Excitatory synaptic site heterogeneity during paired pulse plasticity in CA1 pyramidal cells in rat hippocampus in vitro.

Turner, Dennis A.; Chen, Y; Isaac, John T.R.; West, Mike; Wheal, H.V.

doi:10.1113/jphysiol.1997.sp022032

Cited by 14 publications

(11 citation statements)

References 40 publications

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“…A change in synaptic transmission directly alters the level of postsynaptic depolarization, affecting not only AP generation in the postsynaptic neuron but also information storage within individual synapses (or synaptic plasticity, thought to represent cellular memory) by affecting postsynaptic Ca 2ϩ influx. At CA3-CA1 synapses, long-term potentiation, manifested as a lasting increase in synaptic strength, has been shown to mediate certain forms of hippocampusdependent memory (Gruart et al, 2006;Pastalkova et al, 2006;Whitlock et al, 2006). The reduced synaptic strength at CA3-CA1 synapses that we described for OVX LT rats would significantly impair hippocampal function, making it a plausible cellular mechanism underlying cognitive impairment in OVX animals (Gibbs, 2000;Markowska and Savonenko, 2002;Daniel et al, 2006) and surgically menopausal women (Nappi et al, 1999;Farrag et al, 2002;Rocca et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

“…1A). This E 2 treatment protocol has been shown to increase CA1 spine density (Gould et al, 1990), the frequency of presynaptic CA3 boutons synapsing with multiple CA1 spines (Woolley et al, 1996), and levels of presynaptic and postsynaptic proteins in the CA1 stratum radiatum (Brake et al, 2001;Waters et al, 2009). This E 2 treatment protocol produces ϳ35 pg/ml (or ϳ130 pM) serum E 2 level on the day of being killed (Woolley and McEwen, 1993), a level within the range of a rat during proestrus (Kalra and Kalra, 1974;Smith et al, 1975;Bridges and Byrnes, 2006).…”

Section: Methodsmentioning

confidence: 99%

“…Pr was estimated using two parameters that are sensitive to changes in the presynaptic function (Malinow and Tsien, 1990;Manabe et al, 1993;Dobrunz and Stevens, 1997). The first is the degree of PPF (or EPSC 2 /EPSC 1 ), which at the hippocampal synapses reflects a form of short-term presynaptic plasticity that is inversely related to the initial Pr (Dobrunz and Stevens, 1997;Murthy et al, 1997;Turner et al, 1997). The second parameter is the square of the inverse of the coefficient of variation (CV Ϫ2 ) of EPSC 1 amplitude measured across multiple consecutive trials.…”

Section: Long-term Ovarian Hormone Loss and Acute E 2 Application Do mentioning

confidence: 99%

“…More than 300,000 women in the United States undergo ovariectomy (OVX) for disease treatment and cancer prevention annually (Whiteman et al, 2008). OVX results in a sudden decline in the circulating ovarian hormones including E 2 , creating "surgical menopause."…”

Section: Introductionmentioning

confidence: 99%

“…E 2 regulates both the structure and function of CA3-CA1 synapses. In OVX rats, in vivo E 2 treatment for days increases CA1 spine density (Gould et al, 1990;Woolley and McEwen, 1993), the frequency of CA3 boutons synapsing with multiple CA1 spines (Woolley et al, 1996), and levels of CA1 synaptic proteins (Brake et al, 2001;Liu et al, 2008;Waters et al, 2009)-changes consistent with an increased synaptic strength. E 2 also acutely increases CA3-CA1 synaptic strength within minutes of bath application (Wong and Moss, 1992;Foy et al, 1999;Bi et al, 2000;Fugger et al, 2001;Sharrow et al, 2002;Smejkalova and Woolley, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Ovarian Hormone Loss Impairs Excitatory Synaptic Transmission at Hippocampal CA3–CA1 Synapses

Wu¹,

Bryant

Dorsa

et al. 2013

J. Neurosci.

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Premature and long-term ovarian hormone loss following ovariectomy (OVX) is associated with cognitive impairment. This condition is prevented by estradiol (E 2 ) therapy when initiated shortly following OVX but not after substantial delay. To determine whether these clinical findings are correlated with changes in synaptic functions, we used adult OVX rats to evaluate the consequences of short-term (7-10 d, OVX Control ) and long-term (ϳ5 months, OVX LT ) ovarian hormone loss, as well as subsequent in vivo E 2 treatment, on excitatory synaptic transmission at the hippocampal CA3-CA1 synapses important for learning and memory. The results show that ovarian hormone loss was associated with a marked decrease in synaptic strength. E 2 treatment increased synaptic strength in OVX Control but not OVX LT rats, demonstrating a change in the efficacy for E 2 5 months following OVX. E 2 also had a more rapid effect: within minutes of bath application, E 2 acutely increased synaptic strength in all groups except OVX LT rats that did not receive in vivo E 2 treatment. E 2 's acute effect was mediated postsynaptically, and required Ca 2ϩ influx through the voltage-gated Ca 2ϩ channels. Despite E 2 's acute effect, synaptic strength of OVX LT rats remained significantly lower than that of OVX Control rats. Thus, changes in CA3-CA1 synaptic transmission associated with ovarian hormone loss cannot be fully reversed with delayed E 2 treatment. Given that synaptic strength at CA3-CA1 synapses is related to the ability to learn hippocampus-dependent tasks, these findings provide additional insights for understanding cognitive impairment-associated long-term ovarian hormone loss and ineffectiveness for delayed E 2 treatment to maintain cognitive functions.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Long-term Ovarian Hormone Loss and Acute E 2 Application Do mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Ovarian Hormone Loss Impairs Excitatory Synaptic Transmission at Hippocampal CA3–CA1 Synapses

Wu¹,

Bryant

Dorsa

et al. 2013

J. Neurosci.

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Statistical mixture modeling for cell subtype identification in flow cytometry

et al. 2008

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Statistical mixture modeling provides an opportunity for automated identification and resolution of cell subtypes in flow cytometric data. The configuration of cells as represented by multiple markers simultaneously can be modeled arbitrarily well as a mixture of Gaussian distributions in the dimension of the number of markers. Cellular subtypes may be related to one or multiple components of such mixtures, and fitted mixture models can be evaluated in the full set of markers as an alternative, or adjunct, to traditional subjective gating methods that rely on choosing one or two dimensions. Four color flow data from human blood cells labeled with FITC-conjugated anti-CD3, PEconjugated anti-CD8, PE-Cy5-conjugated anti-CD4, and APC-conjugated anti-CD19 Abs was acquired on a FACSCalibur. Cells from four murine cell lines, JAWS II, RAW 264.7, CTLL-2, and A20, were also stained with FITC-conjugated anti-CD11c, PE-conjugated anti-CD11b, PE-Cy5-conjugated anti-CD8a, and PE-Cy7-conjugated-CD45R/ B220 Abs, respectively, and single color flow data were collected on an LSRII. The data were fitted with a mixture of multivariate Gaussians using standard Bayesian statistical approaches and Markov chain Monte Carlo computations. Statistical mixture models were able to identify and purify major cell subsets in human peripheral blood, using an automated process that can be generalized to an arbitrary number of markers. Validation against both traditional expert gating and synthetic mixtures of murine cell lines with known mixing proportions was also performed. This article describes the studies of statistical mixture modeling of flow cytometric data, and demonstrates their utility in examples with four-color flow data from human peripheral blood samples and synthetic mixtures of murine cell lines. ' International Society for Advancement of Cytometry Key termsstatistics; mixture models; Markov chain Monte Carlo; Bayesian analysis; identification; automation; gating ONE of the fundamental uses of flow cytometry is the identification and quantification of distinct cell subsets with phenotypes defined by the density of cell surface or intracellular markers. Ideally, such a biological classification should be objective, stable, and predictive (1).Objectivity, stability, and predictivity are all problematic with the traditional approach in which samples are sequentially gated in one-or two-dimensions. In particular, the choice of which sequence of markers to gate on and where to draw the gates depends on expertise and is highly subjective. This makes it difficult to replicate the cell subset identification procedure across different laboratories. The problem is compounded with polychromatic flow cytometry, because the number of possible gating sequences rises rapidly with the number of channels used. In a recent study of flow cytometric standardization involving 15 institutions, the mean inter-laboratory coefficient of variation ranged from 17 to 44%, even though preparation was standardized and performed using the same samp...

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