Biology subjects

Ibanez, V.

Publications and source records attributed to Ibanez, V..

3 recordsLinked to original sources

bioRxiv2024

Brain-wide microstrokes affect the stability of memory circuits in the hippocampus

Cognitive deficits affect over 70% of stroke survivors, yet the mechanisms by which multiple small ischemic events contribute to cognitive decline remain poorly understood. In this study, we employed chronic two-photon calcium imaging to longitudinally track the fate of individual neurons in the hippocampus of mice navigating a virtual reality environment, both before and after inducing brain-wide microstrokes. Our findings reveal that, under normal conditions, hippocampal neurons exhibit varying degrees of stability in their spatial memory coding. However, microstrokes disrupted this functional network architecture, leading to cognitive impairments. Notably, the preservation of stable coding place cells, along with the stability, precision, and persistence of the hippocampal network, was strongly predictive of cognitive outcomes. Mice with more synchronously active place cells near important locations demonstrated recovery from cognitive impairment. This study uncovers critical cellular responses and network alterations following brain injury, providing a foundation for novel therapeutic strategies preventing cognitive decline.

neuroscience↗

bioRxiv2023

Effect of the LSD1 Inhibitor RN-1 on gamma;-globin and Global Gene Expression during Erythroid Differentiation in Baboons (Papio anubis)

Increased levels of Fetal Hemoglobin reduce the severity of symptoms of patients with sickle cell disease and decrease the risk of death. An affordable, small molecule drug that stimulates HbF expression in vivo would be ideally suited to treat the large numbers of SCD patients that exist worldwide. Our previous work showed that administration of the LSD1 (KDM1A) inhibitor RN-1 to normal baboons increased Fetal Hemoglobin (HbF) and was tolerated over a prolonged treatment period. HbF elevations were associated with changes in epigenetic modifications that included increased levels of H3K4 di-and tri-methyl lysine at the {gamma}-globin promoter. While dramatic effects of the loss of LSD1 on hematopoietic differentiation have been observed in murine LSD1 gene deletion and silencing models, the effect of pharmacological inhibition of LSD1 in vivo on hematopoietic differentiation is unknown. The goal of these experiments was to investigate the in vivo mechanism of action of the LSD1 inhibitor RN-1 by determining its effect on {gamma}-globin expression in highly purified subpopulations of bone marrow erythroid cells enriched for varying stages of erythroid differentiation isolated directly from baboons treated with RN-1 and also by investigating the effect of RN1 on the global transcriptome in a highly purified population of proerythroblasts. Our results show that RN-1 administered to baboons targets an early event during erythroid differentiation responsible for {gamma}-globin repression and increases the expression of a limited number of genes including genes involved in erythroid differentiation such as GATA2, GFi-1B, and LYN.

molecular biology↗

bioRxiv2022

EXPLORE: A novel deep learning-based analysis method for exploration behaviour in object recognition tests

Object recognition tests are widely used in neuroscience to assess memory function in rodents. Despite the experimental simplicity of the task, the interpretation of behavioural features that are counted as object exploration can be complicated. Thus, object exploration is often analysed by manual scoring, which is time-consuming and variable across researchers. Current software using tracking points often lacks precision in capturing complex ethological behaviour. Switching or losing tracking points can bias outcome measures. To overcome these limitations we developed "EXPLORE", a simple, ready-to use and open source pipeline. EXPLORE consists of a convolutional neural network trained in a supervised manner, that extracts features from images and classifies behaviour of rodents near a presented object. EXPLORE achieves human-level accuracy in identifying and scoring exploration behaviour and outperforms commercial software with higher precision, higher versatility and lower time investment, in particular in complex situations. By labeling the respective training data set, users decide by themselves, which types of animal interactions on objects are in- or excluded, ensuring a precise analysis of exploration behaviour. A set of graphical user interfaces (GUIs) provides a beginning-to-end analysis of object recognition tests, accelerating a fast and reproducible data analysis without the need of expertise in programming or deep learning.

animal behavior and cognition↗