Simple mechanochemistry describes the dynamics of kinesin molecules

Recently, Block and coworkers [Visscher, K., Schnitzer, M. J., & Block, S. M. (1999) Nature (London) 400, 184–189 and Schnitzer, M. J., Visscher, K. & Block, S. M. (2000) Nat. Cell Biol. 2, 718–723] have reported extensive observations of individual kinesin molecules moving along microtubules in vitro under controlled loads, F = 1 to 8 pN, with [ATP] = 1 μM to 2 mM. Their measurements of velocity, V, randomness, r, stalling force, and mean run length, L, reveal a need for improved theoretical understanding. We show, presenting explicit formulae that provide a quantitative basis for comparing distinct molecular motors, that their data are satisfactorily described by simple, discrete-state, sequential stochastic models. The simplest (N = 2)-state model with fixed load-distribution factors and kinetic rate constants concordant with stopped-flow experiments, accounts for the global (V, F, L, [ATP]) interdependence and, further, matches relative acceleration observed under assisting loads. The randomness, r(F,[ATP]), is accounted for by a waiting-time distribution, ψ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}{\mathrm{_{1}^{+}}}\end{equation*}\end{document}(t), [for the transition(s) following ATP binding] with a width parameter ν ≡ 〈t〉2/〈(Δt)2〉≃2.5, indicative of a dispersive stroke of mechanicity ≃0.6 or of a few (≳ν − 1) further, kinetically coupled states: indeed, N = 4 (but not N = 3) models do well. The analysis reveals: (i) a substep of d0 = 1.8–2.1 nm on ATP binding (consistent with structurally based suggestions); (ii) comparable load dependence for ATP binding and unbinding; (iii) a strong load dependence for reverse hydrolysis and subsequent reverse rates; and (iv) a large (≳50-fold) increase in detachment rate, with a marked load dependence, following ATP binding.

A neuronal model of a global workspace in effortful cognitive tasks

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

Mouse model of Sanfilippo syndrome type B produced by targeted disruption of the gene encoding α-N-acetylglucosaminidase

The Sanfilippo syndrome type B is an autosomal recessive disorder caused by mutation in the gene (NAGLU) encoding α-N-acetylglucosaminidase, a lysosomal enzyme required for the stepwise degradation of heparan sulfate. The most serious manifestations are profound mental retardation, intractable behavior problems, and death in the second decade. To generate a model for studies of pathophysiology and of potential therapy, we disrupted exon 6 of Naglu, the homologous mouse gene. Naglu−/− mice were healthy and fertile while young and could survive for 8–12 mo. They were totally deficient in α-N-acetylglucosaminidase and had massive accumulation of heparan sulfate in liver and kidney as well as secondary changes in activity of several other lysosomal enzymes in liver and brain and elevation of gangliosides GM2 and GM3 in brain. Vacuolation was seen in many cells, including macrophages, epithelial cells, and neurons, and became more prominent with age. Although most vacuoles contained finely granular material characteristic of glycosaminoglycan accumulation, large pleiomorphic inclusions were seen in some neurons and pericytes in the brain. Abnormal hypoactive behavior was manifested by 4.5-mo-old Naglu−/− mice in an open field test; the hyperactivity that is characteristic of affected children was not observed even in younger mice. In a Pavlovian fear conditioning test, the 4.5-mo-old mutant mice showed normal response to context, indicating intact hippocampal-dependent learning, but reduced response to a conditioning tone, perhaps attributable to hearing impairment. The phenotype of the α-N-acetylglucosaminidase-deficient mice is sufficiently similar to that of patients with the Sanfilippo syndrome type B to make these mice a good model for study of pathophysiology and for development of therapy.

Ts1Cje, a partial trisomy 16 mouse model for Down syndrome, exhibits learning and behavioral abnormalities

A mouse model for Down syndrome, Ts1Cje, has been developed. This model has made possible a step in the genetic dissection of the learning, behavioral, and neurological abnormalities associated with segmental trisomy for the region of mouse chromosome 16 homologous with the so-called “Down syndrome region” of human chromosome segment 21q22. Tests of learning in the Morris water maze and assessment of spontaneous locomotor activity reveal distinct learning and behavioral abnormalities, some of which are indicative of hippocampal dysfunction. The triplicated region in Ts1Cje, from Sod1 to Mx1, is smaller than that in Ts65Dn, another segmental trisomy 16 mouse, and the learning deficits in Ts1Cje are less severe than those in Ts65Dn. In addition, degeneration of basal forebrain cholinergic neurons, which was observed in Ts65Dn, was absent in Ts1Cje.

Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.

We present a general approach to forming structure-activity relationships (SARs). This approach is based on representing chemical structure by atoms and their bond connectivities in combination with the inductive logic programming (ILP) algorithm PROGOL. Existing SAR methods describe chemical structure by using attributes which are general properties of an object. It is not possible to map chemical structure directly to attribute-based descriptions, as such descriptions have no internal organization. A more natural and general way to describe chemical structure is to use a relational description, where the internal construction of the description maps that of the object described. Our atom and bond connectivities representation is a relational description. ILP algorithms can form SARs with relational descriptions. We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds. These compounds had been split previously into two subsets, 188 compounds that were amenable to regression and 42 that were not. For the 188 compounds, a SAR was found that was as accurate as the best statistical or neural network-generated SARs. The PROGOL SAR has the advantages that it did not need the use of any indicator variables handcrafted by an expert, and the generated rules were easily comprehensible. For the 42 compounds, PROGOL formed a SAR that was significantly (P < 0.025) more accurate than linear regression, quadratic regression, and back-propagation. This SAR is based on an automatically generated structural alert for mutagenicity.

Age-related learning deficits in transgenic mice expressing the 751-amino acid isoform of human beta-amyloid precursor protein.

The beta-amyloid precursor protein (beta-APP), from which the beta-A4 peptide is derived, is considered to be central to the pathogenesis of Alzheimer disease (AD). Transgenic mice expressing the 751-amino acid isoform of human beta-APP (beta-APP751) have been shown to develop early AD-like histopathology with diffuse deposits of beta-A4 and aberrant tau protein expression in the brain, particularly in the hippocampus, cortex, and amygdala. We now report that beta-APP751 transgenic mice exhibit age-dependent deficits in spatial learning in a water-maze task and in spontaneous alternation in a Y maze. These deficits were mild or absent in 6-month-old transgenic mice but were severe in 12-month-old transgenic mice compared to age-matched wild-type control mice. No other behavioral abnormalities were observed. These mice therefore model the progressive learning and memory impairment that is a cardinal feature of AD. These results provide evidence for a relationship between abnormal expression of beta-APP and cognitive impairments.