Primary CNS lymphoma with intravitreal metastasis : using vitreous cavity samples to monitor response to therapy

A fifty-eight year old male patient presented to the ophthalmic department with a 3 day history of reduced visual acuity, blurred vision and floaters, associated with recent lethargy, headaches and behavioural changes. Fundal examination revealed a bilateral vitritis. Steroid therapy was started. MRI of the brain revealed multiple hypodense and hyperdense lesions. Vitrectomy was performed in view of the poor response to steroids. A biopsy showed non-hodgkin B-Cell lymphoma. The patient was started on intravenous Methotrexate and Cytarabine. Repeat vitreous cavity biopsies were performed in order to assess response to therapy. All biopsies to date have revealed evidence of on-going lymphoma.peer-reviewe

Bivariant long exact sequences II

Given a pair of short exact sequences 1) 0 → X → Y → Z → 0, 0 → A → B → C → 0 in an abelian category A, with sufficiently many projectives and injectives, and given an additive bifunctor T we show that T applied to the pair (1) gives rise to a diagram of a type described by C. T. C. Wall that contains 15 interlocking long exact sequences involving the derived functors of T at (A, X), (A, Y), etc. and also involving the derived functors of Tp and Tq which are two functors with domain A2 that arise through the failure of T to preserve pullbacks and pushouts. In the case of Hom (respectively ø) in the category of G-modules for a group G the derived functors of Tp (respectively Tq) are expressed in terms of group cohomology (respectively homology)

The two-square lemma

A new proof is given of the connecting homomorphism

MAP Estimation for Hyperspectral Image Resolution Enhancement Using an Auxiliary Sensor

This paper presents a novel maximum a posteriori (MAP) estimator for enhancing the spatial resolution of an image using co-registered high spatial-resolution imagery from an auxiliary sensor. Here we focus on the use of high-resolution panchomatic data to enhance hyperspectral imagery. However, the estimation framework developed allows for any number of spectral bands in the primary and auxiliary image. The proposed technique is suitable for applications where some correlation, either localized or global, exists between the auxiliary image and the image being enhanced. To exploit localized correlations, a spatially varying statistical model, based on vector quantization, is used. Another important aspect of the proposed algorithm is that it allows for the use of an accurate observation model relating the “true” scene with the low-resolutions observations. Experimental results with hyperspectral data derived from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) are presented to demonstrate the efficacy of the proposed estimator

Bayesian Inference for the Negative Binomial Distribution via Polynomial Expansions

To date, Bayesian inferences for the negative binomial distribution (NBD) have relied on computationally intensive numerical methods (e.g., Markov chain Monte Carlo) as it is thought that the posterior densities of interest are not amenable to closed-form integration. In this article, we present a “closed-form” solution to the Bayesian inference problem for the NBD that can be written as a sum of polynomial terms. The key insight is to approximate the ratio of two gamma functions using a polynomial expansion, which then allows for the use of a conjugate prior. Given this approximation, we arrive at closed-form expressions for the moments of both the marginal posterior densities and the predictive distribution by integrating the terms of the polynomial expansion in turn (now feasible due to conjugacy). We demonstrate via a large-scale simulation that this approach is very accurate and that the corresponding gains in computing time are quite substantial. Furthermore, even in cases where the computing gains are more modest our approach provides a method for obtaining starting values for other algorithms, and a method for data exploration

Anomaly Detection in Hyperspectral Imagery: Comparison of Methods Using Diurnal and Seasonal Data

The use of hyperspectral imaging is a fast growing field with many applications in the civilian, commercial and military sectors. Hyperspectral images are typically composed of many spectral bands in the visible and infrared regions of the electromagnetic spectrum and have the potential to deliver a great deal of information about a remotely sensed scene. One area of interest regarding hyperspectral images is anomaly detection, or the ability to find spectral outliers within a complex background in a scene with no a priori information about the scene or its specific contents. Anomaly detectors typically operate by creating a statistical background model of a hyperspectral image and measuring anomalies as image pixels that do not conform properly to that given model. In this study we compare the performance over diurnal and seasonal changes for several different anomaly detection methods found in the literature and a new anomaly detector that we refer to as the fuzzy cluster-based anomaly detector. Here we also compare the performance of several anomaly-based change detection algorithms. Our results indicate that all anomaly detectors tested in this experimentation exhibit strong performance under optimum illumination and environmental conditions. However, our results point toward a significant performance advantage for cluster-based anomaly detectors in the presence of adverse environmental conditions

"How to project customer retention" revisited: the role of duration dependence

Cohort-level retention rates typically increase over time, and the beta-geometric (BG) distribution has proven to be a robust model for capturing and projecting these patterns into the future. According to this model, the phenomenon of increasing cohort-level retention rates is purely due to cross-sectional heterogeneity; an individual customer’s propensity to churn does not change over time. In this paper we present the beta-discrete-Weibull (BdW) distribution as an extension to the BG model, one that allows individual-level churn probabilities to increase or decrease over time. In addition to capturing the phenomenon of increasing cohort-level retention rates, this new model can also accommodate situations in which there is an initial dip in retention rates before they increase (i.e., a U-shaped cohort-level retention curve). A key finding is that even when aggregate retention rates are monotonically increasing, the individual-level churn probabilities are unlikely to be declining over time, as conventional wisdom would suggest. We carefully explore these connections between heterogeneity, duration dependence, and the shape of the retention curve, and draw some managerially relevant conclusions, e.g., that accounting for cross-sectional heterogeneity is more important than accounting for any individual-level dynamics in churn propensities

Electrical coupling of neuro-ommatidial photoreceptor cells in the blowfly

A new method of microstimulation of the blowfly eye using corneal neutralization was applied to the 6 peripheral photoreceptor cells (R1-R6) connected to one neuro-ommatidium (and thus looking into the same direction), whilst the receptor potential of a dark-adapted photoreceptor cell was recorded by means of an intracellular microelectrode. Stimulation of the photoreceptor cells not impaled elicited responses in the recorded cell of about 20% of the response elicited when stimulating the recorded cell. This is probably caused by gap junctions recently found between the axon terminals of these cells. Stimulation of all 6 cells together yielded responses that were larger and longer than those obtained with stimulation of just the recorded cell, and intensity-response curves that deviated more strongly from linearity. Evidence is presented that the resistance of the axon terminal of the photoreceptor cells quickly drops in response to a light flash, depending on the light intensity. Incorporating the cable properties of the cell body and the axon, the resistance of the gap junctions, and the (adapting) terminal resistance, a theoretical model is presented that explains the measurements well. Finally, it is argued that the gap junctions between the photoreceptor cells may effectively uncouple the synaptic responses of the cells by counteracting the influence of field potentials.