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AMPA Receptors

AMPA receptors are ionotropic glutamate receptors that mediate fast excitatory synaptic transmission in the central nervous system.
They are activated by the neurotransmitter glutamate and permeable to sodium, potassium, and calcium ions.
AMPA receptors play a crucial role in synaptic plasticity, learning, and memory.
Dysregulation of AMPA receptors has been implicated in various neurological and psychiatric disorders, making them an important target for pharmacological interventions.
The PubCompare.ai platform offers researchers powerful tools to optimize their AMPA receptor studies, enhancing reproducibility and accuracy by providing access to the best protocols from literature, pre-printa, and patents.

Most cited protocols related to «AMPA Receptors»

Melanopsin-driven Retinal Ganglion Cell Recordings

Cited 22 times

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Publication 2010

2-amino-4-phosphonobutyric acid 6,7-dinitroquinoxaline-2,3-dione Amino Acids AMPA Receptors Animals antagonists Bath Excitatory Amino Acid Antagonists Eye Ganglia Halogens isolation Light lucifer yellow melanopsin Mercury Microscopy N-Methyl-D-Aspartate Receptors neurobiotin Receptors, Ionotropic Glutamate Resting Potentials Retina Retinal Cone Rod Photoreceptors Streptavidin Transillumination Tungsten

Quantitative PCR Analysis of Gene Expression

Cited 21 times

qPCR was performed in triplicate on the same microdissected frozen tissue samples subjected to the RNA amplification procedures. Samples were assayed on a real-time PCR cycler (7900HT, Applied Biosystems). Mouse TaqMan hydrolysis probes designed against the AMPA glutamate receptor subunit 1 (GRIA1) (Mn00514377_m1), beta actin (ACTB; Mm00447557_m1), and glyceraldehyde-3 phosphate dehydrogenase (GAPDH; Hs00266705_g1) were utilized (Applied Biosystems). Standard curves and cycle threshold (Ct) were generated using standards obtained from total mouse brain RNA. The ddCT method was employed to determine relative gene level differences. A total of 3-4 independent samples per RNA concentration were assayed in triplicate. Negative controls were used for each assay, and consisted of the reaction mixture without input RNA.

Alldred M.J., Che S, & Ginsberg S.D. (2008). Terminal Continuation (TC) RNA Amplification Enables Expression Profiling Using Minute RNA Input Obtained from Mouse Brain. International Journal of Molecular Sciences, 9(11), 2091-2104.

Publication 2008

alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid AMPA Receptors beta-Actin Biological Assay Brain Freezing GAPDH protein, human Genes Glutamate Glutamate Receptor Glyceraldehyde-3-Phosphate Dehydrogenases Hydrolysis Mice, House Protein Subunits Real-Time Polymerase Chain Reaction RNA Amplification Techniques Tissues

Modeling Synaptic Transmission Dynamics in Hippocampal CA1 Neurons

Cited 13 times

All simulations were performed using the NEURON simulation environment (v7.2) (Hines and Carnevale, 1997 (link)), with a previously published model of hippocampal CA1 pyramidal neurons (Bianchi et al., 2012 (link)). To implement synaptic inputs suitable to model changes in release probability and synaptic integration, for each synapse we used the kinetic scheme introduced by Tsodyks et al. (1998 (link)) and widely used to study synaptic transmission mechanisms and short-term plasticity effects (Tsodyks et al., 1998 (link)).
Briefly, in this model a synapse contains a finite amount of ‘resources’, which can be divided in three fractions: recovered (x), active (y), and inactive (z), in a dynamical relation to each other. At the arrival of a spike (at time t_sp), a fraction p of recovered resource is activated, quickly inactivated with a time constant τ_in and then recovered with a time constant τ_rec according to the following equations:

\begin{array}{l} \frac{d x}{d t} = \frac{z}{τ_{rec}} - p x δ (t - t_{sp}) \\ \frac{d y}{d t} = - \frac{y}{τ_{in}} + p x δ (t - t_{sp}) \\ \frac{d z}{d t} = \frac{y}{τ_{in}} - \frac{z}{τ_{rec}} \end{array}

with x + y + z = 1 and y₀ = z₀ = 0, x₀ = 1.
p indicates the effective use of the synaptic resources of the synapses and can be seen as the average release probability of a quantal model. During repeated stimulation p can increase due to facilitation. In particular, at the arrival of a spike (t = tⁱ_sp) p is incremented by a factor U(1 − p⁻), where p⁻ is the last pre-spike value of p, so that the post-spike value is p⁺ = p⁻ + U(1 − p⁻). After the spike, instead, p decays to baseline with a time constant τ_facil, (Tsodyks et al., 1998 (link)), so that in the interval between the arrival of two spikes, t ∈ (tⁱ_sp, t^j_sp):

\frac{d p}{d t} = - \frac{p}{τ_{facil}}

U determines the increase in the value of p with each spike and coincides with the value of p reached upon the arrival of the first spike, i.e., p₀ = p(t¹_sp) = U. It is worth noting that p is incremented before x is converted to y.
The resulting excitatory post-synaptic current (EPSC) is proportional to the active resource:

EPSC (t) = Ay (t)

where A is the absolute synaptic strength, corresponding to the maximum EPSC obtained by activating all the resources.
The values used for all parameters are discussed in the Results section. Since the findings in Abramov et al. (2009 (link)) are principally mediated by AMPA receptors, we did not explicitly include NMDA receptors in the CA1 neuron model.
To model the activation of a group of afferent fibers from CA3 pyramidal neurons through the Schaffer collaterals, ten synapses were distributed randomly on the apical trunk between 100 and 400 μm from the soma. Each synapse in the model represents the effect of a population of synapses activated in the oblique dendrites. A range of peak synaptic conductances (weights) was explored. All simulations were repeated 10 times redistributing synaptic location and weights. Results are expressed as mean ± SEM (standard error of the mean, SEM).

Romani A., Marchetti C., Bianchi D., Leinekugel X., Poirazi P., Migliore M, & Marie H. (2013). Computational modeling of the effects of amyloid-beta on release probability at hippocampal synapses. Frontiers in Computational Neuroscience, 7, 1.

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Publication 2013

AMPA Receptors Dendrites factor A Kinetics N-Methyl-D-Aspartate Receptors Neurons Pyramidal Cells Schaffer Collaterals Synapses Synaptic Transmission Vision

Membrane Protein Dynamics in a Realistic Plasma Membrane

Cited 12 times

The detailed methods are described in the Supporting Information. In summary, we embedded 10 membrane proteins in
a previously characterized model of the plasma membrane.^{20 (link)} The starting structures of the 10 membrane proteins
simulated in this study were taken from the Protein Data Bank or obtained
from the corresponding publication: aquaporin-1 (AQP1, PDB ID 1J4N);^{98 (link)} prostaglandin H₂ synthase (COX1, PDB ID 1Q4G);^{99 (link)} the dopamine transporter (DAT, PDB ID 4M48);^{44 (link)} the epidermal growth factor receptor (EGFR);^{77 (link)} AMPA-sensitive glutamate receptor 2 (GluA2,
PDB ID 3KG2);^{100 (link)} glucose transporter 1 (GluT1, PDB ID 4PYP);^{101 (link)} voltage-dependent Shaker potassium channel 1.2 (Kv1.2,
PDB ID 3LUT,^{102 (link)} residues 32 to 4421 for each monomer); sodium,
potassium pump (Na,K-ATPase, PDB ID 4HYT);^{103 (link)} δ-opioid
receptor (δ-OPR, PDB ID 4N6H);^{104 (link)} and P-glycoprotein
(P-gp, PDB ID 4M1M).^{105 (link)} In each system, four copies of each
protein were included and positioned at a distance of ca. 20 nm from
each other. Proteins were simulated using standard Martini protocols
with minor variations between systems to accommodate system-specific
issues (Supporting Information). The following
lipid classes were included: cholesterol (CHOL), in both leaflets;
charged lipids phosphatidylserine (PS), phosphatidic acid (PA), phosphatidylinositol
(PI), and the PI-phosphate, PI-bisphosphate, and PI-trisphosphate
(PIPs) placed in the inner leaflet; and ganglioside (GM) in the outer
leaflet. The zwitterionic phosphatidylcholine (PC), phosphatidylethanolamine
(PE), and sphingomyelin (SM) lipids were placed in both leaflets,
with PC and SM primarily in the outer leaflet and PE in the inner
leaflet. Ceramide (CER), diacylglycerol (DAG), and lysophosphatidylcholine
(LPC) lipids were also included, with all the LPC in the inner leaflet,
and CER and DAG primarily in the outer leaflet. The details of the
Martini lipids used in this study can be found on the Martini Lipidome
webpage (http://www.cgmartini.nl/index.php/force-field-parameters/lipids) and are described by Ingolfsson et al., and Wassenaar et al.^{20 (link),106 (link)} The exact lipid composition of each system is given in the Supporting Information. The systems are ca. 42
× 42 nm in the membrane plane (x and y), including 4 proteins and ca. 6000 lipids.
Production
runs were performed in the presence of weak position
restraints applied to the protein backbone beads, with a force constant
of 1 kJ mol^–1 nm^–2, preventing
proteins from associating with each other. Each of the systems has
been simulated for 30 μs, which turned out to be adequate to
obtain convergence of major lipid components in the lipid shells around
the individual copies of the proteins (Supporting Information). Additional control simulations were performed
in the AQP1 system, in order to test the effects of simulation length,
position restraints on the proteins, lipid composition, and water
model on the results of lipid composition near the proteins (Supporting Information).
Simulations were
performed using the GROMACS simulation package
version 4.6.3,^{107 (link)} with the Martini v2.2
force field parameters,^{62 (link),63 (link)} and standard simulation
settings.^{108 (link)} Additional details are provided
in Supporting Information. All the analyses
were performed on the last 5 μs of each simulation system.

Corradi V., Mendez-Villuendas E., Ingólfsson H.I., Gu R.X., Siuda I., Melo M.N., Moussatova A., DeGagné L.J., Sejdiu B.I., Singh G., Wassenaar T.A., Delgado Magnero K., Marrink S.J, & Tieleman D.P. (2018). Lipid–Protein Interactions Are Unique Fingerprints for Membrane Proteins. ACS Central Science, 4(6), 709-717.

Publication 2018

Adenosinetriphosphatase alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid AMPA Receptors AQP1 protein, human Aquaporin 1 Cell Membrane Proteins Ceramides Cholesterol Debility Diacylglycerol Dopamine Transporter Epidermal Growth Factor Receptor Gangliosides Glucose Transporter Glutamate Glutamate Receptor Lipids Lysophosphatidylcholines Na(+)-K(+)-Exchanging ATPase P-Glycoproteins Phosphates Phosphatidic Acid Phosphatidylcholines phosphatidylethanolamine Phosphatidylinositols Phosphatidylserines Potassium Channel Proteins PTGS1 protein, human SLC2A1 protein, human Sphingomyelins Tissue, Membrane Vertebral Column

Quantitative PCR Analysis of Hippocampal Genes

Cited 11 times

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Publication 2008

alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid AMPA Receptors Anabolism beta-Actin Brain Freezing GAPDH protein, human Genes, Housekeeping Glutamate Glutamate Receptor Glyceraldehyde-3-Phosphate Dehydrogenases Homo sapiens Hydrolysis Mice, Laboratory neuro-oncological ventral antigen 2, human Proteins Protein Subunits Real-Time Polymerase Chain Reaction RNA Amplification Techniques Synaptophysin Technique, Dilution Tissues

Most recents protocols related to «AMPA Receptors»

Intravenous Nicotine Administration and Neurotransmitter Antagonists

The (−)-Nicotine hydrogen tartrate salt (Sigma-Aldrich) was dissolved in sterile physiological saline (0.9% NaCl) and administered intravenously at a concentration of 30.0 μg/kg/0.1 ml infusion. The pH of the solution was adjusted to 7.4 with NaOH 5 m. The GABAA receptor antagonist bicuculline-methiodide (bicuculline) was diluted in Milli-Q to 20 mm and further diluted in artificial CSF (aCSF; 20 μm), while the AMPA receptor antagonist CNQX was dissolved in aCSF (10 μm) shortly before use. All drugs were purchased from Sigma-Aldrich.

Domi A., Domi E., Lagstrom O., Gobbo F., Jerlhag E, & Adermark L. (2023). Abstinence-Induced Nicotine Seeking Relays on a Persistent Hypoglutamatergic State within the Amygdalo-Striatal Neurocircuitry. eNeuro, 10(2), ENEURO.0468-22.2023.

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Publication 2023

6-Cyano-7-nitroquinoxaline-2,3-dione AMPA Receptors Bicuculline bicuculline methiodide GABA-A Receptor Antagonists Hydrogen Nicotine Bitartrate Normal Saline Pharmaceutical Preparations physiology Saline Solution Sodium Chloride Sterility, Reproductive

Cerebellar Plasticity Study via STDP

To test whether the PC could learn to respond to a sequence with the reverse order, we mimicked long-term depression (LTD) at PF induced by the CF inputs. A stimulus with a certain direction and set of parameters was fed, and after 2 ms of the end of stimulation, we fed a paired simulated CF stimulus. Then, the synaptic weight of the PF was modified based of the time difference between the onset of the PF stimulation and that of the CF stimulation (i.e., STDP). We then examined whether the same stimulus or the stimulus in the reverse order was able to activate the PC.
For implementation of STDP, we defined trace x_j of PF at compartment j,

\begin{array}{l} x_{j} (t) = exp (- \frac{Δ t}{τ_{pre}}) x_{j} (t - Δ t) + S_{j} (t), \end{array}

where t is time, τ_pre is a time constant, and S_j is either 0 or 1 representing a pulse input at compartment j. Similarly, trace y of CF was defined as:

\begin{array}{l} y (t) = exp (- \frac{Δ t}{τ_{post}}) y (t - Δ t) + S (t), \end{array}

where τ_post is a time constant, and S is either 0 or 1 representing non-spiking and spiking, respectively. From Equation (8),(9), the STDP rule is described as follows:

\begin{array}{l} \begin{array}{l} w_{j} (t + Δ t) = w_{j} (t) + Δ w_{j} (t) \\ Δ w_{j} (t) = - A_{1} y (t) S_{j} (t) + A_{2} x_{j} (t) S (t) + A_{3}, \end{array} \end{array}

where w_j is the PF synaptic weight at compartment j, and A₁, A₂, A₃ are constants set at 0.9, 0, and 0.001, respectively. Here, we set A₂ = 0 to simulate LTD. If w_j became negative by learning, it was set to zero. On the contrary, if it became more than 12.87 nA, it was fixed to 12.87 nA. The LTD between PF–PC is caused by α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors on the surface of the membrane that are introduced again to the inner surface of the membrane over time. Physiologically, the A₃ can be regarded as a representation of the function of AMPA receptors that have gone under the membrane and appear on the surface once more (Hansel et al., 2001 (link)).
The exact procedure was as follows. First, we identified sequences that evoked responses in either IN or OUT direction while turning learning off. Next, we turned on the learning, and applied each sequence again, which was followed by CF stimulus immediately with a 2-ms delay. The entire simulation period was set at 5,000 ms. Then, we applied each sequence once again while turning the learning off, and examined whether the stimulation evoked somatic spikes. Finally, we searched sequences that changed the direction to evoke responses before and after learning.

Tamura K., Yamamoto Y., Kobayashi T., Kuriyama R, & Yamazaki T. (2023). Discrimination and learning of temporal input sequences in a cerebellar Purkinje cell model. Frontiers in Cellular Neuroscience, 17, 1075005.

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Publication 2023

Amino Acids AMPA Receptors Diploid Cell Hydroxy Acids Pulse Rate Tissue, Membrane

Immunocytochemistry and surface AMPA receptor staining

Primary neuronal cultures were fixed with 4% PFA/4% sucrose solution for 10 min at RT, washed with PBS, and permeabilized with 0.2% TX‐100 in PBS for 10 min. Then, cells were incubated for 1 h in blocking solution (2% glycine, 0.2% gelatine, 2% BSA, and 50 mM NH₄Cl (pH 7.4)) and primary antibodies were applied overnight at 4°C. Next, the coverslips were incubated with secondary antibodies diluted 1:500. Coverslips were mounted with Mowiol 4‐88 (Merck Chemicals). For detection of Jacob‐CREB and Jacob‐LMO4 co‐localization in STED imaging, a heat‐based antigen retrieval protocol was used.
For assessing surface expression of AMPA receptors, dissociated hippocampal neurons were incubated for 10 min at RT with anti‐GluA1 antibody diluted in Tyrode's buffer (128 mM NaCl, 5 mM KCl, 1 mM MgCl2, 2 mM CaCl2, 4.2 mM NaHCo3, 15 mM HEPES, 20 mM glucose, pH 7.2–7.4), rinsed, and fixed for 10 min at RT with 4% PFA‐sucrose, and subsequently stained with other antibodies as described above.

Grochowska K.M., Gomes G.M., Raman R., Kaushik R., Sosulina L., Kaneko H., Oelschlegel A.M., Yuanxiang P., Reyes‐Resina I., Bayraktar G., Samer S., Spilker C., Woo M.S., Morawski M., Goldschmidt J., Friese M.A., Rossner S., Navarro G., Remy S., Reissner C., Karpova A, & Kreutz M.R. (2023). Jacob‐induced transcriptional inactivation of CREB promotes Aβ‐induced synapse loss in Alzheimer's disease. The EMBO Journal, 42(4), e112453.

Publication 2023

AMPA Receptors Antibodies Antibodies, Anti-Idiotypic Antigens Bicarbonate, Sodium Buffers Cells Gelatins Glucose Glycine HEPES Magnesium Chloride Neurons polyethylene glycol monooctylphenyl ether Sodium Chloride Sucrose

Glutamate Receptor Modulation Protocol

All drugs used in the current experiments were from Tocris Bioscience. Drugs used in the study and their concentrations are as follows: dihydrokainic acid (DHK), a competitive and selective GLT-1 blocker (300 µM; low DHK experiments used 1, 2, or 5 µM as indicated); _DL-threo-β-benzloxsapartic acid (_DL-TBOA), a competitive and nonselective EAAT blocker (100 µM); DNQX disodium salt, an AMPA/kainate receptor antagonist (20 µM); D-APV, a selective NMDA receptor antagonist (50 µM); MSOP, a selective group III metabotropic glutamate receptor antagonist (100 µM); and MTEP hydrochloride, a selective mGluR5 antagonist (100 µM). In DHK, TBOA, or MSOP/MTEP experiments, slices were incubated for 5–10 min before imaging or electrophysiology was conducted.

Brymer K.J., Hurley E.P., Barron J.C., Mukherjee B., Barnes J.R., Nafar F, & Parsons M.P. (2023). Asymmetric dysregulation of glutamate dynamics across the synaptic cleft in a mouse model of Alzheimer’s disease. Acta Neuropathologica Communications, 11, 27.

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Publication 2023

6,7-dinitroquinoxaline-2,3-dione Acids alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid AMPA Receptors dihydrokainic acid DL-threo-beta-benzyloxyaspartate Excitatory Amino Acid Antagonists GRM5 protein, human Kainate methylserine phosphate N-Methyl-D-Aspartate Receptors Pharmaceutical Preparations Receptors, Kainic Acid Sodium Chloride

Modeling Cortical Lateral Inhibition Networks

Twenty TC cells receive input that is considered to come from the right eye (TC_R) and the other twenty TC cells receive input considered to come from the left eye (TC_L). Thalamic neurons project more strongly to one PYR cell and one PV cell and relatively weakly to all other pyramidal cells and to PV cells of the same PV population (PV cells receive input from either TC_L or TC_R). PV cells that receive input from TC_R connect less strongly to other PV cells that receive input from TC_R and more strongly to PV cells that receive input from TC_L and vice versa for PV cells that receive input from TC_L. This network connectivity scheme is used to model lateral inhibition between different functional units of interneurons. Additionally, gap junctions (when present) are only put between PV cells of the same functional unit (i.e., those receiving input from TC_R or from TC_L).
In the pre-CP, all intracortical connections are weak because we are interested in the early (unspecified) state of the cortex. All inhibitory synapses use GABA_A receptor kinetics and all excitatory synapses use AMPA receptors. Cortical PV cells are connected all-to-all via GABA_A receptors with stronger connections between PV populations than within a population. The critical period is modeled by strengthening all PV-to-PV maximal conductances and adding electrical connections between PV neurons of the same population. Details of the equations and parameters used for the synaptic conductances are in SI Appendix.
Detailed methods can be found in SI Appendix.

Quast K.B., Reh R.K., Caiati M.D., Kopell N., McCarthy M.M, & Hensch T.K. (2023). Rapid synaptic and gamma rhythm signature of mouse critical period plasticity. Proceedings of the National Academy of Sciences of the United States of America, 120(2), e2123182120.

Publication 2023

AMPA Receptors Cells Cortex, Cerebral Debility Electricity GABA-A Receptor Gap Junctions Interneurons Kinetics Neurons Psychological Inhibition Pyramidal Cells Synapses Thalamus

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What are AMPA Receptors and what is their role in the central nervous system?

AMPA receptors are a type of ionotropic glutamate receptor that play a crucial role in fast excitatory synaptic transmission in the central nervous system. They are activated by the neurotransmitter glutamate and are permeable to sodium, potassium, and calcium ions. AMPA receptors are essential for synaptic plasticity, learning, and memory processes. Dysregulation of AMPA receptors has been implicated in various neurological and psychiatric disorders, making them an important target for pharmacological interventions.

What are some common challenges in studying AMPA Receptors?

Studying AMPA receptors can present several challenges, such as ensuring the reproducibility and accuracy of experimental protocols. Researchers often need to sift through a vast amount of literature, pre-prints, and patents to identify the most effective and reliable protocols for their specific research goals. This can be a time-consuming and arduous process, potentially leading to suboptimal experimental design and results.

How can PubCompare.ai assist in optimizing AMPA Receptor research?

PubCompare.ai is an AI-driven platform that can help researchers streamline their AMPA receptor studies. The platform allows you to efficiently screen protocol literature, leveraging AI to pinpoint critical insights. PubCompare.ai can assist in identifying the most effective protocols related to AMPA receptors for your specific research goals. The platform's intelligent analysis can highlight key differences in protocol effectiveness, enabling you to choose the best option for reproducibility and accuracy, thus enhancing the quality and impact of your AMPA receptor research.

Are there different variations or types of AMPA Receptors, and how do they differ?

Yes, there are different subytpes of AMPA receptros that can vary in their subunit composition, ion permeability, and functional properties. The four main AMPA receptor subunits are GluA1, GluA2, GluA3, and GluA4. The specific combination of these subunits can result in AMPA receptors with distinct characteristics, such as different calcium permeability or desensitization kinetics. Understanding the unique features of AMPA receptor subtypes is important when designing experiments and interpreting results, as they may have different roles in synaptic transmission and plasticity.

What are some specific applications of AMPA Receptor research?

AMPA receptor research has numerous applications in the field of neuroscience and beyond. These receptors are heavily involved in processes like learning, memory, and synaptic plasticity, making them a key target for understanding and treating neurological and psychiatric disorders. AMPA receptor dysregulation has been implicated in conditions such as Alzheimer's disease, Parkinson's disease, epilepsy, schizophrenia, and depression. Additionally, AMPA receptor modulators are being investigated as potential therapeutic agents for these disorders. Researchers studying synapttic function, neurodevelopment, and neurodegeneration also rely on AMPA receptor research to gain insights into these critical neural processes.

More about "AMPA Receptors"

AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptors are a crucial type of ionotropic glutamate receptors that play a vital role in fast excitatory synaptic transmission within the central nervous system.
These receptors are activated by the neurotransmitter glutamate and are permeable to sodium, potassium, and calcium ions.
AMPA receptors are instrumental in synaptic plasticity, learning, and memory processes.
Dysregulation or malfunction of AMPA receptors has been implicated in various neurological and psychiatric disorders, making them an important target for pharmacological interventions.
Researchers can optimize their AMPA receptor studies by utilizing the powerful tools offered by the PubCompare.ai platform, which provides access to the best protocols from literature, pre-prints, and patents.
Some related terms and concepts that are relevant to AMPA receptor research include D-AP5 (an NMDA receptor antagonist), PClamp 10 software (for electrophysiological data analysis), Picrotoxin (a GABA receptor antagonist), Bicuculline (another GABA receptor antagonist), Strychnine (a glycine receptor antagonist), Multiclamp 700B amplifier (for electrophysiological recordings), Gabazine (a GABA receptor antagonist), and CNQX (6-cyano-7-nitroquinoxaline-2,3-dione, an AMPA/kainate receptor antagonist).
By leveraging the insights and tools provided by PubCompare.ai, researchers can enhance the reproducibility and accuracy of their AMPA receptor studies, leading to more reliable and effective results in their quest to understand and address the role of these receptors in various neurological and psychiatric disorders.