Combining pharmacological interventions with neuroimaging in Alzheimer's disease (AD) research presents logistical and methodological challengesparticularly during early study phases, such as recruitment and study visits. Yet, these challenges are rarely reported in detail. This perspective article shares early-phase experiences from a 7-tesla (7T) fMRI clinical study involving individuals with mild cognitive impairment due to AD (MCI-AD) and mild Alzheimer's disease dementia (mild ADD), highlighting recruitment hurdles and offering practical recommendations. From a pool of 1,001 patients, 476 had a clinical diagnosis of MCI-AD or mild ADD; after pre-selection and screening, only 48 participants (10%) met all inclusion criteria. Major exclusion factors included metal or tattoos (8%), missing surgical documentation (2%), beta-blocker use (27.5%), recent cancer/chemotherapy or brain radiation (1%), and lack of interest (20%). Effective communication, often requiring caregiver assistance, was essential for obtaining accurate medical histories and improving adherence. Internally, clear team coordination supported scheduling and protocol compliance. While strict eligibility criteria improve data quality, they can substantially limit recruitment and feasibility in pharmacological and high-field MRI drug studies. We propose strategies to optimize recruitment and screening, facilitate data collection, and balance scientific rigor with real-world clinical feasibility.

Tinnitus, a prevalent auditory perception symptom, is closely associated with maladaptive neuroplasticity within the central auditory and non-auditory pathways. Its complex pathophysiology shares significant mechanistic parallels with neurodegenerative processes, including neuroinflammation, synaptic dysfunction, excitotoxicity, and aberrant neural network reorganization. This review explores the therapeutic potential of repurposing strategies originally developed for neurodegenerative diseases for tinnitus intervention. We systematically examine key approaches, such as targeting neuroinflammatory cascades, modulating neurotrophic factors, and mitigating glutamate-mediated excitotoxicity. The discussion synthesizes evidence from preclinical studies suggesting their mechanisms of action within tinnitus models and evaluates the current landscape of translational and clinical research. By bridging insights from neurodegeneration and auditory neuroscience, this article aims to provide a cohesive theoretical framework and identify future directions for developing novel, mechanism-based therapeutic interventions for tinnitus.

Temporal prediction is the ability to anticipate the likely time of occurrence of events and is important for adaptive behaviour in our everyday lives. Studies indicated that predictive aspects of environmental stimuli can be leveraged to reduce reaction times and enhance stimulus processing. Particularly, a recent study showed that this optimized behaviour is associated with a phase adjustment of ongoing neural oscillations aligning with the expected onset of upcoming stimuli. In ageing, there is some evidence that temporal predictions might be altered, however findings are inconsistent. Thus, we aimed to explore whether and how anticipatory oscillatory markers of temporal prediction change with age. To this end, 20 right-handed younger adults (14 females, age = 25.4 ± 4.13 years) and 20 right-handed older adults (13 females, age = 60.35 ± 3.92 years) performed a temporal prediction task while 64-channel EEG was recorded. In the task, a visual stimulus moved across the screen toward an occluder, disappeared and reappeared after a variable time delay. Participants judged whether the visual stimulus reappeared “too early” or “too late.” Results indicated comparable temporal prediction performance between younger and older adults. We observed a stronger task-related decrease of beta activity in older compared to younger adults. Further, we observed phase adjustments of ongoing delta activity aligning with the disappearance of moving stimuli which was stronger in older compared to younger adults. Together, these observations provide several new insights into the neural dynamics supporting temporal prediction and suggest that neural dynamics associated with temporal prediction appear sensitive to ageing.

IntroductionNeurodegenerative diseases (NDDs) including Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and non-AD dementias share chronic neuroinflammatory mechanisms that contribute to neuronal injury and disease progression. While anti-inflammatory therapies (AITs) are associated with reduced neurodegenerative disease risk, knowledge regarding the impact of biological sex and treatment duration across multiple NDDs remains limited.MethodsWe conducted a retrospective cohort analysis using a large propensity-score-matched population (n = 190,308; 95,154 treated vs. 95,154 untreated) to evaluate associations between long-term AIT exposure and incidence of major NDDs. Disease-specific and combined outcomes were assessed across drug classes (NSAIDs, corticosteroids, immunomodulators), sex, age, and therapy duration.ResultsAIT exposure was associated with a significantly lower risk of developing any NDD (RR = 0.47, 95% CI 0.43–0.48, p < 0.0001) and was equally effective in both sexes. Risk reduction was observed for each age-associated disease: AD (RR = 0.40), non-AD dementia (RR = 0.51), PD (RR = 0.43), MS (RR = 0.25), and ALS (RR = 0.48). Among drug classes, immunomodulators conferred the greatest reduction (RR = 0.19), followed by corticosteroids (RR = 0.41) and NSAIDs (RR = 0.42). Duration analyses revealed a graded benefit, with RR declining from 0.94 ( < 1 year) to 0.25 ( > 6 years). Risk reduction was greatest in older participants (75–79 years).DiscussionChronic use of anti-inflammatory or immunomodulatory therapies was associated with significantly reduced incidence of multiple neurodegenerative diseases in both sexes. The strongest effects were observed with immunomodulator use and prolonged therapy duration, suggesting that sustained modulation of systemic inflammation confers broad neuroprotective effects in both sexes. These findings highlight the potential of targeting immune-inflammatory pathways for neurodegenerative disease prevention and can inform prospective mechanistic and interventional studies.

BackgroundHigh blood pressure (BP) is a known risk factor for dementia, but the relationships between BP and gross brain volumes are mixed and are understudied in groups who are at particularly high risk for dementia, such as Hispanic/Latino adults. Therefore, we aimed to investigate the relationships between BP and brain volumes, among Hispanic/Latino older adults.MethodsParticipants included 122 cognitively healthy Hispanic/Latino late middle-aged and older adults ages (mean age = 73.48 years, SD = 7.32) from the National Alzheimer’s Coordinating Center. Data were collected from 2005 to 2024 from 20 Alzheimer’s Disease Research Centers. BP measures included systolic (SBP), diastolic (DBP), and pulse pressure (PP). Brain outcomes included total, hippocampal, gray matter, and white matter hyperintensity volumes. Covariates included age, sex, Hispanic/Latino heritage, hypertension, diabetes, hypercholesterolemia, body mass index, hypotensive status, and smoking status.ResultsNo BP measure was significantly associated with brain outcomes (all p > 0.05).DiscussionOverall, we found no relationships between BP measures and brain volumes in this sample of late middle-aged and older Hispanic/Latino adults. Our findings warrant longitudinal studies to better characterize the relationships between BP and other cardiovascular disease risk factors with brain health in this population.

Background and purposeThe aging brain is particularly sensitive to alterations in selenium status. Selenium deficiency has been associated with impaired neural function, cognitive decline, and increased vulnerability to neurodegeneration. However, the molecular mechanisms that link selenium biology to brain aging remain poorly understood.MethodsWe conducted a bibliometric analysis of 1,826 publications and identified brain-aging DEGs from public datasets. After intersecting these with selenium-related gene sets, we used machine-learning feature selection and SHAP/nomogram evaluation to prioritize core genes, validated findings in an independent cohort, performed immune-infiltration and gene-drug enrichment analyses, and confirmed age-related transcriptional and protein changes in mouse brain tissue.ResultsBibliometric analysis showed a steady increase in publications on selenium and aging over the past two decades, with major research hotspots focusing on oxidative stress, selenoproteins, and cognitive function, while the selenium-cognition relationship remains relatively underexplored. Intersection analysis identified seven potential targets linking selenium to brain aging, from which machine-learning feature selection prioritized three core genes (SP1, SEPHS2, and MSRB1) that were significantly differentially expressed in aged samples. SHAP and nomogram analyses indicated that SP1 and SEPHS2 were the main contributors to model discrimination. Animal experiments further confirmed increased SP1 and decreased SEPHS2 expression at both mRNA and protein levels in aged mouse brains, consistent with the bioinformatic findings.ConclusionThis study identifies SP1 and SEPHS2 as key genes linking selenium to brain aging, providing new insights into the role of selenium in brain aging and suggesting that these genes may represent potential biomarkers or therapeutic targets for brain aging and aging-related brain disorders.

BackgroundParkinson’s disease (PD) is a neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons, leading to a spectrum of motor and non-motor symptoms. In addition to the motor deficits serving as the primary criteria for diagnosis, mood and anxiety disorders also play a significant role in shaping the prognosis and overall disease progression in PD.ObjectivesIn this study, our aim was to characterize the progression of anxiety-like behavioral deficits in a rat model of neurotoxicity induced by 6-hydroxydopamine (6-OHDA) and to investigate insulin-like growth factor 1 (IGF-1) potential therapeutic effects on these pathological markers.MethodsBehavioral changes were evaluated in male Wistar rats at 1, 2, and 3 weeks post-lesion using the elevated plus maze and dark–light box tests. Anxiety-like behaviors emerged as early as week 1 post-lesion and persisted through week 3. Following 6-OHDA infusion, immunohistochemical analysis revealed a decrease in tyrosine hydroxylase (TH) immunoreactivity within the ventral tegmental area (VTA) indicating a partial lesion of the nigrostriatal dopaminergic system. As a therapeutic approach we performed the intracisternal administration of a recombinant adenoviral vector encoding IGF-1 (RAd IGF-1) one week after 6-OHDA-induced neurotoxicity.ResultsAt a behavioral level, IGF-1 treatment effectively prevented anxiety-like behavior by the third week of neurotoxicity. Nevertheless, IGF-1 overexpression was not able to modulate VTA dopaminergic neuron loss. These results reveal a dissociation between the behavioral effects of IGF-1 and its impact on dopaminergic neurodegeneration.DiscussionThese findings emphasize time-dependent alterations in anxiety-like behavior and dopaminergic neurodegeneration. In addition, these data support the potential use of IGF-1 as a therapeutic molecule and its novel administrations for future gene transfer interventions, which will shed light on the progressive nature of neurodegenerative mechanisms.

IntroductionAssessing attention and frontal lobe function is essential for diagnosing dementia. The Stroop test is widely used for these purposes, and its validity and reliability have been verified. Nevertheless, test-related burdens and procedural complexity have prevented their use as a screening tool. We developed a novel Stroop test using eye-tracking technology and evaluated its validity and utility in a clinical setting.MethodsThe study included 97 older adults at a memory clinic. Participants completed both the eye-tracking-based and conventional paper-based Stroop tests, along with MMSE, FAB, and TMT-A/B.ResultsScores on the eye-tracking-based Stroop test significantly correlated with the paper-based test (r = 0.634), FAB (r = 0.480), and TMT-B (r = −0.536). It achieved an AUC–ROC of 0.701 for frontal lobe dysfunction and 0.708 for dementia.DiscussionThe eye-tracking-based Stroop test has the potential to efficiently assess frontal lobe function and serve as a screening tool for dementia.

IntroductionEarly detection of Alzheimer’s disease (AD) is critical for timely intervention, particularly during the mild cognitive impairment (MCI) stage. This study aimed to develop and evaluate a multidomain speech analysis framework to support cognitive screening, biomarker prediction within the amyloid, tau and neurodegeneration (ATN) framework, and estimation of cognitive function across the AD continuum.MethodsThis study analyzed speech from 2,320 individuals spanning the cognitive spectrum-including those with subjective cognitive decline (SCD), MCI, and Alzheimer’s disease dementia (ADD)-using three spoken tasks (∼3 min) and extracted multidomain features including acoustic, lexical, syntactic, and semantic features. Machine learning models were trained to classify cognitive status, predict amyloid, tau and neurodegeneration (ATN) biomarker positivity, and estimate scores across six neuropsychological domains.ResultsMultidomain speech models achieved high performance in differentiating cognitive stages, with AUC values of up to 0.94 for SCD vs. ADD and 0.82 for SCD vs. MCI classifications. In biomarker prediction, the models yielded AUCs of 0.71, 0.74, and 0.73 for ATN classification, respectively. Speech-based models also showed strong correlations (up to 0.83) with cognitive function scores. Feature importance analysis revealed that verbal fluency measures were the most predictive. Explainability analyses indicated minimal dependency on age, sex, or education, supporting model fairness.DiscussionThese findings show that multidomain speech features capture clinically and biologically relevant information across the AD continuum, enabling cognitive classification, biomarker prediction, and cognitive estimation. These results underscore the potential of speech analysis as a non-invasive, accessible tool for scalable cognitive screening and early detection of AD. These results underscore the potential of speech analysis as a non-invasive, accessible tool for scalable cognitive screening and early detection of AD.

ObjectiveThis study aims to explore the associations of C-reactive protein-albumin-lymphocyte (CALLY) index with hemorrhagic transformation (HT), malignant cerebral edema (MCE), and 90-day unfavorable outcome and all-cause mortality in patients with acute ischemic stroke (AIS) following mechanical thrombectomy (MT).MethodsA retrospective study was conducted. The CALLY index was calculated as albumin × lymphocyte count/(CRP × 10). Unfavorable outcome was defined as the modified Rankin Scale score >2 at 90-day follow-up. Multivariable logistic analyses were performed to evaluate the associations between the CALLY index and clinical outcomes. The restricted cubic spines (RCS) curves were employed for pinpointing any nonlinear associations. In addition, mediation analysis was conducted to assess the potential mediating roles of HT and MCE linking the relationship between the CALLY index and 90-day outcomes.ResultsA total of 477 patients were enrolled, demonstrating the rates of HT, MCE, unfavorable outcome, and all-cause mortality were 29.8% (142), 22.9 (109), 54.5 (260), and 25.6 (122), respectively. Multivariable logistic analysis revealed that the CALLY index was associated with reduced risk of HT (odds ratio [OR] 0.843, 95% confidence interval [CI] 0.769–0.924, p < 0.001), MCE (OR 0.894, 95% CI 0.824–0.971, p = 0.008), unfavorable outcome (OR 0.895, 95% CI 0.840–0.954, p = 0.001), and mortality (OR 0.907, 95% CI 0.836–0.984, p = 0.019). RCS curves exhibited non-linear relationship between the CALLY index and HT (p-non-linear = 0.008), manifesting that CALLY index was associated with HT when its value below 2.681 (OR 0.530, 95% CI 0.357–0.785, p = 0.002). Mediation analysis indicated that the association between the CALLY index and unfavorable outcome may be partially mediated by HT (29.1%, p < 0.001) and MCE (28.1%, p = 0.003).ConclusionThe CALLY index is associated with reduced risk of HT, MCE, and 90-day unfavorable outcome and all-cause mortality. HT and MCE may be the mediators linking the CALLY index to 90-day unfavorable outcome.