Trust–SIoT: Towards Trustworthy Object Classification in the Social Internet of Things

The recent emergence of the promising paradigm of the Social Internet of Things (SIoT) is a result of an intelligent amalgamation of the social networking concepts with the Internet of Things (IoT) objects (also referred to as “things”) in an attempt to unravel the challenges of network discovery, navigability, and service composition. This is realized by facilitating the IoT objects to socialize with one another, i.e., similar to the social interactions amongst human beings. A fundamental issue that mandates careful attention is to thus establish, and over time, maintain trustworthy relationships amongst these IoT objects. Therefore, a trust framework for SIoT must include object-object interactions, the aspects of social relationships, credible recommendations, etc., however, the existing literature has only focused on some aspects of trust by primarily relying on the conventional approaches that govern linear relationships between input and output. In this paper, an artificial neural network-based trust framework, Trust–SIoT, has been envisaged for identifying the complex nonlinear relationships between input and output in a bid to classify trustworthy objects. Moreover, Trust–SIoT has been designed for capturing a number of key trust metrics as input, i.e., direct trust by integrating both current and past interactions, reliability and benevolence of an object, credible recommendations, and the degree of relationship by employing knowledge graph embedding. Finally, we have performed extensive experiments to evaluate the performance of Trust–SIoT vis-á-vis state-of-the-art heuristics on two real-world datasets. The results demonstrate that Trust–SIoT achieves a higher F1-score and lower MAE and MSE scores.Subhash Sagar, Adnan Mahmood, Kai Wang, Quan Z. Sheng, Jitander Kumar Pabani, and Wei Emma Zhan

Treatment outcomes of immune-related cutaneous adverse events

PURPOSE: The aim of the current study was to report the efficacy of topical and systemic treatments for immune-related cutaneous adverse events (ircAEs) attributed to checkpoint inhibitors in an uncontrolled cohort of patients referred to oncodermatology clinics. METHODS: A retrospective analysis of patients with ircAEs evaluated by dermatologists from January 1, 2014, to December 31, 2017, at three tertiary care hospitals and cancer centers were identified through electronic medical records. Clinicopathologic characteristics, dermatologic therapy outcome, and laboratory data were analyzed. RESULTS: A total of 285 patients (median age, 65 years [range, 17 to 89 years]) with 427 ircAEs were included: pruritus (n = 138; 32%), maculopapular rash (n = 120; 28%), psoriasiform rash (n = 22; 5%), and others (n = 147; 34%). Immune checkpoint inhibitor class was associated with ircAE phenotype (P = .007), where maculopapular rash was predominant in patients who received combination therapy. Severity of ircAEs was significantly reduced (mean Common Terminology Criteria for Adverse Events grade: 1.74 v 0.71; P, .001) with dermatologic interventions, including topical corticosteroids, oral antipruritics, and systemic immunomodulators. A total of 88 ircAEs (20%) were managed with systemic immunomodulators. Of these, 22 (25%) of 88 persisted or worsened. In seven patients with corticosteroid-refractory ircAEs, improvement resulted from targeted biologic immunomodulatory therapies that included rituximab and dupilumab. Serum interleukin-6 (IL-6) was elevated in 34 (52%) of 65 patients; grade 3 or greater ircAEs were associated with increased absolute eosinophils (odds ratio, 4.1; 95% CI, 1.3 to 13.4) and IL-10 (odds ratio, 23.8; 95% CI, 2.1 to 262.5); mean immunoglobulin E serum levels were greater in higher-grade ircAEs: 1,093 kU/L (grade 3), 245 kU/L (grade 2), and 112 kU/L (grade 1; P = .043). CONCLUSION: Most ircAEs responded to symptom- and phenotype-directed dermatologic therapies, whereas biologic therapies were effective in patients with corticosteroid-refractory disease. Increased eosinophils, IL-6, IL-10, and immunoglobulin E were associated with ircAEs, and they may represent actionable therapeutic targets for immune-related skin toxicities