News

Dernière mise à jour : le 22/05/2025

Find here all the news linked to RRI IMPACT (publications, seminars, events, AAP...)

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Scientific events

Conference - Mitochondrial psychobiology: foundation and emerging evidence of a mind-mitochondria connection, June 13, 10am, IBIO Conference Room

The next IBIO conference will take place on Friday June 13 at 10am in the conference room.

We will welcome Martin Picard, Associate Professor of Behavioral Medicine at Columbia University, and Caroline Trumpff, Assistant Professor of Medical Psychology in the Department of Psychiatry at Columbia University, who will present their conference: "Mitochondrial psychobiology: foundation and emerging evidence of a mind-mitochondria connection"

Abstract:

Mitochondrial psychobiology is an interdisciplinary research field that seeks to understand the intricate connections between mitochondria biology, the mind, and the body. Its primary goal is to study how mitochondrial biology influences psychological and biological processes, ultimately shaping human health, aging, and resilience. Mitochondrial phenotyping using omics data can be used to derives indices of specific aspect of mitochondria biology. Using these advanced tools on post-mortem brain omics data, we found that positive psychosocial experiences are associated with greater energy transformation machinery in the human brain. Finally, we have identified that the circulating marker GDF15, which is elevated with aging, mitochondrial defects and diseases states, is elevated with chronic psychosocial stress and increases in response to psychological stress in blood and saliva. These findings provide emerging evidence of a dynamic mind-mitochondria connection, offering new insights into the bioenergetic underpinnings of psychological resilience and stress adaptation.

You can also attend these two conferences via this zoom link: https://u-bordeaux-fr.zoom.us/j/83291803540?pwd=R23MrZyqaqdTXPfSbgwPJvWKMIz9Ad.1

Contacts:

- Hervé Lemaître (herve.lemaitre@u-bordeaux.fr)

- Fanny Munsch (fanny.munsch@u-bordeaux.fr)

- Michel Thiebaut de Schotten (michel.thiebaut@u-bordeaux.fr)

Conference - Pupillary evoked response: A biomarker for the coeruleo-cingulate circuit, June 27, 11am, IBIO conference room

The next IBIO conference will take place on Thursday June 27 at 11am in the conference room.

We will welcome Vianney Salvi, PhD student at INCIA (Team Motor control and cognition - Mococo), who will present his conference:

"Pupillary evoked response: A biomarker for the coeruleo-cingulate circuit"

Abstract:

The organization of the cingulate cortex has been the subject of intensive studies, concluding to its central role in motor control, cognition, and arousal. One of the key anatomical pathways through which the cingulate cortex influences behavior is its efferent connection to the locus coeruleus (LC). This brainstem region is responsible for noradrenaline (NA) release and is critical for various cognitive and behavioral functions. However, the specific impact of cingulate subregions on the LC-NA system remains unexplored. This study investigated how the different cingulate cortex areas affect LC-NA activity by measuring pupil-evoked responses (PERs) as an index of LC-NA activity.

You can also attend these two conferences via this zoom link: https://u-bordeaux-fr.zoom.us/j/82641278280?pwd=eIeos6zKuZe1udTqmqMfaXfh6LCOjb.1

Contacts:

- Hervé Lemaître (herve.lemaitre@u-bordeaux.fr)

- Fanny Munsch (fanny.munsch@u-bordeaux.fr)

Symposium - Focus on Brain Energy Metabolism, July 17th & 18th, Domaine du Haut-Carré, Talence

We are pleased to invite you to the "Focus on Brain 🧠 Energy Metabolism" symposium, to be held on July 17–18, 2025, at the Domaine du Haut-Carré in Talence.

Day 1 will focus on fundamental research 🔬, presenting the latest findings on metabolic interactions between different brain cell types, with particular attention to lactate exchanges – not only the astrocyte-neuron lactate shuttle, but also metabolic exchanges with microglia and oligodendrocytes.

Day 2 will be dedicated to translational research 🩺, addressing the consequences of energy metabolism dysregulation in brain disorders, with a focus on preclinical and clinical research and roundtable discussions between scientists and clinicians.

A strong emphasis will be placed on young researchers, with multiple opportunities for oral and poster presentations. Prizes🏅will be awarded for the best contributions !

The event will take place in a friendly and welcoming atmosphere, including a wine 🍷 & cheese 🧀 poster session on the evening of Day 1.

📄 Full program: fbem.sciencesconf.org/resource/page/id/3
📅 Registration (deadline: June 15, 11:59 PM): fbem.sciencesconf.org/registration?lang=en
📣 Abstract submission (young researchers, dead-line June 15): fbem.sciencesconf.org/submission/submit?lang=en

We look forward to seeing many of you there !

Organizing Committee

Anne-Karine Bouzier-Sore
Aude Panatier
Hélène Roumes

Distinction

Amel Imene Hadj Bouzid, winner of the "Prize of the President of the Republic for Innovative Researchers"

Charged by the President of the Republic of Algeria, Mr Abdelmadjid Tebboune, and as part of the activities to commemorate National Student Day, celebrated on 19 May each year, the Algerian Prime Minister, Mr Nadir Larbaoui, together with the Minister of Higher Education and Scientific Research, Mr Kamel Baddari, presided over the award ceremony for the Prize of the President of the Republic for the best student.

On Tuesday 20 May, together with the Minister of Higher Education and Scientific Research, Kamel Baddari, Prime Minister Nadir Larbaoui presided over the award ceremony for the first edition of the President of the Republic's Prize for the Innovative Researcher, at the "Abdelhafid Ihaddaden" science and technology centre in Sidi Abdellah (Algiers).

This prestigious award was delivered to Amel Imene Hadj Bouzid, doctoral student at IMPACT working in WP2 "Cardio-thoracic imaging".

Her research centers on the detection of pulmonary lesions using various imaging techniques, including CT scans and MRI, utilizing deep learning methodologies. The goal of her thesis is to ascertain the severity of lung impairments and to explore the potential for applying these methods across different imaging modalities. Her work is especially significant in the context of emerging treatments, aiming to enhance the precision of diagnosing chronic lung diseases.

Call for projects

No call for the moment.
See you soon!

Crédits photo - jannoon028 on Freepik

New publications

Publication - Bronchial wall T2w MRI signal as a new imaging biomarker of severe asthma by Benlala I, Dournes G, Girodet PO, Laurent F, Ben Hassen W, Baldacci F, De Senneville BD, Berger P. in Insights Imaging.

Abstract

Objectives: Severe asthma patients are prone to severe exacerbations with a need of hospital admission increasing the economic burden on healthcare systems. T2w lung MRI was found to be useful in the assessment of bronchial inflammation. The main goal of this study is to compare quantitative MRI T2 signal bronchial intensity between patients with severe and non-severe asthma.

Methods: This is an ancillary study of a prospective single-center study (NCT03089346). We assessed the mean T2 intensity MRI signal of the bronchial wall area (BrWall_T2-MIS) in 15 severe and 15 age and sex-matched non-severe asthmatic patients. They also have had pulmonary function tests (PFTs), fractional exhaled nitric oxide (FeNO) and blood eosinophils count (Eos). Comparisons between the two groups were performed using Student's t-test. Correlations were assessed using Pearson coefficients. Reproducibility was assessed using intraclass correlation coefficient and Bland-Altman analysis.

Results: BrWall_T2-MIS was higher in severe than in non-severe asthma patients (74 ± 12 vs 49 ± 14; respectively p < 0.001). BrWall_T2-MIS showed a moderate inverse correlation with PFTs in the whole cohort (r = -0.54, r = -0.44 for FEV1(%pred) and FEV1/FVC respectively, p ≤ 0.01) and in the severe asthma group (r = -0.53, r = -0.44 for FEV1(%pred) and FEV1/FVC respectively, p ≤ 0.01). Eos was moderately correlated with BrWall_T2-MIS in severe asthma group (r = 0.52, p = 0.047). Reproducibility was almost perfect with ICC = 0.99 and mean difference in Bland-Altman analysis of -0.15 [95% CI = -0.48-0.16].

Conclusion: Quantification of bronchial wall T2w signal intensity appears to be able to differentiate severe from non-severe asthma and correlates with obstructive PFTs' parameters and inflammatory markers in severe asthma.

Critical relevance statement: The development of non-ionizing imaging biomarkers could play an essential role in the management of patients with severe asthma in the current era of biological therapies.

Key points: Severe asthma exhibits severe exacerbations with a high burden on healthcare systems. T2w bronchial wall signal intensity is related to inflammatory biomarker in severe asthma. T2w MRI may represent a non-invasive tool to follow up severe asthma patients.

Keywords: Asthma; Inflammation; MRI.

Publication - Real-time multislice MR-thermometry of the prostate: Assessment of feasibility, accuracy and sources of biases in patients by Marcelin C, Crombé A, Jambon E, Robert G, Bladou F, Bour P, Faller T, Ozenne V, Grenier N, Quesson B. in Diagn Interv Imaging.

Abstract

Purpose: The primary purpose of this study was to evaluate the accuracy of an MR-thermometry sequence for monitoring prostate temperature. The secondary purposes were to analyze clinical and technical factors that may affect accuracy and testing the method in a realistic setting, with MR-guided Laser ablation on an ex vivo muscle sample.

Materials and methods: An ex vivo muscle sample was subjected to Laser ablation while using a two-dimensional multislice segmented echo planar imaging sequence for MR thermometry. The MR thermometry measurements were compared with invasive sensor temperature readings to assess accuracy. Subsequently, 56 men with a median age of 70 years (age range: 53-84 years) who underwent prostate MRI examinations at 1.5- (n = 27) or 3 T (n = 24) were prospectively included. For each patient, the proportion of 'noisy voxels' (i.e., those with a temporal standard deviation of temperature [SD(T)] > 2 °C) in the prostate was calculated. The impact of clinical and technical factors on the proportion of noisy voxels was also examined.

Results: MR-thermometry showed excellent correlation with invasive sensors during MR-guided Laser ablation on the ex vivo muscle sample. The median proportion of noisy voxels per patient in the entire cohort was 1 % (Q1, 0.2; Q3, 4.9; range: 0-90.4). No significant differences in median proportion of noisy voxels were observed between examinations performed at 1.5 T and those at 3 T (P = 0.89 before and after adjustment). No clinical or technical factors significantly influenced the proportion of noisy voxels.

Conclusion: Two-dimensional real time multislice MR-thermometry is feasible and accurate for monitoring prostate temperature in patients.

Keywords: MR-thermometry; Magnetic resonance imaging; Prostate; Prostate cancer; Thermal ablation.

Publication - Positive impact of sodium L-lactate supplementation on blood acid-base status in preterm newborns by Ibrahim, I., Perrot, C., Roumes, H. and al. in Pediatr Res.

Abstract

Background

Preclinical studies indicate that lactate is a crucial cerebral energy substrate, with Na-L-lactate administration significantly reducing brain lesion volumes and improving motor and cognitive functions following neonatal hypoxia-ischemia in rat pups. Its neuroprotective effects are linked to neuronal metabolic utilization, making it a promising candidate for treating newborns with hypoxia-ischemia encephalopathy, a condition where hypothermia remains the only established therapy. However, before initiating a clinical trial, it is necessary to assess the effects of Na-L-lactate infusion on blood parameters.

Methods

We retrospectively analyzed blood parameters in 60 premature neonates during their first days of life. Among them, 30 received Na-L-lactate instead of Na-Cl to prevent hyperchloremic acidosis. Blood pH, lactatemia, bicarbonates, glycemia, natremia, chloremia, base excess, and hemoglobin were monitored before, during, and after Na-L-lactate infusion.

Results

Our findings showed that Na-L-lactate infusion lowered blood lactate levels while increasing pH from 7.25 to 7.31. After stopping the infusion, lactatemia was 1.9 mM, and pH reached 7.32. Na-L-lactate supplementation effectively restored normal blood pH, maintained natremia, and prevented hyperchloremia. Notably, even in cases of high initial lactatemia, lactate levels decreased during the infusion.

Conclusion

Our data are promising and emphasize the need for further research to explore its potential applications in neonatal clinical care.

Impact

Sodium L-lactate infusion does not increase blood lactate levels and restores normal pH in premature neonates.
The study demonstrates that sodium L-lactate infusion avoids hyperchloremia while maintaining sodium levels, offering a potential alternative to sodium chloride.
These findings highlight the need for additional research studies to further evaluate the safety, efficacy, and potential applications of sodium L-lactate infusion in neonatal care.

Publication - 3D Semantic Segmentation of Airway Abnormalities on UTE-MRI with Reinforcement Learning on Deep Supervision by A. I. H. Bouzid & al., 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), Houston, TX, USA

Abstract

Cystic fibrosis (CF) monitoring traditionally relies on CT scans, which involve radiation exposure concerns. Ultra-short echo time (UTE) MRI has emerged as a promising radiation-free alternative for lung imaging. However, automated segmentation of CF lesions on UTE MRI has not been reported yet, mainly due to lower signal-to-noise ratio and contrast compared to CT. This study evaluates the feasibility of fully automated semantic segmentation of three main hallmarks of CF: bronchiectasis, bronchial wall thickening, and bronchial mucus. To address the challenges of low proton MRI signal and resolution, we propose a novel Reinforcement learning for deep Supervision adapted to nnU-Net (RiSeNet). This approach enhances the standard nnU-Net by dynamically adjusting deep supervision weights during training through reinforcement learning. We compare RiSeNet against both the baseline nnU-Net and selected state-of-the-art architectures: SAMed and nnSAM for global context modeling, MedNeXt for large-scale feature capture, and U-Mamba for efficient volumetric processing. All models were evaluated using registered same-day CT-derived ground truth labels. Results demonstrate RiSeNet's superior performance in both accuracy and efficiency when handling the unique challenges of UTE MRI segmentation.