The role of squamous cell carcinoma antigen in the management of laryngeal and hypopharyngeal cancer

BACKGROUND: The efficacy of squamous cell carcinoma antigen (SCC-Ag) in laryngeal cancer to predict those patients who will relapse after primary treatment (surgery or radiotherapy) and its utility to detect relapses early and thereby increase salvage rates and cure were assessed. METHODS: Sixty healthy donors and 168 patients with laryngeal cancer were included in this prospective trial. Squamous cell carcinoma antigen was measured at diagnosis in all patients, 24 hours and 1 week after surgery in 113 patients and every 10 Gy of administered dose and 2 weeks after treatment in 49 patients primarily referred to radiotherapy. The marker was determined every 3-6 months during follow-up. All patients who relapsed had SCC-Ag studies before and after salvage treatment. RESULTS: The selected cut-off value was 1.5 ngr/ml (mean value in control group, 0.65 + 2 standard deviation [0.38]). Seventy-eight percent of patients with cancer had elevated SCC-Ag values at diagnosis. Squamous cell carcinoma antigen was statistically related to TNM categories (T, P < 0.04; N, P < 0.05; Stage, P < 0.01). Seventy-five percent of those patients with previously elevated pretreatment values normalized after treatment. Incomplete surgical resection (P < 0.0001) or persistence of the disease after radiotherapy (P < 0.01) were related to high posttreatment values. Squamous cell carcinoma antigen was elevated in 88% of the patients who relapsed. In 55% of the recurrences, SCC-Ag was elevated 3 months before pathologic confirmation of relapse. Salvage by surgery or radiotherapy was effective in 70% of the patients. Squamous cell carcinoma antigen posttreatment values were the most important factor in predicting disease free survival (DFS) (P < 0.0001) and overall survival (P < 0.03). CONCLUSIONS: Squamous cell carcinoma antigen is an excellent marker of residual disease after primary treatment that can lead to the addition of other therapeutic procedures (surgery and postoperative radiotherapy). The absence of posttreatment SCC-Ag is the best predictor of DFS, its presence detects recurrence in early stages, permitting salvage of an increased proportion of patients primarily referred for palliative treatment.     

Incorporating If...Then...Personality Signatures in Person Perception: Beyond the Person-Situation Dichotomy.

Three studies investigated conditions in which perceivers view dispositions and situations as interactive, rather than independent, causal forces when making judgments about another's personality. Study 1 showed that perceivers associated 5 common trait terms (e.g., friendly and shy) with characteristic if...then... (if situation a, then the person does x, but if situation b, then the person does y) personality signatures. Study 2 demonstrated that perceivers used information about a target's stable if...then... signature to infer the target's motives and traits; dispositional judgments were mediated by inferences about the target's motivations. Study 3 tested whether perceivers draw on if...then... signatures when making judgments about Big Five trait dimensions. Together, the findings indicate that perceivers take account of person-situation interactions (reflected in if...then... signatures) in everyday explanations of social behavior and personality dispositions. Boundary conditions are also discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Target Score—A Proteomics Data Selection Tool Applied to Esophageal Cancer Identifies GLUT1-Sialyl Tn Glycoforms as Biomarkers of Cancer Aggressiveness

Esophageal cancer (EC) is a life-threatening disease, demanding the discovery of new biomarkers and molecular targets for precision oncology. Aberrantly glycosylated proteins hold tremendous potential towards this objective. In the current study, a series of esophageal squamous cell carcinomas (ESCC) and EC-derived circulating tumor cells (CTCs) were screened by immunoassays for the sialyl-Tn (STn) antigen, a glycan rarely expressed in healthy tissues and widely observed in aggressive gastrointestinal cancers. An ESCC cell model was glycoengineered to express STn and characterized in relation to cell proliferation and invasion in vitro. STn was found to be widely present in ESCC (70% of tumors) and in CTCs in 20% of patients, being associated with general recurrence and reduced survival. Furthermore, STn expression in ESCC cells increased invasion in vitro, while reducing cancer cells proliferation. In parallel, an ESCC mass spectrometry-based proteomics dataset, obtained from the PRIDE database, was comprehensively interrogated for abnormally glycosylated proteins. Data integration with the Target Score, an algorithm developed in-house, pinpointed the glucose transporter type 1 (GLUT1) as a biomarker of poor prognosis. GLUT1-STn glycoproteoforms were latter identified in tumor tissues in patients facing worst prognosis. Furthermore, healthy human tissues analysis suggested that STn glycosylation provided cancer specificity to GLUT1. In conclusion, STn is a biomarker of worst prognosis in EC and GLUT1-STn glycoforms may be used to increase its specificity on the stratification and targeting of aggressive ESCC forms.     

Domain-specific discrete event modelling and simulation using graph transformation

Graph transformation is being increasingly used to express the semantics of domain-specific visual languages since its graphical nature makes rules intuitive. However, many application domains require an explicit handling of time to accurately represent the behaviour of a real system and to obtain useful simulation metrics to measure throughputs, utilization times and average delays. Inspired by the vast knowledge and experience accumulated by the discrete event simulation community, we propose a novel way of adding explicit time to graph transformation rules. In particular, we take the event scheduling discrete simulation world view and provide rules with the ability to schedule the occurrence of other rules in the future. Hence, our work combines standard, efficient techniques for discrete event simulation (based on the handling of a future event set) and the intuitive, visual nature of graph transformation. Moreover, we show how our formalism can be used to give semantics to other timed approaches and provide an implementation on top of the rewriting logic system Maude.     

Smooth Loops from Unconstrained Video

Converting unconstrained video sequences into videos that loop seamlessly is an extremely challenging problem. In this work, we take the first steps towards automating this process by focusing on an important subclass of videos containing a single dominant foreground object. Our technique makes two novel contributions over previous work: first, we propose a correspondence‐based similarity metric to automatically identify a good transition point in the video where the appearance and dynamics of the foreground are most consistent. Second, we develop a technique that aligns both the foreground and background about this transition point using a combination of global camera path planning and patch‐based video morphing. We demonstrate that this allows us to create natural, compelling, loopy videos from a wide range of videos collected from the internet.     

Modeling collaboration protocols for collaborative modeling tools: Experiences and applications

Over the last two decades, Collaborative Systems have become increasingly popular thanks to the many advances made in networks, communications and software tools. Within this field, Collaborative Modeling Systems apply the collaborative paradigm to the construction of (often visual) models, where users build diagrams from building blocks and the relationships between them. In these kinds of applications, the work is usually arranged into sessions, with the definition of some kind of time organization between those sessions. This organization is known as a collaboration protocol. Unfortunately, it is not usually easy to define these protocols, and many applications do not allow users to make any use of them.In an effort to overcome these difficulties, in this paper we propose a visual language for defining collaboration protocols for these systems. As such, in our language, sessions, artifacts and the transformations between them can be specified visually, and different coordination relationships (such as fork and join) can be defined. The visual language is included in a development method for collaborative systems that take advantage of the Eclipse platform in order to develop model-driven graphical editors that are enhanced with collaboration capabilities.     

A UML/OCL framework for the analysis of graph transformation rules

In this paper we present an approach for the analysis of graph transformation rules based on an intermediate OCL representation. We translate different rule semantics into OCL, together with the properties of interest (like rule applicability, conflicts or independence). The intermediate representation serves three purposes: (1) it allows the seamless integration of graph transformation rules with the MOF and OCL standards, and enables taking the meta-model and its OCL constraints (i.e. well-formedness rules) into account when verifying the correctness of the rules; (2) it permits the interoperability of graph transformation concepts with a number of standards-based model-driven development tools; and (3) it makes available a plethora of OCL tools to actually perform the rule analysis. This approach is especially useful to analyse the operational semantics of Domain Specific Visual Languages. We have automated these ideas by providing designers with tools for the graphical specification and analysis of graph transformation rules, including a back-annotation mechanism that presents the analysis results in terms of the original language notation.     

Two-space variability compensation technique for speaker verification in short length and reverberant environments

The performance of state-of-the-art speaker verification in uncontrolled environment is affected by different variabilities. Short duration variability is very common in these scenarios and causes the speaker verification performance to decrease quickly while the duration of verification utterances decreases. Linear discriminant analysis (LDA) is the most common session variability compensation algorithm, nevertheless it presents some shortcomings when trained with insufficient data. In this paper we introduce two methods for session variability compensation to deal with short-length utterances on i-vector space. The first method proposes to incorporate the short duration variability information in the within-class variance estimation process. The second proposes to compensate the session and short duration variabilities in two different spaces with LDA algorithms (2S-LDA). First, we analyzed the behavior of the within and between class scatters in the first proposed method. Then, both proposed methods are evaluated on telephone session from NIST SRE-08 for different duration of the evaluation utterances: full (average 2.5 min), 20, 15, 10 and 5 s. The 2S-LDA method obtains good results on different short-length utterances conditions in the evaluations, with a EER relative average improvement of 1.58%, compared to the best baseline (WCCN[LDA]). Finally, we applied the 2S-LDA method in speaker verification under reverberant environment, using different reverberant conditions from Reverb challenge 2013, obtaining an improvement of 8.96 and 23% under matched and mismatched reverberant conditions, respectively.     

Visual specification of measurements and redesigns for domain specific visual languages

Ensuring model quality is a key success factor in many computer science areas, and becomes crucial in recent software engineering paradigms like the one proposed by model-driven software development. Tool support for measurements and redesigns becomes essential to help developers improve the quality of their models. However, developing such helper tools for the wide variety of (frequently domain specific) visual notations used by software engineers is a hard and repetitive task that does not take advantage from previous developments, thus being frequently forgotten.In this paper we present our approach for the visual specification of measurements and redesigns for Domain Specific Visual Languages (DSVLs). With this purpose, we introduce a novel DSVL called SLAMMER that contains generalisations of some of the more used types of internal product measurements and redesigns. The goal is to facilitate the task of defining measurements and redesigns for any DSVL, as well as the generation of tools from such specification reducing or eliminating the necessity of coding. We rely on the use of visual patterns for the specification of the relevant elements for each measurement and redesign type. In addition, SLAMMER allows the specification of redesigns either procedurally or by means of graph transformation rules. These redesigns can be triggered when the measurements reach a certain threshold.These concepts have been implemented in the meta-modelling tool AToM³. In this way, when a DSVL is designed, it is possible to specify measurements and redesigns that will become available in the final modelling environment generated for the language. As an example, we show a case study in the web modelling domain.