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Dive into the research topics where Joseph B. Patlak is active.

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Featured researches published by Joseph B. Patlak.


Biophysical Journal | 1997

Smooth muscle and skeletal muscle myosins produce similar unitary forces and displacements in the laser trap.

William H. Guilford; D. E. Dupuis; Guy G. Kennedy; J. Wu; Joseph B. Patlak; David M. Warshaw

Purified smooth muscle myosin in the in vitro motility assay propels actin filaments at 1/10 the velocity, yet produces 3-4 times more force than skeletal muscle myosin. At the level of a single myosin molecule, these differences in force and actin filament velocity may be reflected in the size and duration of single motion and force-generating events, or in the kinetics of the cross-bridge cycle. Specifically, an increase in either unitary force or duty cycle may explain the enhanced force-generating capacity of smooth muscle myosin. Similarly, an increase in attached time or decrease in unitary displacement may explain the reduced actin filament velocity of smooth muscle myosin. To discriminate between these possibilities, we used a laser trap to measure unitary forces and displacements from single smooth and skeletal muscle myosin molecules. We analyzed our data using mean-variance analysis, which does not rely on scoring individual events by eye, and emphasizes periods in the data with constant properties. Both myosins demonstrated multiple but similar event populations with discrete peaks at approximately +11 and -11 nm in displacement, and 1.5 and 3.5 pN in force. Mean attached times for smooth muscle myosin were longer than for skeletal-muscle myosin. These results explain much of the difference in actin filament velocity between these myosins, and suggest that an increased duty cycle is responsible for the enhanced force-generating capacity of smooth over skeletal-muscle myosin.


Journal of Cell Biology | 2003

A mutant heterodimeric myosin with one inactive head generates maximal displacement.

Arthur S. Rovner; Patricia M. Fagnant; Peteranne B. Joel; Guy G. Kennedy; Joseph B. Patlak; David M. Warshaw; Kathleen M. Trybus

Each of the heads of the motor protein myosin II is capable of supporting motion. A previous report showed that double-headed myosin generates twice the displacement of single-headed myosin (Tyska, M.J., D.E. Dupuis, W.H. Guilford, J.B. Patlak, G.S. Waller, K.M. Trybus, D.M. Warshaw, and S. Lowey. 1999. Proc. Natl. Acad. Sci. USA. 96:4402–4407). To determine the role of the second head, we expressed a smooth muscle heterodimeric heavy meromyosin (HMM) with one wild-type head, and the other locked in a weak actin-binding state by introducing a point mutation in switch II (E470A). Homodimeric E470A HMM did not support in vitro motility, and only slowly hydrolyzed MgATP. Optical trap measurements revealed that the heterodimer generated unitary displacements of 10.4 nm, strikingly similar to wild-type HMM (10.2 nm) and approximately twice that of single-headed subfragment-1 (4.4 nm). These data show that a double-headed molecule can achieve a working stroke of ∼10 nm with only one active head and an inactive weak-binding partner. We propose that the second head optimizes the orientation and/or stabilizes the structure of the motion-generating head, thereby resulting in maximum displacement.


Biophysical Journal | 2000

Analysis and Implications of Equivalent Uniform Approximations of Nonuniform Unitary Synaptic Systems

Vladimir V. Uteshev; Joseph B. Patlak; Peter S. Pennefather

Real synaptic systems consist of a nonuniform population of synapses with a broad spectrum of probability and response distributions varying between synapses, and broad amplitude distributions of postsynaptic unitary responses within a given synapse. A common approach to such systems has been to assume identical synapses and recover apparent quantal parameters by deconvolution procedures from measured evoked (ePSC) and unitary evoked postsynaptic current (uePSC) distributions. Here we explicitly consider nonuniform synaptic systems with both intra (type I) and intersynaptic (type II) response variability and formally define an equivalent system of uniform synapses in which both uePSC and ePSC amplitude distributions best approximate those of the actual nonuniform synaptic system. This equivalent system has the advantage of being fully defined by just four quantal parameters: ñ, the number of equivalent synapses;p, the mean probability of quantal release; mu, mean; and sigma(2), variance of the uePSC distribution. We show that these equivalent parameters are weighted averages of intrinsic parameters and can be approximated by apparent quantal parameters, therefore establishing a useful analytical link between the apparent and intrinsic parameters. The present study extends previous work on compound binomial analysis of synaptic transmission by highlighting the importance of the product of p and mu, and the variance of that product. Conditions for a unique deconvolution of apparent uniform synaptic parameters have been derived and justified. Our approach does not require independence of synaptic parameters, such as p and mu from each other, therefore the approach will hold even if feedback (i.e., via retrograde transmission) exists between pre and postsynaptic signals. Using numerical simulations we demonstrate how equivalent parameters are meaningful even when there is considerable variation in intrinsic parameters, including systems where subpopulations of high- and low-release probability synapses are present, therefore even under such conditions the apparent parameters estimated from experiments would be informative.


Archive | 1984

The Information Content of Single Channel Data

Joseph B. Patlak

Single channel signals were initially observed in artificial bilayer membranes (Bean et al., 1969; Gordon and Haydon, 1972; Hladkey and Haydon, 1972). They were first seen in biological membranes using the patch clamp technique (Neher and Sakmann, 1976). A number of excellent reviews have detailed this technique, including gigohm (>109 ohm) seals and ultra-high resolution recordings, as well as the many different types of preparations and channels from which recordings have been made (Neher et al., 1978; Hamill et al., 1981). In this chapter I will examine a different aspect of this subject. I seek to clarify the reasons for recording single channels, instead of measuring the mean behavior of a population of channels (whole cell recording), or the fluctuations caused by the random activity of such a population.


The Journal of General Physiology | 1999

Functional coupling of ryanodine receptors to KCa channels in smooth muscle cells from rat cerebral arteries.

Guillermo J. Pérez; Adrian D. Bonev; Joseph B. Patlak; Mark T. Nelson


The Journal of General Physiology | 1995

TRANSFER OF TWELVE CHARGES IS NEEDED TO OPEN SKELETAL MUSCLE NA+ CHANNELS

Birgit Hirschberg; Arthur S. Rovner; Mitchell Lieberman; Joseph B. Patlak


The Journal of General Physiology | 1996

Ca2+ currents in cerebral artery smooth muscle cells of rat at physiological Ca2+ concentrations.

Michael Rubart; Joseph B. Patlak; Mark T. Nelson


American Journal of Physiology-heart and Circulatory Physiology | 2007

Hypertrophic and dilated cardiomyopathy mutations differentially affect the molecular force generation of mouse α-cardiac myosin in the laser trap assay

Edward P. Debold; Joachim P. Schmitt; Joseph B. Patlak; Samantha Beck; J. R. Moore; Jonathan G. Seidman; Christine E. Seidman; David M. Warshaw


Biophysical Journal | 1993

Measuring kinetics of complex single ion channel data using mean-variance histograms

Joseph B. Patlak


The Journal of General Physiology | 1988

Sodium channel subconductance levels measured with a new variance-mean analysis.

Joseph B. Patlak

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