Biology subjects

Karimi, H.

Publications and source records attributed to Karimi, H..

4 recordsLinked to original sources

bioRxiv2022

3D melanoma spheroid model for the development of positronium biomarker

It was recently demonstrated that newly invented positronium imaging may be used for improving cancer diagnostics by providing additional information about tissue pathology with respect to the standardized uptake value currently available in positron emission tomography (PET). Positronium imaging utilizes properties of a positronium atoms, which are built from the electron and positron produced in the body during PET examinations. We hypothesized whether positronium imaging would be sensitive to in vitro discrimination of tumour-like three-dimensional structures (spheroids) build of melanoma cell lines with different cancer activity and biological properties. The lifetime of ortho-Positronium (o-Ps) was evaluated in melanoma spheroids from two cell lines (WM266-4 and WM115) differing in the stage of malignancy. Additionally, we considered such parameters: as cell size, proliferation rate and malignancy to evaluate their relationship with o-Ps lifetime. We demonstrate the pilot results for the o-Ps lifetime measurement in extracellular matrix free spheroids. With the statistical significance of two standard deviations, we demonstrated that the higher the degree of malignancy and the rate of proliferation of neoplastic cells the shorter the lifetime of ortho-positronium. In particular we observed following indications encouraging further research: (i) WM266-4 spheroids characterized with higher proliferation rate and malignancy showed shorter o-Ps lifetime compared to WM115 spheroids characterized by lower growth rate, (ii) Both cell lines showed a decrease in the lifetime of o-Ps after spheroid generation in 8th day comparing to 4th day in culture and the mean o-Ps lifetime is longer for spheroids formed from WM115 cells than these from WM266-4 cells, regardless spheroid age. The results of these study revealed that positronium is a promising biomarker that may be applied in PET diagnostics for the assessment of the degree of cancer malignancy.

biophysics↗

bioRxiv2021

Genomics analysis of hexanoic acid exposure in Drosophila species

Drosophila sechellia is a dietary specialist endemic to the Seychelles islands that has evolved to consume the fruit of Morinda citrifolia. When ripe, the fruit of M. citrifolia contains octanoic acid and hexanoic acid, two medium chain fatty acid volatiles that deter and are toxic to generalist insects. D. sechellia has evolved resistance to these volatiles allowing it to feed almost exclusively on this host plant. The genetic basis of octanoic acid resistance has been the focus of multiple recent studies, but the mechanisms that govern hexanoic acid resistance in D. sechellia remain unknown. To understand how D. sechellia has evolved to specialize on M. citrifolia fruit and avoid the toxic effects of hexanoic acid, we exposed adult D. sechellia, D. melanogaster and D. simulans to hexanoic acid and performed RNA sequencing comparing their transcriptional responses to identify D. sechellia specific responses. Our analysis identified many more genes responding transcriptionally to hexanoic acid in the susceptible generalist species than in the specialist D. sechellia. Interrogation of the sets of differentially expressed genes showed that generalists regulated the expression of many genes involved in metabolism and detoxification whereas the specialist primarily downregulated genes involved in the innate immunity. Using these data we have identified interesting candidate genes that may be critically important in aspects of adaptation to their food source that contains high concentrations of HA. Understanding how gene expression evolves during dietary specialization is crucial for our understanding of how ecological communities are built and how evolution shapes trophic interactions.

genomics↗

bioRxiv2021

Validity and cultural generalisability of a 5-minute AI-based, computerised cognitive assessment in Mild Cognitive Impairment and Alzheimer's Dementia

INTRODUCTIONEarly detection and monitoring of mild cognitive impairment (MCI) and Alzheimers Disease (AD) patients are key to tackling dementia and providing benefits to patients, caregivers, healthcare providers and society. We developed the Integrated Cognitive Assessment (ICA); a 5-minute, language independent computerised cognitive test that employs an Artificial Intelligence (AI) model to improve its accuracy in detecting cognitive impairment. In this study, we aimed to evaluate the generalisability of the ICA in detecting cognitive impairment in MCI and mild AD patients. METHODSWe studied the ICA in a total of 230 participants. 95 healthy volunteers, 80 MCI, and 55 participants with mild AD completed the ICA, the Montreal Cognitive Assessment (MoCA) and Addenbrookes Cognitive Examination (ACE) cognitive tests. RESULTSThe ICA demonstrated convergent validity with MoCA (Pearson r = 0.58, p<0.0001) and ACE (r = 0.62, p<0.0001). The ICA AI model was able to detect cognitive impairment with an AUC of 81% for MCI patients, and 88% for mild AD patients. The AI model demonstrated improved performance with increased training data and showed generalisability in performance from one population to another. The ICA correlation of 0.17 (p=0.01) with education years is considerably smaller than that of MoCA (r=0.34, p<0.0001) and ACE (r=0.41, p<0.0001) which displayed significant correlations. In a separate study the ICA demonstrated no significant practice effect observed over the duration of the study. DISCUSSIONThe ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large-scale screening of cognitive impairment. The ICA is unbiased by differences in language, culture and education.

neuroscience↗

bioRxiv2020

Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment

Electroencephalography (EEG) has been commonly used to measure brain alterations in Alzheimers Disease (AD). However, reported changes are limited to those obtained from using univariate measures, including activation level and frequency bands. To look beyond the activation level, we used multivariate pattern analysis (MVPA) to extract patterns of information from EEG responses to images in an animacy categorization task. Comparing healthy controls (HC) with patients with mild cognitive impairment (MCI), we found that the neural speed of animacy information processing is decreased in MCI patients. Moreover, we found critical time-points during which the representational pattern of animacy for MCI patients was significantly discriminable from that of HC, while the activation level remained unchanged. Together, these results suggest that the speed and pattern of animacy information processing provide clinically useful information as a potential biomarker for detecting early changes in MCI and AD patients.

neuroscience↗