Themes

@article{pizzolla_network_2026,

title = {A Network Analysis of Panic Disorder, Agoraphobia, and Generalized Anxiety Disorder in 463 Patients From a Psychiatric Hospital},

author = {Emanuela Pizzolla and Juan Martin Tecco and Moritz Bruno Petzold and Giovanni Briganti},

url = {https://onlinelibrary.wiley.com/doi/10.1002/brb3.71241},

doi = {10.1002/brb3.71241},

issn = {2162-3279, 2162-3279},

year  = {2026},

date = {2026-02-01},

urldate = {2026-05-18},

journal = {Brain and Behavior},

volume = {16},

number = {2},

pages = {e71241},

abstract = {ABSTRACT 

 Introduction: 

 Panic disorder, agoraphobia, and generalized anxiety disorder (GAD) frequently co‐occur and share overlapping symptoms, yet it remains unclear whether they reflect distinct or interconnected symptom systems. This study examined the network structure of these disorders using clinician‐administered diagnostic data. 

 Methods: 

 A total of 463 adults completed the Mini International Neuropsychiatric Interview (M.I.N.I.) conducted by trained clinicians. Eighteen items from the panic disorder, agoraphobia, and GAD modules were retained after a multistep selection procedure ensuring clinical relevance, endorsement variability, and nonredundancy. A binary Ising network was estimated using eLASSO with EBIC model selection. Network accuracy, stability, and edge differences were evaluated through nonparametric bootstrapping. 

 Results: 

 The estimated network revealed two well‐defined symptom clusters corresponding to (1) panic–agoraphobia and (2) GAD. Within the panic–agoraphobia cluster, physiological symptoms (e.g., palpitations, shortness of breath, sweating, dizziness) were tightly interconnected, and catastrophic cognitions (fear of dying, fear of losing control) were moderately linked to bodily sensations. Agoraphobia symptoms were strongly connected to each other but relatively peripheral to other panic symptoms. The GAD cluster was anchored by difficulty controlling worry, which emerged as the most central symptom and showed strong associations with restlessness, sleep disturbance, fatigue, and irritability. Notably, no direct edges were found between panic–agoraphobia and GAD symptoms, suggesting distinct anxiety systems. 

 Conclusion: 

 These findings indicate that fear‐based and worry‐based anxiety symptoms form separable yet clinically relevant structures. Focusing on core processes like excessive worry and interoceptive regulation could enhance the specificity of interventions and more effectively disrupt anxiety maintenance mechanisms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{delinte_white_2026,

title = {White matter microstructure alterations from alcohol use disorder persist into early abstinence},

author = {Nicolas Delinte and Melissa Salavrakos and Manon Dausort and Laurence Dricot and Pauline Hermans and Philippe De Timary and Benoit Macq},

url = {https://academic.oup.com/braincomms/article/doi/10.1093/braincomms/fcag018/8430769},

doi = {10.1093/braincomms/fcag018},

issn = {2632-1297},

year  = {2026},

date = {2026-01-01},

urldate = {2026-02-23},

journal = {Brain Communications},

volume = {8},

number = {1},

pages = {fcag018},

abstract = {Abstract 

 Alcohol use disorder (AUD) is a complex condition including affective, cognitive and motivational dimensions. Although AUD is known to induce diffuse brain damage, including grey matter shrinkage and ventricular enlargement, the microstructural changes it induces in white matter remain incompletely understood. This study leverages multi-shell diffusion MRI and multi-fixel models to (i) undertake whole-brain and tract-specific analyses to investigate the microstructure of white matter (WM) tracts affected by AUD, (ii) evaluate whether these differences persist in early abstinence, and (iii) correlate these results with clinical measures evaluated by validated psychological questionnaires. We recruited a final cohort of 37 AUD patients, admitted for alcohol withdrawal and selected for their ongoing alcohol consumption at the time of admission, and a demographically matched control group of 19 healthy subjects. Both groups underwent MRI scans at baseline and 18 days later, with assessments of depression, obsession-compulsion, and anxiety conducted in both sessions for the AUD patients and once for the control group. The imaging results confirmed the presence in AUD participants of clusters microstructural alterations in the fornix, corpus callosum, cingulum, uncinate fasciculus and anterior thalamic radiations. These white matter tracts presented global and localized microstructural changes in axial diffusivity and fractional anisotropy, which are linked to axonal damage and inflammation. There was no significant improvement in the diffusion metrics after almost three weeks of abstinence, although clinical measures did improve significantly. Depression scores were significantly elevated in the patients at admission and decreased with time. Depression scores before withdrawal showed correlations with microstructural metrics across the right anterior thalamic radiations, the isthmus of the corpus callosum, and the right uncinate fasciculus. Lower fractional anisotropy and higher radial diffusivity were predictive of higher depression scores. Overall, these findings highlight the long-term vulnerability of WM tracts affected by AUD and the link between tract microstructure, brain function and behaviour.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pizzolla_mapping_2026,

title = {Mapping Symptom Complexity in Dementia With Lewy Bodies: A Network Analysis Approach},

author = {Emanuela Pizzolla and Wissal El Ouahidi and Kurt Segers and Murielle Surquin and Florence Benoît and Giovanni Briganti},

url = {https://psychiatryonline.org/doi/10.1176/appi.neuropsych.20240223},

doi = {10.1176/appi.neuropsych.20240223},

issn = {0895-0172, 1545-7222},

year  = {2026},

date = {2026-01-01},

urldate = {2026-05-18},

journal = {The Journal of Neuropsychiatry and Clinical Neurosciences},

pages = {appi.neuropsych.20240223},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ghislain_optimal_2025,

title = {Optimal Fractionation Scheduling for Radiotherapy Treatments with Reinforcement Learning, Tumor Growth Modeling and Outcome Modeling},

author = {Mélanie Ghislain and Florian Martin and Manon Dausort and Damien Dasnoy-Sumell and Ana Maria Barragan Montero and Benoît Macq},

url = {https://www.mdpi.com/2227-9059/13/6/1367},

doi = {10.3390/biomedicines13061367},

issn = {2227-9059},

year  = {2025},

date = {2025-06-01},

urldate = {2026-05-18},

journal = {Biomedicines},

volume = {13},

number = {6},

pages = {1367},

abstract = {Objective: Radiotherapy is a primary method for cancer treatment, wherein radiation doses are divided into multiple sessions or fractions to effectively target tumors and minimize damage to surrounding tissues. Methods: In this study, we leverage reinforcement learning (RL) to enhance treatment planning with the aim of improving the adaptability and robustness of RL agents given the inherent inaccuracies in tumor growth models. A 2D simulation model of tumor growth is employed, where tabular RL techniques are used to determine the optimal treatment strategies. We emphasize the significance of tissue damage predictions and incorporate the Lyman NTCP model to assess treatment outcomes, analyzing complications across three simulated body sites: the rectum, head and neck and lung. Results: For all the tumor sites, the RL approach significantly reduces healthy tissue damage by 10.7%, 49.1% and 37.5%, respectively, for rectal, head and neck and lung cancers compared with the baseline treatment. Conclusions: The RL-based approach in radiotherapy not only achieves tumor eradication but also significantly reduces healthy tissue damage compared with traditional treatment methods. This study demonstrates the potential of reinforcement learning to optimize treatment planning in radiotherapy, offering a promising path towards more personalized and effective cancer treatments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dessain_leveraging_2025,

title = {Leveraging Swin Transformer for enhanced diagnosis of Alzheimer's disease using multi-shell diffusion MRI},

author = {Quentin Dessain and Nicolas Delinte and Bernard Hanseeuw and Laurence Dricot and Benoit Macq},

url = {https://ieeexplore.ieee.org/document/11267073/},

doi = {10.1109/TBME.2025.3636745},

issn = {0018-9294, 1558-2531},

year  = {2025},

date = {2025-01-01},

urldate = {2026-05-13},

journal = {IEEE Transactions on Biomedical Engineering},

pages = {1–10},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{boyer_comparison_2024,

title = {Comparison of plasma soluble and extracellular vesicles-associated biomarkers in Alzheimer’s disease patients and cognitively normal individuals},

author = {Emilien Boyer and Louise Deltenre and Marion Dourte and Lise Colmant and Esther Paître and Kristel Sleegers and Nuria Suelves and Bernard Hanseeuw and Pascal Kienlen-Campard},

url = {https://alzres.biomedcentral.com/articles/10.1186/s13195-024-01508-6},

doi = {10.1186/s13195-024-01508-6},

issn = {1758-9193},

year  = {2024},

date = {2024-06-01},

urldate = {2026-05-13},

journal = {Alzheimer's Research & Therapy},

volume = {16},

number = {1},

pages = {141},

abstract = {Abstract 

 Background 

 Amyloid-β (Aβ) and tau are brain hallmarks of Alzheimer’s disease (AD), also present in blood as soluble biomarkers or encapsulated in extracellular vesicles (EVs). Our goal was to assess how soluble plasma biomarkers of AD pathology correlate with the number and content of EVs. 

 Methods 

 Single-molecule enzyme-linked assays were used to quantify Aβ42/40 and tau in plasma samples and neurally-derived EVs (NDEVs) from a cohort of 

 APOE 

 ε4– ( 

 n = 168) and 

 APOE 

 ε4+ ( 

 n = 68) cognitively normal individuals and AD patients ( 

 n = 55). The ratio of CD56 (Neuronal cell-adhesion molecule) to CD81 signal measured by ELISA-DELFIA was used for the relative quantification of NDEVs in plasma samples. 

 Results 

 The soluble plasma Aβ42/40 ratio is decreased in AD patients compared to cognitively normal individuals. The amount and content (Aβ40, Aβ42, tau) of plasma NDEVs were similar between groups. Plasma NDEVs quantity remain consistent with aging and between AD and CN individuals. However, the quantity of soluble biomarkers was negatively correlated to NDEVs number in cognitively normal individuals, while in AD patients, this correlation is lost, suggesting a shift in the mechanism underpinning the production and the release of these biomarkers in pathological conditions. 

 Conclusion 

 Soluble plasma Aβ42/40 ratio is the most robust biomarker to discriminate between AD patients and CN individuals, as it normalizes for the number of NDEVs. Analysis of NDEVs and their content pointed toward peculiar mechanisms of Aβ release in AD. Further research on independent cohorts can confirm our findings and assess whether plasma Aβ and tau need correction by NDEVs for better AD risk identification in CN populations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{fuchs_sparse_2024,

title = {Sparse Blind Spherical Deconvolution of diffusion weighted MRI},

author = {Clément Fuchs and Quentin Dessain and Nicolas Delinte and Manon Dausort and Benoît Macq},

url = {https://www.frontiersin.org/articles/10.3389/fnins.2024.1385975/full},

doi = {10.3389/fnins.2024.1385975},

issn = {1662-453X},

year  = {2024},

date = {2024-05-01},

urldate = {2024-05-23},

journal = {Frontiers in Neuroscience},

volume = {18},

pages = {1385975},

abstract = {Diffusion-weighted magnetic resonance imaging provides invaluable insights into 

 in-vivo 

 neurological pathways. However, accurate and robust characterization of white matter fibers microstructure remains challenging. Widely used spherical deconvolution algorithms retrieve the fiber Orientation Distribution Function (ODF) by using an estimation of a response function, i.e., the signal arising from individual fascicles within a voxel. In this paper, an algorithm of blind spherical deconvolution is proposed, which only assumes the axial symmetry of the response function instead of its exact knowledge. This algorithm provides a method for estimating the peaks of the ODF in a voxel without any explicit response function, as well as a method for estimating signals associated with the peaks of the ODF, regardless of how those peaks were obtained. The two stages of the algorithm are tested on Monte Carlo simulations, as well as compared to state-of-the-art methods on real 

 in-vivo 

 data for the orientation retrieval task. Although the proposed algorithm was shown to attain lower angular errors than the state-of-the-art constrained spherical deconvolution algorithm on synthetic data, it was outperformed by state-of-the-art spherical deconvolution algorithms on 

 in-vivo 

 data. In conjunction with state-of-the art methods for axon bundles direction estimation, the proposed method showed its potential for the derivation of per-voxel per-direction metrics on synthetic as well as 

 in-vivo 

 data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{colmant_definition_2024,

title = {Definition of a Threshold for the Plasma Aβ42/Aβ40 Ratio Measured by Single-Molecule Array to Predict the Amyloid Status of Individuals without Dementia},

author = {Lise Colmant and Emilien Boyer and Thomas Gerard and Kristel Sleegers and Renaud Lhommel and Adrian Ivanoiu and Philippe Lefèvre and Pascal Kienlen-Campard and Bernard Hanseeuw},

url = {https://www.mdpi.com/1422-0067/25/2/1173},

doi = {10.3390/ijms25021173},

issn = {1422-0067},

year  = {2024},

date = {2024-01-01},

urldate = {2026-05-13},

journal = {International Journal of Molecular Sciences},

volume = {25},

number = {2},

pages = {1173},

abstract = {Alzheimer’s disease (AD) is characterized by amyloid beta (Aβ) plaques and hyperphosphorylated tau in the brain. Aβ plaques precede cognitive impairments and can be detected through amyloid-positron emission tomography (PET) or in cerebrospinal fluid (CSF). Assessing the plasma Aβ42/Aβ40 ratio seems promising for non-invasive and cost-effective detection of brain Aβ accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aβ42/Aβ40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n = 88) and some volunteers (n = 66) were subject to evaluation of amyloid status by CSF Aβ quantification or PET analysis. Thresholds of plasma Aβ42/Aβ40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden’s index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ward_hygieia_2022,

title = {HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach},

author = {Bradley Ward and Jean Cyr Yombi and Jean-Luc Balligand and Patrice D. Cani and Jean-François Collet and Julien De Greef and Joseph P. Dewulf and Laurent Gatto and Vincent Haufroid and Sébastien Jodogne and Benoît Kabamba and Sébastien Pyr Dit Ruys and Didier Vertommen and Laure Elens and Leïla Belkhir},

url = {https://www.mdpi.com/1999-4915/14/7/1373},

doi = {10.3390/v14071373},

issn = {1999-4915},

year  = {2022},

date = {2022-06-01},

urldate = {2026-05-18},

journal = {Viruses},

volume = {14},

number = {7},

pages = {1373},

abstract = {More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}