Fluorescent fatty acid conjugates for live cell imaging of peroxisomes.

Peroxisomes are eukaryotic organelles that are essential for multiple metabolic pathways, including fatty acid oxidation, degradation of amino acids, and biosynthesis of ether lipids. Consequently, peroxisome dysfunction leads to pediatric-onset neurodegenerative conditions, including Peroxisome Biogenesis Disorders (PBD). Due to the dynamic, tissue-specific, and context-dependent nature of their biogenesis and function, live cell imaging of peroxisomes is essential for studying peroxisome regulation, as well as for the diagnosis of PBD-linked abnormalities.

Opposite, bidirectional shifts in excitation and inhibition in specific types of dorsal horn interneurons are associated with spasticity and pain post-SCI.

Spasticity, a common complication after spinal cord injury (SCI), is frequently accompanied by chronic pain. The physiological origin of this pain (critical to its treatment) remains unknown, although spastic motor dysfunction has been related to the hyperexcitability of motoneurons and to changes in spinal sensory processing. Here we show that the pain mechanism involves changes in sensory circuits of the dorsal horn (DH) where nociceptive inputs integrate for pain processing.

Maximum likelihood estimation of biophysical parameters of synaptic receptors from macroscopic currents.

Dendritic integration and neuronal firing patterns strongly depend on biophysical properties of synaptic ligand-gated channels. However, precise estimation of biophysical parameters of these channels in their intrinsic environment is complicated and still unresolved problem. Here we describe a novel method based on a maximum likelihood approach that allows to estimate not only the unitary current of synaptic receptor channels but also their multiple conductance levels, kinetic constants, the number of receptors bound with a neurotransmitter, and the peak open probability from experimentally feasible number of postsynaptic currents.

Nociceptive neurons differentially express fast and slow T-type Ca²⁺ currents in different types of diabetic neuropathy.

T-type Ca²⁺ channels are known as important participants of nociception and their remodeling contributes to diabetes-induced alterations of pain sensation. In this work we have established that about 30% of rat nonpeptidergic thermal C-type nociceptive (NTCN) neurons of segments L4-L6 express a slow T-type Ca²⁺ current (T-current) while a fast T-current is expressed in the other 70% of these neurons. Streptozotocin-induced diabetes in young rats resulted in thermal hyperalgesia, hypoalgesia, or normalgesia 5-6 weeks after the induction.

Different pools of postsynaptic GABAA receptors mediate inhibition evoked by low- and high-frequency presynaptic stimulation at hippocampal synapses.

Patterns of short-term synaptic plasticity could considerably differ between synapses of the same axon. This may lead to separation of synaptic receptors transmitting either low- or high-frequency signals and, therefore, may have functional consequences for the information transfer in the brain. Here, we estimated a degree of such separation at hippocampal GABAergic synapses using a use-dependent GABAA receptor antagonist, picrotoxin, to selectively suppress a pool of GABAA receptors monosynaptically activated during the low-frequency stimulation.

Specific functioning of Cav3.2 T-type calcium and TRPV1 channels under different types of STZ-diabetic neuropathy.

Streptozotocin (STZ)-induced type 1 diabetes in rats leads to the development of peripheral diabetic neuropathy (PDN) manifested as thermal hyperalgesia at early stages (4th week) followed by hypoalgesia after 8weeks of diabetes development. Here we found that 6-7 week STZ-diabetic rats developed either thermal hyper- (18%), hypo- (25%) or normalgesic (57%) types of PDN. These developmentally similar diabetic rats were studied in order to analyze mechanisms potentially underlying different thermal nociception.

Efficient maximum likelihood estimation of kinetic rate constants from macroscopic currents.

A new method is described that accurately estimates kinetic constants, conductance and number of ion channels from macroscopic currents. The method uses both the time course and the strength of correlations between different time points of macroscopic currents and utilizes the property of semiseparability of covariance matrix for computationally efficient estimation of current likelihood and its gradient. The number of calculation steps scales linearly with the number of channel states as opposed to the cubic dependence in a previously described method.