Content Addressable Memories and Transformable Logic Circuits Based on Ferroelectric Reconfigurable Transistors for In-Memory Computing

As a promising alternative to the Von Neumann architecture, in-memory computing holds the promise of delivering high computing capacity while consuming low power. Content addressable memory (CAM) can implement pattern matching and distance measurement in memory with massive parallelism, making them highly desirable for data-intensive applications. In this paper, we propose and demonstrate a novel 1-transistor-per-bit CAM based on the ferroelectric reconfigurable transistor. By exploiting the switchable polarity of the ferroelectric reconfigurable transistor, XOR/XNOR-like matching operation in CAM can be realized in a single transistor. By eliminating the need for the complementary circuit, these non-volatile CAMs based on reconfigurable transistors can offer a significant improvement in area and energy efficiency compared to conventional CAMs. NAND- and NOR-arrays of CAMs are also demonstrated, which enable multi-bit matching in a single reading operation. In addition, the NOR array of CAM cells effectively measures the Hamming distance between the input query and stored entries. Furthermore, utilizing the switchable polarity of these ferroelectric Schottky barrier transistors, we demonstrate reconfigurable logic gates with NAND/NOR dual functions, whose input-output mapping can be transformed in real-time without changing the layout. These reconfigurable circuits will serve as important building blocks for high-density data-stream processors and reconfigurable Application-Specific Integrated Circuits (r-ASICs). The CAMs and transformable logic gates based on ferroelectric reconfigurable transistors will have broad applications in data-intensive applications from image processing to machine learning and artificial intelligence

Low-Thermal-Budget Ferroelectric Field-Effect Transistors Based on CuInP2S6 and InZnO

In this paper, we demonstrate low-thermal-budget ferroelectric field-effect transistors (FeFETs) based on two-dimensional ferroelectric CuInP2S6 (CIPS) and oxide semiconductor InZnO (IZO). The CIPS/IZO FeFETs exhibit non-volatile memory windows of ~1 V, low off-state drain currents, and high carrier mobilities. The ferroelectric CIPS layer serves a dual purpose by providing electrostatic doping in IZO and acting as a passivation layer for the IZO channel. We also investigate the CIPS/IZO FeFETs as artificial synaptic devices for neural networks. The CIPS/IZO synapse demonstrates a sizeable dynamic ratio (125) and maintains stable multi-level states. Neural networks based on CIPS/IZO FeFETs achieve an accuracy rate of over 80% in recognizing MNIST handwritten digits. These ferroelectric transistors can be vertically stacked on silicon CMOS with a low thermal budget, offering broad applications in CMOS+X technologies and energy-efficient 3D neural networks

Transcriptome and proteomic analysis of mpox virus F3L-expressing cells

BackgroundMonkeypox or mpox virus (mpox) is a double-stranded DNA virus that poses a significant threat to global public health security. The F3 protein, encoded by mpox, is an apoenzyme believed to possess a double-stranded RNA-binding domain (dsRBD). However, limited research has been conducted on its function. In this study, we present data on the transcriptomics and proteomics of F3L-transfected HEK293T cells, aiming to enhance our comprehension of F3L.MethodsThe gene expression profiles of pCAGGS-HA-F3L transfected HEK293T cells were analyzed using RNA-seq. Proteomics was used to identify and study proteins that interact with F3L. Real-time PCR was used to detect mRNA levels of several differentially expressed genes (DEGs) in HEK293T cells (or Vero cells) after the expression of F3 protein.ResultsA total of 14,822 genes were obtained in cells by RNA-Seq and 1,672 DEGs were identified, including 1,156 up-regulated genes and 516 down-regulated genes. A total of 27 cellular proteins interacting with F3 proteins were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and 19 cellular proteins with large differences in abundance ratios were considered to be candidate cellular proteins. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were significantly enriched in immune-related pathways, including type I interferon signaling pathway, response to virus, RIG-I-like receptor signaling pathway, NOD-like receptor signaling pathway, etc. Moreover, some selected DEGs were further confirmed by real-time PCR and the results were consistent with the transcriptome data. Proteomics data show that cellular proteins interacting with F3 proteins are mainly related to RNA splicing and protein translation.ConclusionsOur analysis of transcriptomic and proteomic data showed that (1) F3L up-regulates the transcript levels of key genes in the innate immune signaling pathway, such as RIGI, MDA5, IRF5, IRF7, IRF9, ISG15, IFNA14, and elicits a broad spectrum of antiviral immune responses in the host. F3L also increases the expression of the FOS and JNK genes while decreasing the expression of TNFR2, these factors may ultimately induce apoptosis. (2) F3 protein interacts with host proteins involved in RNA splicing and protein translation, such as SNRNP70, POLR2H, HNRNPA1, DDX17, etc. The findings of this study shed light on the function of the F3 protein

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe