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Diaz, X.

Publications and source records attributed to Diaz, X..

3 recordsLinked to original sources

Alzheimer's Disease-Associated Proteomic Changes in Olfactory Stem Cells Show Pathway-Level Transcriptomic Overlap

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder and the leading cause of dementia worldwide. Although recent therapeutic advances have provided some disease-modifying potential, there is currently no curative treatment for AD, highlighting the need for improved disease models and early biomarkers. Olfactory mucosal stem cells, which can be expanded in vitro as olfactory neurosphere-derived (ONS) cells, represent a promising source for biomarker discovery because olfactory tissue is more accessible than central nervous system tissue and has been reported to exhibit AD-related pathological changes. In this study, we used subcellular fractionation-based proteomics, reconstructed bulk proteomics and integrated transcriptomic-proteomic analyses to characterise alterations in ONS cells derived from healthy control, mild cognitive impairment (MCI) and AD individuals. Fraction-specific proteomics identified cytoplasmic and nuclear-enriched protein abundance changes, including alterations in proteins and pathways associated with cytoskeletal organisation, RNA processing, intracellular trafficking, autophagy and mitochondrial/metabolic processes. Reduced LC3B abundance in cytoplasmic AD ONS cells was supported by western blot analysis, although LC3B abundance alone does not indicate altered autophagic flux. Reconstructed bulk proteomics identified 40 FDR-significant proteins in AD compared with HC, defining an AD-associated protein signature enriched for extracellular matrix, cytoskeletal, organelle-associated and RNA-processing pathways. Despite proteomic enrichment of mitochondrial and metabolic pathways, Seahorse Mito Stress Test analysis did not identify significant group-level differences in mitochondrial respiration. Integrated transcriptomic-proteomic analysis revealed partial RNA-protein concordance and pathway-level overlap across disease-associated processes. Together, these findings support the use of patient-derived ONS cells as a model for investigating AD- and MCI-associated molecular changes and highlight protein signatures for further validation.

neuroscience↗

The Crunchometer: A Low-Cost, Open-Source Acoustic Analysis of Feeding Microstructure

Elucidating the neuronal circuits that govern appetite requires precise, high-resolution monitoring of the microstructure of solid food consumption, a need unmet by existing tools, which are either costly or lack the temporal resolution to align feeding events with neuronal activity. To overcome this, we developed the Crunchometer, a low-cost, open-source acoustic system that uses computational algorithms to generate high-resolution feeding ethograms from the sounds produced during solid food consumption. Validation across energy states (hunger/satiety) confirmed its sensitivity to changes in feeding microstructure, and the system reliably detected semaglutide-induced suppression of intake and reduced preference for a high-fat diet. Leveraging its seamless integration with in vivo recordings in freely behaving mice, we paired the Crunchometer with lateral hypothalamus (LH) electrophysiology to identify "meal-related" neurons that track entire meals rather than individual bouts. Calcium imaging further revealed that distinct subsets of LH GABAergic and glutamatergic neurons were tuned to feeding only, to licking only, or to both behaviors. Thus, LH neuronal ensembles differentially encode the consumption of solid food versus liquid sucrose. These findings demonstrate that the Crunchometer is a robust, accessible platform for dissecting the neural correlates of feeding behavior at the resolution of a single bite. Significance statementThe Crunchometer is a low-cost, open-source technology that democratizes feeding analysis, enabling the precise dissection of neuronal circuits involved in appetite to advance therapies for obesity and eating disorders.

neuroscience↗

Tesofensine, a novel antiobesity drug, silences GABAergic hypothalamic neurons

Obesity is a major global health epidemic that has adverse effects on both the people affected as well as the cost to society. Several anti-obesity drugs that target GLP-1 receptors have recently come to the market. Here we describe the effects of tesofensine, a novel anti-obesity drug that acts as a triple monoamine neurotransmitter reuptake inhibitor. We investigated its effects on weight loss and underlying neuronal mechanisms in mice and rats using various techniques. These include behavioral tasks, DeepLabCut videotaped analysis, electrophysiological ensemble recordings, optogenetic activation, and chemogenetic silencing of GABAergic neurons in the Lateral Hypothalamus (LH). We found that tesofensine induced greater weight loss in obese than lean rats, which was associated with changes in LH ensemble activity. In Vgat-ChR2 and Vgat-IRES-cre transgenic mice, we found for the first time that tesofensine inhibited a subset of LH GABAergic neurons, reducing their ability to promote feeding behavior, and chemogenetically silencing them enhanced tesofensines food-suppressing effects. Unlike phentermine, a dopaminergic appetite suppressant, tesofensine causes few, if any, head-weaving stereotypy at therapeutic doses. Most importantly, we found that tesofensine prolonged the weight loss induced by 5-HTP, a serotonin precursor, and blocked the body weight rebound that often occurs after weight loss. Behavioral studies on rats with the tastant sucrose indicated that tesofensines appetite suppressant effects are independent of taste aversion and do not directly affect the perception of sweetness or palatability of sucrose. In summary, our data provide new insights into the effects of tesofensine on weight loss and the underlying neuronal mechanisms, suggesting that tesofensine may be an effective treatment for obesity and that it may be a valuable adjunct to other appetite suppressants to prevent body weight rebound.

neuroscience↗