Cardiopulmonary and skeletal muscle strategies underlying exhaustive exercise in adults with glycogen storage disease type III F. Lanfranconi, L. Peli, L. Pollastri, A. Ferri, L. Tremolizzo, et al. Physiological Reports, 2026 People with glycogen storage disease type III (GSDIII‐p) have a remarkably reduced exercise tolerance. Aim of this study was to analyze the oxygen transport‐utilization chain strategies adopted by GSDIII‐p during exercise. Nine GSDIII‐p (39.4 ± 10.0 year, 33% female) and 11 healthy controls (CTRL), age and gender matched, underwent an incremental cardiopulmonary exhaustion test (CPET) to assess peak heart rate (HR), blood lactate [La]p and vastus lateralis O 2 fractional extraction (ΔHHb/isch) using near‐infrared spectroscopy. Patterns of breathing (PBr) were assessed accordingly by analyzing pulmonary O 2 uptake (V̇O 2 ), tidal volume (Vt), respiratory frequency (Rf), end‐tidal CO 2 (PETCO 2 ) and alveolar ventilation (V̇A). GSDIII‐p exhibited significantly ( p < 0.05) lower peak values of V̇O 2 , pulmonary ventilation (V̇E) [La] and ΔHHb/isch compared to CTRL (1.7 ± 0.7 vs. 3.2 ± 1.1 L/min, 50.5 ± 19.8 vs. 113.6 ± 40.4 L/min, 1.8 ± 0.7 vs. 7.6 ± 3.0 mmol/L and 39.1% ± 9.9% vs. 74.8% ± 36.6%, respectively). The range of peak V̇O 2 values for GSDIII‐p, compared to the predicted values for age and sex, was between 79% and 35%. Both GSDIII‐p and CTRL were arbitrarily divided into 4 groups according to individual V̇E values. GSDIII‐p with exercise intolerance relied on increased Rf with inadequate Vt adaptation to maintain V̇E and reduce PETCO 2 , with low V̇A values and low to moderate workloads tolerance. Reduced exercise tolerance in GSDIII‐p is related to respiratory and skeletal muscle inefficiencies. GSDIII‐p strong heterogeneity evaluated throught CPET provides insights into clinical management.
Cognitive and social intervention with Go and chess in early and subjective cognitive decline: The COGniChESs study results, with an updated meta-analysis Federico Emanuele Pozzi, Alessandro Spanio, Francesco Gallo, Giovanni Isgrò, Giulia Remoli, et al. Journal of Alzheimer S Disease, 2026 Background There is a growing interest in dementia prevention and scalable cognitive enhancement strategies for individuals at-risk, with or without Alzheimer's disease. Board games have shown potential cognitive and mood benefits, but randomized controlled evidence remains limited and heterogeneous. Objective We aimed at assessing whether chess and/or Go could improve cognition, mood, and quality of life in individuals with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Methods Individuals with MCI or SCD aged ≥55 years were randomized to one of three arms: chess, Go (each consisting of 12 weekly group sessions), or a waitlist control group. Montreal Cognitive Assessment, digit span, trail making test, categorical fluency, Geriatric Depression Scale, and the World Health Organization Quality of Life scale were administered at baseline and follow-up. We also updated our previously published meta-analysis including these new results. Results 69 subjects completed the study. Categorical fluency improved significantly in the games groups (p < 0.05). No between-group differences were found in overall cognition. A significant group × diagnosis × time interaction showed improved quality of life in MCI participants in the games groups (p = 0.002). A group × gender × time interaction revealed reduced depression in females in the games groups (p = 0.013). The updated meta-analysis confirmed a significant effect on depression (standardized mean differences −0.48, p = 0.013), but not on cognition. Conclusions The improvements in mood and quality of life, particularly among females and MCI subjects, underscore the psychological value of board games interventions, possibly through their social component. These activities may foster emotional well-being in older adults at risk for Alzheimer's disease, even without cognitive benefits. Clinicaltrials.gov Identifier: NCT06281652
Multicomponent interventions and technologies to reduce the burden of frailty, functional, and cognitive decline: insights from the Age-It Research Program Chukwuma Okoye, Luca Cuffaro, Federico Emanuele Pozzi, Maria Cristina Ferrara, Marianna Noale, et al. Journals of Gerontology Series B Psychological Sciences and Social Sciences, 2025 Objectives Preventing age-related complications is a critical priority for health systems. Within the Age-It program, Spoke 8 aims to evaluate scalable, multicomponent, technology-assisted interventions to prevent frailty and mitigate functional and cognitive decline in older adults across different care settings. Methods Spoke 8 includes three clinical studies conducted in community, hospital, and long-term care settings, supported by cross-cutting work packages on digital infrastructure, technology development, and economic evaluation. The intervention model integrates physical, cognitive, nutritional, and psychosocial components, supported by digital tools, biomarkers of aging, and a centralized data platform. Results The project is expected to generate evidence on the effectiveness, feasibility, and cost-effectiveness of multidomain interventions implemented across diverse real-world settings, including community, hospital, and long-term care. Technology-assisted strategies—such as wearable sensors and digital cognitive tools—may enhance adherence and enable remote monitoring, while also supporting more personalized care delivery. The integration of artificial intelligence will facilitate the interpretation of complex clinical and biological data, improving risk stratification and the early identification of individuals most likely to benefit from targeted interventions. Together, these approaches may help reduce hospitalizations, delay functional decline, and promote aging in place. Discussion This initiative supports the transition toward more integrated and equitable care models for older adults. Through the implementation of scalable, person-centered interventions within routine services, the project offers policy-relevant strategies to address frailty and functional decline—contributing to the redesign of aging care in Italy and providing insights applicable across diverse health systems facing the challenges of population aging countries.
Machine learning in Alzheimer’s disease genetics Matthew Bracher-Smith, Federico Melograna, Brittany Ulm, Céline Bellenguez, Benjamin Grenier-Boley, et al. Nature Communications, 2025 Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer’s disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics.
Distinctive Progression Patterns of Brain Structural Damage Aid Classification of Frontotemporal Dementia Variants Edoardo Gioele Spinelli, Francesca Orlandi, Silvia Basaia, Francesco Costa, Stefano Pisano, et al. European Journal of Neurology, 2025 BackgroundFrontotemporal dementia (FTD) encompasses diverse clinical phenotypes, primarily characterized by behavioral and/or language dysfunction. A newly characterized variant, semantic behavioral variant FTD (sbvFTD), exhibits predominant right temporal atrophy with features bridging behavioral variant FTD (bvFTD) and semantic variant primary progressive aphasia (svPPA). This study investigates the longitudinal structural MRI correlates of these FTD variants, focusing on cortical and subcortical structural damage to aid differential diagnosis and prognosis.MethodsSeventy‐one FTD patients (bvFTD = 45, sbvFTD = 11, svPPA = 15) and 37 healthy controls participated in a prospective study involving up to 24 months of serial neurological, neuropsychological, and 3 T MRI assessments. Cortical thickness and subcortical/cerebellar volumes were analyzed with linear mixed‐effect models. Support vector machine (SVM) models were used to classify subjects using baseline and longitudinal patterns of structural damage.ResultsAt baseline, sbvFTD showed right‐predominant temporal pole involvement associated with significant right frontal atrophy. Longitudinally, bvFTD showed widespread bilateral cortical and basal ganglia damage, svPPA demonstrated steady temporal lobe progression, and sbvFTD progressed primarily in left temporal and frontal regions with limited right hemisphere involvement. Baseline cortical thickness of frontal regions predicted subsequent functional decline in bvFTD and sbvFTD. A multiclass SVM model provided a good diagnostic classification accuracy, with similar results when using baseline data only (82%) and adding longitudinal data (83%).ConclusionsThis study delineates the unique structural MRI features and progression of FTD variants, highlighting sbvFTD as a distinct entity with early extra‐temporal involvement. These findings support the development of diagnostic and prognostic tools leveraging neuroimaging biomarkers.
Brain functional connectivity changes in amyotrophic lateral sclerosis with apathy and depression Veronica Castelnovo, Elisa Canu, Silvia Basaia, Edoardo Gioele Spinelli, Fabiola Freri, et al. Journal of Neurology, 2025 Background Apathy and depression are the most prevalent neuropsychiatric symptoms in amyotrophic lateral sclerosis (ALS). Although insufficiently investigated, their distinction holds important clinical relevance for accurate diagnosis of ALS with behavioural impairment and for patients’ prognosis and management. In the present study, we aimed to assess both apathy and depressive symptoms in patients with ALS and whether they have similar or different functional neural correlates. Methods Using graph analysis and connectomics, global and lobar nodal properties and regional functional brain connectivity were assessed in ALS patients without apathy/depression (ALSn, n = 42), with apathy without depression (ALSa, n = 14), with depressive symptoms without apathy (ALSd, n = 20), and with apathy and depressive symptoms (ALSad, n = 6), and 46 healthy controls. Correlations between brain functional properties, apathy and depressive symptoms were performed in all patients. Results Depressive symptoms were related with reduced path length within bilateral basal ganglia (BG) network, and apathy was related with increased path length, decreased nodal strength and local efficiency within left BG network. ALSa patients showed altered functional nodal properties within BG network compared to ALSn and ALSd. Compared to healthy controls and all non-apathetic patients (ALSn and ALSd), all apathetic patients (ALSa and ALSad) exhibited altered functional nodal properties within parietal, occipital and frontal networks. Non-apathetic patients, compared to apathetic patients, showed relatively preserved functional nodal properties in the BG network. Conclusions Our findings indicate differences in brain functional neural organization associated with apathy and depression, underscoring the importance of distinguishing these symptoms in ALS and highlighting the need for targeted interventions.
The neurologist in dante's inferno Michele Augusto Riva, Iacopo Bellani, Lucio Tremolizzo, Lorenzo Lorusso, Carlo Ferrarese, et al. European Neurology, 2015
Positive signs of functional weakness Lucio Tremolizzo, Emanuela Susani, Michele Augusto Riva, Giancarlo Cesana, Carlo Ferrarese, et al. Journal of the Neurological Sciences, 2014
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Back to the ring: Knocking-out headache Marco Tironi, Lucio Tremolizzo, Giovanni Stefanoni, Monica Airoldi, Eleonora Motta, et al. Neurological Sciences, 2012
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