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Experimental Data fromthe paper 'Spatiotemporal characterization of the field-induced insulator-to-metal transition' by Javier del Valle et al.

Although a number of studies have explored deep learning in neuroscience, the application of these algorithms to neural systems on a microscopic scale, i.e. parameters relevant to lower scales of organization, remains relatively novel. Motivated by advances in whole-brain imaging, we examined the performance of deep learning models on microscopic neural dynamics and resulting emergent behaviors using calcium imaging data from the nematode C. elegans. As one of the only species for which neuron-level dynamics can be recorded, C. elegans serves as the ideal organism for designing and testing models bridging recent advances in deep learning and established concepts in neuroscience. We show that neural networks perform remarkably well on both neuron-level dynamics prediction and behavioral state classification. In addition, we compared the performance of structure agnostic neural networks and graph neural networks to investigate if graph structure can be exploited as a favourable inductive bias. To perform this experiment, we designed a graph neural network which explicitly infers relations between neurons from neural activity and leverages the inferred graph structure during computations. In our experiments, we found that graph neural networks generally outperformed structure agnostic models and excel in generalization on unseen organisms, implying a potential path to generalizable machine learning in neuroscience.

Metasurfaces are two-dimensional nanostructures that allow unprecedented control of light through engineering the amplitude, phase, and polarization across meta-atom resonators. Adding tunability to metasurface components would boost their potential and unlock a vast array of new application possibilities such as dynamic beam steering, tunable metalenses, and reconfigurable meta-holograms, to name a few. We present here high-index meta-atoms, resonators, and metasurfaces reconfigured by thermal effects, across the near to mid-infrared spectral ranges. We study thermal tunability in group IV and group IV–VI semiconductors, as well as in phase-transition materials, and demonstrate large dynamic resonance frequency shifts accompanied by significant amplitude and phase modulation in metasurfaces and resonators. We highlight the importance of high-Q resonances along with peak performance of thermal and thermo-optic effects, for efficient and practical reconfigurable devices. This paper paves the way to efficient high-Q reconfigurable and active infrared metadevices.

Resistive switching, a phenomenon in which the resistance of a device can be modified by applying an electric field1–5, is at the core of emerging technologies such as neuromorphic computing and resistive memories6–9. Among the different types of resistive switching, threshold firing10–14 is one of the most promising, as it may enable the implementation of artificial spiking neurons7,13,14. Threshold firing is observed in Mott insulators featuring an insulator-to-metal transition15,16, which can be triggered by applying an external voltage: the material becomes conducting (‘fires’) if a threshold voltage is exceeded7,10–12. The dynamics of this induced transition have been thoroughly studied, and its underlying mechanism and characteristic time are well documented10,12,17,18. By contrast, there is little knowledge regarding the opposite transition: the process by which the system returns to the insulating state after the voltage is removed. Here we show that Mott nanodevices retain a memory of previous resistive switching events long after the insulating resistance has recovered. We demonstrate that, although the device returns to its insulating state within 50 to 150 nanoseconds, it is possible to re-trigger the insulator-to-metal transition by using subthreshold voltages for a much longer time (up to several milliseconds). We find that the intrinsic metastability of first-order phase transitions is the origin of this phenomenon, and so it is potentially present in all Mott systems. This effect constitutes a new type of volatile memory in Mott-based devices, with potential applications in resistive memories, solid-state frequency discriminators and neuromorphic circuits. Mott materials feature scale-less relaxation dynamics after the insulator-to-metal transition that make its electric triggering dependent on recent switching events.

We report the existence of two competing mechanisms in the current-driven electrical breakdown of vanadium sesquioxide (${\mathrm{V}}_{2}{\mathrm{O}}_{3}$) and vanadium dioxide ($\mathrm{V}{\mathrm{O}}_{2}$) nanodevices. Our experiments and simulations show that the competition between a purely electronic (PE) mechanism and an electrothermal (ET) mechanism, suppressed in nanoscale devices, explains the current-driven insulator-to-metal phase transition (IMT). We find that the relative contribution of PE and ET effects is dictated by thermal coupling and resistivity, a discovery which disambiguates a long-standing controversy surrounding the physical nature of the current-driven IMT in vanadium oxides. Furthermore, we show that the electrothermally driven IMT occurs through a nanoscopic surface-confined filament. This nanoconfined filament has a very large thermal gradient, thus generating a large Seebeck-effect electric field.

GLUT1, and to a lesser extent, GLUT3, appear to be interesting targets in the treatment of glioblastoma multiforme. The current review aims to give a brief history of the scientific community’s understanding of these glucose transporters and to relate their importance to the metabolic changes that occur as a result of cancer. One of the primary changes that occurs in cancer, the Warburg Effect, is characterized by an extreme shift toward glycolysis from the usual reliance on oxidative phosphorylation and is currently being investigated to target the upstream and downstream factors responsible for Warburg-induced changes. Further, it aims to explain the differential expression of GLUT1 and GLUT3 in glioblastoma tissue, and how these modulations in expression can serve as targets to restore a more normal metabolism. Additionally, hypoxia-induced factor-1α’s (HIF1α) role in a number of transcriptional changes typical to GBM will be discussed, including its role in GLUT upregulation. Finally, the four known subtypes of GBM [proneural, neural, mesenchymal, and classical] will be characterized in order to discuss how metabolic changes differ in each subtype. These changes have the potential to be selectively targeted in order to provide specificity to the clinical treatment options in GBM.

Sustained-release implants for insulin can be made by compressing a powder admixture with palmitic acid as the excipient. At less than 20%, insulin does not disperse uniformly in the admixture. The size distribution of the excipient particles obtained after grinding for 15 min does not affect the sustained release action. When tested in a 33 d period, an 1/8-size piece (approximately 25 mg) implant cut from a pellet disc containing 20% insulin which is 13 mm in diameter and 1.5 mm thick released 0.12-0.17 mg insulin/d in diabetic Wistar rats. The 1/8-size piece containing 20% insulin or a rod of similar weight with a diameter of 3 mm, which can be inserted by a trocar, was optimal for the implant to provide a service-life of 49 +/- 7 d. The service-life decreased with progressive reduction in implant size. The implant functioned just as well subcutaneously or intraperitoneally and was eroded subcutaneously by 33.6-53.1% in 33 d. The glycosylated haemoglobin contents of diabetic animals on implant therapy which had a blood glucose level of 4.7 +/- 2.5 mmol/l were in a range of 6.2-8.9% compared to the control value of greater than 13% with chronic hyperglycemia. The overall results indicated that the implant was a promising alternative to daily insulin injections.

Solvent-extracted white birch, kept near 20° in liquid ammonia under pressure for 72 h and then extracted with methanol to remove acetamide, retained 0.25% of amide nitrogen. Extraction of the very finely ground residual wood with hot water yielded 21% as a 4-O-methylglucuronoxylan containing 0.53% of amide nitrogen. Alkaline hydrolysis removed the amide absorption in the infrared and restored the normal xylan spectrum. These results, supported by various control experiments, showed that amide groups in the ammonia-treated wood were derived from lactone or ester groups in the original 4-O-methylglucuronoxylan. Some of the uronic acid groups in the native wood presumably existed as ester crosslinks.

Previously, a small implant of compressed insulin in palmitic acid provided a basal dose to reduce hyperglycaemia for 42 +/- 12 d in rats with induced diabetes. This study describes a silicone implant that can be used for preprandial dose supplements. The device consists of two compartments assembled by attaching a 9 mm diameter foam ring to a 6 mm diameter ring of the same material. The assembly is then enclosed between two membranes, and an annular external wall. Before sealing, a 6 mg piece of compressed insulin (Zn) is inserted into the smaller ring with 2 mg tetracycline to hinder microbial growth. The top membrane is pierced once with an 18 gauge needle, and the device is tested by implanting under the abdominal skin of diabetic rats. Serous fluid soon enters to fill the 141 microliter internal volume through the orifice and dissolves some of the insulin which does not leak out. Sidewise compression weekly over the skin fold of the unanesthetized animal shows that the insulin remained potent until used up after 154 d. When compressed daily, the insulin supply lasted for 24 +/- 4 d and maintained the blood glucose consistently at 3.4 +/- 1.1 mM/l for 6-8 h each day. The dependable device is refillable percutaneously by injection of an insulin suspension.