PURPOSE:To test the hypothesis that T1-w and T2-w volumetric pipelines are not interchangeable, particularly regarding their differential sensitivity to physiological traits and disease effects in the red nucleus (RN) and substantia nigra (SN). METHODS:Thirty-one patients with ALS (mean age: 59.39 ± 8.73 years; 23 males) and 21 non-neurodegenerative controls (mean age: 53.43 ± 10.01 years; 16 males). Bilateral RN and SN volumes were automatically extracted using deep learning pipelines optimized for T1-w (OpenMAP-T1) and T2-w (pBrain) images. Volumes were normalized to total intracranial volume. A 2 × 2 × 2 repeated-measures general linear model (GLM) assessed interactions between Method, Region, Side, and Group, controlling for age, sex, BMI, and handedness. RESULTS:There was no significant main effect of the disease group (p = 0.829) or Method × Group interaction (p = 0.682), indicating both pipelines agreed on the absence of disease-specific macrostructural atrophy. However, a significant four-way Method × Region × Side × Age interaction (P = 0.031) was observed. In the RN, the T2-w pipeline detected robust age-related atrophy (Left: Slope = -1.84 × 10-6; Right: Slope = -1.70 ×10⁻⁶), whereas the T1-w pipeline did not (p > 0.05). Conversely, in the SN, T1-w consistently identified bilateral age-related loss, whereas T2-w yielded lateralized results (Right: p = 0.011; Left: P = 0.465). CONCLUSIONS:T1-w and T2-w pipelines are not interchangeable. Though both confirm the absence of gross atrophy in this ALS cohort, their differing sensitivity to physiological aging highlights their distinct biological tissue properties, requiring method-specific interpretation.

Abstract Amyotrophic Lateral Sclerosis (ALS) is increasingly recognized as a multisystem neurodegenerative disorder in which motor-neuron degeneration is accompanied by widespread alterations in cortical dynamics. Among its most reproducible neurophysiological signatures is cortical hyperexcitability, yet how this local excitability imbalance shapes distributed whole-brain activity remains poorly understood. Here, we combined source-reconstructed resting-state MEG data, tractography-informed whole-brain modeling, and simulation-based inference to investigate whether ALS-related alterations in large-scale brain dynamics can be mechanistically explained by changes in cortical excitability. First, we characterized empirical brain dynamics using complementary features spanning regional activity amplitude and variability, functional connectivity, and neuronal avalanche-based metrics. These analyses revealed significant alterations in ALS patients relative to healthy controls, as well as associations with clinical impairment and disease staging. To mechanistically interpret these changes, we employed a reduced Wong–Wang whole-brain model in which local recurrent excitation modulates emergent large-scale neural dynamics. Simulations showed that increasing excitability systematically reproduced the empirical dynamical signatures observed in ALS. We then applied a simulation-based inference framework to estimate latent excitability parameters directly from empirical observations. Whole-brain model inversion revealed increased excitability in ALS patients compared with controls. The recovered excitability parameter was associated with disease staging, supporting its clinical relevance as a model-derived descriptor of ALS progression. Finally, by extending the model to estimate frontal and non-frontal excitability separately, we found that ALS-related alterations were predominantly associated with increased frontal excitability, whereas non-frontal regions appeared comparatively less affected. The recovered parameters related to disease staging. Together, these findings provide a mechanistic framework linking altered large-scale brain dynamics in ALS to selective cortical hyperexcitability, explaining how local excitability changes can give rise to global network reorganization. More broadly, they show how computational model inversion can recover latent multiscale pathophysiological processes from empirical neural recordings, offering a non-perturbative alternative to complex experimental paradigms typically required to probe local-to-global mechanisms causally.

Abstract Neurodegenerative diseases such as Mild Cognitive Impairment (MCI), Multiple Sclerosis (MS), Parkinson’s Disease (PD), and Amyotrophic Lateral Sclerosis (ALS) are becoming more prevalent. Each of these diseases, despite its specific pathophysiological mechanisms, leads to widespread reorganization of brain activity. However, the corresponding neurophysiological signatures of these changes have been elusive. As a consequence, to date, it is not possible to effectively distinguish these diseases from neurophysiological data alone. This work uses Magnetoencephalography (MEG) resting-state data, combined with interpretable machine learning techniques, to support differential diagnosis. We expand on previous work and design a Riemannian geometry-based classification pipeline. The pipeline is fed with typical connectivity metrics, such as covariance or correlation matrices. To maintain interpretability while reducing feature dimensionality, we introduce a classifier-independent feature selection procedure that uses effect-sizes derived from the Kruskal-Wallis test. The ensemble classification pipeline, called REDDI, achieved a mean balanced accuracy of 0.81 (±0.04) across five folds, representing a 13% improvement over the state-of-the-art, while remaining clinically transparent. As such, our approach achieves reliable, interpretable, data-driven, operator-independent decision-support tools in Neurology.

Automating the diagnostic process steps has been of interest for research grounds and to help manage the healthcare systems. Improved classification accuracies, provided by ever more sophisticated algorithms, were mirrored by the loss of interpretability on the criteria for achieving accuracy. In other words, the mechanisms responsible for generating the distinguishing features are typically not investigated. Furthermore, the vast majority of the classification studies focus on the classification of one disease as opposed to matched controls. While this scenario has internal validity, concerning the appropriateness toward answering scientific questions, it does not have external validity. In other words, differentiating multiple diseases at once is a classification problem closer to many real-world scenarios. In this work, we test the hypothesis that specific data features hold most of the discriminative power across multiple neurodegenerative diseases. Furthermore, we perform an explorative analysis to compare metrics based on different assumptions (concerning the underlying mechanisms). To test this hypothesis, we leverage a large Magnetoencephalography dataset (N = 109) merging four cohorts, recorded in the same clinical setting, of patients affected by multiple sclerosis, amyotrophic lateral sclerosis, Parkinson's disease, and mild cognitive impairment. Our results show that it is possible to reach a balanced accuracy of 67,1 % (chance level = 35 %), based on a small set of (non-disease specific) features. We show that edge metrics (defined as statistical dependencies between pairs of brain signals) perform better than nodal metrics (considering region while disregarding the interactions. Moreover, phase-based metrics slightly outperform amplitude-based metrics. In conclusion, our work shows that a small set of phase-based connectivity metrics applied to MEG data successfully distinguishes across multiple neurological diseases.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that, beyond motor neuron loss, involves distributed cortical network dysfunction and marked clinical heterogeneity, motivating biologically grounded markers to track disease-related network disruption. Neuronal avalanches provide a framework to probe nonstationary propagation. We introduced a novel functional connectivity metric derived from neuronal avalanches and adapted from the original avalanche transition matrix (ATM) by incorporating activation and avalanche duration: weighted-stochastic ATM (ws-ATM). We hypothesized that embedding temporal persistence would improve robustness and sensitivity to ALS-related alterations, quantitatively linked to standardized clinical severity and staging. We tested this hypothesis on resting-state MEG source-reconstructed data from 39 individuals with ALS and matched healthy controls. For each neuronal avalanche, we constructed a transition count matrix T, where each element T ij was incremented whenever region i was active at time t and region j at time t+1, thus capturing persistence through consecutive co-activations. Each matrix was then row-normalized to produce a row-stochastic transition probability matrix. Finally, these matrices were aggregated into a subject-level ws-ATM, with weights scaled according to the duration of each avalanche. Robustness was assessed by progressively removing avalanches and quantifying deviations from the full-signal ws-ATM. For clinical relevance, we propose a concordance framework that (i) identifies large-scale reorganization in ALS vs controls, (ii) tests whether individual propagation differences correlate with impairment (ALSFRS-R/MiToS), and (iii) highlights edges whose between-group changes align with within-patient severity in a directionally consistent, clinically interpretable way. ws-ATM converged earlier and stayed stable under substantial avalanche removal, with reduced inter-subject dispersion versus ATM; effects persisted across most truncation levels (up to ∼65% removal). In ALS, ws-ATM detected more altered edges than ATM (370 vs 74), revealing widespread changes with prominent frontal and fronto-motor involvement. Clinical associations strengthened, with greater overlap between ALS–control edges and disability-related edges (ws-ATM: 17/15 for ALSFRS-R/MiToS vs ATM: 6/2), enriching frontal/fronto-motor nodes including superior frontal and precentral regions. Our findings indicate that ws-ATM remains reliable with shorter recordings and after removing artifact-contaminated segments, an advantage for clinical diagnostic use. Moreover, it appears to better capture disease-relevant network alterations, providing a biologically grounded set of features that could support ALS stratification.

Tofersen is a gene-targeted therapy for superoxide dismutase 1 (SOD1)-associated amyotrophic lateral sclerosis (ALS), but neurofilament light chain (NfL) may not fully capture the biological response to treatment. We performed a multicentre retrospective longitudinal study including 24 patients with SOD1-ALS treated with intrathecal tofersen at four Italian referral centres between 2022 and 2025. Cerebrospinal fluid (CSF) and serum biomarkers were assessed at baseline, month 3, month 6, and last available administration using single-molecule array assays to quantify NfL, glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCHL-1), and total Tau. NfL decreased after treatment initiation in both CSF and serum, providing the clearest pharmacodynamic signal. In contrast, CSF GFAP increased progressively over follow-up, while CSF total Tau and UCHL-1 rose mainly at later timepoints; serum GFAP, total Tau, and UCHL-1 also showed increases during follow-up. ALS Functional Rating Scale-Revised trajectories were broadly stable, whereas disease progression rate was lower at last follow-up than at baseline. Greater reductions in CSF NfL were observed in pathogenic versus uncertain SOD1 variants, and early serum NfL and UCHL-1 changes were associated with longer-term changes in disease progression. These findings suggest that longitudinal multi-analyte profiling may refine biological response stratification beyond NfL alone in tofersen-treated SOD1-ALS.

BACKGROUND:Although treatment goals in migraine prevention have moved beyond the benchmark of a 50% reduction in monthly attacks, residual disease burden is still evaluated based on residual headache frequency. However, migraine-related symptoms can persist despite headache freedom, leading to so-called unclear days that may meaningfully contribute to interictal burden. METHODS:In this prospective, real-world study, patients with chronic or high-frequency episodic migraine treated with CGRP-monoclonal antibodies (CGRP-mAbs) were followed for six months. Interictal burden was assessed using the Migraine Interictal Burden Scale (MIBS-4) alongside the monthly unclear and crystal clear days. Patients achieving optimal (< 4 monthly attacks) or modest (4-6 monthly attacks) migraine control were stratified according to the presence of "residual interictal burden" (MIBS-4 ≥ 3). RESULTS:Two hundred patients were included. CGRP-mAbs treatment was associated with a reduction in MIBS-4 scores and an increase in crystal clear days (p < 0.001). Despite optimal or modest migraine control, 45.1% of patients at month 3 and 27.2% at month 6 continued to exhibit a substantial "residual interictal burden". Patients with "residual interictal burden" showed significantly more unclear days and fewer crystal clear days compared with those without residual interictal migraine burden, while no differences were observed in residual headache days, concomitant preventive treatments, or cephalalgiophobia. DISCUSSION:Even when migraine attacks are adequately controlled, residual interictal burden may remain and seems to be predominantly associated with unclear days rather than with residual attacks. Assessing crystal clear and unclear days provides a complementary, patient-centered perspective on treatment response and interictal recovery in migraine.

IntroductionAmyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease involving widespread network disruption beyond the motor cortex. Deep gray matter (DGM) nuclei, crucial for motor and cognitive integration, remain underexplored in vivo. This study applied neurite orientation dispersion and density imaging (NODDI) to evaluate DGM microstructure and its relationship with clinical disability in ALS.MethodsDiffusion-weighted MRI data were acquired from 23 ALS patients and 24 age- and sex-matched healthy controls. Orientation dispersion index (ODI), neurite density index (NDI), and free water fraction (FWF) were extracted from the bilateral thalamus, caudate, putamen, pallidum, hippocampus, and amygdala using the Destrieux atlas. Group comparisons and partial correlations were adjusted for age, sex, and disease duration.ResultsNo significant group differences in DGM volumes or NODDI-derived metrics survived correction for multiple comparisons. Within the ALS group, several nominal (uncorrected) associations were observed between DGM microstructural metrics and ALSFRS-R subscores. Reduced respiratory subscores were associated with higher ODI in the left thalamus (ρ = 0.57, p = 0.0047, uncorrected). Fine-motor subscores showed nominal positive associations with ODI in the left (ρ = 0.48, p = 0.021, uncorrected) and right amygdala (ρ = 0.51, p = 0.012, uncorrected). Gross motor subscores were nominally associated with NDI in the right thalamus (ρ = 0.58, p = 0.004, uncorrected), left thalamus (ρ = 0.42, p = 0.047, uncorrected), left caudate (ρ = 0.52, p = 0.011, uncorrected), and right caudate (ρ = 0.57, p = 0.033, uncorrected). None of these associations survived false discovery rate correction and should therefore be interpreted as exploratory.DiscussionThese findings suggest subtle and predominantly exploratory associations between DGM microstructural properties and clinical measures in ALS. NODDI derived metrics, particularly ODI and NDI, may provide sensitive indices of subcortical microstructural variation, warranting further investigation in larger cohorts.

Motor Neuron Diseases (MNDs) such as Amyotrophic Lateral Sclerosis (ALS), Primary Lateral Sclerosis (PLS), Hereditary Spastic Paraplegia (HSP), Spinal Muscular Atrophy with Respiratory Distress Type 1 (SMARD1), Multisystem Proteinopathy (MSP), Spinal and Bulbar Muscular Atrophy (SBMA), and ALS associated to Frontotemporal Dementia (ALS-FTD), have traditionally been studied as distinct entities, each one with unique genetic and clinical characteristics. However, emerging research reveals that these seemingly disparate conditions converge on shared molecular mechanisms that drive progressive neuroaxonal degeneration. This narrative review addresses a critical gap in the field by synthesizing the most recent findings into a comprehensive, cross-disease mechanisms framework. By integrating insights into RNA dysregulation, protein misfolding, mitochondrial dysfunction, DNA damage, kinase signaling, axonal transport failure, and immune activation, we highlight how these converging pathways create a common pathogenic landscape across MNDs. Importantly, this perspective not only reframes MNDs as interconnected neurodegenerative models but also identifies shared therapeutic targets and emerging strategies, including antisense oligonucleotides, autophagy modulators, kinase inhibitors, and immunotherapies that transcend individual disease boundaries. The diagnostic and prognostic potential of Neurofilament Light Chain (NfL) biomarkers is also emphasized. By shifting focus from gene-specific to mechanism-based approaches, this paper offers a much-needed roadmap for advancing both research and clinical management in MNDs, paving the way for cross-disease therapeutic innovations.

Objective: Perturbation of iron homeostasis is a potential key mechanism involved in neurodegeneration across many neurological disorders, including amyotrophic lateral sclerosis (ALS). We hypothesized that changes in quantitative susceptibility mapping (QSM) could capture perturbations in brain iron concentration in subgroups of ALS patients stratified by clinical phenotype and disease progression. Method: We enrolled 38 ALS patients (23 males - mean age: 58.7 ± 9.8), screened by clinical (ALS functional rating scale-revised, ALSFRS-R) and neuropsychological scales. Patients were a posteriori classified as fast (n = 16) or slow (n = 22) progressors. Two subgroups were also considered: pyramidal (or upper motor neuron+, UMN+) patients (n = 18), and patients with other phenotypes (n = 20). Results: Comparing fast vs. slow progressors, significant differences in iron deposits were observed in the left (p = 0.028) and right amygdala (p = 0.022), and in susceptibility distribution on the right hippocampus (p = 0.0011). Comparing UMN+ vs. other phenotypes, significant susceptibility differences emerged in the left thalamus (p = 0.0014) and right amygdala (p = 0.001). QSM changes were associated with baseline ALSFRS-R (rho = 0.36, p = 0.026) in the left paracentral cortex, and iron concentration with UMN score (rho = 0.35, p = 0.034). Moreover, the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) was associated with iron deposits in the left thalamus (rho=-0.46, p = 0.0041). Conclusions: We confirmed that QSM alterations in extra-motor areas and subcortical regions may be distinctive hallmarks of neurodegeneration in pure/dominant UMN phenotypes of ALS. Moreover, we showed that QSM could be a valuable tool to differentiate patients with different progression rates and phenotypes, suggesting that QSM may support a prognostically useful early stratification of ALS patients.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder involving the progressive degeneration of upper and lower motor neurons. While oxidative stress, RNA-binding protein (RBP) pathology, mitochondrial dysfunction, and glial–neuronal dysregulation is involved in ALS pathogenesis, current therapies provide limited benefit, underscoring the need for multi-target disease-modifying strategies. Nuclear factor erythroid 2-related factor 2 (Nrf2), classically regarded as a master regulator of redox homeostasis, has recently emerged as a central integrator of cellular stress responses relevant to ALS. Beyond its canonical antioxidant function, Nrf2 regulates critical pathways involved in mitochondrial quality control, proteostasis, nucleocytoplasmic transport, RNA surveillance, and glial reactivity. Experimental models demonstrate that astrocyte-specific Nrf2 activation enhances glutathione metabolism, suppresses neuroinflammation, promotes stress granule disassembly, and reduces RBP aggregation. In C9orf72-linked ALS, Nrf2 activation mitigates dipeptide repeat protein toxicity and restores RNA processing fidelity via modulation of nonsense-mediated decay and R-loop resolution. Recent advances in Nrf2-targeted interventions including Keap1–Nrf2 protein–protein interaction inhibitors, dual Nrf2/HSF1 activators, and cell-type-selective Adeno-associated virus 9 (AAV9) vectors show promise in preclinical ALS models. These multimodal approaches highlight Nrf2’s therapeutic versatility and potential to address the upstream convergence points of ALS pathogenesis. Taken together, positioning Nrf2 as a systems-level regulator offers a novel framework for developing precision-based therapies in ALS. Integrating Nrf2 activation with RNA- and glia-directed strategies may enable comprehensive modulation of disease progression at its molecular roots.

Background/Objectives: Despite the recent advances in glucose-lowering therapy, achieving diabetes control remains challenging. With the advancing progress of innovative digital health technologies, management of diabetes is taking advantage from telehealth and telemedicine, which allow for remote assistance, virtual visits, and monitoring of diabetes-related parameters, and facilitate the exchange of documents and reports to support clinical decisions. We aim to provide an overview of the impact of telehealth and digital technologies on the care of people with diabetes, from therapeutic management to the assessment of complications. Methods: A comprehensive literature search was conducted using PubMed to assess the impact of digital technologies and telemedicine on diabetes care. Results: From the comprehensive PubMed search, 86 peer-reviewed studies were selected based on relevance, clinical significance, and methodological quality. The selected literature addressed digital health tools such as continuous glucose monitoring, connected insulin pens, automatic insulin delivery systems, mobile applications, and telemedicine systems. These interventions were associated with improved glycemic control (e.g., reduced HbA1c, increased time in range), better adherence to therapy, enhanced patient engagement, and more efficient management of complications such as neuropathy, retinopathy, and cardiovascular risk. Conclusions: Telehealth may offer a fully patient-centered approach to disease management through a tailored individual management plan. This may lead to an improvement in adherence to proper therapy and lifestyle, resulting in a subsequent increase in the quality of life.

The initiation of tofersen, a new specific antisense oligonucleotide (ASO) for SOD1 pathology, marked a significant turning point for SOD1-ALS patients. While clinical trials and early access program studies reported a significant reduction in plasma and cerebrospinal fluid (CSF) neurofilament levels, neuroinflammation following prolonged treatment was never assessed. In this multicenter study, we evaluated a cohort of 18 SOD1-ALS patients treated with tofersen, analyzing correlations between biomarkers of neurodegeneration/neuroinflammation and clinical variables indicative of disease progression. NfL, NfH, CHI3L1, and Serpina1 levels in serum and CSF were determined by semi-automated immunoassays (Ella™ technology). Generalized linear mixed models were employed to investigate longitudinal trends of these biomarkers. Our data highlighted a progressive decrease in CSF neurofilament levels during tofersen treatment (MR = 0.97, 95% CI 0.94–0.99, p = 0.006 and MR = 0.98, 95% CI 0.95–1.00, p = 0.076 for NfL and NfH in CSF, respectively). Conversely, CSF levels of SerpinA1 and CHI3L1 increased over time (MR = 1.12, 95% CI 1.08–1.16, p < 0.0001 and MR = 1.039, 95% CI 1.015–1.062, p = 0.001 for SerpinA1 and CHI3L1 in CSF, respectively), but these modifications were most apparent after six and twelve months of therapy, respectively. Disease progression rate did not correlate with these biomarker trends. We observed a significant decrease in neurofilament levels during Tofersen treatment, alongside an increase in neuroinflammatory markers, potentially linked to an immune response triggered by ASO treatment. Given the limited data on tofersen’s long-term efficacy in ALS due to its recent introduction, identifying biomarkers that predict clinical outcomes such as diminished therapeutic response or adverse effects is crucial. These biomarkers may help to better understand the underlying pathomechanisms of ALS and tofersen’s role in modulating disease progression.

Background Cognitive deficits related to frontotemporal dysfunction are common in Amyotrophic Lateral Sclerosis (ALS). Visuospatial deficits, related to posterior cerebral regions, are often underestimated in ALS, though they play a crucial role in attending daily living activities. Our pilot study aims at assessing visuospatial abilities using a domain-specific tool in ALS patients compared to healthy controls (HC). Methods Twenty-three patients with early ALS and 23 age- and education-matched HC underwent the Battery for Visuospatial Abilities (BVA), including 4 visuo-perceptual and 4 visuo-representational subtests. Results When compared to HC, ALS scored worse in 2 visuo-perceptual subtests (i.e., Line Length Judgment and Line Orientation Judgment) and 1 visuo-representational tasks (i.e., Hidden Figure Identification, HFI) ( p < 0.01). No correlations arose between ALS clinical features and BVA performance. More than 80% of the ALS cohort obtained abnormal scores in the HFI subtest. Conclusions Our findings revealed that patients with ALS scored worse (compared to HC) on selective tests tapping “perceptual” and “representational” visuospatial abilities, since the early stages of disease. In clinical practice, our findings highlight the need for multi-domain neuropsychological assessment, for monitoring disease courses and properly organizing care management of patients with ALS.

BackgroundAlthough withdrawal from analgesics with or without detoxification strategy represented a mainstay in medication overuse headache (MOH) management, recent evidence supports that it is no longer beneficial when CGRP-targeting monoclonal antibodies (CGRP-mAbs) are employed. However, MOH could be stratified into simple and complex MOH phenotypes according to different clinical parameters (i.e., amounts and class of analgesics, psychiatric comorbidities, history of relapse after withdrawal, symptoms of central sensitization, and maladaptive anticipatory response to pain experience). Herein, we explored the effectiveness of CGRP-mAbs plus detoxification strategy compared to CGRP- mAbs preventive treatment alone in patients with either simple or complex MOH phenotypes.MethodsThis is a six-month observational study including chronic migraine patients with MOH treated with subcutaneous CGRP-mAbs. Patients were stratified based on both MOH complexity and detoxification strategy to evaluate differences in the changes of monthly headache days, pain intensity and duration, and monthly days with acute medication intake after the first, third and sixth month of preventive treatment with CGRP-mAbs.ResultsTwo hundred patients with migraine and MOH were recruited. A significant reduction of headache attacks frequency, intensity, duration and monthly days with acute medication intake has been observed both in patients sub-classified as complex MOH (58.5%) and in those with simple MOH (41.5%) after the first, third and sixth month of preventive treatment with CGRP-mAbs (p < 0.001). Furthermore, stratifying patients based on the MOH complexity and detoxification strategy, no differences were found in the reduction of monthly headache days as well as in other parameters of disease severity (p > 0.05).ConclusionOur findings might suggest a change in the mind-set of clinicians, still considering the withdrawal with or without detoxification strategy as a "conditio sine qua non" in patients with MOH, towards a novel approach where the reduction of analgesics intake represents the natural consequence of CGRP-mAbs effectiveness.

Background: Long-term Type 2 diabetes mellitus (T2DM) affects multiple organs and systems throughout the body, including the cardiovascular, renal, and nervous systems. In the brain, T2DM impacts brain function, leading to cognitive impairment. Due to the faster progression of cognitive decline in diabetic patients, we aim to investigate the relationship between newly diagnosed T2DM and iron deposition by brain MRI technique. Methods: We used Quantitative Susceptibility Mapping (QSM), an advanced brain MRI technique, to non-invasively quantify iron deposition in the brain of elderly patients and healthy control subjects. In all patients, blood glucose and iron levels and their correlates parameters were evaluated. Results: QSM revealed increased iron deposition in the putamen of elderly diabetic patients although newly diagnosed compared to healthy controls. QSM significantly correlated with high blood glucose levels and insulin resistance, but not with blood iron levels. Conclusions: Results suggest that increased iron deposition in the putamen, as analyzed by QSM, is worsened by hyperglycemia and insulin resistance, already when diabetes is newly diagnosed. Addressing this issue could improve on the one clinical inertia towards diabetes hand newly diagnosed, with an improvement in diabetes management strategies itself, and on the other hand, it could focus attention on increased putamen iron deposition as a predictive indicator of neurocognitive impairment in T2DM.

Brain parcellation enables the extraction of region-specific measurements from multimodal MRI data and represents a crucial step in neuroimaging analyses. Different atlases, derived using segmentation or clustering approaches, may play a crucial role in shaping analytical outcomes. Neurovascu-lar coupling (NVC)-the local spatial relationship between blood perfusion and neuronal activity-can be estimated by correlating functional connectivity with cerebral blood flow measures within predefined brain parcels. Although NVC alterations have been investigated in several neurological conditions, the impact of parcellation schemes on the resulting NVC estimates-both regionally and within large-scale functional net-works-has yet to be systematically assessed. The present study addresses this gap by comparing NVC estimates across Yeo's seven canonical large-scale brain networks using two widely adopted network-labelled parcellation schemes: the Schaefer atlas, originally derived from functional MRI data only, and the Brainnetome atlas, constructed from multimodal structural and functional connectivity data. Despite the overall good consistency in NVC estimates across all networks (Interclass Correlation Coefficient ≥ 0.702), significant differences (p < 0.05) were observed between the Schaefer and Brainnetome atlases in all networks, especially in dorsal and ventral attention networks. These findings highlight that parcellation choice can substantially impact NVC estimation, even when using atlases with high overall consistency, underscoring the need to carefully consider atlas properties when investigating more subtle neurovascular alterations across brain networks.

Background: Monoclonal antibodies acting on the CGRP pathway (CGRP-mAbs) are characterized by subcutaneous administration via autoinjectors or prefilled syringes. Unfortunately, significant local tolerability concerns about injection site pain (ISP) may degrade patient comfort, increase the fear and stress of dose administration, and negatively impact patient adherence. The aim of the present cross-sectional study was to assess the experience of patients with migraine using either CGRP-mAbs prefilled syringes or autoinjectors regarding local tolerability and perceived ease-of-usability. Methods: A self-administered electronic questionnaire was created using “Google questionnaires” to collect from migraine inpatients treated with CGR-mAbs: i) demographic and clinical parameters; ii) data related to ongoing preventive CGRP-mAb treatments and their local tolerability (in particular, evaluated by numerical rating scale); iii) data on perceived ease-of-usability; and iv) data on putative previous onabotulinumtoxinA treatment. Results: The questionnaire was sent to 405 migraine patients. After 10 days, 283 (69.87%) patients had completed the electronic form. No significant differences were found among groups regarding data on ease-of-usability and local tolerability of CGRP-mAbs regarding simplicity and modality of administration (self-administered or not), ISP, or reactions at the site of administration. However, we did identify young females (OR=0.22; p<0.001) with chronic migraine (OR=4.87; p=0.007) to be the phenotype most prone to experience ISP during CGRP-mAbs treatment. Of 96 patients who had previously received at least 3 onabotulinumtoxinA administrations, injection site pain was significantly higher with onabotulinumtoxinA compared to CGRP-mAbs (6±4 vs. 4±5; p<0.001). Conclusions: Devices used for CGRP-mAbs administration (auto-injector and prefilled syringes) are characterized by several strengths and disadvantages, one compensating for the other so that no differences in perceived ease-of-usability and local tolerability can be observed. These findings may also result in economic and ecological implications, considering the lower impact on costs and environmental pollution of prefilled syringes compared to more expensive and polluting plastic autoinjectors.

INTRODUCTION:Although the landscape of migraine symptomatic treatment has been enriched by novel effective drugs, it is mandatory to critically reappraise older molecules to ascertain whether they could still represent reliable alternatives in specific endophenotypes of patients or migraine attacks. Among these, dihydroergotamine (DHE) nasal spray has been shown to be effective and is characterized by greater tolerability and manageability than the parenteral DHE formulation.AREAS COVERED:In this narrative review, the authors describe the pharmacodynamic and pharmacokinetic properties of DHE nasal spray and explore the results of the trials which explored its efficacy, safety and tolerability as migraine symptomatic treatment. They also discuss the limitations of the classically used device and the attempts that several companies are carrying out to generate devices warranting a more reproducible drug absorption.EXPERT OPINION:DHE nasal spray could be considered as rescue treatment in patients who have failed other symptomatic therapeutic strategies. Nevertheless, in the perspective of tailored therapy, the intranasal route of administration and the consequent rapid onset of action may represent benefits putatively making DHE a treatment of choice for challenging migraine attacks such as those with nocturnal onset or quickly reaching the climax of both headache and neurovegetative associated symptoms.