MoDeST: a compositional modeling formalism for hard and softly timed systems

This paper presents Modest (MOdeling and DEscription language for Stochastic Timed systems), a formalism that is aimed to support (i) the modular description of reactive system's behaviour while covering both (ii) functional and (iii) nonfunctional system aspects such as timing and quality-of-service constraints in a single specification. The language contains features such as simple and structured data types, structuring mechanisms like parallel composition and abstraction, means to control the granularity of assignments, exception handling, and non-deterministic and random branching and timing. Modest can be viewed as an overarching notation for a wide spectrum of models, ranging from labeled transition systems, to timed automata (and probabilistic variants thereof) as well as prominent stochastic processes such as (generalized semi-)Markov chains and decision processes. The paper describes the design rationales and details of the syntax and semantics

Efficient CSL Model Checking Using Stratification

For continuous-time Markov chains, the model-checking problem with respect to continuous-time stochastic logic (CSL) has been introduced and shown to be decidable by Aziz, Sanwal, Singhal and Brayton in 1996. Their proof can be turned into an approximation algorithm with worse than exponential complexity. In 2000, Baier, Haverkort, Hermanns and Katoen presented an efficient polynomial-time approximation algorithm for the sublogic in which only binary until is allowed. In this paper, we propose such an efficient polynomial-time approximation algorithm for full CSL. The key to our method is the notion of stratified CTMCs with respect to the CSL property to be checked. On a stratified CTMC, the probability to satisfy a CSL path formula can be approximated by a transient analysis in polynomial time (using uniformization). We present a measure-preserving, linear-time and -space transformation of any CTMC into an equivalent, stratified one. This makes the present work the centerpiece of a broadly applicable full CSL model checker. Recently, the decision algorithm by Aziz et al. was shown to work only for stratified CTMCs. As an additional contribution, our measure-preserving transformation can be used to ensure the decidability for general CTMCs.Comment: 18 pages, preprint for LMCS. An extended abstract appeared in ICALP 201

Probabilistic Reachability for Parametric Markov Models

Abstract. Given a parametric Markov model, we consider the problem of computing the formula expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression is computed. Afterwards, this expression is evaluated to a closed form expression representing the reachability probability. This paper investigates how this idea can be turned into an effective procedure. It turns out that the bottleneck lies in an exponential growth of the regular expression relative to the number of states. We therefore proceed differently, by tightly intertwining the regular expression computation with its evaluation. This allows us to arrive at an effective method that avoids the exponential blow up in most practical cases. We give a detailed account of the approach, also extending to parametric models with rewards and with non-determinism. Experimental evidence is provided, illustrating that our implementation provides meaningful insights on non-trivial models.

Probabilistic Model-Based Safety Analysis

Model-based safety analysis approaches aim at finding critical failure combinations by analysis of models of the whole system (i.e. software, hardware, failure modes and environment). The advantage of these methods compared to traditional approaches is that the analysis of the whole system gives more precise results. Only few model-based approaches have been applied to answer quantitative questions in safety analysis, often limited to analysis of specific failure propagation models, limited types of failure modes or without system dynamics and behavior, as direct quantitative analysis is uses large amounts of computing resources. New achievements in the domain of (probabilistic) model-checking now allow for overcoming this problem. This paper shows how functional models based on synchronous parallel semantics, which can be used for system design, implementation and qualitative safety analysis, can be directly re-used for (model-based) quantitative safety analysis. Accurate modeling of different types of probabilistic failure occurrence is shown as well as accurate interpretation of the results of the analysis. This allows for reliable and expressive assessment of the safety of a system in early design stages

MAGE-C2/CT10 Protein Expression Is an Independent Predictor of Recurrence in Prostate Cancer

The cancer-testis (CT) family of antigens is expressed in a variety of malignant neoplasms. In most cases, no CT antigen is found in normal tissues, except in testis, making them ideal targets for cancer immunotherapy. A comprehensive analysis of CT antigen expression has not yet been reported in prostate cancer. MAGE-C2/CT-10 is a novel CT antigen. The objective of this study was to analyze extent and prognostic significance of MAGE-C2/CT10 protein expression in prostate cancer. 348 prostate carcinomas from consecutive radical prostatectomies, 29 castration-refractory prostate cancer, 46 metastases, and 45 benign hyperplasias were immunohistochemically analyzed for MAGE-C2/CT10 expression using tissue microarrays. Nuclear MAGE-C2/CT10 expression was identified in only 3.3% primary prostate carcinomas. MAGE-C2/CT10 protein expression was significantly more frequent in metastatic (16.3% positivity) and castration-resistant prostate cancer (17% positivity; p<0.001). Nuclear MAGE-C2/CT10 expression was identified as predictor of biochemical recurrence after radical prostatectomy (p = 0.015), which was independent of preoperative PSA, Gleason score, tumor stage, and surgical margin status in multivariate analysis (p<0.05). MAGE-C2/CT10 expression in prostate cancer correlates with the degree of malignancy and indicates a higher risk for biochemical recurrence after radical prostatectomy. Further, the results suggest MAGE-C2/CT10 as a potential target for adjuvant and palliative immunotherapy in patients with prostate cancer

Periostin is up-regulated in high grade and high stage prostate cancer

BACKGROUND: Expression of periostin is an indicator of epithelial-mesenchymal transition in cancer but a detailed analysis of periostin expression in prostate cancer has not been conducted so far. METHODS: Here, we evaluated periostin expression in prostate cancer cells and peritumoural stroma immunohistochemically in two independent prostate cancer cohorts, including a training cohort (n = 93) and a test cohort (n = 325). Metastatic prostate cancers (n = 20), hormone refractory prostate cancers (n = 19) and benign prostatic tissues (n = 38) were also analyzed. RESULTS: In total, strong epithelial periostin expression was detectable in 142 of 418 (34.0%) of prostate carcinomas and in 11 of 38 benign prostate glands (28.9%). Increased periostin expression in carcinoma cells was significantly associated with high Gleason score (p < 0.01) and advanced tumour stage (p < 0.05) in the test cohort. Whereas periostin expression was weak or absent in the stroma around normal prostate glands, strong periostin expression in tumour stroma was found in most primary and metastatic prostate cancers. High stromal periostin expression was associated with higher Gleason scores (p < 0.001). There was a relationship between stromal periostin expression and shortened PSA relapse free survival times in the training cohort (p < 0.05). CONCLUSIONS: Our data indicate that periostin up-regulation is related to increased tumour aggressiveness in prostate cancer and might be a promising target for therapeutical interventions in primary and metastatic prostate cancer

Clinical and virological characteristics of hospitalised COVID-19 patients in a German tertiary care centre during the first wave of the SARS-CoV-2 pandemic: a prospective observational study

Purpose: Adequate patient allocation is pivotal for optimal resource management in strained healthcare systems, and requires detailed knowledge of clinical and virological disease trajectories. The purpose of this work was to identify risk factors associated with need for invasive mechanical ventilation (IMV), to analyse viral kinetics in patients with and without IMV and to provide a comprehensive description of clinical course. Methods: A cohort of 168 hospitalised adult COVID-19 patients enrolled in a prospective observational study at a large European tertiary care centre was analysed. Results: Forty-four per cent (71/161) of patients required invasive mechanical ventilation (IMV). Shorter duration of symptoms before admission (aOR 1.22 per day less, 95% CI 1.10-1.37, p < 0.01) and history of hypertension (aOR 5.55, 95% CI 2.00-16.82, p < 0.01) were associated with need for IMV. Patients on IMV had higher maximal concentrations, slower decline rates, and longer shedding of SARS-CoV-2 than non-IMV patients (33 days, IQR 26-46.75, vs 18 days, IQR 16-46.75, respectively, p < 0.01). Median duration of hospitalisation was 9 days (IQR 6-15.5) for non-IMV and 49.5 days (IQR 36.8-82.5) for IMV patients. Conclusions: Our results indicate a short duration of symptoms before admission as a risk factor for severe disease that merits further investigation and different viral load kinetics in severely affected patients. Median duration of hospitalisation of IMV patients was longer than described for acute respiratory distress syndrome unrelated to COVID-19

TE

When a process is capable of executing an unbounded number of non-observable actions it is said to be divergent. Different capabilities of an observer to identify this phenomen along the execution leads to different divergent sensitive semantics. This paper develops sound and complete axiomatisations for the divergence sensitive spectrum of weak bisimulation equivalence. The axiomatisations separates the axioms concerning recursion and those that capture the essence of diverging behaviour