[Concurrent irradiation and DNA tumor vaccination in canine oral malignant melanoma: a pilot study].

Melanoma is the most common oral tumor in dogs, characterized by rapid growth, local invasion, and high metastatic rate. The goal of this study was to evaluate the combination of radiation therapy and DNA tumor vaccine. We hypothesized, that the concurrent use would not increase toxicity. Nine dogs with oral melanoma were treated with 4 fractions of 8 Gray at 7-day intervals. The vaccine was given 4 times every 14 days, beginning at the first radiation fraction. Local acute radiation toxicities were assessed according to the VRTOG toxicity scoring scheme over a time period of 7 weeks. In none of the evaluated dogs, mucositis, dermatitis and conjunctivitis exceeded grade 2. In 3 dogs mild fever, lethargy, and local swelling at the injection site were seen after vaccine application. In conclusion, the concurrent administration of radiation therapy and vaccine was well tolerated in all dogs.

Rising serum sodium levels are associated with a concurrent development of metabolic alkalosis in critically ill patients

PURPOSE Changes in electrolyte homeostasis are important causes of acid-base disorders. While the effects of chloride are well studied, only little is known of the potential contributions of sodium to metabolic acid-base state. Thus, we investigated the effects of intensive care unit (ICU)-acquired hypernatremia on acid-base state. METHODS We included critically ill patients who developed hypernatremia, defined as a serum sodium concentration exceeding 149 mmol/L, after ICU admission in this retrospective study. Data on electrolyte and acid-base state in all included patients were gathered in order to analyze the effects of hypernatremia on metabolic acid-base state by use of the physical-chemical approach. RESULTS A total of 51 patients were included in the study. The time of rising serum sodium and hypernatremia was accompanied by metabolic alkalosis. A transient increase in total base excess (standard base excess from 0.1 to 5.5 mmol/L) paralleled by a transient increase in the base excess due to sodium (base excess sodium from 0.7 to 4.1 mmol/L) could be observed. The other determinants of metabolic acid-base state remained stable. The increase in base excess was accompanied by a slight increase in overall pH (from 7.392 to 7.429, standard base excess from 0.1 to 5.5 mmol/L). CONCLUSIONS Hypernatremia is accompanied by metabolic alkalosis and an increase in pH. Given the high prevalence of hypernatremia, especially in critically ill patients, hypernatremic alkalosis should be part of the differential diagnosis of metabolic acid-base disorders.

SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

Multimodal treatment for high-risk prostate cancer with high-dose intensity-modulated radiation therapy preceded or not by radical prostatectomy, concurrent intensified-dose docetaxel and long-term androgen deprivation therapy: results of a prospective phase II trial.

BACKGROUND The optimal management of high-risk prostate cancer remains uncertain. In this study we assessed the safety and efficacy of a novel multimodal treatment paradigm for high-risk prostate cancer. METHODS This was a prospective phase II trial including 35 patients with newly diagnosed high-risk localized or locally advanced prostate cancer treated with high-dose intensity-modulated radiation therapy preceded or not by radical prostatectomy, concurrent intensified-dose docetaxel-based chemotherapy and long-term androgen deprivation therapy. Primary endpoint was acute and late toxicity evaluated with the Common Terminology Criteria for Adverse Events version 3.0. Secondary endpoint was biochemical and clinical recurrence-free survival explored with the Kaplan-Meier method. RESULTS Acute gastro-intestinal and genito-urinary toxicity was grade 2 in 23% and 20% of patients, and grade 3 in 9% and 3% of patients, respectively. Acute blood/bone marrow toxicity was grade 2 in 20% of patients. No acute grade ≥ 4 toxicity was observed. Late gastro-intestinal and genito-urinary toxicity was grade 2 in 9% of patients each. No late grade ≥ 3 toxicity was observed. Median follow-up was 63 months (interquartile range 31-79). Actuarial 5-year biochemical and clinical recurrence-free survival rate was 55% (95% confidence interval, 35-75%) and 70% (95% confidence interval, 52-88%), respectively. CONCLUSIONS In our phase II trial testing a novel multimodal treatment paradigm for high-risk prostate cancer, toxicity was acceptably low and mid-term oncological outcome was good. This treatment paradigm, thus, may warrant further evaluation in phase III randomized trials.

General distress, hopelessness—suicidal ideation and worrying in adolescence: Concurrent and predictive validity of a symptom-level bifactor model for clinical diagnoses

BACKGROUND: Clinical disorders often share common symptoms and aetiological factors. Bifactor models acknowledge the role of an underlying general distress component and more specific sub-domains of psychopathology which specify the unique components of disorders over and above a general factor. METHODS: A bifactor model jointly calibrated data on subjective distress from The Mood and Feelings Questionnaire and the Revised Children's Manifest Anxiety Scale. The bifactor model encompassed a general distress factor, and specific factors for (a) hopelessness-suicidal ideation, (b) generalised worrying and (c) restlessness-fatigue at age 14 which were related to lifetime clinical diagnoses established by interviews at ages 14 (concurrent validity) and current diagnoses at 17 years (predictive validity) in a British population sample of 1159 adolescents. RESULTS: Diagnostic interviews confirmed the validity of a symptom-level bifactor model. The underlying general distress factor was a powerful but non-specific predictor of affective, anxiety and behaviour disorders. The specific factors for hopelessness-suicidal ideation and generalised worrying contributed to predictive specificity. Hopelessness-suicidal ideation predicted concurrent and future affective disorder; generalised worrying predicted concurrent and future anxiety, specifically concurrent generalised anxiety disorders. Generalised worrying was negatively associated with behaviour disorders. LIMITATIONS: The analyses of gender differences and the prediction of specific disorders was limited due to a low frequency of disorders other than depression. CONCLUSIONS: The bifactor model was able to differentiate concurrent and predict future clinical diagnoses. This can inform the development of targeted as well as non-specific interventions for prevention and treatment of different disorders.

Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

Von Fuzzy-Sets zu Computing-with-Words

Dieser Artikel bietet einen Überblick über die Entwicklung und Zusammenhänge der einzelnen Elemente der Fuzzy-Logik, wovon Fuzzy-Set-Theorie die Grundlage bildet. Die Grundproblematik besteht in der Handhabung von linguistischen Informationen, die häufig durch Ungenauigkeit gekennzeichnet sind. Die verschiedenen technischen Anwendungen von Fuzzy-Logik bieten eine Möglichkeit, intelligentere Computersysteme zu konstruieren, die mit unpräzisen Informationen umgehen können. Solche Systeme sind Indizien für die Entstehung einer neuen Ära des Cognitive-Computing, di in diesemArtikel ebenfalls zur Sprache kommt. Für das bessere Verständnis wird der Artikel mit einem Beispiel aus der Meteorologie (d. h. Schnee in Adelboden) begleitet.

Granular computing as a tool of human data interaction - a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.