The Degradome database: mammalian proteases and diseases of proteolysis

The degradome is defined as the complete set of proteases present in an organism. The recent availability of whole genomic sequences from multiple organisms has led us to predict the contents of the degradomes of several mammalian species. To ensure the fidelity of these predictions, our methods have included manual curation of individual sequences and, when necessary, direct cloning and sequencing experiments. The results of these studies in human, chimpanzee, mouse and rat have been incorporated into the Degradome database, which can be accessed through a web interface at http://degradome.uniovi.es. The annotations about each individual protease can be retrieved by browsing catalytic classes and families or by searching specific terms. This web site also provides detailed information about genetic diseases of proteolysis, a growing field of great importance for multiple users. Finally, the user can find additional information about protease structures, protease inhibitors, ancillary domains of proteases and differences between mammalian degradomes

Early and late morbidity and mortality and life expectancy following thoracoscopic talc insufflation for control of malignant pleural effusions: a review of 400 cases

<p>Abstract</p> <p>Background</p> <p>Malignant pleural effusion is a common sequelae in patients with certain malignancies. It represents a terminal condition with short median survival (in terms of months) and the goal is palliation. Aim of our study is to analyze morbidity, mortality and life expectancy following videothoracoscopic talc poudrage.</p> <p>Materials and methods</p> <p>From September 2004 to October 2009, 400 patients underwent video-assisted thoracic surgery (VATS) for malignant pleural effusion. The conditions of patients were assessed and graded before and after treatment concerning morbidity, mortality, success rate of pleurodesis and median survival.</p> <p>Results</p> <p>The median duration of follow up was 40 months (range 4-61 months). All patients demonstrated notable improvement in dyspnea. Intraoperative mortality was zero. The procedure was well tolerated and no significant adverse effects were observed. In hospital mortality was 2% and the pleurodesis success rate was 85%. A poor Karnofsky Performance Status and delay between diagnosis of pleural effusion and pleurodesis were statistically significant factors for in-hospital mortality. The best survival was seen in breast cancer, followed by ovarian cancer, lymphoma and pleural mesothelioma.</p> <p>Conclusions</p> <p>Video-assisted thoracoscopic talc poudrage is an effective and safe procedure that yields a high rate of successful pleurodesis and achieves long-term control with marked dyspnea decrease.</p

Frequent COL4 mutations in familial microhematuria accompanied by later-onset Alport nephropathy due to focal segmental glomerulosclerosis

Familial microscopic hematuria (FMH) is associated with a genetically heterogeneous group of conditions including the collagen-IV nephropathies, the heritable C3/CFHR5 nephropathy and the glomerulopathy with fibronectin deposits. The clinical course varies widely, ranging from isolated benign familial hematuria to end-stage renal disease (ESRD) later in life. We investigated 24 families using Next Generation Sequencing (NGS) for five genes: COL4A3, COL4A4, COL4A5, CFHR5 and FN1. In 17 families (71%), we found 15 pathogenic mutations in COL4A3/A4/A5, nine of them novel. In five families patients inherited classical AS with hemizygous X-linked COL4A5 mutations. Even more patients developed later-onset Alport-related nephropathy having inherited heterozygous COL4A3/A4 mutations that cause thin basement membranes. Amongst 62 heterozygous or hemizygous patients, eight (13%) reached ESRD, while 25% of patients with heterozygous COL4A3/A4 mutations, aged >50-yrs, reached ESRD. In conclusion, COL4A mutations comprise a frequent cause of FMH. Heterozygous COL4A3/A4 mutations predispose to renal function impairment, supporting that thin basement membrane nephropathy is not always benign. The molecular diagnosis is essential for differentiating the X-linked from the autosomal recessive and dominant inheritance. Finally, NGS technology is established as the gold standard for the diagnosis of FMH and associated collagen-IV glomerulopathies, frequently averting the need for invasive renal biopsies

Kallikrein-related peptidase 6 regulates epithelial-to-mesenchymal transition and serves as prognostic biomarker for head and neck squamous cell carcinoma patients

Background: Dysregulated expression of Kallikrein-related peptidase 6 (KLK6) is a common feature for many human malignancies and numerous studies evaluated KLK6 as a promising biomarker for early diagnosis or unfavorable prognosis. However, the expression of KLK6 in carcinomas derived from mucosal epithelia, including head and neck squamous cell carcinoma (HNSCC), and its mode of action has not been addressed so far. Methods: Stable clones of human mucosal tumor cell lines were generated with shRNA-mediated silencing or ectopic overexpression to characterize the impact of KLK6 on tumor relevant processes in vitro. Tissue microarrays with primary HNSCC samples from a retrospective patient cohort (n = 162) were stained by immunohistochemistry and the correlation between KLK6 staining and survival was addressed by univariate Kaplan-Meier and multivariate Cox proportional hazard model analysis. Results: KLK6 expression was detected in head and neck tumor cell lines (FaDu, Cal27 and SCC25), but not in HeLa cervix carcinoma cells. Silencing in FaDu cells and ectopic expression in HeLa cells unraveled an inhibitory function of KLK6 on tumor cell proliferation and mobility. FaDu clones with silenced KLK6 expression displayed molecular features resembling epithelial-to-mesenchymal transition, nuclear β-catenin accumulation and higher resistance against irradiation. Low KLK6 protein expression in primary tumors from oropharyngeal and laryngeal SCC patients was significantly correlated with poor progression-free (p = 0.001) and overall survival (p < 0.0005), and served as an independent risk factor for unfavorable clinical outcome. Conclusions: In summary, detection of low KLK6 expression in primary tumors represents a promising tool to stratify HNSCC patients with high risk for treatment failure. These patients might benefit from restoration of KLK6 expression or pharmacological targeting of signaling pathways implicated in EMT

Event recognition for unobtrusive assisted living

Developing intelligent systems towards automated clinical monitoring and assistance for the elderly is attracting growing attention. USEFIL is an FP7 project aiming to provide health-care assistance in a smart-home setting. We present the data fusion component of USEFIL which is based on a complex event recognition methodology. In particular, we present our knowledge-driven approach to the detection of Activities of Daily Living (ADL) and functional ability, based on a probabilistic version of the Event Calculus. To investigate the feasibility of our approach, we present an empirical evaluation on synthetic data. © 2014 Springer International Publishing

Incremental learning of event definitions with Inductive Logic Programming

Event recognition systems rely on knowledge bases of event definitions to infer occurrences of events in time. Using a logical framework for representing and reasoning about events offers direct connections to machine learning, via Inductive Logic Programming (ILP), thus allowing to avoid the tedious and error-prone task of manual knowledge construction. However, learning temporal logical formalisms, which are typically utilized by logic-based event recognition systems is a challenging task, which most ILP systems cannot fully undertake. In addition, event-based data is usually massive and collected at different times and under various circumstances. Ideally, systems that learn from temporal data should be able to operate in an incremental mode, that is, revise prior constructed knowledge in the face of new evidence. In this work we present an incremental method for learning and revising event-based knowledge, in the form of Event Calculus programs. The proposed algorithm relies on abductive–inductive learning and comprises a scalable clause refinement methodology, based on a compressive summarization of clause coverage in a stream of examples. We present an empirical evaluation of our approach on real and synthetic data from activity recognition and city transport applications. © 2015, The Author(s)

Online learning of weighted relational rules for complex event recognition

Systems for symbolic complex event recognition detect occurrences of events in time using a set of event definitions in the form of logical rules. The Event Calculus is a temporal logic that has been used as a basis in event recognition applications, providing among others, connections to techniques for learning such rules from data. We advance the state-of-the-art by combining an existing online algorithm for learning crisp relational structure with an online method for weight learning in Markov Logic Networks (MLN). The result is an algorithm that learns complex event patterns in the form of Event Calculus theories in the MLN semantics. We evaluate our approach on a challenging real-world application for activity recognition and show that it outperforms both its crisp predecessor and competing online MLN learners in terms of predictive performance, at the price of a small increase in training time. Code related to this paper is available at: https://github.com/nkatzz/OLED. © 2019, Springer Nature Switzerland AG