The Stochastic Modeling of TiO 2 Memristor and Its Usage in Neuromorphic System Design

Abstract Memristor, the fourth basic circuit element, has shown great potential in neuromorphic circuit design for its unique synapse-like feature. However, though the continuous resistance state of memristor has been expected, obtaining and maintaining an arbitrary intermediate state cannot be well controlled in nowadays memristive system. In addition, the stochastic switching behaviors have been widely observed. To facilitate the investigation on memristor-based hardware implementation, we built a stochastic behavior model of TiO 2 memristive devices based on the real experimental results. By leveraging the stochastic behavior of memristors, a macro cell design composed of multiple parallel connecting memristors can be successfully used in implementing the weight storage unit and the stochastic neuron the two fundamental components in neural network (NN)s, providing a feasible solution in memristor-based hardware implementation

Cooperation between NRF2-mediated transcription and MDIG-dependent epigenetic modifications in arsenic-induced carcinogenesis and cancer stem cells

Environmental exposure to arsenic, a well-established carcinogen linked to a number of human cancers, is a public health concern in many areas of the world. Despite extensive studies on the molecular mechanisms of arsenic-induced carcinogenesis, how initial cellular responses, such as activation of stress kinases and the generation of reactive oxygen species, converge to affect the transcriptional and/or epigenetic reprogramming required for the malignant transformation of normal cells or normal stem cells remains to be elucidated. In this review, we discuss some recent discoveries showing how the transcription factor NRF2 and an epigenetic regulator, MDIG, contribute to the arsenic-induced generation of cancer stem-like cells (CSCs) as determined by applying CRISPR-Cas9 gene editing and chromosome immunoprecipitation followed by DNA sequencing (ChIP-seq)

A genome-wide association study of anorexia nervosa suggests a risk locus implicated in dysregulated leptin signaling

J. Kaprio, A. Palotie, A. Raevuori-Helkamaa ja S. Ripatti ovat työryhmän Eating Disorders Working Group of the Psychiatric Genomics Consortium jäseniä. Erratum in: Sci Rep. 2017 Aug 21;7(1):8379, doi: 10.1038/s41598-017-06409-3We conducted a genome-wide association study (GWAS) of anorexia nervosa (AN) using a stringently defined phenotype. Analysis of phenotypic variability led to the identification of a specific genetic risk factor that approached genome-wide significance (rs929626 in EBF1 (Early B-Cell Factor 1); P = 2.04 x 10(-7); OR = 0.7; 95% confidence interval (CI) = 0.61-0.8) with independent replication (P = 0.04), suggesting a variant-mediated dysregulation of leptin signaling may play a role in AN. Multiple SNPs in LD with the variant support the nominal association. This demonstrates that although the clinical and etiologic heterogeneity of AN is universally recognized, further careful sub-typing of cases may provide more precise genomic signals. In this study, through a refinement of the phenotype spectrum of AN, we present a replicable GWAS signal that is nominally associated with AN, highlighting a potentially important candidate locus for further investigation.Peer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases

Three State Estimation Fusion Methods Based on the Characteristic Function Filtering

There are three state estimation fusion methods for a class of strong nonlinear measurement systems, based on the characteristic function filter, namely the centralized filter, parallel filter, and sequential filter. Under ideal communication conditions, the centralized filter can obtain the best state estimation accuracy, and the parallel filter can simplify centralized calculation complexity and improve feasibility; in addition, the performance of the sequential filter is very close to that of the centralized filter and far better than that of the parallel filter. However, the sequential filter can tolerate non-ideal conditions, such as delay and packet loss, and the first two filters cannot operate normally online for delay and will be invalid for packet loss. The performance of the three designed fusion filters is illustrated by three typical cases, which are all better than that of the most popular Extended Kalman Filter (EKF) performance

Immunotherapeutic interventions of Triple Negative Breast Cancer

Abstract Triple Negative Breast Cancer (TNBC) is a highly heterogeneous subtype of breast cancer that lacks the expression of oestrogen receptors, progesterone receptors and human epidermal growth factor receptor 2. Although TNBC is sensitive to chemotherapy, the overall outcomes of TNBC are worse than for other breast cancers, and TNBC is still one of the most fatal diseases for women. With the discovery of antigens specifically expressed in TNBC cells and the developing technology of monoclonal antibodies, chimeric antigen receptors and cancer vaccines, immunotherapy is emerging as a novel promising option for TNBC. This review is mainly focused on the tumour microenvironment and host immunity, Triple Negative Breast Cancer and the clinical treatment of TNBC, novel therapies for cancer and immunotherapy for TNBC, and the future outlook for the treatment for TNBC and the interplay between the therapies, including immune checkpoint inhibitors, combination of immune checkpoint inhibitors with targeted treatments in TNBC, adoptive cell therapy, cancer vaccines. The review also highlights recent reports on the synergistic effects of immunotherapy and chemotherapy, antibody–drug conjugates, and exosomes, as potential multifunctional therapeutic agents in TNBC

Enhancing Scientific Papers Summarization with Citation Graph

Previous work for text summarization in scientific domain mainly focused on the content of the input document, but seldom considering its citation network. However, scientific papers are full of uncommon domain-specific terms, making it almost impossible for the model to understand its true meaning without the help of the relevant research community. In this paper, we redefine the task of scientific papers summarization by utilizing their citation graph and propose a citation graph-based summarization model CGSum which can incorporate the information of both the source paper and its references. In addition, we construct a novel scientific papers summarization dataset Semantic Scholar Network (SSN) which contains 141K research papers in different domains and 661K citation relationships. The entire dataset constitutes a large connected citation graph. Extensive experiments show that our model can achieve competitive performance when compared with the pretrained models even with a simple architecture. The results also indicates the citation graph is crucial to better understand the content of papers and generate high-quality summaries

The impact of wind energy on plant biomass production in China

Global wind power expansion raises concerns about its potential impact on plant biomass production (PBP). Using a high-dimensional fixed effects model, this study reveals significant PBP reduction due to wind farm construction based on 2404 wind farms, 108,361 wind turbines, and 7,904,352 PBP observations during 2000-2022 in China. Within a 1-10 km buffer, the normalized differential vegetation and enhanced vegetation indices decrease from 0.0097 to 0.0045 and 0.0075 to 0.0028, respectively. Similarly, absorbed photosynthetically active radiation and gross primary productivity decline from 0.0094 to 0.0034% and 0.0003-0.0002 g*C/m2 within a 1-7 km buffer. Adverse effects last over three years, magnified in summer and autumn, and are more pronounced at lower altitudes and in plains. Forest carbon sinks decrease by 12,034 tons within a 0-20 km radius, causing an average economic loss of $1.81 million per wind farm. Our findings underscore the balanced mitigation strategies for renewable energy transition when transiting from fossil fuels

Inhibition Effect of <i>Pseudomonas stutzeri</i> on the Corrosion of X70 Pipeline Steel Caused by Sulfate-Reducing Bacteria

Microbiologically influenced corrosion (MIC) is a common phenomenon in water treatment, shipping, construction, marine and other industries. Sulfate-reducing bacteria (SRB) often lead to MIC. In this paper, a strain of Pseudomonas stutzeri (P. stutzeri) with the ability to inhibit SRB corrosion is isolated from the soil through enrichment culture. P. stutzeri is a short, rod-shaped, white and transparent colony with denitrification ability. Our 16SrDNA sequencing results verify the properties of P. stutzeri strains. The growth conditions of P. stutzeri bacteria and SRB are similar, and the optimal culture conditions are about 30 °C, pH 7, and the stable stage is reached in about seven days. The bacteria can coexist in the same growth environment. Using the weight loss method, electrochemical experiments and composition analysis techniques we found that P. stutzeri can inhibit the corrosion of X70 steel by SRB at 20~40 °C, pH 6~8. Furthermore, long-term tests at 3, 6 and 9 months reveal that P. stutzeri can effectively inhibit the corrosion of X70 steel caused by SRB