Biology subjects

Slachevsky, A.

Publications and source records attributed to Slachevsky, A..

3 recordsLinked to original sources

bioRxiv2026

Retinal Electrophysiological Patterns in Alzheimer's Disease: A Multi-Domain Signal Processing Framework for Non-Invasive Biomarker Discovery Using a Portable ERG Device

Alzheimers disease (AD) is a neurodegenerative disorder affecting more than 55 million people worldwide, with a diagnosis that remains predominantly clinical and frequently delayed. The electroretinogram (ERG) offers a non-invasive electrophysiological method for detecting retinal dysfunction associated with neurodegeneration; however, it remains unclear whether robust and reliable candidate biomarkers can be extracted from ERG signals beyond conventional amplitude- and latency-based parameters. Here we present a pilot study of a multi-domain signal processing framework applied to ERGs recorded from 46 participants (20 AD patients, 26 controls) with a handheld device (RETeval, LKC Technologies) using sinusoidal (1-50 Hz) and photopic ISCEV protocols. Five complementary techniques were implemented: (i) multiscale fuzzy entropy (MSFuzzyEn); (ii) FFT harmonic analysis; (iii) stimulus-response wavelet time-frequency coherence (WTC); (iv) a novel inter-cycle lag variant of sample entropy (SampEnT), introduced to isolate cycle-to-cycle retinal response consistency independently of stimulus periodicity; and (v) discrete wavelet transform (DWT) for energetic extraction of oscillatory potentials (OPs). Univariate comparisons (Mann-Whitney, Cliffs{delta} , Benjamini-Hochberg FDR) identified seven significant candidate biomarkers (q < 0.05), five with large effect size: AUCfast (|{delta}| = 0.546, q = 0.009), Slopevery-slow (|{delta}| = 0.554, q = 0.007), R14f (|{delta}| = 0.515, q = 0.031), SampEnT (|{delta}| = 0.504, q = 0.019) and WTCR,mean (|{delta}| = 0.531, q = 0.023); and two with medium effect size (OP_amp_sum, band_snr). A logistic regression classifier combining three candidate biomarkers, validated by leave-one-out cross-validation, achieved ROC-AUC = 0.858, sensitivity = 70.0% and specificity = 88.5% (n = 46). These proof-of-concept results demonstrate that multi-domain ERG analysis captures retinal temporal dysfunction signatures in AD that are inaccessible to standard clinical analysis, supporting further investigation of portable ERG devices as a source of non-invasive candidate biomarkers for early AD detection.

bioengineering↗

bioRxiv2024

The Neuroactive Potential of the Elderly Human Gut Microbiome is Associated with Mental Health Status

Ageing is usually associated with physiological decline, increased mental health issues, and cognitive deterioration, alongside specific changes in the gut microbiome. However, the relationship between the neuroactive potential of the gut microbiome and mental health and cognition among the elderly remains less explored. This study examines a cohort of 153 older Chilean adults with cognitive complaints, assessing anthropometric data, mental health via five distinct tests, and gut microbiome composition through 16SV4 sequencing. Our findings reveal associations between anthropometric factors and depression scores in mental tests of participants with their gut microbiome composition. Notably, depression was associated with changes in the abundance of Lachnospiraceae Eubacterium xylanophilum group and Fusobacteriaceae Fusobacterium. Additionally, bacterial pathways involved in metabolising neuroactive compounds such as tryptophan, short-chain fatty acids, p-cresol, glutamate, and nitric oxide were associated with participant age, sex, and cognitive performance. Moreover, participants sex was associated with the neuroactive potential of specific bacteria, suggesting a role of the gut microbiome in sex-related mental health differences in the elderly. Together, to the best of our knowledge, this study demonstrates for the first time the association between the neuroactive potential of the human gut microbiome and mental health status in older individuals with cognitive complaints.

animal behavior and cognition↗

bioRxiv2024

Impact of cardiometabolic factors and blood beta-amyloid on the volume of white matter hyperintensities in dementia-free subjects with cognitive complaints

IntroductionWhite matter hyperintensities (WMH) in Alzheimers disease (AD) have traditionally been associated with cerebrovascular diseases. Amyloid {beta} (A{beta}) deposition reportedly contributes to WMHs; however, this relationship remains unclear in dementia-free subjects with cognitive complaints (CC). Here, we explored the relationship between WMHs and cardiometabolic and A{beta} blood biomarkers in a community-based cohort of Latin American CC participants. MethodsWe recruited 112 individuals with CC (69 - 92 YO, 90 females) with available plasma A{beta} biomarkers and cardiometabolic markers (systolic - diastolic blood pressure and glycaemia). WMHs were quantified using a lesion segmentation tool based on SPM12 and segmented using the John Hopkins University (JHU) Atlas and ALVIN segmentation for periventricular and subcortical white matter. Linear multiple regression models were fitted to assess total WMH lesions and the segmented tract, using demographics, cardiometabolic, and A{beta} blood biomarker measures as independent variables. ResultsAfter multiple comparison corrections, diastolic blood pressure was associated with WMHs, specifically in the right anterior thalamic radiation, left cingulum, minor forceps, and subcortical ALVIN segmentation. Glycaemia was associated with WMH volume in forceps major, forceps minor, and right fronto-occipital fasciculi. Conversely, A{beta} blood biomarkers and systolic blood pressure showed no association with WMH overall or in specific tracts. ConclusionOur findings suggest that, in dementia-free CC individuals, WMH volume was more related to cardiometabolic factors, whereas A{beta} blood biomarkers might be of less relevance. Dementia prevention strategies in individuals might be a useful focus for managing high peripheral vessel resistance and endothelial damage due to hypertension and hyperglycaemia.

neuroscience↗