BRCA1 Functions as a Differential Modulator of Chemotherapy-induced Apoptosis

We have evaluated the role played by BRCA1 in mediating the phenotypic response to a range of chemotherapeutic agents commonly used in cancer treatment. Here we provide evidence that BRCA1 functions as a differential mediator of chemotherapy-induced apoptosis. Specifically, we demonstrate that BRCA1 mediates sensitivity to apoptosis induced by antimicrotubule agents but conversely induces resistance to DNA-damaging agents. These data are supported by a variety of experimental models including cells with inducible expression of BRCA1, siRNA-mediated inactivation of endogenous BRCA1, and reconstitution of BRCA1-deficient cells with wild-type BRCA1. Most notably we demonstrate that BRCA1 induces a 10–1000-fold increase in resistance to a range of DNA-damaging agents, in particular those that give rise to double-strand breaks such as etoposide or bleomycin. In contrast, BRCA1 induces a >1000-fold increase in sensitivity to the spindle poisons, paclitaxel and vinorelbine. Fluorescence-activated cell sorter analysis demonstrated that BRCA1 mediates G2/M arrest in response to both antimicrotubule and DNA-damaging agents. However, poly(ADP-ribose) polymerase and caspase-3 cleavage assays indicate that the differential effect mediated by BRCA1 in response to these agents occurs through the inhibition or induction of apoptosis. Therefore, our data suggest that BRCA1 acts as a differential modulator of apoptosis depending on the nature of the cellular insult.

Computing Zeros of Analytic Functions in the Complex Plane without using Derivatives

A new approach to evaluating all multiple complex roots of analytical function f(z) confined to the specified rectangular domain of complex plane has been developed and implemented in Fortran code. Generally f (z), despite being holomorphic function, does not have a closed analytical form thereby inhibiting explicit evaluation of its derivatives. The latter constraint poses a major challenge to implementation of the robust numerical algorithm. This work is at the instrumental level and provides an enabling tool for solving a broad class of eigenvalue problems and polynomial approximations.

Analyzing the degree of conflict among belief functions.

The study of alternative combination rules in DS theory when evidence is in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. These studies have mainly focused on investigating which alternative would be appropriate for which conflicting situation, under the assumption that a conflict is identified. The issue of detection (or identification) of conflict among evidence has been ignored. In this paper, we formally define when two basic belief assignments are in conflict. This definition deploys quantitative measures of both the mass of the combined belief assigned to the emptyset before normalization and the distance between betting commitments of beliefs.We argue that only when both measures are high, it is safe to say the evidence is in conflict. This definition can be served as a prerequisite for selecting appropriate combination rules.

A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.

Gender influences the detection of spatial working memory deficits in bipolar disorder.

Objective: Despite evidence that gender may influence neurocognitive functioning, few studies have examined its effects in bipolar disorder (BD) a priori. The aim of this study was to examine how gender influences executive-type functions, which are potentially useful as endophenotypes for BD. Methods: The performance of 26 euthymic patients(12 males, 14 females) with DSM-IV BD (20 BD type I and six BD type II) was compared to that of 26 controls (12 males, 14 females) on tests of executive function. Controls were matched to patients on an individual basis for sex, age and premorbid IQ. Tests assessed spatial working memory (SWM), planning, attentional set-shifting and verbal fluency. Results: Overall, patients showed deficits in SWM strategy (p < 0.001) and made more SWM errors relative to controls (p < 0.001). These deficits were more apparent in male-only comparisons (both p < 0.001) than in female-only comparisons (both p < 0.05). When examined in isolation, male controls were significantly better at performing the SWM task than female controls (both p < 0.05). This pattern was not observed in the patient cohort: male patients had poorer strategy scores than female patients (p < 0.05), but made a similar number of SWM errors. Conclusions: These findings provide evidence that gender can influence the detection of SWM deficits in the euthymic phase of BD, as the sex-related disequilibrium in SWM identified in healthy controls was disrupted in BD. © 2008 The Authors Journal compilation © 2008 Blackwell Munksgaard.