely to be present only in the two most severe clusters. Discussion and conclusions: This study confirms that, beyond the fluctuations of GD states, the presence of individual criteria also varies over time. These findings provide new insights into the dynamic progression of GD and may help tailor therapeutic approaches to better address the specific needs of gamblers at different stages of the disorder.</div
Optical photothermal infrared (OPTIR) spectroscopy assisted by machine learning for lactic acid bacteria identification at strain level
No full textInternational audienceLactic acid bacteria (LAB) are widely used in food, health, and biotechnology sectors, where accurate strain level identification is critical. Conventional methods, such as 16S rRNA sequencing, PCR-based fingerprinting (RAPD, AFLP), and MALDI-TOF mass spectrometry are powerful tools to identify bacteria at species level but often fail to resolve closely related strains due to limited taxonomic resolution, protocol sensitivity, or database dependence. In this study, we evaluated the capacity of Optical photothermal infrared (OPTIR) spectroscopy, a single-cell vibrational imaging technique, combined with supervised neural networks, to classify LAB at both species and strain levels. A total of 13 strains were analysed, including five Lactiplantibacillus plantarum, one Lactiplantibacillus pentosus, one Limosilactobacillus fermentum, three Lacticaseibacillus casei/paracasei, and three Streptococcus thermophilus, covering both intra- and inter-species diversity. Spectral data from LAB were acquired using a mIRage LS OPTIR system, preprocessed, and used to train a fully connected neural network for each level. The models achieved macro F1-scores of 97% for species level and 91% for strain level classification. These results demonstrate the potential of OPTIR, when integrated with machine learning, as a robust tool for high-resolution bacterial classification, with promising applications in microbiological quality control, probiotic selection, and microbial ecology