Grazers and diggers: Exploitation competition and coexistence among foragers with different feeding strategies on a single resource

A mathematical model is presented that describes a system where two consumer species compete exploitatively for a single renewable resource. The resource is distributed in a patchy but homogeneous environment; that is, all patches are intrinsically identical. The two consumer species are referred to as diggers and grazers, where diggers deplete the resource within a patch to lower densities than grazers. We show that the two distinct feeding strategies can produce a heterogeneous resource distribution that enables their coexistence. Coexistence requires that grazers must either move faster than diggers between patches or convert the resources to population growth much more efficiently than diggers. The model shows that the functional form of resource renewal within a patch is also important for coexistence. These results contrast with theory that considers exploitation competition for a single resource when the resource is assumed to be well mixed throughout the system.

Causal loops and the independence of causal facts

According to Hugh Mellor in Real Time II (1998, Ch. 12), assuming the logical independence of causal facts and the 'law of large numbers', causal loops are impossible because if they were possible they would produce inconsistent sets of frequencies. I clarify the argument, and argue that it would be preferable to abandon the relevant independence assumption in the case of causal loops.

Purification of the keratan sulfate proteoglycan expressed in prostatic secretory cells and its identification as lumican

BACKGROUND. Secretory epithelial cells of human prostate contain a keratan sulfate proteoglycan (KSPG) associated with the prostatic secretory granules (PSGs). The proteoglycan has not been identified, but like the PSGs, it is lost in the early stages of malignant transformation. METHODS. Anion exchange and affinity chromatography were used to purify KSPG from human prostate tissue. Enzymatic deglycosylation was used to remove keratan sulfate (KS). The core protein was isolated using 2D gel electrophoresis, digested in-gel with trypsin, and identified by peptide mass fingerprinting (PMF). RESULTS. The purified proteoglycan was detected as a broad smear on Western blots with an apparent molecular weight of 65-95 kDa. The KS moiety was susceptible to digestion with keratanase 11 and peptide N-glycosidase F defining it as highly sulfated and N-linked to the core protein. The core protein was identified, following deglycosylation and PMF, as lumican and subsequently confirmed by Western blotting using an anti-lumican antibody. CONCLUSIONS. The KSPG associated with PSGs in normal prostate epithelium is lumican. While the role of lumican in extracellular matrix is well established, its function in the prostate secretory process is not known. It's potential to facilitate packaging of polyamines in PSGs, to act as a tumor suppressor and to mark the early stages of malignant transformation warrant further investigation. (C) 2003 Wiley-Liss, Inc.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

Characterization of baboon (Papio hamadryas) milk proteins

The major proteins of baboon milk were identified as beta -lactoglobulin (beta LG), alpha -lactalbumin (alpha LA), lysozyme, lactoferrin, casein, and albumin by immobiline isoelectric focusing, SDS-PAGE, immunoblotting of gels with rabbit antisera to human alpha LA, lysozyme, and albumin and bovine beta LG and casein, and N-terminal sequencing of proteins blotted from gels. The first 30 N-terminal residues of baboon polymorphism at residue 2. The complete cDNA sequence and derived amino acid composition of beta LG were elucidated using RT-PCR amplification of poly(A)(+) mRNA purified from lactating mammary gland. Baboon beta LG identified to date. beta LG and alpha LA polymorphisms with three (A, B, and C) and two (A and B) variants, respectively, were detected by immobiline IEF, pH 4-6, of individual baboon milk samples at varying stages of lactation.

MRI based diffusion and perfusion predictive model to estimate stroke evolution

In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/-0.19 and 1.20 +/-0.36. For recovered tissue the mean values were 0.99 +/-0.25 and 1.87 +/-0.71, respectively. There was a significant difference between these two regions for both measures (P