Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging

Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images

Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Studies on the membrane interactions of the cyclotides kalata B1 and kalata B6 on model membrane systems by surface plasmon resonance

In this study we have demonstrated the interactions of kalata B1 and its naturally occurring analogue kalata B6 with five model lipid membranes and have analyzed the binding kinetics using surface plasmon resonance. Two kalata peptides showed a higher affinity for the phosphatidylethanolamine-containing membranes, indicating that the peptides would bind selectively to bacterial membranes. Also we have optimized the procedure for the immobilization of five liposome mixtures and have shown that the procedure provides reproducible levels of immobilized liposomes and could be used to screen the selective binding of putative antimicrobial peptides to model mammalian or microbial phospholipid membranes. (C) 2004 Elsevier Inc. All rights reserved.

Renal structural and functional repair in a mouse model of reversal of ureteral obstruction

The end point of immune and nonimmune renal injury typically involves glomerular and tubulointerstitial fibrosis. Although numerous studies have focused on the events that lead to renal fibrosis, less is known about the mechanisms that promote cellular repair and tissue remodeling. Described is a model of renal injury and repair after the reversal of unilateral ureteral obstruction (UUO) in male C57b1/6J mice. Male mice (20 to 25 g) underwent 10 d of UUO with or without 1, 2, 4, or 6 wk of reversal of UUO (R-UUO). UUO resulted in cortical tubular cell atrophy and tubular dilation in conjunction with an almost complete ablation of the outer medulla. This was associated with interstitial macrophage infiltration; increased hydroxyproline content; and upregulated type I, III, IV, and V collagen expression. The volume density of kidney occupied by renal tubules that exhibited a brush border was measured as an assessment of the degree of repair after R-UUO. After 6 wk of R-UUO, there was an increase in the area of kidney occupied by repaired tubules (83.7 +/- 5.9%), compared with 10 d UUO kidneys (32.6 +/- 7.3%). This coincided with reduced macrophage numbers, decreased hydroxyproline content, and reduced collagen accumulation and interstitial matrix expansion, compared with obstructed kidneys from UUO mice. GFR in the 6-wk R-UUO kidneys was restored to 43 to 88% of the GFR in the contralateral unobstructed kidneys. This study describes the regenerative potential of the kidney after the established interstitial matrix expansion and medullary ablation associated with UUO in the adult mouse.