פרסומים

Abstract Intrusion detection as well distributed denial of service (DDoS) are vital in ensuring computer network security. Some researchers claim that current approaches cannot meet the requirements of today's networks are either not workable or sustainable. In a more specific sense, these concerns are related to an increasing number of human interactions, along with reducing levels of detection ability. With our study, a novel deep learning model for intrusion detection is developed for addressing these issues. We proposed a novel deep learning classification algorithm constructed using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) named CLSTMNet. Our proposed model has been implemented and evaluated using the benchmark NSL-KDD datasets. Compared with many conventional machine learning algorithms, the satisfied outcomes have been obtained from our model.

Over the next decade, more than a million eukaryotic species are expected to be fully sequenced. This has the potential to improve our understanding of genotype and phenotype crosstalk, gene function and interactions, and answer evolutionary questions. Here, we develop a machine-learning approach for utilizing phylogenetic profiles across 1154 eukaryotic species. This method integrates co-evolution across eukaryotic clades to predict functional interactions between human genes and the context for these interactions. We benchmark our approach showing a 14% performance increase (auROC) compared to previous methods. Using this approach, we predict functional annotations for less studied genes. We focus on DNA repair and verify that 9 of the top 50 predicted genes have been identified elsewhere, with others previously prioritized by high-throughput screens. Overall, our approach enables better annotation of function and functional interactions and facilitates the understanding of evolutionary processes underlying co-evolution. The manuscript is accompanied by a webserver available at: https://mlpp.cs.huji.ac.il.

Over the next decade, more than a million eukaryotic species are expected to be fully sequenced. This has the potential to improve our understanding of genotype and phenotype crosstalk, gene function and interactions, and answer evolutionary questions. Here, we develop a machine-learning approach for utilizing phylogenetic profiles across 1154 eukaryotic species. This method integrates co-evolution across eukaryotic clades to predict functional interactions between human genes and the context for these interactions. We benchmark our approach showing a 14% performance increase (auROC) compared to previous methods. Using this approach, we predict functional annotations for less studied genes. We focus on DNA repair and verify that 9 of the top 50 predicted genes have been identified elsewhere, with others previously prioritized by high-throughput screens. Overall, our approach enables better annotation of function and functional interactions and facilitates the understanding of evolutionary processes underlying co-evolution. The manuscript is accompanied by a webserver available at: https://mlpp.cs.huji.ac.il.

When the past is contested by political actors, it can play a notable role both in present and in future politics. This is especially true when it comes to the memory of dominant parties, which are part and parcel of political and national history. Focusing on dominant parties in parliamentary democracies, this article examines the memory dynamics of a dominant party after its demise and highlights the importance of memory modes in understanding these dynamics. Using theories of collective memory, it identifies four possible modes of memory in a post-dominance era, suggesting discursive and power-related indications for each mode. The article then utilizes this framework to examine the memory of Mapai, the once-dominant party in Israel. On the basis of this analysis, the authors propose hypotheses concerning the comparative cases of Sweden, Italy, and Japan.

Decreased insulin secretion, associated with pancreatic β-cell failure, plays a critical role in many human diseases including diabetes, obesity, and cancer. While numerous studies linked β-cell failure with enhanced levels of reactive oxygen species (ROS), the development of diabetes associated with hereditary conditions that result in iron overload, e.g., hemochromatosis, Friedreich's ataxia, and Wolfram syndrome type 2 (WFS-T2; a mutation in CISD2, encoding the [2Fe-2S] protein NAF-1), underscores an additional link between iron metabolism and β-cell failure. Here, using NAF-1-repressed INS-1E pancreatic cells, we observed that NAF-1 repression inhibited insulin se-cretion, as well as impaired mitochondrial and ER structure and function. Importantly, we found that a combined treatment with the cell permeant iron chelator deferiprone and the glutathione precursor N-acetyl cysteine promoted the structural repair of mitochondria and ER, decreased mi-tochondrial labile iron and ROS levels, and restored glucose-stimulated insulin secretion. Addition-ally, treatment with the ferroptosis inhibitor ferrostatin-1 decreased cellular ROS formation and improved cellular growth of NAF-1 repressed pancreatic cells. Our findings reveal that suppressed expression of NAF-1 is associated with the development of ferroptosis-like features in pancreatic cells, and that reducing the levels of mitochondrial iron and ROS levels could be used as a therapeutic avenue for WFS-T2 patients. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Neoantigens are now recognized drivers of the antitumor immune response. Recurrent neoantigens, shared among groups of patients, have thus become increasingly coveted therapeutic targets. Here, we report on the data-driven identification of a robustly presented, immunogenic neoantigen that is derived from the combination of HLA-A*01:01 and RAS.Q61K. Analysis of large patient cohorts indicated that this combination applies to 3% of patients with melanoma. Using HLA peptidomics, we were able to demonstrate robust endogenous presentation of the neoantigen in 10 tumor samples. We detected specific reactivity to the mutated peptide within tumor-infiltrating lymphocytes (TILs) from 2 unrelated patients, thus confirming its natural immunogenicity. We further investigated the neoantigen-specific clones and their T cell receptors (TCRs) via a combination of TCR sequencing, TCR overexpression, functional assays, and single-cell transcriptomics. Our analysis revealed a diverse repertoire of neoantigen-specific clones with both intra-and interpatient TCR similarities. Moreover, 1 dominant clone proved to cross-react with the highly prevalent RAS.Q61R variant. Transcriptome analysis revealed a high association of TCR clones with specific T cell phenotypes in response to cognate melanoma, with neoantigen-specific cells showing an activated and dysfunctional phenotype. Identification of recurrent neoantigens and their reactive TCRs can promote ``off-the shelf'' precision immunotherapies, alleviating limitations of personalized treatments.

Recently, reservoirs in southern China are witnessing incidents involving black water, which are harmful to the aquatic ecosystem. This study unravels the cause of the black water events by studying the occurrence and the ecological risks of contaminants (Pb, Cu, Cd, Zn, Ni, TFe, Mn, S, P, and DOC) in sediments of Tianbao reservoir. Due to the significantly high concentration of TFe, Mn, and P in the sediments, the study further used the thin film diffusion gradient (DGT) technology and high-resolution dialysis method to investigate the movement of Fe2+, Mn2+, S2-, and reactive P within the sediments. The ecological risk assessment (threshold effect level and probable effect level) showed that the sediments had a low concentration of Pb, Cu, Cd, Zn, and Ni. High organic matter from the Eucalyptus plantation surrounding the reservoir, as well as the intense thermal stratification of the reservoir, caused the hypolimnion to be hypoxic (DO < 2 mg/L). The diffusion fluxes at the water-sediment boundary (WSB) demonstrated a significant movement of Fe2+, Mn2+, and PO43- from the sediments into the overlying water, while the movement of S2- was in both directions due to hypoxia. A high correlation Fe-DOC (r = 0.9), Fe-S (r = 0.8), and Mn-S (r = 0.7) and the redox interaction of Fe2+, Mn2+, S2-, P, and DOC at the hypoxic WSB caused the production of black substances in the hypolimnion contributing to the so-called black water reservoir.