This study explores several speech parameters related to mild cognitive impairment, as well as those that might be flagging the presence of an underlying neurodegenerative process. Speech is an excellent biomarker because it is not invasive and, what is more, its analysis is rapid and economical. Our aim has been to ascertain whether the typical speech patterns of people with Alzheimer’s disease are also present during the disorder’s preclinical stages. To do so, we shall be using a task that involves reading out aloud. This is followed by an analysis of the recordings, looking for the possible parameters differentiating between those older people with MCI and a high probability of developing dementia and those with MCI that will not do so. We found that the disease’s most differentiating parameters prior to its onset involve changes in speech duration and an alteration in rhythm rate and intensity. These parameters seem to be related to the first difficulties in lexical access among older people with AD.

Background: During aging, changes in human speech may arise because of the neurophysiological deterioration associated with age, or as the result of an impairment in the cognitive processes underlying speech production. Some speech parameters show specific alterations under the presence of dementia. The objective of our study is to identify which of these parameters change because of age, cognitive state, or the interaction of both. Methods: The sample includes 400 people over 55 years old, who were divided into four groups, according to their age. The cognitive state of the participants was assessed through the MMSE test and three ranks were stablished. Gender was also considered in the analysis. Results: Certain temporal, fluency, rhythm, amplitude and voice quality parameters were found to be related to the cognitive state, while disturbance parameters changed due to age. Frequency parameters were exclusively influenced by gender. Conclusions: Understanding how speech parameters are specifically affected by age, cognitive state, or the interaction of both, is determinant to advance in the use of speech as a clinical marker for the detection of cognitive impairments.

This study explores young adults’ emotional affect and attitudes towards ageing, as well as older adults’ emotional affect and self-esteem following participation in the intergenerational videoconferencing programme Smile Connect (SC). The sample consisted of 94 participants (46 older Spanish adults living in a care home in Spain and 48 young Italian adults -secondary students- learning Spanish at school in Italy). Each age group was divided into an intervention and control group. SC consists of twelve 30-minute chat sessions conducted via Skype between the target groups over six weeks. Pre and post evaluations were made to assess the affect level in both groups, self-esteem among older people, and the level of negative stereotypes about ageing among young adults. At the end of the SC, the intervention group of older adults recorded significantly improved scores in self-esteem compared to the control group. Young adults recorded a reduction in their negative stereotypes about old age after taking part in the SC programme compared to those who did not. These findings suggest that involvement in the SC programme helps to improve the emotional affect of older adults living in care homes, as well as change the negative stereotypes about ageing among young adults.

Las primeras alteraciones lingüísticas propias de la Enfermedad de Alzheimer (EA) ocurren en el nivel léxico-semántico, fuertemente dependiente del estado de la memoria del hablante. Los cambios cualitativos en la memoria semántica, derivados de los procesos neurodegenerativos, dan lugar a la aparición de la anomia: la incapacidad de la persona afectada de acceder y recuperar tanto las unidades léxicas como sus bases conceptuales. En este trabajo, nos proponemos estudiar las características cognitivas y semánticas de la afectación anómica en EA e indagar en la posibilidad de su uso en pruebas para la detección temprana de la demencia. Para ello, analizamos los resultados de un modelo experimental de la clásica prueba de fluidez verbal semántica (FVSem), que introduce la división de la misma en cuatro intervalos de 15 segundos con el fin de determinar qué procesos de acceso semántico -los automáticos o los controlados- están alterados en diferentes estados cognitivos de la vejez (hablantes sin patología, hablantes con deterioro cognitivo leve y hablantes con EA). Los resultados de nuestro experimento apuntan a que existe una clara correlación entre el estado cognitivo del hablante y su habilidad léxico-semántica. Asimismo, evidencian, por un lado, que es importante aplicar la prueba de FVSem con duración no inferior a 60 segundos y con distribución en 4 intervalos de 15 segundos, y, por otro lado, que determinadas categorías semánticas -colores y frutas- son más susceptibles a la retrogénesis cognitiva propia de EA.

Alzheimer’s disease (AD) is the most common cause of dementia. With the increasing average age of humans worldwide, the total number of people with dementia is projected to reach 82 million by 2030 and 152 million by 2050. No effective pharmaceutical agents exist to halt or slow down the disease progression. Hence, there is a tremendous imperative to gain a better understanding of the pathogenesis of AD and to develop effective treatments. This book brings together an international team of experts to provide a comprehensive and up-to-date overview of AD. The most current information on several critical aspects of AD are presented, providing the readers with a broad picture of the underlying neuropathology, genetics, proteomics, risk factors, novel biomarkers, and potential interventions. Chapters 1–5 discuss the underlying AD pathogenesis using genomic and proteomic approaches, linking diverse pathways that can lead to complex metabolic dysfunction. Chapter 6 reviews the potential role of trace metals in AD, while Chapter 7 examines the diversity of Aβ species involved in AD pathology. Chapter 8 discusses the contributions of white matter degeneration in AD. Chapter 9 examines the potential intriguing role of the brain-gut-microbiota axis in mediating AD. Chapters 10 and 11 discuss potential biomarkers for AD, such as deficits in ocular exploration and early language impairments, respectively. Chapters 12–15 examine possible novel preventative and/or therapeutic methodologies such as exercise, optimizing depression therapy, and diverse psychosocial interventions. The book will be of value to clinicians and health professionals caring for patients with AD and will provide a comprehensive and thought-provoking introduction to young investigators interested in translational aspects of the AD and related dementias.

Se sintetizan los avances de 2020-2025 en predicción del riesgo de incendios forestales mediante teledetección y modelos de inteligencia artificial. Se resume el uso de índices espectrales (NDVI, EVI, NDMI), variables térmicas, topográficas y antrópicas, y se comparan líneas base (regresión, Random Forest, SVM) con arquitecturas profundas (CNN, ConvLSTM, Transformers). Se destacan resultados recientes con AUC entre 0.85 y 0.96 y F1 entre 0.67 y 0.85, así como la incorporación de autosupervisión y adaptación eficiente de parámetros para transferir modelos entre regiones. Se proponen buenas prácticas de evaluación (F1/AUC, RMSE/MAE y Kappa) y recomendaciones para despliegue operativo con datos multifuente y restricciones de costo computacional.