CrownLabs - A Collaborative Environment to Deliver Remote Computing Laboratories

The coronavirus pandemic hit the entire education sector hard. All students were sent home and lectures started to be delivered through video-conferencing systems. CrownLabs is an open-source project providing an answer to the problem of delivering remote computing laboratories. Simplicity is one of its main characteristics, requiring nothing but a simple web browser to interact with the system and being all heavyweight computations performed at the university premises. Cooperation and mentoring are also encouraged through parallel access to the same remote desktop. The entire system is built up using components from the Kubernetes ecosystem, to replicate a "cloud grade" infrastructure, coupled with custom software implementing the core business logic. To this end, most of the complexity has been delegated to the infrastructure, to speed up the development process and reduce the maintenance burden. An extensive evaluation has been performed in both real and simulated scenarios to validate the overall performance: the results are encouraging, as well as the feedback from the early adopters of the system

User-specific Network Service Functions in an SDN-enabled Network Node

Network Functions Virtualization can enable each user (tenant) to define his desired set of network services, called (network) service graph. For instance, a User1 may want his traffic to traverse a firewall before reaching his terminal, while a User2 may be interested in a different type of firewall and in a network monitor as well. This paper presents a prototype of an SDN-enabled node that, given a new user connected to one of its physical ports, it is able to dynamically instantiate the user’s network service graph and force all his traffic to traverse the proper set of network functions

SARS-CoV-2 Infection in Cancer Patients: A Picture of an Italian Onco-Covid Unit

Background: The world, and Italy on the front lines, has experienced a major medical emergency due to the novel coronavirus outbreak. Cancer patients are one of the potentially most vulnerable cohorts of people, but data about their management are still few. Patients and Methods: In this monocentric retrospective study we included all SARS-CoV-2 oncological patients accepted, between March 27th and April 19th 2020, at the Onco-COVID Unit at San Luigi Gonzaga Hospital, one of the few Italian oncological-COVID wards. Data were obtained from medical records. Results: Eighteen cancer patients with COVID-19 were included. The mean (±SD) age of patients was 67 ± 14 years, 89% were men. Seven (39%) developed infection in communities and 11 (61%) during hospitalization. Lung cancer was the most frequent type of cancer (10, 56%). Seven patients (39%) were symptomatic for COVID-19 at the time of diagnosis and symptoms began 2 (±2) days before. The most common were shortness of breath and diarrhea. Fever was present in 5 patients (28%). Among the 11 asymptomatic patients, 8 (73%) became symptomatic during the hospitalization (mean time of symptoms onset 4 days ±4). Six patients (33%) were on active anti-tumor treatment: 2 (33%) received anti-tumor therapy within 2 weeks before the infection diagnosis and 2 (33%) continued oncological treatment after SARS-CoV-2 positivity. Eight (44%) patients died within a mean of 12 days (±8) from the infection diagnosis. Conclusions: Our series confirms the high mortality among cancer patients with COVID-19. The presence of asymptomatic cases evidences that typical symptoms and fever are not the only parameters to suspect the infection. The Onco-Covid unit suggests the importance of a tailored and holistic approach, even in this difficult situation

Second line therapy with axitinib after only prior sunitinib in metastatic renal cell cancer: Italian multicenter real world SAX study final results

Background: This multi-institutional retrospective real life study was conducted in 22 Italian Oncology Centers and evaluated the role of Axitinib in second line treatment in not selected mRCC patients. Methods: 148 mRCC patients were evaluated. According to Heng score 15.5%, 60.1% and 24.4% of patients were at poor risk, intermediate and favorable risk, respectively. Results: PFS, OS, DCR and ORR were 7.14 months, 15.5 months, 70.6% and 16.6%, respectively. The duration of prior sunitinib treatment correlated with a longer significant mPFS, 8.8 vs 6.3 months, respectively. Axitinib therapy was safe, without grade 4 adverse events. The most frequent toxicities of all grades were: fatigue (50%), hypertension (26%), and hypothyroidism (18%). G3 blood pressure elevation significantly correlated with longer mPFS and mOS compared to G1-G2 or no toxicity. Dose titration (DT) to 7 mg and 10 mg bid was feasible in 24% with no statistically significant differences in mPFS and mOS. The sunitinib-axitinib sequence was safe and effective, the mOS was 41.15 months. At multivariate analysis, gender, DCR to axitinib and to previous sunitinib correlated significantly with PFS; whereas DCR to axitinib, nephrectomy and Heng score independently affected overall survival. Conclusions: Axitinib was effective and safe in a not selected real life mRCC population. Trial registration INT - Napoli - 11/16 oss. Registered 20 April 2016. http://www.istitutotumori.na.it