Rosette-forming glioneuronal tumor of the cerebellum in statu nascendi: an incidentally detected diminutive example indicates derivation from the internal granule cell layer

Rosette-forming glioneuronal tumor (RGNT) is a recently introduced, indolent neoplasm composed of diminutive circular aggregates of neurocytic-like cells on a noninfiltrative astrocytic background, typically located in the cerebellar midline The traded concept of RGNT being derived from site-specific periventricular precursors may be questioned in the face of extracerebellar examples as well as ones occurring in combination with other representatives of the glioneuronal family. We describe a hitherto not documented example of asymptomatic RGNT discovered during autopsy of a 74-year-old male. Located in the tuberal vermis, this lesion of 6 mm diameter consisted of several microscopic nests of what were felt to represent nascent stages of RGNT, all of them centered on the internal granular layer, and ranging from mucoid dehiscences thereof to fully evolved - if small - tumor foci. Molecular genetic analysis revealed a missense mutation in Exon 20 of the PIK3CA gene involving an A→G transition at Nucleotide 3140. On the other hand, neither codeletion of chromosomes 1p/19q nor pathogenic mutations of IDH1/2 were detected. By analogy with in situ paradigms in other organs, we propose that this tumor is likely to have arisen from the internal granular layer, rather than the plate of the 4th ventricle. A suggestive departure from the wholesale argument of "undifferentiated precursors", this finding also indirectly indicates that a subset of non-classical RGNTs - in particular extracerebellar examples, whose origin cannot be mechanistically accounted for by either of the above structures - may possibly reflect an instance of phenotypic convergence, rather than a lineage-restricted entity.

Derivation and validation of multimarker prognostication for normotensive patients with acute symptomatic pulmonary embolism.

RATIONALE Not all patients with acute pulmonary embolism (PE) have a high risk of an adverse short-term outcome. OBJECTIVES This prospective cohort study aimed to develop a multimarker prognostic model that accurately classifies normotensive patients with PE into low and high categories of risk of adverse medical outcomes. METHODS The study enrolled 848 outpatients from the PROTECT (PROgnosTic valuE of Computed Tomography) study (derivation cohort) and 529 patients from the Prognostic Factors for Pulmonary Embolism (PREP) study (validation cohort). Investigators assessed study participants for a 30-day complicated course, defined as death from any cause, hemodynamic collapse, and/or adjudicated recurrent PE. MEASUREMENTS AND MAIN RESULTS A complicated course occurred in 63 (7.4%) of the 848 normotensive patients with acute symptomatic PE in the derivation cohort and in 24 patients (4.5%) in the validation cohort. The final model included the simplified Pulmonary Embolism Severity Index, cardiac troponin I, brain natriuretic peptide, and lower limb ultrasound testing. The model performed similarly in the derivation (c-index of 0.75) and validation (c-index of 0.85) cohorts. The combination of the simplified Pulmonary Embolism Severity Index and brain natriuretic peptide testing showed a negative predictive value for a complicated course of 99.1 and 100% in the derivation and validation cohorts, respectively. The combination of all modalities had a positive predictive value for the prediction of a complicated course of 25.8% in the derivation cohort and 21.2% in the validation cohort. CONCLUSIONS For normotensive patients who have acute PE, we derived and validated a multimarker model that predicts all-cause mortality, hemodynamic collapse, and/or recurrent PE within the following 30 days.

The nature of syntactic impairment in autism

This paper presents a first exploration of the syntactic abilities of autistic children using the framework of truncation theory (Rizzi 1993-4, 2000). It is the first step of an ongoing research project aiming to (a) provide a complete map of syntax in autism, for such work has never been attempted from a sound linguistic perspective (b) develop a targeted remediation program to enhance syntactic abilities of autistic children. Recently, a growing body of work has emphasized the existence of a causal relation between the acquisition of complex syntax (embedding) and the development of a theory of mind (in normally-developing, deaf and autistic children). Early identification and remediation of syntactic deficits is therefore crucial not only to enhance cognitive abilites related to theory of mind, but also because of the critical period hypothesis for language acquisition.

Derivation of Change from Sequences of Snapshots

Current research in the domain of geographic information science considers possibilities of including another dimension, time, which is generally missing to this point. Users interested in changes have few functions available to compare datasets of spatial configurations at different points in time. Such a comparison of spatial configurations requires large amounts of manual labor. An automatic derivation of changes would decrease amounts of manual labor. The thesis introduces a set of methods that allows for an automatic derivation of changes. These methods analyze identity and topological states of objects in snapshots and derive types of change for the specific configuration of data. The set of change types that can be computed by the methods presented includes continuous changes such as growing, shrinking, and moving of objects. For these continuous changes identity remains unchanged, while topological relations might be altered over time. Also discrete changes such as merging and splitting where both identity and topology are affected can be derived. Evaluation of the methods using a prototype application with simple examples suggests that the methods compute uniquely and correctly the type of change that applied in spatial scenarios captured in two snapshots.

BIOMEDICAL LANGUAGE UNDERSTANDING AND EXTRACTION (BLUE-TEXT): A MINIMAL SYNTACTIC, SEMANTIC METHOD

Clinical text understanding (CTU) is of interest to health informatics because critical clinical information frequently represented as unconstrained text in electronic health records are extensively used by human experts to guide clinical practice, decision making, and to document delivery of care, but are largely unusable by information systems for queries and computations. Recent initiatives advocating for translational research call for generation of technologies that can integrate structured clinical data with unstructured data, provide a unified interface to all data, and contextualize clinical information for reuse in multidisciplinary and collaborative environment envisioned by CTSA program. This implies that technologies for the processing and interpretation of clinical text should be evaluated not only in terms of their validity and reliability in their intended environment, but also in light of their interoperability, and ability to support information integration and contextualization in a distributed and dynamic environment. This vision adds a new layer of information representation requirements that needs to be accounted for when conceptualizing implementation or acquisition of clinical text processing tools and technologies for multidisciplinary research. On the other hand, electronic health records frequently contain unconstrained clinical text with high variability in use of terms and documentation practices, and without commitmentto grammatical or syntactic structure of the language (e.g. Triage notes, physician and nurse notes, chief complaints, etc). This hinders performance of natural language processing technologies which typically rely heavily on the syntax of language and grammatical structure of the text. This document introduces our method to transform unconstrained clinical text found in electronic health information systems to a formal (computationally understandable) representation that is suitable for querying, integration, contextualization and reuse, and is resilient to the grammatical and syntactic irregularities of the clinical text. We present our design rationale, method, and results of evaluation in processing chief complaints and triage notes from 8 different emergency departments in Houston Texas. At the end, we will discuss significance of our contribution in enabling use of clinical text in a practical bio-surveillance setting.

An Economic Derivation on Trade Coefficients under the Framework of Multi-regional I-O Analysis

The gravity model, entropy model, potential type model and others like these have been adopted to formulate interregional trade coefficients under the framework of Multi-Regional I-O (MRIO) analysis. Since most of these models are based upon analogies in physics or on statistical principles, they do not provide a theoretical explanation from the view of a firm's or individual's rational and deterministic decision making. In this paper, according to the deterministic choice theory, not only is an alternative formulation of the trade coefficients presented, but also a discussion of an appropriate definition for purchasing prices indices. Since this formulation is consistent with the MRIO system, it can be employed as a useful model-building tool in multi-regional models such as the spatial CGE model.

Compile-time derivation of variable dependency using abstract interpretation

Traditional schemes for abstract interpretation-based global analysis of logic programs generally focus on obtaining procedure argument mode and type information. Variable sharing information is often given only the attention needed to preserve the correctness of the analysis. However, such sharing information can be very useful. In particular, it can be used for predicting runtime goal independence, which can eliminate costly run-time checks in and-parallel execution. In this paper, a new algorithm for doing abstract interpretation in logic programs is described which concentrates on inferring the dependencies of the terms bound to program variables with increased precisión and at all points in the execution of the program, rather than just at a procedure level. Algorithms are presented for computing abstract entry and success substitutions which extensively keep track of variable aliasing and term dependence information. In addition, a new, abstract domain independent ñxpoint algorithm is presented and described in detail. The algorithms are illustrated with examples. Finally, results from an implementation of the abstract interpreter are presented.