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Importance of analyzing spasticity and co-activation as complementary biomarkers of gait in children with cerebral palsy
No full textInternational audienceBackground: Cerebral palsy (CP) is a neurological disorder characterized by motor impairments, including muscle spasticity, weakness, and abnormal co-activation leading to gait abnormalities. Understanding the relationship between these factors is essential for optimizing rehabilitation strategies but remains unclear, particularly in terms of phase-specific neuromuscular adaptations during gait. This study investigated the correlations between muscle spasticity, strength, coactivation, and gait variable scores (GVS) in children with CP during clinical gait analysis. Two muscle pairs were analyzed: Gastrocnemius Medialis-Tibialis Anterior (GM-TA) and Rectus Femoris-Semitendinosus (RF-ST). Methods:We retrospectively analyzed 55 children with CP using surface electromyography and clinical scales (Modified Ashworth Scale for spasticity, Medical Research Council scale for strength). Co-activation was computed for stance and swing phases and compared to reference values from literature data about typically developing children. Correlations between variables were assessed using Spearman's coefficient and Chi-square tests evaluated categorical relationships between spasticity and abnormal co-activation.Findings: No clear correlations between spasticity and co-activation were demonstrated, except for RF during swing (moderate correlation). GVS for ankle and hip flexion was moderately correlated with co-activation. Muscle strength negatively correlated with co-activation and deviations of joint angles relative to healthy gait.Interpretation: These findings highlight partial correlations between clinical examination (i.e., spasticity and strength) and gait data (i.e., muscle co-activation and kinematic alterations), reinforcing the importance of assessing multiple biomarkers to better characterize gait abnormalities. Future rehabilitation protocols should comprehensively evaluate spasticity, muscle strength, co-activation, and GVS to better adapt interventions and optimize motor function in children with CP.</div
Design, simulation, and experimental validation of metamaterials with direction-dependent stiffness
No full textMechanical metamaterials derive their functionality from geometry rather than composition, yet achieving experimentally validated three-dimensional direction-dependent stiffness (DDS) has remained challenging. This work introduces a 3D metamaterial unit cell with strong, tunable DDS, developed through a heuristic, gradient-free optimization framework that iteratively generated and refined geometries using finite element analysis. The final design features asymmetric internal struts and orientation-specific contact surfaces that activate bending- or stretching-dominated modes depending on loading direction. The unit cell and corresponding lattices were fabricated using high-resolution digital light processing (DLP) additive manufacturing and tested under compression along all three orthogonal axes. Simulations and experiments show excellent agreement (<1 % deviation), confirming distinct mechanical responses in the X, Y, and Z directions. The structure exhibits a stiffness increase above 350 % across deformation regions and up to 80 % contrast between its stiffest and most compliant orientations, while maintaining smooth force–displacement behavior with negligible stress concentrations. It also demonstrates substantial direction-dependent energy absorption, reaching several hundred joules in the stiffest orientation. These results establish a practical and manufacturable pathway toward architected materials with true 3D DDS, offering strong potential for exoskeletons, crash-protection systems, biomedical implants, and seismic-resistant components
Current knowledge and perspectives on the emerging Inquilinus limosus pathogen
No full textInternational audienceInquilinus limosus is a nonfermentative Gram-negative rod that has been reported as an emergent pathogen, particularly in chronic respiratory diseases. I. limosus was first isolated from the airways of a lung transplant patient suffering from cystic fibrosis (CF). As I. limosus is almost exclusively recovered from the airways of CF patients, its identification may be challenging for non-CF specialists. Indeed, I. limosus is mainly isolated from the airways of CF patients, and its pathogenesis and treatments are still debated. We have extensively reported and reviewed the different clinical cases described in the literature, the identification methods used, and the antimicrobial susceptibility testing performed. Therefore, we provide here an exhaustive description of the phenotypic features and antimicrobial susceptibilities of I. limosus . Only seven I. limosus genomes are currently available in public databases. These genomes are not fully assembled and therefore allow only partial genomic analyses, which could not unveil antimicrobial resistance determinants or virulence factors. They are approximately 7 Mb in size and encode between 6,036 and 7,483 genes. Given that the available genomes are incomplete, our genomic analyses are still limited and would undoubtedly benefit from further fully sequenced and annotated genomes to provide additional information on the antibiotic resistance and pathogenesis of I. limosus . We anticipate that our review will be a starting point for more genome sequencing studies, as well as epidemiological studies, to provide additional information on I. limosus for better management of patients
Adaptive LASSO Quantile Regression with Fixed Effects
No full textInternational audienceQuantile regression with fixed effects for longitudinal data accounts for individual-specific intercepts.When the number of individuals is large relative to the number of repeated measurements and the covariate dimension is high, we propose a dimension-reduction approach based on the least absolute shrinkage and selection operator (LASSO) penalty. Specifically, we extend adaptive LASSO quantile regression to accommodate longitudinal data. The proposed method retains oracle properties, including asymptotic normality and consistent variable selection. Monte Carlo simulations demonstrate that it performs best under moderate dimensionality, while also outperforming alternative methods in low-dimensional settings, though with smaller margins.The practical relevance of the approach is illustrated through two real-world applications: French electricity consumption and the Millennium Cohort Study. Using departmental-level data from France, we analyze non-residential electricity consumption to uncover patterns in energy demand. The log-transformed outcome remains markedly skewed, emphasizing the need for models capable of handling non-Gaussian distributions. Drawing on data from the Millennium Cohort Study, we examine factors associated with children's internalizing difficulties across different quantiles of the outcome distribution, identifying maternal mental health (Kessler scale) as the most influential predictor.</p
Identification of transdiagnostic phenomena among patients, the general population, relatives, and mental health professionals using topic modeling techniques
No full textInternational audienceIntroduction Recent research has highlighted the limitations of the categorical approach to mental disorders and has increasingly supported the development of a transdiagnostic perspective. This emerging approach focuses on common distal factors (circumstantial, biological, and social) and psychological processes that contribute to psychological suffering across a range of disorders, as well as on the resulting psychological symptoms. The present study aims to identify transdiagnostic distal factors, psychological processes, and symptoms by analyzing narratives through topic modeling—an unsupervised machine learning technique, specifically within Natural Language Processing (NLP). Topic modeling enables the automatic extraction of latent themes from unstructured text, making it possible to identify psychological patterns grounded in patients’ lived experiences. Methods We recruited four groups of participants: Patients diagnosed with a psychiatric disorder ( N = 445), Individuals from the general population ( N = 570), Relatives of patients with psychiatric disorders ( N = 354), and Mental health professionals ( N = 131). Participants answered open-ended questions exploring the causes of psychological suffering, their wishes for change, and their previous experiences with psychotherapy. Results We identified 258 topics, which were organized into 12 overarching themes. The most prominent topics concerned Emotional and Psychological Difficulties , Family and Social Relationships , and Therapeutic Processes . Each theme showed a comparable prevalence across the different diagnostic categories, supporting the transdiagnostic nature of these phenomena. Conclusion Topic modeling can be used effectively to identify transdiagnostic distal factors, psychological processes, and symptoms from diverse narratives. This approach tends to provide a novel means of supporting the relevance and validity of the transdiagnostic perspective
Prediction of inclisiran efficacy in patients with established atherosclerotic cardiovascular disease: the SIRIUS In-Silico modelling of cardiovascular outcomes
No full textInternational audienceAims: Inclisiran, an siRNA-targeting hepatic PCSK9 mRNA, reduces low-density lipoprotein cholesterol (LDL-C), but its effect on major adverse cardiovascular event (MACE) remains unconfirmed. The SIRIUS in-silico modelling program aimed to predict the efficacy of inclisiran on MACE in virtual patients with atherosclerotic cardiovascular disease (ASCVD).Methods: The SIRIUS simulation (NCT05974345) used a validated mechanistic model of ASCVD and lipid-lowering therapy (LLT) effects in a virtual population with established ASCVD and LDL-C ≥70 mg/dL. Each virtual patient served as their own control to compare inclisiran versus placebo as an adjunct to high-intensity statin therapy, alone or with ezetimibe over 5 years. The model did not account for non-adherence, recurrent events, or adverse effects.Results: Among 204 691 virtual patients, inclisiran was predicted to reduce LDL-C by 49.7% versus placebo (from 91.1 to 48.3 mg/dL). Relative to placebo, inclisiran was predicted to lower 5 years risk of 3-point MACE by 25.2% (11.3% vs. 14.9%), myocardial infarction by 34.8% (5.7% vs. 8.6%; HR 0.65), ischaemic stroke by 26% (2.6% vs. 3.4%; HR 0.74), and major adverse limb event by 34.1% (0.5% vs. 0.8%; HR 0.66). A 7.1% relative reduction of cardiovascular death was predicted (4.2% vs. 4.5%; HR 0.93).Conclusions: SIRIUS is the first in-silico simulation using a knowledge-based mechanistic model to predict the efficacy of LLT on cardiovascular outcomes in ASCVD. These findings offer early model-based prediction of inclisiran's potential cardiovascular benefit ahead of phase 3 outcome trials
Relationship between amyloid choroidopathy and neurological involvement severity scores in transthyretin amyloidosis
No full textInternational audienceBackground: Transthyretin amyloidosis (ATTR) is a disorder characterized by amyloid fibril deposits in various tissues, leading to dysfunction of one or multiple organs. Ocular manifestations include keratoconjunctivitis, secondary glaucoma, vitreous deposits, and amyloid choroidopathy. This study aims to describe the angiographic findings in 40 patients with either hereditary (ATTRv) or wild-type (ATTRwt) transthyretin amyloidosis, analyze the 3-year progression of choroidal involvement, and correlate these findings with neurological and cardiac involvement.Patients and methods: We retrospectively analyzed 79 eyes of 40 patients who underwent a comprehensive ophthalmological examination, including fluorescein angiography and indocyanine green angiography (ICGA), between 2018 and 2021. A neurological assessment (SFN-SIQ questionnaire, PND, FAP, and NIS scores) and cardiology evaluation (NYHA, LVEF) were systematically performed.Results: A total of 25 men and 15 women with a mean age of 65.8±16.8 years were included. Seventy-five percent had ATTRv, mostly with the Val30Met (p.Val50Met) mutation (35%). In 61.1% of cases, hyperfluorescent lesions were observed on ICGA. Only Val30Met (p.Val50Met) patients exhibited firework-like patterns on ICGA. There was no progression of choroidal involvement over 3 years. Ninety-five percent of patients showed neurological involvement. Diffuse choroidal involvement is associated with higher SFN-SIQ questionnaire value (P=0.02), FAP score (P=0.017) and NIS score (P=0.046). In contrast, no relationship was found between cardiac involvement and choroidal involvement.Conclusion: ICG may be used as a marker for neural components of the choroid in this disease. A prospective longitudinal study is needed to evaluate the progression of hyperfluorescent lesions on ICGA in choroidal neuropathy under treatment over time in ATTR
Circulating tumour DNA in head and neck squamous-cell carcinomas: A literature review
No full textInternational audienceBackground: In 60 % of cases, head and neck cancers (HNCs) are diagnosed at an advanced stage and therefore have a poor prognosis with survival rates of only 49 months. Circulating tumour DNA (ctDNA) has emerged as a minimally invasive biomarker able to improve early detection, assess minimal residual disease, monitor systemic treatment response and identify therapeutic targets. This literature review aims to critically synthesise evidence from the past decade on the clinical use of ctDNA in both HPV-related and HPV-unrelated HNCs. Patients and methods: A literature review was performed using PubMed and Cochrane Library on March 11th 2024, updated on November 21st, 2025, using the keywords: "circulating tumour DNA", "head and neck cancer", "ctHPV-DNA associated with HNSCC", "liquid biopsy and HNSCC". Results: After evaluation of 363 articles identified, 92 were included. ctDNA has been investigated for screening, diagnosis, prognostic stratification, treatment-response assessment, relapse detection and identification of therapeutic targets. However, performance varies considerably across studies due to methodological and biological heterogeneity.Conclusion: ctDNA shows strong potential for response assessment and post-treatment monitoring, particularly in HPV-related disease. Nevertheless, its integration into clinical practice requires methodological standardisation and validation in larger prospective studies
Interaction of bioactive glasses with fibrinogen protein. Effect of porosity and surface modification
No full textInternational audienceBioactive glasses are of great interest because of their osteostimulative effects and their intimate bond with bone tissue. Their porosity structuring and surface modification also offer opportunities for controlled adsorption, and further controlled release, of active molecules. These new textural properties and chemical surface modifications undoubtedly have an impact on their interaction with blood proteins. In the present work, we investigate the influence of two parameters, together or separately, mesostructuring porosity and surface modification by silanization, on the interactions of a sol-gel derived bioactive glass (92S6) with the blood protein fibrinogen. Results indicate first that the ordered porosity significantly favors the fibrinogen adsorption at the glass surface. On the other hand, surface silanization induces systematically a delayed adsorption of fibrinogen for at least 8 h. After this period of inhibition of protein adsorption, the protein is better adsorbed on silanized glasses surfaces comparatively to unsilanized surfaces. This effect is particularly noticeable when the glass has no mesostructured porosity. In the case of mesostructured porosity, the surface silanization has a minor impact on the adsorbed quantity of protein after 48 h, the protein adsorption being more influenced by the mesostructured porosity. The study also highlights that a modification of the protein conformation occurs when its approaches the glass surface. This modification is not related to ions release in the medium but really related to surface contact. Additionally, the study shows that the strong fibrinogen adsorption is not associated to the creation of covalent bond between fibrinogen and glass surface but due to a reversible electrostatic interaction.The mesostructured porosity and surface silanization offer new opportunities for tunable properties of the 92S6 bioactive glass
Scalable model development of carbon photosynthetic assimilation and partitioning in a green microalga during nitrogen starvation
No full textInternational audienceLipid accumulation in green microalgae is induced by stresses (e.g. nitrogen starvation) which compromise photosynthetic activity resulting in significantly lower biomass productivity than under nutrient replete conditions. While algae photosynthetic growth has been well characterized and modelled under nutrient replete conditions, the loss of photosynthetic activity during nitrogen starvation lacks specific studies to determine suitable parameterisation. The loss of photosynthetic activity of the lipid-accumulating microalgae Chlorella vulgaris NIES 227 was studied under varying light intensities during nitrogen starvation. Partition of assimilated carbon between the different macromolecules pools (carbohydrates, lipids, and proteins) was concomitantly monitored. The results showed that the decrease of photosynthetic activity correlated well to the increase of cell C:N ratio = 0,883, =65) enabling to develop a model of microalgae growth and carbon partition under nitrogen starvation. Biomass dry-weight increase could be predicted with good accuracy ( = 0,940, = 66), as total lipid and carbohydrate production could also be predicted with fair accuracy (=0,841 and 0,618 respectively). The present study henceforth showed that modelling microalgae productivity based on photosynthetic activity inferred from local light intensity, as done in scalable models under nutrient replete conditions, may be extended to nitrogen starvation conditions and enabled the prediction of lipids and carbohydrates productivity. The model proposed should thus prove useful in optimizing photobioreactors design for the production of important energetic molecules based on light distribution knowledge