Functional analysis of actin fibrils in Physarum polycephalum

Calcium is supposed to play an important role in the control of protoplasmic streaming in slime mold plasmodia. The motive force for protoplasmic streaming is generated by the interaction of actin and myosin. This contraction is supposed to be controlled by intracellular Ca-fluxes similar to the triggering system in skeleton muscle. The histochemical localisation of calcium however is problematic because of the possible diffusion artifacts especially in aquous media.To evaluate this problem calcium localisation was studied in small pieces of shock frozen (liquid propane at -189°C) plasmodial strands of Physarum polycephalum, which were further processed with 3 different methods: 1) freeze substitution in ethanol at -75°C, staining in 100% ethanol with 1% uranyl acetate, and embedding in styrene-methacrylate. For comparison the staining procedure was omitted in some preparations. 2)Freeze drying at about -95°C, followed by immersion with 100% ethanol containing 1% uranyl acetate, and embedding. 3) Freeze fracture, carbon coating and SEM investigation at temperatures below -100° C.

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A freeze-fracture-etched study of the physarum polycephalum plasma membrane during early formation of the macroplasmodial stage

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100147570 ◽

1993 ◽

Vol 51 ◽

pp. 346-347

Author(s):

Randolph W. Taylor ◽

Henrie Treadwell

Keyword(s):

Plasma Membrane ◽

Life Cycle ◽

Growth Phase ◽

Filter Paper ◽

Physarum Polycephalum ◽

Freeze Fracture ◽

Petri Dish ◽

Wire Screen ◽

Wide Mouth ◽

Sterile Filter

The plasma membrane of the Slime Mold, Physarum polycephalum, process unique morphological distinctions at different stages of the life cycle. Investigations of the plasma membrane of P. polycephalum, particularly, the arrangements of the intramembranous particles has provided useful information concerning possible changes occurring in higher organisms. In this report Freeze-fracture-etched techniques were used to investigate 3 hours post-fusion of the macroplasmodia stage of the P. polycephalum plasma membrane.Microplasmodia of Physarum polycephalum (M3C), axenically maintained, were collected in mid-expotential growth phase by centrifugation. Aliquots of microplasmodia were spread in 3 cm circles with a wide mouth pipette onto sterile filter paper which was supported on a wire screen contained in a petri dish. The cells were starved for 2 hrs at 24°C. After starvation, the cells were feed semidefined medium supplemented with hemin and incubated at 24°C. Three hours after incubation, samples were collected randomly from the petri plates, placed in plancettes and frozen with a propane-nitrogen jet freezer.

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Characterization of a Motile Cellular Domain Arising During the Amoebo-Flagellate Transformation of Physarum Polycephalum

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s1431927600002440 ◽

1980 ◽

Vol 38 ◽

pp. 552-553

Author(s):

K.I. Pagh ◽

M.R. Adelman

Keyword(s):

Cell Shape ◽

Physarum Polycephalum ◽

Slime Mold ◽

Live Cells ◽

Cellular Domain

Unicellular amoebae of the slime mold Physarum polycephalum undergo marked changes in cell shape and motility during their conversion into flagellate swimming cells (l). To understand the processes underlying motile activities expressed during the amoebo-flagellate transformation, we have undertaken detailed investigations of the organization, formation and functions of subcellular structures or domains of the cell which are hypothesized to play a role in movement. One focus of our studies is on a structure, termed the “ridge” which appears as a flattened extension of the periphery along the length of transforming cells (Fig. 1). Observations of live cells using Nomarski optics reveal two types of movement in this region:propagation of undulations along the length of the ridge and formation and retraction of filopodial projections from its edge. The differing activities appear to be associated with two characteristic morphologies, illustrated in Fig. 1.

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Clinical Issues: What’s in a Word? A Functional Analysis of Word Learning

Perspectives on Language Learning and Education ◽

10.1044/lle12.3.4 ◽

2005 ◽

Vol 12 (3) ◽

pp. 4-8 ◽

Cited By ~ 7

Author(s):

Prahlad Gupta

Keyword(s):

Functional Analysis ◽

Word Learning ◽

Clinical Issues

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Review for "High‐throughput single‐cell sequencing of paired TCRα and TCRβ genes for the direct expression‐cloning and functional analysis of murine T cell receptors"

10.1002/eji.201848030/v1/review1 ◽

2019 ◽

Keyword(s):

Functional Analysis ◽

T Cell ◽

Single Cell ◽

High Throughput ◽

T Cell Receptors ◽

Expression Cloning ◽

Cell Receptors ◽

Single Cell Sequencing

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Case Formulation and Design of Behavioral Treatment Programs

European Journal of Psychological Assessment ◽

10.1027//1015-5759.19.3.164 ◽

2003 ◽

Vol 19 (3) ◽

pp. 164-174 ◽

Cited By ~ 27

Author(s):

Stephen N. Haynes ◽

Andrew E. Williams

Keyword(s):

Functional Analysis ◽

Behavior Problems ◽

Behavioral Treatment ◽

Clinical Case ◽

Relative Magnitude ◽

Mechanisms Of Action ◽

Treatment Programs ◽

Case Formulation ◽

Functional Relations ◽

Causal Variables

Summary: We review the rationale for behavioral clinical case formulations and emphasize the role of the functional analysis in the design of individualized treatments. Standardized treatments may not be optimally effective for clients who have multiple behavior problems. These problems can affect each other in complex ways and each behavior problem can be influenced by multiple, interacting causal variables. The mechanisms of action of standardized treatments may not always address the most important causal variables for a client's behavior problems. The functional analysis integrates judgments about the client's behavior problems, important causal variables, and functional relations among variables. The functional analysis aids treatment decisions by helping the clinician estimate the relative magnitude of effect of each causal variable on the client's behavior problems, so that the most effective treatments can be selected. The parameters of, and issues associated with, a functional analysis and Functional Analytic Clinical Case Models (FACCM) are illustrated with a clinical case. The task of selecting the best treatment for a client is complicated because treatments differ in their level of specificity and have unequally weighted mechanisms of action. Further, a treatment's mechanism of action is often unknown.

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