Glioma-Induced Alterations in Excitatory Neurons are Reversed by mTOR Inhibition.

Gliomas are highly aggressive brain tumors characterized by poor prognosis and composed of diffusely infiltrating tumor cells that intermingle with non-neoplastic cells in the tumor microenvironment, including neurons. Neurons are increasingly appreciated as important reactive components of the glioma microenvironment, due to their role in causing hallmark glioma symptoms, such as cognitive deficits and seizures, as well as their potential ability to drive glioma progression. Separately, mTOR signaling has been shown to have pleiotropic effects in the brain tumor microenvironment, including regulation of neuronal hyperexcitability. However, the local cellular-level effects of mTOR inhibition on glioma-induced neuronal alterations are not well understood. Here we employed neuron-specific profiling of ribosome-bound mRNA via 'RiboTag,' morphometric analysis of dendritic spines, and in vivo calcium imaging, along with pharmacological mTOR inhibition to investigate the impact of glioma burden and mTOR inhibition on these neuronal alterations. The RiboTag analysis of tumor-associated excitatory neurons showed a downregulation of transcripts encoding excitatory and inhibitory postsynaptic proteins and dendritic spine development, and an upregulation of transcripts encoding cytoskeletal proteins involved in dendritic spine turnover. Light and electron microscopy of tumor-associated excitatory neurons demonstrated marked decreases in dendritic spine density. In vivo two-photon calcium imaging in tumor-associated excitatory neurons revealed progressive alterations in neuronal activity, both at the population and single-neuron level, throughout tumor growth. This in vivo calcium imaging also revealed altered stimulus-evoked somatic calcium events, with changes in event rate, size, and temporal alignment to stimulus, which was most pronounced in neurons with high-tumor burden. A single acute dose of AZD8055, a combined mTORC1/2 inhibitor, reversed the glioma-induced alterations on the excitatory neurons, including the alterations in ribosome-bound transcripts, dendritic spine density, and stimulus evoked responses seen by calcium imaging. These results point to mTOR-driven pathological plasticity in neurons at the infiltrative margin of glioma - manifested by alterations in ribosome-bound mRNA, dendritic spine density, and stimulus-evoked neuronal activity. Collectively, our work identifies the pathological changes that tumor-associated excitatory neurons experience as both hyperlocal and reversible under the influence of mTOR inhibition, providing a foundation for developing therapies targeting neuronal signaling in glioma.

Intracranial EEG seizure onset and termination patterns and their association.

OBJECTIVE: The study of seizure onset and termination patterns has the potential to enhance our understanding of the underlying mechanisms of seizure generation and cessation. It is largely unclear whether seizures with distinct onset patterns originate from varying network interactions and terminate through different termination pathways. METHODS: We investigated the morphology and location of 103 intracranial EEG seizure onset and termination patterns from 20 patients with drug-resistant focal epilepsy. We determined if seizure onset patterns were associated with specific termination patterns. Finally, we looked at network interactions prior to the generation of distinct seizure onset patterns by calculating directed functional connectivity matrices. RESULTS: We identified nine seizure onset and six seizure termination patterns. The most common onset pattern was Low-Voltage Fast Activity (36 %), and the most frequent termination pattern was Burst Suppression (44 %). All seizures with fast (>13 Hz) termination patterns had a fast (>13 Hz) onset pattern type. Almost any onset pattern could terminate with the Burst Suppression and rhythmic Spike/PolySpike and Wave (rSW/rPSW) termination patterns. Seizures with a fast activity onset had higher inflow to the seizure onset zone from other regions in the gamma and high gamma frequency ranges prior to their generation compared to seizures with a slow onset. SIGNIFICANCE: Our observations suggest that different mechanisms underlie the generation of different seizure onset patterns although seizure onset patterns can share a common termination pattern. Possible mechanisms underlying these patterns are discussed.

Estimation of the tissue damage after MI through time-frequency analysis of the electromechanical signals.

Abstract Coronary congestion is a heart disease that puts many lives at risk each year. The task of coronary arteries is to distribute blood to the heart tissue and any blockage in them can cause the tissue to absorb less oxygen and nutrients than needed (ischaemia disease). This imbalance will continue until the first cell is destroyed (myocardial infarction). Simulating the myocardial infarction in the laboratory rats, this study tries to determine the extent of tissue damage through the electrocardiogram (ECG) and atrial blood pressure (ABP) synchronic signals. The signals of 50 wistar rats with a weight range of 200-300 g were recorded at 30 min in the normal case and 30 min in the ischaemia and myocardial infarction (MI) case (the artificial complete blockage was in the left anterior descending coronary artery (LAD)). For a different injury in the rats' heart, the vasopressin (AVP) with different doses was injected to 40 rats. After that the images of the heart sections and the data were extracted, the 50-dimensional feature vector was generated by using the wavelet packet transform (WPT) on the ECG and ABP signals and also by obtaining the entropy of the wavelet coefficients. The extent of tissue damage on the images of the heart tissue was extracted by using the image processing method. Finally, the amount of the damaged tissue was estimated by four artificial neural networks (ANN) (with different structures) with an averaging criterion. The intelligent machine estimated the ischaemia and normal tissues with the average error of 2.91% for all the AVP doses and control cases.