In vitro and in situ activation of the complement system by the fungus Lacazia loboi

Since there are no studies evaluating the participation of the complement system (CS) in Jorge Lobo's disease and its activity on the fungus Lacazia loboi, we carried out the present investigation. Fungal cells with a viability index of 48% were obtained from the footpads of BALB/c mice and incubated with a pool of inactivated serum from patients with the mycosis or with sterile saline for 30 min at 37 ºC. Next, the tubes were incubated for 2 h with a pool of noninactivated AB+ serum, inactivated serum, serum diluted in EGTA-MgCl2, and serum diluted in EDTA. The viability of L. loboi was evaluated and the fungal suspension was cytocentrifuged. The slides were submitted to immunofluorescence staining using human anti-C3 antibody. The results revealed that 98% of the fungi activated the CS by the alternative pathway and no significant difference in L. loboi viability was observed after CS activation. In parallel, frozen histological sections from 11 patients were analyzed regarding the presence of C3 and IgG by immunofluorescence staining. C3 and IgG deposits were observed in the fungal wall of 100% and 91% of the lesions evaluated, respectively. The results suggest that the CS and immunoglobulins may contribute to the defense mechanisms of the host against L. loboi

Remarks on the assessment, representation, aggregation and utilization of expert opinion

This report considers the relevance of recent ideas in the foundations of probability to the rational use of expert opinion in the design of a nuclear waste repository, and the assessment of its performance. The main probability concepts introduce are those of modal (probably A), comparative (A is at least as probable as B) and interval-valued (the lower probability of A is P(A) and the upper probability of A is P(anti A)) probabilities. We then outline an approach first using comparative probability to model the resuls of binary elicitation of an expert's opinions concerning repository uncertainties and then employing interval-valued probability to represent comparative probability in a computationally convenient form. We further consider the issue of aggregating or amalgamating the responses of several experts, and we emphasize the need to preserve some measure of the disagreements among the experts. The resulting aggregated interval-valued representation of the responses concerning the uncertainties surrounding the performance of a nuclear waste repository design can then be used to numerically assess this performance in a manner parallel to that of utility theory. Utility theory is the basis for statistical decision theory. Our recommendations can only be tentative, and research is recommended to gain some working experience with the results of the proposed decision-making process in the repostory design context

Neural-network design for small training sets of high dimension

We introduce a statistically based methodology for the design of neural networks when the dimension d of the network input is comparable to the size n of the training set. If one proceeds straightforwardly, then one is committed to a network of complexity exceeding n. The result will be good performance on the training set but poor generalization performance when the network is presented with new data. To avoid this we need to select carefully the network architecture, including control over the input variables. Our approach to selecting a network architecture first selects a subset of input variables (features) using the nonparametric statistical process of difference-based variance estimation and then selects a simple network architecture using projection pursuit regression (PPR) ideas combined with the statistical idea of slicing inverse regression (SIR). The resulting network, which is then retrained without regard to the PPR/SIR determined parameters, is one of moderate complexity (number of parameters significantly less than n) whose performance on the training set can be expected to generalize well. The application of this methodology is illustrated in detail in the context of shortterm forecasting of the demand for electric power from an electric utility

What Is ‘Real’ in Interpersonal Comparisons of Confidence

According to comparativism, comparative confidence is more fundamental than absolute confidence. In two recent AJP papers, Stefánsson has argued that comparativism is capable of explaining interpersonal confidence comparisons. In this paper, I will argue that Stefansson’s proposed explanation is inadequate; that we have good reasons to think that comparativism cannot handle interpersonal comparisons; and that the best explanation of interpersonal comparisons requires thinking about confidence in a fundamentally different way than that which comparativists propose: specifically, we should think of confidence as a dimensionless quantity