Biologically Plausible Information Propagation in a CMOS Integrate-and-Fire Artificial Neuron Circuit with Memristive Synapses

Neuromorphic circuits based on spikes are currently envisioned as a viable option to achieve brain-like computation capabilities in specific electronic implementations while limiting power dissipation given their ability to mimic energy efficient bio-inspired mechanisms. While several network architectures have been developed to embed in hardware the bio-inspired learning rules found in the biological brain, such as the Spike Timing Dependent Plasticity, it is still unclear if hardware spiking neural network architectures can handle and transfer information akin to biological networks. In this work, we investigate the analogies between an artificial neuron combining memristor synapses and rate-based learning rule with biological neuron response in terms of information propagation from a theoretical perspective. Bio-inspired experiments have been reproduced by linking the biological probability of release with the artificial synapses conductance. Mutual information and surprise have been chosen as metrics to evidence how, for different values of synaptic weights, an artificial neuron allows to develop a reliable and biological resembling neural network in terms of information propagation and analysi

Study of RRAM-Based Binarized Neural Networks Inference Accelerators Using an RRAM Physics-Based Compact Model

In-memory computing hardware accelerators for binarized neural networks based on resistive RAM (RRAM) memory technologies represent a promising solution for enabling the execution of deep neural network algorithms on resource-constrained devices at the edge of the network. However, the intrinsic stochasticity and nonidealities of RRAM devices can easily lead to unreliable circuit operations if not appropriately considered during the design phase. In this chapter, analysis and design methodologies enabled by RRAM physics-based compact models of LIM and mixed-signal BNN inference accelerators are discussed. As a use case example, the UNIMORE RRAM physics-based compact model calibrated on an RRAM technology from the literature, is used to determine the performance vs. reliability trade-offs of different in-memory computing accelerators: i) a logic-in-memory accelerator based on the material implication logic, ii) a mixed-signal BNN accelerator, and iii) a hybrid accelerator enabling both computing paradigms on the same array. Finally, the performance of the three accelerators on a BNN inference task is compared and benchmarked with the state of the art

Information Transfer in Neuronal Circuits: From Biological Neurons to Neuromorphic Electronics

The advent of neuromorphic electronics is increasingly revolutionizing the concept of computation. In the last decade, several studies have shown how materials, architectures, and neuromorphic devices can be leveraged to achieve brain-like computation with limited power consumption and high energy efficiency. Neuromorphic systems have been mainly conceived to support spiking neural networks that embed bioinspired plasticity rules such as spike time-dependent plasticity to potentially support both unsupervised and supervised learning. Despite substantial progress in the field, the information transfer capabilities of biological circuits have not yet been achieved. More importantly, demonstrations of the actual performance of neuromorphic systems in this context have never been presented. In this paper, we report similarities between biological, simulated, and artificially reconstructed microcircuits in terms of information transfer from a computational perspective. Specifically, we extensively analyzed the mutual information transfer at the synapse between mossy fibers and granule cells by measuring the relationship between pre- and post-synaptic variability. We extended this analysis to memristor synapses that embed rate-based learning rules, thus providing quantitative validation for neuromorphic hardware and demonstrating the reliability of brain-inspired applications

Mitochondrial Metabolism and EV Cargo of Endothelial Cells Is Affected in Presence of EVs Derived from MSCs on Which HIF Is Activated

Small extracellular vesicles (sEVs) derived from mesenchymal stem cells (MSCs) have attracted growing interest as a possible novel therapeutic agent for the management of different cardiovascular diseases (CVDs). Hypoxia significantly enhances the secretion of angiogenic mediators from MSCs as well as sEVs. The iron-chelating deferoxamine mesylate (DFO) is a stabilizer of hypoxia-inducible factor 1 and consequently used as a substitute for environmental hypoxia. The improved regenerative potential of DFO-treated MSCs has been attributed to the increased release of angiogenic factors, but whether this effect is also mediated by the secreted sEVs has not yet been investigated. In this study, we treated adipose-derived stem cells (ASCs) with a nontoxic dose of DFO to harvest sEVs (DFO-sEVs). Human umbilical vein endothelial cells (HUVECs) treated with DFO-sEVs underwent mRNA sequencing and miRNA profiling of sEV cargo (HUVEC-sEVs). The transcriptomes revealed the upregulation of mitochondrial genes linked to oxidative phosphorylation. Functional enrichment analysis on miRNAs of HUVEC-sEVs showed a connection with the signaling pathways of cell proliferation and angiogenesis. In conclusion, mesenchymal cells treated with DFO release sEVs that induce in the recipient endothelial cells molecular pathways and biological processes strongly linked to proliferation and angiogenesis

Structural biology of Helicobacter pylori type IV secretion system

Helicobacter pylori chronically infects the gastric mucosa of millions of people annually worldwide: it has been estimated that over 50% of the world population carries this infection. H. pylori has been associated with the development of several diseases, like chronic gastritis, gastric and duodenal ulcer, gastric adenocarcinoma and mucosa-associated lymphoma [1-3]. The complete genome sequence of two different isolates of H. pylori (J99 and 26995) is known. The strains that contain a 37 kb foreign DNA region, called cag pathogenicity island (cag-PAI), cause the most severe form of virulence [4]. The cag-PAI encodes for a functional type IV secretion apparatus homologous to the VirB/D4 Type IV Secretion System (T4SS) of the plant pathogen Agrobacterium tumefaciens and other Gram-negative bacteria [5]. T4SSs are involved in conjugal DNA transfer, in the DNA delivery to (or uptake from) the environment, for instance the release of oncogenic DNA into infected plant cells by A. tumefaciens, or in the translocation of effector proteins [6,7]. The T4SS encoded by the cag-PAI of H. pylori is responsible for the translocation into the host cell of the protein CagA, a major antigenic virulence factor encoded within the cag-PAI. Once secreted into the gastric epithelial cells, CagA induces cellular modifications, such as elongation and spreading of host cells [8]. The aim of this structural genomic project is to determine the three-dimensional structure of most of the proteins encoded by the cag-PAI, a task that will allow to elucidate the function and the organization of the entire T4SS of such a relevant pathogenic bacterium [9]

Reliability of Logic-in-Memory Circuits in Resistive Memory Arrays

Producción CientíficaLogic-in-memory (LiM) circuits based on resistive random access memory (RRAM) devices and the material implication logic are promising candidates for the development of low-power computing devices that could fulfill the growing demand of distributed computing systems. However, these circuits are affected by many reliability challenges that arise from device nonidealities (e.g., variability) and the characteristics of the employed circuit architecture. Thus, an accurate investigation of the variability at the array level is needed to evaluate the reliability and performance of such circuit architectures. In this work, we explore the reliability and performance of smart IMPLY (SIMPLY) (i.e., a recently proposed LiM architecture with improved reliability and performance) on two 4-kb RRAM arrays based on different resistive switching oxides integrated in the back end of line (BEOL) of the 0.25-μm BiCMOS process. We analyze the tradeoff between reliability and energy consumption of SIMPLY architecture by exploiting the results of an extensive array-level variability characterization of the two technologies. Finally, we study the worst case performance of a full adder implemented with the SIMPLY architecture and benchmark it on the analogous CMOS implementation.European Union’s Horizon 2020 Research and Innovation Programme under Grant 64863

Innovative In Vitro Strategy for Assessing Aluminum Bioavailability in Oral Care Cosmetics

Aluminum is an element found in nature and in cosmetic products. It can interfere with the metabolism of other cations, thus inducing gastrointestinal disorder. In cosmetics, aluminum is used in antiperspirants, lipsticks, and toothpastes. The aim of this work is to investigate aluminum bioavailability after accidental oral ingestion derived from the use of a toothpaste containing a greater amount of aluminum hydroxide than advised by the Scientific Committee on Consumer Safety (SCCS). To simulate in vitro toothpaste accidental ingestion, the INFOGEST model was employed, and the amount of aluminum was measured through the ICP-AES analysis. Tissue barrier integrity was analyzed by measuring transepithelial electric resistance, and the tissue architecture was checked through light microscopy. The margin of safety was also calculated. Overall, our results indicate that the acute exposure to aluminum accidentally ingested from toothpastes is safe for the final user, even in amounts higher than SCCS indications

Advanced Data Encryption ​using 2D Materials

Advanced data encryption requires the use of true random number generators (TRNGs) to produce unpredictable sequences of bits. TRNG circuits with high degree of randomness and low power consumption may be fabricated by using the random telegraph noise (RTN) current signals produced by polarized metal/insulator/metal (MIM) devices as entropy source. However, the RTN signals produced by MIM devices made of traditional insulators, i.e., transition metal oxides like HfO and AlO, are not stable enough due to the formation and lateral expansion of defect clusters, resulting in undesired current fluctuations and the disappearance of the RTN effect. Here, the fabrication of highly stable TRNG circuits with low power consumption, high degree of randomness (even for a long string of 2 − 1 bits), and high throughput of 1 Mbit s by using MIM devices made of multilayer hexagonal boron nitride (h-BN) is shown. Their application is also demonstrated to produce one-time passwords, which is ideal for the internet-of-everything. The superior stability of the h-BN-based TRNG is related to the presence of few-atoms-wide defects embedded within the layered and crystalline structure of the h-BN stack, which produces a confinement effect that avoids their lateral expansion and results in stable operation.M.L. acknowledges generous support from the King Abdullah University of Science and Technology. This work was supported by the Ministry of Science and Technology of China (grants no. 2018YFE0100800, 2019YFE0124200), the National Natural Science Foundation of China (grants no. 61874075), the Collaborative Innovation Centre of Suzhou Nano Science & Technology, the Priority Academic Program Development of Jiangsu Higher Education Institutions, and the 111 Project from the State Administration of Foreign Experts Affairs of China. A.A. and S.R. acknowledge the project: ModElling Charge and Heat trANsport in 2D-materIals based Composites—MECHANIC reference number: PCI2018-093120 funded by Ministerio de Ciencia, Innovación y Universidades. ICN2 is funded by the CERCA Programme/Generalitat de Catalunya and is supported by the Severo Ochoa program from Spanish MINECO (Grant No. SEV-2017-0706). Y.S. acknowledges support from the European Union (Marie Sklodowska-Curie actions (grant no. 894840). The authors acknowledge technical advice from H.-S. Philip Wong from Stanford University and Xiaoming Xie from Chinese Academy of Sciences

SARS-CoV-2 vaccination modelling for safe surgery to save lives : data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.Peer reviewe

The commissioning of the CUORE experiment: the mini-tower run

CUORE is a ton-scale experiment approaching the data taking phase in Gran Sasso National Laboratory. Its primary goal is to search for the neutrinoless double-beta decay in 130Te using 988 crystals of tellurim dioxide. The crystals are operated as bolometers at about 10 mK taking advantage of one of the largest dilution cryostat ever built. Concluded in March 2016, the cryostat commissioning consisted in a sequence of cool down runs each one integrating new parts of the apparatus. The last run was performed with the fully configured cryostat and the thermal load at 4 K reached the impressive mass of about 14 tons. During that run the base temperature of 6.3 mK was reached and maintained for more than 70 days. An array of 8 crystals, called mini-tower, was used to check bolometers operation, readout electronics and DAQ. Results will be presented in terms of cooling power, electronic noise, energy resolution and preliminary background measurements