bioRxiv Science⌕ Search

Biology subjects

Alizadeh, J.

Publications and source records attributed to Alizadeh, J..

2 recordsLinked to original sources

A multi-omics analysis of glioma chemoresistance using a hybrid microphysiological model of glioblastoma

Chemoresistance is a major clinical challenge in the management of glioblastoma (GBM) Temozolomide (TMZ) is the chemotherapeutic drug of choice for GBM; however, the therapeutic effect of TMZ is limited due to the development of resistance. Recapitulating GBM chemoresistance in a controlled environment is thus essential in understanding the mechanism of chemoresistance. Herein, we present a hybrid microphysiological model of chemoresistant GBM-on-a-chip (HGoC) by directly co-culturing TMZ-resistant GBM spheroids with healthy neurons to mimic the microenvironment of both the tumor and the surrounding healthy tissue. We characterized the model with proteomics, lipidomics, and secretome assays. The results showed that our artificial model recapitulated the molecular signatures of recurrent GBM in humans. Both showed alterations in vesicular transport and cholesterol pathways, mitotic quiescence, and a switch in metabolism to oxidative phosphorylation associated with a transition from mesenchymal to amoeboid. This is the first report to unravel the interplay of all these molecular changes as a mechanism of chemoresistance in glioblastoma. Moreover, we have shown that the acquisition of resistance increases invasiveness and the presence of neurons decreases this property.

bioengineering↗

Multivariate pattern analysis reveals location specific aftereffects of 10Hz motor cortex transcranial alternating current stimulation

BackgroundTranscranial alternating current stimulation (tACS) may induce frequency-specific aftereffects on brain oscillations in the stimulated location, which could serve as evidence for region-specific neuroplasticity. Aftereffects of tACS on the motor system remain unknown. ObjectiveTo find evidence for aftereffects in short EEG segments following tACS to two critical nodes of the motor network, namely, left motor cortex (lMC) and right cerebellum (rCB). We hypothesized that aftereffects of lMC will be stronger in and around lMC compared to both active stimulation of rCB, as well as inactive ("sham") control conditions. MethodsTo this end, we employed multivariate pattern analysis (MVPA), and trained a classifier to distinguish between EEG signals following each of the three stimulation protocols. This method accounts for the multitude facets of the EEG signal and thus is more sensitive to subtle modulation of the EEG signal. ResultsEEG signals in both theta ({theta}, 4-8Hz) and alpha (, 8-13Hz) were better classified to lMC-tACS compared to rCB-tACS/sham, in and around lMC-tACS stimulation locations (electrodes FC3 and CP3). This effect was associated with a decrease in power following tACS. Source reconstruction revealed significant differences in premotor cortex but not in primary motor cortex as the computational model suggested. Correlation between classification accuracies in {theta} and in lMC-tACS was stronger compared to rCB-tACS/sham, suggesting cross-frequency effects of tACS. Nonetheless, {theta}/ phase-coupling did not differ between stimulation protocols. ConclusionsSuccessful classification of EEG signals to left motor cortex using MVPA revealed focal tACS aftereffects on the motor cortex, indicative of region-specific neuroplasticity.

neuroscience↗