Maria Trinidad Herrero

Circadian rhythm disturbance is highly prevalent in patients with Alzheimer's disease (AD) and is consistently associated with more rapid cognitive decline and reduced quality of life. Accumulating evidence supports a bidirectional relationship between circadian rhythm disruption and AD pathology, in which each may reciprocally exacerbate the other. However, whether circadian rhythm disturbance acts as an independent causal driver of AD initiation or primarily as a factor that modifies and accelerates pathology once it is underway remains an open question. This article synthesizes current evidence on the proposed mechanisms linking circadian dysregulation to AD pathophysiology, with particular attention to the suprachiasmatic nucleus (SCN), glymphatic clearance, clock gene networks, and apolipoprotein E ε4 allele (APOE ε4) genotype. Emerging circadian‐targeted interventions, including both pharmacological and nonpharmacological approaches, are also reviewed and their current limitations are discussed. A more complete understanding of this bidirectional axis may help inform future research directions and ultimately contribute to the development of early monitoring and combination treatment strategies for AD.

Anxiety and emotional stress are pervasive psychological challenges that profoundly impact human health in today’s fast-paced society. Traditional assessment methods, such as self-reports and clinical interviews, often suffer from subjective biases and lack the capability for objective, real-time evaluation of mental states. However, the integration of physiological signals—including electroencephalography (EEG), heart rate (HR), electrodermal activity (EDA), and eye movements—with advanced machine learning (ML) techniques, offers a promising approach to automate and objectify mental health assessments. A systematic review was conducted to explore recent advances in the early detection of anxiety and stress by combining physiological signals and ML methods. To assess methodological quality, a specific analysis framework was designed for the 113 studies included, which identified significant deficiencies in the literature. This highlights the urgent need to adopt standardized reporting guidelines in this field. The role of these technologies in feature extraction, classification, and predictive modeling was analyzed, also addressing critical challenges related to data quality, model interpretability, and the influence of intersectional factors like gender and age. Ethical and privacy considerations in the current research were also included. Finally, potential avenues for future research were summarized, highlighting the potential of ML technologies for early detection and proactive intervention in mental disorders.

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Introduction: This study investigated the impact of chronic tinnitus on auditory perception, text comprehension, and physiological stress responses, with a focus on sex-related differences. The main objectives were to assess the influence of sex and stress on tinnitus severity, examine neurophysiological indicators of listening effort, and evaluate the effects of background noise on perceived difficulty and listening pleasantness.Materials and methods: Forty-seven participants (24 with tinnitus, 23 controls) performed a listening task involving audiobook excerpts presented at different signal-to-noise ratios. Subjective ratings, comprehension scores, and physiological data were collected, including salivary alpha-amylase, electrodermal activity, heart rate, and EEG-based measures of listening pleasantness.Results: Control participants outperformed tinnitus participants during the initial quiet condition (p = 0.020), with male controls scoring significantly higher than males with tinnitus (p = 0.008). Tinnitus participants rated listening as less pleasant in both quiet (p = 0.036) and high-noise conditions (p = 0.012). Female participants reported greater difficulty under moderate noise (p = 0.030), while EEG data showed higher enjoyment in males (p = 0.005). Salivary amylase increased post-task (p = 0.016), electrodermal activity differed between the initial and final quiet phases (p < 0.001), and heart rate varied according to noise levels (p = 0.008). Negative correlation emerged between subjective and EEG-based pleasantness in the quiet condition.Discussion: These findings suggest that tinnitus imposes a measurable cognitive and emotional burden, influenced by both sex and stress responses. They emphasize the need for multimodal, personalized, and gender-sensitive approaches in the assessment and management of tinnitus.

This study investigates the effects of an acute 1-metil 4-fenil 1,2,3,6-tetraidro-piridina (MPTP) treatment, a known inducer of parkinsonism, on oxidative stress and epigenetic changes in the mouse ventral midbrain (VM) and striatum. Key markers were analyzed at 4, 8, 24, and 48 h post-injections: the hydroxylated form of the purine guanine (8-hydroxy-2'-deoxyguanosine; 8-OHdG), a marker of oxidative stress; the methylated form of cytosine (5-methylcytosine; 5-mC), associated with gene silencing; the hydroxy methylated form of cytosine (5-hydroxymethylcytosine; 5-hmC), involved in demethylation and gene regulation. The results showed a pronounced decrease in 8-OHdG levels in the VM, suggesting a rapid oxidative stress response, whereas the striatum exhibited a less pronounced response, reflecting regional differences in oxidative stress vulnerability DNA methylation patterns revealed complex and biphasic changes in 5-mC levels in the VM, contrasted with a less pronounced response in the striatum, suggesting disrupted methylation homeostasis and regional epigenetic variability. MPTP treatment also significantly reduced in 5-hmC levels in the VM, pointing to impaired active DNA demethylation and compromised epigenetic flexibility. In contrast, the striatum maintained consistently high 5-hmC levels, reflecting compensatory hydroxymethylation mechanisms specific to this region. These findings highlight pronounced regional differences in oxidative stress vulnerability and epigenetic regulation, with the VM showing heightened sensitivity to oxidative damage and impaired epigenetic flexibility. This underscores the importance of understanding the role of oxidative and epigenetic mechanisms in Parkinson’s disease pathophysiology, The changes pave the way for novel therapeutic strategies targeting oxidative DNA damage and epigenetic homeostasis.

The presence of α-synuclein (α-syn) aggregates, such as Lewy bodies in patients with Parkinson’s disease (PD), contributes to dopaminergic cell death. Injection of PD patient–derived α-syn in nonhuman primates has illustrated the exquisite vulnerability of primate dopaminergic neurons. Here, we aimed to elucidate the temporal and spatial pathological changes induced by two distinct α-syn pathogenic structures, having large or small sizes. To unravel the underlying molecular pathways, we conducted a proteomic analysis of the putamen and the entorhinal cortex, two brain regions carrying notable α-syn pathology. We demonstrate that distinct assemblies of α-syn aggregates drive unique pathogenic changes that ultimately result in a comparable extent of nigrostriatal degeneration at the level of nigral dopaminergic neuron cell bodies and striatal dopaminergic terminals. More broadly, our findings identify pathogenic trajectories associated with large or small α-syn aggregates, suggesting the existence of several possible concomitant pathogenic routes in PD.

Discurso de ingreso pronunciado por la Ilma. Dra. D.ª María Trinidad Herrero Ezquerro con motivo de su incorporación como Académica de Número de la Academia Hispanoamericana de Doctores, en La Rioja, España, el 2 de mayo de 2025.

Swallowing disorders, which are generally underdiagnosed, affect the elderly, leading to a decreased quality of life and complications, including aspiration pneumonia and death. Understanding the neurophysiology of swallowing and the causes of its dysfunction is a fundamental tool for the prevention, early diagnosis, and treatment of dysphagia. New technologies open a wide range of possibilities for the implementation of new care protocols for this disorder.

The human brain demonstrates an exceptional adaptability, which encompasses the ability to regulate emotions, exhibit cognitive flexibility, and generate behavioral responses, all supported by neuroplasticity. Brain–computer interfaces (BCIs) employ adaptive algorithms and machine learning techniques to adapt to variations in the user’s brain activity, allowing for customized interactions with external devices. Older adults may experience cognitive decline, which could affect the ability to learn and adapt to new technologies such as BCIs, but both (human brain and BCI) demonstrate adaptability in their responses. The human brain is skilled at quickly switching between tasks and regulating emotions, while BCIs can modify signal-processing algorithms to accommodate changes in brain activity. Furthermore, the human brain and BCI participate in knowledge acquisition; the first one strengthens cognitive abilities through exposure to new experiences, and the second one improves performance through ongoing adjustment and improvement. Current research seeks to incorporate emotional states into BCI systems to improve the user experience, despite the exceptional emotional regulation abilities of the human brain. The implementation of BCIs for older adults could be more effective, inclusive, and beneficial in improving their quality of life. This review aims to improve the understanding of brain–machine interfaces and their implications for mental health in older adults.