Biology subjects

Kokiko-Cochran, O.

Publications and source records attributed to Kokiko-Cochran, O..

4 recordsLinked to original sources

bioRxiv2026

Non-viral vasculogenic reprogramming restores cognition and mitigates pathology in Alzheimer's disease

Alzheimers Disease (AD) is characterized by progressive cognitive decline associated with amyloid-beta (A{beta}) plaques, neurofibrillaiy tangles, inflammation, synaptic loss, and profuse neuronal death. Accumulating evidence demonstrates that cerebrovascular impairment precedes the emergence of neuropathological hallmarks, implicating vascular dysfunction as an early contributor to AD onset and progression. We investigated a non-viral strategy to generate pro-vasculogenic fibroblasts by transiently overexpressing Et{upsilon}2, Foxc2, and Flii (EFF) as a potential cell-based therapy for neurovascular deficits in AD. To assess therapeutic potential, FFF-primc[d] fibroblasts were injected into a mouse model of AD (3xTg-AD) and wild-type controls via the intracerebroventricular (ICV) route, followed by cognitive assessments and subsequent brain tissue analyses. Our findings demonstrate that FFF-primed fibroblasts acquire vasculogenic properties, enhance cerebral blood flow (CBF), and alleviate spatial memory deficits in 3xTg-AD mice. Moreover, transplanted FFF-primed fibroblasts exhibited long-term survival, integrated into the brain vasculature, and promoted cortical vascular remodeling in the AD brain. Notably, ICV deployment of these cells is also correlated with reduced cortical amyloid-beta load, suggesting potential therapeutic benefits in reducing AD pathology. Transcriptomic analysis identified the activation of genes involved in fatty acid oxidation, such as Ppar, known for its anti-amyloidogenic and anti-inflammatory effects. Collectively, these findings highlight non- viral, reprogramming-based vasculogenic cell therapy as a promising strategy for Alzheimers disease, capable of alleviating cognitive decline and addressing AD pathology across cellular and tissue scales.

neuroscience↗

bioRxiv2025

AI-based decoding of long covid cognitive impairments in mice using automated behavioral system and comparative transcriptomic analysis

Long COVID (LC) following SARS-CoV-2 infection affects millions of individuals world-wide and manifests with a variety of symptoms including cognitive dysfunction also known as "brain fog". This is characterized by difficulties in executive functions, planning, decision-making, working memory, impairments in complex attention, loss of ability to learn new skills and perform sophisticated brain tasks. No effective treatment options currently exist for LC-related cognitive dysfunction. Here, we use the IntelliCage, which is an automated tracking system of cognitive functions, following SARS-CoV-2 infection in mice, measuring the ability of each mouse within a group to perform tasks that mimic complex human behaviors, such as planning, decision-making, cognitive flexibility, and working memory. Artificial intelligence and machine learning analyses of the tracking data classified LC mice into distinct behavioral categories from non-infected control mice, permitting precise identification and quantification of complex cognitive dysfunction in a controlled, replicable manner. Importantly, we find that brains from LC mice with cognitive dysfunction exhibit transcriptomic alterations similar to those observed in humans suffering from LC-related cognitive impairments, including altered expression of genes involved in learning, executive functions, synaptic functions, neurotransmitters and memory. Together, our findings establish a validated murine model and an automated unbiased approach to study LC-related cognitive dysfunction for the first time, and providing a valuable tool for screening potential treatments and therapeutic interventions.

neuroscience↗

bioRxiv2024

Early hippocampal high-amplitude rhythmic spikes predict post-traumatic epilepsy in mice

Oscillations, a highly conserved brain function across mammalian species, are pivotal in brain physiology and pathology. Traumatic brain injury (TBI) often leads to subacute and chronic brain oscillatory alterations associated with complications like post-traumatic epilepsy (PTE) in patients and animal models. Our recent work longitudinally recorded local field potential from the contralateral hippocampus of 12 strains of recombinant inbred Collaborative Cross (CC) mice alongside classical laboratory inbred C57BL/6J mice after lateral fluid percussion injury. In this study, we profiled the acute (<12 hr post-injury) and subacute (12-48 hr post-injury) hippocampal oscillatory responses to TBI and evaluated their predictive value for PTE. We found dynamic high-amplitude rhythmic spikes with elevated power density and reduced entropy that prevailed during the acute phase in CC031 mice who later developed PTE. This characteristic early brain oscillatory alteration is absent in CC031 sham controls or other CC and reference C57BL/6J strains that did not develop PTE after TBI. Our work provides quantitative measures linking early brain oscillation to PTE at a population level in mice under controlled experimental conditions. These findings will offer insights into circuit mechanisms and potential targets for neuromodulatory intervention.

neuroscience↗

bioRxiv2021

Robust transcriptional profiling and identification of differentially expressed genes with low input RNA sequencing of adult hippocampal neural stem and progenitor populations

Multipotent neural stem cells (NSCs) are found in several isolated niches of the adult mammalian brain where they have unique potential to assist in tissue repair. Modern transcriptomics offer high-throughput methods for identifying disease or injury associated gene expression signatures in endogenous adult NSCs, but they require adaptation to accommodate the rarity of NSCs. Bulk RNA sequencing (RNAseq) of NSCs requires pooling several mice, which impedes application to labor-intensive injury models. Alternatively, single cell RNAseq can profile hundreds to thousands of cells from a single mouse and is increasingly used to study NSCs. The consequences of the low RNA input from a single NSC on downstream identification of differentially expressed genes (DEGs) remains largely unexplored. Here, to clarify the role that low RNA input plays in NSC DEG identification, we directly compared DEGs in an oxidative stress model of cultured NSCs by bulk and single cell sequencing. While both methods yielded DEGs that were replicable, single cell sequencing DEGs derived from genes with higher relative transcript counts compared to all detected genes and exhibited smaller fold changes than DEGs identified by bulk RNAseq. The loss of high fold-change DEGs in the single cell platform presents an important limitation for identifying disease-relevant genes. To facilitate identification of such genes, we determined an RNA-input threshold that enables transcriptional profiling of NSCs comparable to standard bulk sequencing and used it to establish a workflow for in vivo profiling of endogenous NSCs. We then applied this workflow to identify DEGs after lateral fluid percussion injury, a labor-intensive animal model of traumatic brain injury. Our work suggests that single cell RNA sequencing may underestimate the diversity of pathologic DEGs but population level transcriptomic analysis can be adapted to capture more of these DEGs with similar efficacy and diversity as standard bulk sequencing. Together, our data and workflow will be useful for investigators interested in understanding and manipulating adult hippocampal NSC responses to various stimuli.

neuroscience↗