1-Social media platforms are commonly employed by law enforcement agencies for collecting Open Source Intelligence (OSNIT) on criminals, and assessing the risk they pose to the environment the live in. However, since no prior research has investigated the relationships between hackers' use of social media platforms and their likelihood to generate cyberattacks, this practice is less common among Information Technology Teams. Addressing this empirical gap, we draw on the social learning theory and estimate the relationships between hackers' use of Facebook, Twitter, and YouTube and the frequency of web defacement attacks they generate in different times (weekdays vs. weekends) and against different targets (USA vs. non-USA websites). To answer our research questions, we use hackers' reports of web defacement they generated (available on http://www.zone-h.org), and complement with an independent data collection we launched to identify these hackers' use of different social media platforms. Results from a series of Negative Binomial Regression analyses reveal that hackers' use of social media platforms, and specifically Twitter and Facebook, significantly increases the frequency of web defacement attacks they generate. However, while using these social media platforms significantly increases the volume of web defacement attacks these hackers generate during weekdays, it has no association with the volume of web defacement they launch over weekends. Finally, although hackers' use of both Facebook and Twitter accounts increase the frequency of attacks they generate against non-USA websites, the use of Twitter only increases significantly the volume of web defacement attacks against USA websites.
CD200/CD200R is an immune checkpoint with broad expression patterns and a potential target for immune therapy. In this study, we assess both CD200 and CD200R expression in solid tumors, with a focus on lung cancer, and evaluate their association with clinicopathologic characteristics, mutation status, outcome, and programmed death-ligand 1 (PD-L1) expression. We used multiplexed quantitative immunofluorescence (QIF) to measure the expression of CD200 and CD200R in a total of 455 patients from three lung cancer cohorts. Using carefully validated antibodies, we performed target measurement with tyramide-based QIF panels and analyzed the data using the PM2000 microscope and AQUA software. CD200 tumor positivity was found in 29.7% of non-small cell lung cancer (NSCLC) patients and 33.3% of lung large cell neuroendocrine carcinoma (LCNEC) patients. CD200 demonstrated notable intratumoral heterogeneity. CD200R was expressed in immune cells in 25% of NSCLC and 41.3% of LCNEC patients. While CD200R is predominantly expressed in immune cells, rare tumor cell staining was seen in a highly heterogeneous pattern. CD200R expression in the stromal compartment was significantly higher in patients with squamous differentiation (p < 0.0001). Neither CD200 nor CD200R were associated with other clinicopathologic characteristics or mutation status. Both biomarkers were not prognostic for disease-free or overall survival in NSCLC. CD200 showed moderate correlation with PD-L1. CD200/CD200R pathway is frequently expressed in lung cancer patients. Differential expression patterns of CD200 and CD200R with PD-L1 suggest a potential role for targeting this pathway alone in patients with NSCLC.
1-Cyber security experts in the U.S. and around the globe assess potential threats to their organizations by evaluating potential attackers' skills, knowledge, resources, access to the target organization and motivation to offend (i.e. SKRAM). Unfortunately, this model fails to incorporate insights regarding online offenders' traits and the conditions surrounding the development of online criminal event. Drawing on contemporary criminological models, we present a theoretical rationale for revising the SKRAM model. The revised model suggests that in addition to the classical SKRAM components, both individual attributes and certain offline and online circumstances fuel cyber attackers' motivation to offend, and increase the probability that a cyber-attack will be launched against an organization. Consistent with our proposed model, and its potential in predicting the occurrence of different types of cyber-dependent crimes against organizations, we propose that Information Technology professionals' efforts to facilitate safe computing environments should design new approaches for collecting indicators regarding attackers' potential threat, and predicting the occurrence and timing of cyber-dependent crimes.
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