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Biology subjects

Wilson, M. T.

Publications and source records attributed to Wilson, M. T..

4 recordsLinked to original sources

Cell Programmed Nutrient Partitioning in the Tumor Microenvironment

The tumor microenvironment (TME) includes transformed cancer and infiltrating immune cells1,2. Cancer cells can consume large quantities of glucose through Warburg metabolism3,4 that can be visualized with positron emission tomography (PET). While infiltrating immune cells also rely on glucose, disruptions to metabolism can contribute to tumor immunological evasion5-9. How immune cell metabolism is programmed or restrained by competition with cancer cells for nutrients, remains uncertain. Here we used PET tracers to measure the accessibility of glucose and glutamine to cell subsets in the TME. Surprisingly, myeloid cells including macrophages were the greatest consumers of intra-tumoral glucose, followed by T cells and cancer cells. Cancer cells, in contrast, had the highest glutamine uptake. This distinct nutrient partitioning was programmed through selective mTORC1 signaling and glucose or glutamine-related gene expression. Inhibition of glutamine uptake enhanced glucose uptake across tumor resident cell types and shifted macrophage phenotype, demonstrating glucose is not limiting in the TME. Thus, cancer cells are not the only cells in tumors which exhibit high glucose uptake in vivo and instead preferentially utilize glutamine over other cell types. We observe that intrinsic cellular programs can play a major role in the use of some nutrients. Together, these data argue cell selective partitioning of glucose and glutamine can be exploited to develop therapies and imaging strategies to alter the metabolic programs of specific cell populations in the TME.

cancer biology↗

Design and demonstration in vitro of mouse-specific Transcranial Magnetic Stimulation coil

BackgroundTranscranial Magnetic Stimulation (TMS) is a technique used to treat different neurological disorders non-invasively. A pulsed current to a coil generates a magnetic field (B-field) which induces an electric field (E-field). Underlying biophysical effects of TMS are unclear. Therefore, animal experiments are needed; however, making small TMS coils suitable for mice is difficult and their field strengths are typically much lower than for human sized coils. Objectives/HypothesisWe aimed to design and demonstrate a mouse-specific coil that can generate high and focused E-field. MethodsWe designed a tapered TMS coil of 50 turns of 0.2 mm diameter copper wire around a 5 mm diameter tapered powdered iron core and discharged a 220 F capacitor at 50 V through it. We measured B-field with a Hall probe and induced E-field with a wire loop. We measured temperature rise with a thermocouple. We applied 1200 pulses of continuous theta burst stimulation (cTBS) and intermittent theta burst stimulation (iTBS) to mouse brain slices and analysed how spontaneous electrical activity changed. ResultsThe coil gave maximum B-field of 685 mT at the base of the coil and 340 mT at 2 mm below the coil, and maximum E-field 2 mm below the coil of approximately 10 V/m, at 50 V power supply, with a temperature increase of 20 degrees after 1200 pulses of cTBS. We observed no changes in B-field with heating. cTBS reduced frequency of spontaneous population events in mouse brain slices up to 20 minutes after stimulation and iTBS increased frequency up to 20 minutes after stimulation. No frequency changes occurred after 20 minutes. No changes in amplitude of spontaneous events were found. ConclusionThe design generated fields strong enough to modulate brain activity in vitro.

neuroscience↗

Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

ObjectiveTo develop a population-based biophysical model of motor-evoked potentials (MEPs) following transcranial magnetic stimulation (TMS). MethodsWe combined an existing MEP model with population-based cortical modeling. Layer 2/3 excitatory and inhibitory neural populations, modeled with neural-field theory, are stimulated with TMS and feed layer 5 corticospinal neurons, which also couple directly but weakly to the TMS pulse. The layer 5 output controls mean motoneuron responses, which generate a series of single motor-unit action potentials that are summed to estimate a MEP. ResultsA MEP waveform was generated comparable to those observed experimentally. The model captured TMS phenomena including a sigmoidal input-output curve, common paired pulse effects (short interval intracortical inhibition, intracortical facilitation, long interval intracortical inhibition) including responses to pharmacological interventions, and a cortical silent period. Changes in MEP amplitude following theta burst paradigms were observed including variability in outcome direction. ConclusionsThe model reproduces effects seen in common TMS paradigms. SignificanceThe model allows population-based modeling of changes in cortical dynamics due to TMS protocols to be assessed in terms of changes in MEPs, thus allowing a clear comparison between population-based modeling predictions and typical experimental outcome measures. HighlightsO_LIA model of motor-evoked potential formation gives a realistic electromyogram in response to TMS. C_LIO_LIThe model reproduces effects of SICI, ICF and LICI. C_LIO_LIA link between existing neural field modeling and realistic outcome measures of TMS is provided. C_LI

biophysics↗

Biophysical modeling of neural plasticity induced by transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a widely used noninvasive brain stimulation method capable of inducing plastic reorganisation of cortical circuits in humans. Changes in neural activity following TMS are often attributed to synaptic plasticity (e.g long-term potentiation and depression; LTP/LTD). However, the precise way in which synaptic processes such as LTP/LTD modulate the activity of large populations of neurons, as stimulated en masse by TMS, are unclear. The recent development of biophysically-informed models, which capture the physiological properties of TMS-induced plasticity using mathematics, provide an excellent framework for reconciling synaptic and macroscopic plasticity. In this article, we overview the TMS paradigms used to induce plasticity, and their limitations. We then describe the development of biophysically-based numerical models of the mechanisms underlying LTP/LTD on population-level neuronal activity, and the application of these models to TMS plasticity paradigms, including theta burst and paired associative stimulation. Finally, we outline how modeling can complement experiment to improve mechanistic understandings and optimize outcomes of TMS-induced plasticity.\n\nAbbreviations

neuroscience↗