A phase I study of irinotecan and temozolomide with bevacizumab in children with recurrent/refractory central nervous system tumors.

PURPOSE: Children with relapsed/refractory central nervous system (CNS) tumors require novel combinations of therapies. Irinotecan and temozolomide (IT) is a frequently used therapy with an established toxicity profile. Bevacizumab is an anti-VEGF monoclonal antibody with demonstrated activity in CNS tumors. Therefore, the combination of these agents has therapeutic potential in CNS tumors. The objective of this study was to determine the maximum tolerated dose (MTD) of escalating dose IT combined with a fixed dose of bevacizumab (BIT) in children with relapsed/refractory CNS tumors. METHODS: A phase I trial was performed in a 3 + 3 design. Therapy toxicities and radiologic responses to treatment were described. RESULTS: One hundred eighty cycles of therapy were administered to 26 patients. The MTD of BIT was dose level 1, (bevacizumab 10 mg/kg on days 1 and 15, irinotecan 125 mg/m2 on days 1 and 15, and temozolomide 125 mg/m2 on days 1-5 of 28-day cycles). The regimen was well tolerated with primarily hematologic toxicity, which was not dose limiting. Among 22 response-evaluable patients, there was 1 complete response (CR), 6 partial responses (PR), and 10 stable diseases (SD) with an overall response rate (ORR: CR + PR) of 31.8%. CONCLUSION: At the MTD, BIT therapy was well tolerated, and prolonged treatment courses of up to 24 cycles were feasible, with radiographic responses observed. Further evaluation is needed for efficacy in a phase II trial (NCT00876993, registered April 7, 2009, www. CLINICALTRIALS: gov ).

An Anomaly Intrusion Detection for High-Density Internet of Things Wireless Communication Network Based Deep Learning Algorithms.

Telecommunication networks are growing exponentially due to their significant role in civilization and industry. As a result of this very significant role, diverse applications have been appeared, which require secured links for data transmission. However, Internet-of-Things (IoT) devices are a substantial field that utilizes the wireless communication infrastructure. However, the IoT, besides the diversity of communications, are more vulnerable to attacks due to the physical distribution in real world. Attackers may prevent the services from running or even forward all of the critical data across the network. That is, an Intrusion Detection System (IDS) has to be integrated into the communication networks. In the literature, there are numerous methodologies to implement the IDSs. In this paper, two distinct models are proposed. In the first model, a custom Convolutional Neural Network (CNN) was constructed and combined with Long Short Term Memory (LSTM) deep network layers. The second model was built about the all fully connected layers (dense layers) to construct an Artificial Neural Network (ANN). Thus, the second model, which is a custom of an ANN layers with various dimensions, is proposed. Results were outstanding a compared to the Logistic Regression algorithm (LR), where an accuracy of 97.01% was obtained in the second model and 96.08% in the first model, compared to the LR algorithm, which showed an accuracy of 92.8%.

Effect of Poloxamer 188 vs Placebo on Painful Vaso-Occlusive Episodes in Children and Adults With Sickle Cell Disease: A Randomized Clinical Trial.

Importance: Although effective agents are available to prevent painful vaso-occlusive episodes of sickle cell disease (SCD), there are no disease-modifying therapies for ongoing painful vaso-occlusive episodes; treatment remains supportive. A previous phase 3 trial of poloxamer 188 reported shortened duration of painful vaso-occlusive episodes in SCD, particularly in children and participants treated with hydroxyurea. Objective: To reassess the efficacy of poloxamer 188 for vaso-occlusive episodes. Design, Setting, and Participants: Phase 3, randomized, double-blind, placebo-controlled, multicenter, international trial conducted from May 2013 to February 2016 that included 66 hospitals in 12 countries and 60 cities; 388 individuals with SCD (hemoglobin SS, SC, S-ß0 thalassemia, or S-ß+ thalassemia disease) aged 4 to 65 years with acute moderate to severe pain typical of painful vaso-occlusive episodes requiring hospitalization were included. Interventions: A 1-hour 100-mg/kg loading dose of poloxamer 188 intravenously followed by a 12-hour to 48-hour 30-mg/kg/h continuous infusion (n = 194) or placebo (n = 194). Main Outcomes and Measures: Time in hours from randomization to the last dose of parenteral opioids among all participants and among those younger than 16 years as a separate subgroup. Results: Of 437 participants assessed for eligibility, 388 were randomized (mean age, 15.2 years; 176 [45.4%] female), the primary outcome was available for 384 (99.0%), 15-day follow-up contacts were available for 357 (92.0%), and 30-day follow-up contacts were available for 368 (94.8%). There was no significant difference between the groups for the mean time to last dose of parenteral opioids (81.8 h for the poloxamer 188 group vs 77.8 h for the placebo group; difference, 4.0 h [95% CI, -7.8 to 15.7]; geometric mean ratio, 1.2 [95% CI, 1.0-1.5]; P = .09). Based on a significant interaction of age and treatment (P = .01), there was a treatment difference in time from randomization to last administration of parenteral opioids for participants younger than 16 years (88.7 h in the poloxamer 188 group vs 71.9 h in the placebo group; difference, 16.8 h [95% CI, 1.7-32.0]; geometric mean ratio, 1.4 [95% CI, 1.1-1.8]; P = .008). Adverse events that were more common in the poloxamer 188 group than the placebo group included hyperbilirubinemia (12.7% vs 5.2%); those more common in the placebo group included hypoxia (12.0% vs 5.3%). Conclusions and Relevance: Among children and adults with SCD, poloxamer 188 did not significantly shorten time to last dose of parenteral opioids during vaso-occlusive episodes. These findings do not support the use of poloxamer 188 for vaso-occlusive episodes. Trial Registration: ClinicalTrials.gov Identifier: NCT01737814.