Abstract
CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living ...computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The BLAST devices leverage a dry ion-selective membrane, enabling long-term potentiation, with ~50 aJ/µm
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switching energy efficiency, at least an order of magnitude lower than previous reports on two-dimensional material-based artificial synapses. The devices show unique metaplasticity, a useful feature for generalizable deep neural networks, and we demonstrate that metaplastic BLASTs outperform ideal linear synapses in classic image classification tasks. With switching energy well below the 1 fJ energy estimated per biological synapse, the proposed devices are powerful candidates for bio-interfaced online learning, bridging the gap between artificial and biological neural networks.
Spintronic devices based on domain wall (DW) motion through ferromagnetic nanowire tracks have received great interest as components of neuromorphic information processing systems. Previous proposals ...for spintronic artificial neurons required external stimuli to perform the leaking functionality, one of the three fundamental functions of a leaky integrate-and-fire (LIF) neuron. The use of this external magnetic field or electrical current stimulus results in either a decrease in energy efficiency or an increase in fabrication complexity. In this article, we modify the shape of previously demonstrated three-terminal magnetic tunnel junction neurons to perform the leaking operation without any external stimuli. The trapezoidal structure causes a shape-based DW drift, thus intrinsically providing the leaking functionality with no hardware cost. This LIF neuron, therefore, promises to advance the development of spintronic neural network crossbar arrays.
With increasing numbers of immune-compromised patients with malignancy, hematologic disease, and HIV, as well as those receiving immunosupressive drug regimens for the management of organ ...transplantation or autoimmune inflammatory conditions, the incidence of fungal infections has dramatically increased over recent years. Definitive diagnosis of pulmonary fungal infections has also been substantially assisted by the development of newer diagnostic methods and techniques, including the use of antigen detection, polymerase chain reaction, serologies, computed tomography and positron emission tomography scans, bronchoscopy, mediastinoscopy, and video-assisted thorascopic biopsy. At the same time, the introduction of new treatment modalities has significantly broadened options available to physicians who treat these conditions. While traditionally antifungal therapy was limited to the use of amphotericin B, flucytosine, and a handful of clinically available azole agents, current pharmacologic treatment options include potent new azole compounds with extended antifungal activity, lipid forms of amphotericin B, and newer antifungal drugs, including the echinocandins. In view of the changing treatment of pulmonary fungal infections, the American Thoracic Society convened a working group of experts in fungal infections to develop a concise clinical statement of current therapeutic options for those fungal infections of particular relevance to pulmonary and critical care practice. This document focuses on three primary areas of concern: the endemic mycoses, including histoplasmosis, sporotrichosis, blastomycosis, and coccidioidomycosis; fungal infections of special concern for immune-compromised and critically ill patients, including cryptococcosis, aspergillosis, candidiasis, and Pneumocystis pneumonia; and rare and emerging fungal infections.
Mild cognitive impairment is a transitional state between the cognitive changes of normal aging and early Alzheimer's disease.
In a double-blind study, we evaluated subjects with the amnestic subtype ...of mild cognitive impairment. Subjects were randomly assigned to receive 2000 IU of vitamin E daily, 10 mg of donepezil daily, or placebo for three years. The primary outcome was clinically possible or probable Alzheimer's disease; secondary outcomes were cognition and function.
A total of 769 subjects were enrolled, and possible or probable Alzheimer's disease developed in 212. The overall rate of progression from mild cognitive impairment to Alzheimer's disease was 16 percent per year. As compared with the placebo group, there were no significant differences in the probability of progression to Alzheimer's disease in the vitamin E group (hazard ratio, 1.02; 95 percent confidence interval, 0.74 to 1.41; P=0.91) or the donepezil group (hazard ratio, 0.80; 95 percent confidence interval, 0.57 to 1.13; P=0.42) during the three years of treatment. Prespecified analyses of the treatment effects at 6-month intervals showed that as compared with the placebo group, the donepezil group had a reduced likelihood of progression to Alzheimer's disease during the first 12 months of the study (P=0.04), a finding supported by the secondary outcome measures. Among carriers of one or more apolipoprotein E epsilon4 alleles, the benefit of donepezil was evident throughout the three-year follow-up. There were no significant differences in the rate of progression to Alzheimer's disease between the vitamin E and placebo groups at any point, either among all patients or among apolipoprotein E epsilon4 carriers.
Vitamin E had no benefit in patients with mild cognitive impairment. Although donepezil therapy was associated with a lower rate of progression to Alzheimer's disease during the first 12 months of treatment, the rate of progression to Alzheimer's disease after three years was not lower among patients treated with donepezil than among those given placebo.
Digital computing is nearing its physical limits as computing needs and energy consumption rapidly increase. Analogue‐memory‐based neuromorphic computing can be orders of magnitude more energy ...efficient at data‐intensive tasks like deep neural networks, but has been limited by the inaccurate and unpredictable switching of analogue resistive memory. Filamentary resistive random access memory (RRAM) suffers from stochastic switching due to the random kinetic motion of discrete defects in the nanometer‐sized filament. In this work, this stochasticity is overcome by incorporating a solid electrolyte interlayer, in this case, yttria‐stabilized zirconia (YSZ), toward eliminating filaments. Filament‐free, bulk‐RRAM cells instead store analogue states using the bulk point defect concentration, yielding predictable switching because the statistical ensemble behavior of oxygen vacancy defects is deterministic even when individual defects are stochastic. Both experiments and modeling show bulk‐RRAM devices using TiO2‐X switching layers and YSZ electrolytes yield deterministic and linear analogue switching for efficient inference and training. Bulk‐RRAM solves many outstanding issues with memristor unpredictability that have inhibited commercialization, and can, therefore, enable unprecedented new applications for energy‐efficient neuromorphic computing. Beyond RRAM, this work shows how harnessing bulk point defects in ionic materials can be used to engineer deterministic nanoelectronic materials and devices.
A resistive memory cell based on the electrochemical migration of oxygen vacancies for in‐memory neuromorphic computing is presented. By using the average statistical behavior of all oxygen vacancies to store analogue information states, this cell overcomes the stochastic and unpredictable switching plaguing filament‐forming memristors, and instead achieves linear, predictable, and deterministic switching.
Theranostics is the highly targeted molecular imaging and therapy of tumors. Targeted peptide receptor radionuclide therapy has taken the lead in demonstrating the safety and effectiveness of this ...molecular approach to treating cancers. Metastatic, well-differentiated gastroenteropancreatic neuroendocrine tumors may be most effectively imaged and treated with DOTATATE ligands. We review the current practice, safety, advantages, and limitations of DOTATATE based theranostics. Finally, we briefly describe the exciting new areas of development and future directions of gastroenteropancreatic neuroendocrine tumor theranostics.
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