Multifocal Renal Cell Carcinoma: Clinicopathologic Features and Outcomes for Tumors ≤4 cm

A significant increase in the incidental detection of small renal tumors has been observed with the routine use of cross-sectional abdominal imaging. However, the proportion of small renal tumors associated with multifocal RCC has yet to be established. Here then, we report our experience with the treatment of multifocal RCC in which the primary tumor was ≤4 cm. In our series of 1113 RCC patients, 5.4% (60/1113) had multifocal disease at the time of nephrectomy. Discordant histology was present in 17% (10/60) of patients with multifocal RCC. Nephron sparing surgery was utilized more frequently in patients with solitary tumors. Overall, cancer-specific, and distant metastasis-free survival appeared to be similar between multifocal and solitary tumors. These findings are consistent with previous series which evaluated multifocal RCC with tumors >4 cm. With the known incidence of multifocality RCC, careful inspection of the entire renal unit should be performed when performing nephron sparing surgery

Simulating causal collapse models

We present simulations of causal dynamical collapse models of field theories on a 1+1 null lattice. We use our simulations to compare and contrast two possible interpretations of the models, one in which the field values are real and the other in which the state vector is real. We suggest that a procedure of coarse graining and renormalising the fundamental field can overcome its noisiness and argue that this coarse grained renormalised field will show interesting structure if the state vector does on the coarse grained scale.Comment: 18 pages, 8 fugures, LaTeX, Reference added, discussion of probability distribution of labellings correcte

On Linear Information Systems

Scott's information systems provide a categorically equivalent, intensional description of Scott domains and continuous functions. Following a well established pattern in denotational semantics, we define a linear version of information systems, providing a model of intuitionistic linear logic (a new-Seely category), with a "set-theoretic" interpretation of exponentials that recovers Scott continuous functions via the co-Kleisli construction. From a domain theoretic point of view, linear information systems are equivalent to prime algebraic Scott domains, which in turn generalize prime algebraic lattices, already known to provide a model of classical linear logic

Predictive Nomogram for Recurrence following Surgery for Nonmetastatic Renal Cell Cancer with Tumor Thrombus

Purpose Following surgery for nonmetastatic renal cell carcinoma with tumor thrombus the risk of recurrence is significant but variable among patients. The purpose of this study was to develop and validate a predictive nomogram for individual estimation of recurrence risk following surgery for renal cell carcinoma with venous tumor thrombus. Materials and Methods Comprehensive data were collected on patients with nonmetastatic renal cell carcinoma and thrombus treated at a total of 5 institutions from 2000 to 2013. Independent predictors of recurrent renal cell carcinoma from a competing risks analysis were developed into a nomogram. Predictive accuracy was compared between the development and validation cohorts, and between the nomogram and the UISS (UCLA Integrated Staging System, SSIGN (Stage, Size, Grade and Necrosis) and Sorbellini models. Results A total of 636 patients were analyzed, including the development cohort of 465 and the validation cohort of 171. Independent predictors, including tumor diameter, body mass index, preoperative hemoglobin less than the lower limit of normal, thrombus level, perinephric fat invasion and nonclear cell histology, were developed into a nomogram. Estimated 5-year recurrence-free survival was 49% overall. Five-year recurrence-free survival in patients with 0, 1, 2 and more than 2 risk factors was 77%, 53%, 47% and 20%, respectively. Predictive accuracy was similar in the development and validation cohorts (AUC 0.726 and 0.724, respectively). Predictive accuracy of the thrombus nomogram was higher than that of the UISS (AUC 0.726 vs 0.595, p = 0.001), SSIGN (AUC 0.713 vs 0.612, p = 0.04) and Sorbellini models (AUC 0.709 vs 0.638, p = 0.02). Conclusions We present a predictive nomogram for postoperative recurrence in patients with nonmetastatic renal cell carcinoma with venous thrombus. Improving individual postoperative risk assessment may allow for better design and analysis of future adjuvant clinical trials

Prognostic relevance of number and bilaterality of positive surgical margins after radical prostatectomy

Item does not contain fulltextPURPOSE: Positive surgical margin (PSM) status following radical prostatectomy (RP) is a well-established prognostic factor. The aim of the present study is to evaluate whether number of PSMs or bilaterality of PSMs might have prognostic significance for biochemical recurrence (BCR) in the population with a PSM status following RP. METHODS: We evaluated 1,395 RP pathology reports from our center between 1980 and 2006. All patients who underwent (neo)-adjuvant therapy were excluded, leaving a cohort of 1,009 patients, with 249 (24.7%) subjects having a PSM at RP of whom 29.4% had multiple PSMs (>/= 2 sites), while 13.6% had bilateral PSMs. Median follow-up was 40 months (range 0-258 months). We used BCR-free survival as the primary study outcome. BCR was defined as any rise in PSA above or equal to 0.2 ng/ml. RESULTS: Of patients with a PSM status, 41% (95% CI: 33-49%) developed BCR within 5 years, compared to 12% (95% CI: 9-15%) in the population without a PSM. Multivariable analysis identified PSA at diagnosis and RP Gleason score as independent predictive factors for BCR. Increasing number and/or bilaterality of PSM did not lead to significant higher rates of BCR. CONCLUSION: In patients with a PSM, the number of positive sites or bilaterality of PSM status does not add prognostic information for risk of BCR. Survival curve slopes were different for patients with bilateral PSM, showing a significant tendency to progress to BCR earlier during follow-up than patients with unilateral PSM.1 februari 201

Infinets: The parallel syntax for non-wellfounded proof-theory

Logics based on the µ-calculus are used to model induc-tive and coinductive reasoning and to verify reactive systems. A well-structured proof-theory is needed in order to apply such logics to the study of programming languages with (co)inductive data types and automated (co)inductive theorem proving. While traditional proof system suffers some defects, non-wellfounded (or infinitary) and circular proofs have been recognized as a valuable alternative, and significant progress have been made in this direction in recent years. Such proofs are non-wellfounded sequent derivations together with a global validity condition expressed in terms of progressing threads. The present paper investigates a discrepancy found in such proof systems , between the sequential nature of sequent proofs and the parallel structure of threads: various proof attempts may have the exact threading structure while differing in the order of inference rules applications. The paper introduces infinets, that are proof-nets for non-wellfounded proofs in the setting of multiplicative linear logic with least and greatest fixed-points (µMLL ∞) and study their correctness and sequentialization. Inductive and coinductive reasoning is pervasive in computer science to specify and reason about infinite data as well as reactive properties. Developing appropriate proof systems amenable to automated reasoning over (co)inductive statements is therefore important for designing programs as well as for analyzing computational systems. Various logical settings have been introduced to reason about such inductive and coinductive statements, both at the level of the logical languages modelling (co)induction (such as Martin Löf's inductive predicates or fixed-point logics, also known as µ-calculi) and at the level of the proof-theoretical framework considered (finite proofs with explicit (co)induction rulesà la Park [23] or infinite, non-wellfounded proofs with fixed-point unfold-ings) [6-8, 4, 1, 2]. Moreover, such proof systems have been considered over classical logic [6, 8], intuitionistic logic [9], linear-time or branching-time temporal logic [19, 18, 25, 26, 13-15] or linear logic [24, 16, 4, 3, 14]

Causal categories: relativistically interacting processes

A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a `causal category'. We provide methods of constructing causal categories, and we study the consequences of these methods for the general framework of categorical quantum mechanics.Comment: 43 pages, lots of figure

Physics, Topology, Logic and Computation: A Rosetta Stone

In physics, Feynman diagrams are used to reason about quantum processes. In the 1980s, it became clear that underlying these diagrams is a powerful analogy between quantum physics and topology: namely, a linear operator behaves very much like a "cobordism". Similar diagrams can be used to reason about logic, where they represent proofs, and computation, where they represent programs. With the rise of interest in quantum cryptography and quantum computation, it became clear that there is extensive network of analogies between physics, topology, logic and computation. In this expository paper, we make some of these analogies precise using the concept of "closed symmetric monoidal category". We assume no prior knowledge of category theory, proof theory or computer science.Comment: 73 pages, 8 encapsulated postscript figure

Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions

Prediction of pathological stage in patients with prostate cancer: a neuro-fuzzy model

The prediction of cancer staging in prostate cancer is a process for estimating the likelihood that the cancer has spread before treatment is given to the patient. Although important for determining the most suitable treatment and optimal management strategy for patients, staging continues to present significant challenges to clinicians. Clinical test results such as the pre-treatment Prostate-Specific Antigen (PSA) level, the biopsy most common tumor pattern (Primary Gleason pattern) and the second most common tumor pattern (Secondary Gleason pattern) in tissue biopsies, and the clinical T stage can be used by clinicians to predict the pathological stage of cancer. However, not every patient will return abnormal results in all tests. This significantly influences the capacity to effectively predict the stage of prostate cancer. Herein we have developed a neuro-fuzzy computational intelligence model for classifying and predicting the likelihood of a patient having Organ-Confined Disease (OCD) or Extra-Prostatic Disease (ED) using a prostate cancer patient dataset obtained from The Cancer Genome Atlas (TCGA) Research Network. The system input consisted of the following variables: Primary and Secondary Gleason biopsy patterns, PSA levels, age at diagnosis, and clinical T stage. The performance of the neuro-fuzzy system was compared to other computational intelligence based approaches, namely the Artificial Neural Network, Fuzzy C-Means, Support Vector Machine, the Naive Bayes classifiers, and also the AJCC pTNM Staging Nomogram which is commonly used by clinicians. A comparison of the optimal Receiver Operating Characteristic (ROC) points that were identified using these approaches, revealed that the neuro-fuzzy system, at its optimal point, returns the largest Area Under the ROC Curve (AUC), with a low number of false positives (FPR = 0.274, TPR = 0.789, AUC = 0.812). The proposed approach is also an improvement over the AJCC pTNM Staging Nomogram (FPR = 0.032, TPR = 0.197, AUC = 0.582)