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Objective Emerging evidence raises the possibility that progesterone receptor (PR) signaling may contribute to the reproductive hormone fluctuation–linked seizure precipitation, called catamenial epilepsy. Therefore, we studied PR isoform expression in limbic regions involved in temporal lobe epilepsy and the effect of PR activation on neuronal activity and seizures. Methods We evaluated PR expression in the limbic regions, entorhinal cortex (EC), hippocampus, and amygdala in female rats using quantitative real‐time polymerase chain reaction (qRT‐PCR). A selective agonist, Nestorone (16‐methylene‐17 alpha‐acetoxy‐19‐nor‐pregn‐4‐ene‐3,20‐dione) activated PRs, and the effect on excitability and α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptor (AMPAR)–mediated synaptic transmission of EC neurons was studied using electrophysiology. Finally, we assessed PR regulation of epileptic seizures and status epilepticus (SE) induced by lithium‐pilocarpine in female rats with the global deletion of PRs (PR knockout; PRKO) using video electroencephalography (‐EEG). Results Limbic regions EC, hippocampus, and amygdala robustly expressed PR messenger RNA (mRNA). Nestorone (16‐methylene‐17 alpha‐acetoxy‐19‐nor‐pregn‐4‐ene‐3,20‐dione) treatment reduced the action potential threshold of layer II/III EC neurons and increased the frequency of AMPA receptor–mediated synaptic currents of ovariectomized and estrogen‐primed female rats. Female rats lacking PRs (PRKO) experienced a shorter duration, less intense, and less fatal SE than wild‐type (WT) animals. Furthermore, Nestorone treatment caused seizure exacerbation in the WT epileptic animals, but not in the PRKO epileptic animals. Significance Activation of PRs expressed in the EC and hippocampus increased neuronal excitability and worsened seizures. These receptors may play a role in catamenial epilepsy.

Objective Bilateral synchronous cortical activity occurs during sleep, attention, and seizures. Canonical models place the thalamus at the center of bilateral cortical synchronization because it generates bilateral sleep spindle oscillations and primarily generalized absence seizures. However, classical studies suggest that the corpus callosum mediates bilateral cortical synchronization. Methods We mapped the spread of right frontal lobe‐onset, focal to bilateral seizures in mice and modified it using chemo and optogenetic suppression of motor thalamic nucleus and corpus callosotomy. Results Seizures from the right cortex spread faster to the left cortex than to the left thalamus. The 2 thalami have minimal monosynaptic commissural connections compared to the massive commissure corpus callosum. Chemogenetic and closed‐loop optogenetic inhibition of the right ventrolateral thalamic nucleus did not alter inter‐hemispheric seizure spread. However, anterior callosotomy delayed bilateral seizure oscillations. Interpretation Thalamocortical oscillations amplify focal onset motor seizures, and corpus callosum spreads them bilaterally. ANN NEUROL 2022;91:682–696

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Bacterial biofilm segmentation poses significant challenges due to lack of apparent structure, poor imaging resolution, limited contrast between conterminous cells and high density of cells that overlap. Although there exist bacterial segmentation algorithms in the existing art, they fail to delineate cells in dense biofilms, especially in 3D imaging scenarios in which the cells are growing and subdividing in a complex manner. A graph-based data clustering method, LCuts, is presented with the application on bacterial cell segmentation. By constructing a weighted graph with node features in locations and principal orientations, the proposed method can automatically classify and detect differently oriented aggregations of linear structures (represent by bacteria in the application). The method assists in the assessment of several facets, such as bacterium tracking, cluster growth, and mapping of migration patterns of bacterial biofilms. Quantitative and qualitative measures for 2D data demonstrate the superiority of proposed method over the state of the art. Preliminary 3D results exhibit reliable classification of the cells with 97% accuracy.

In the study of neurons, morphology influences function. The complexity in the structure of neurons poses a challenge in the identification and analysis of similar and dissimilar neuronal cells. Existing methodologies carry out structural and geometrical simplifications, which substantially change the morphological statistics. Using digitally-reconstructed neurons, we extend the work of Path2Path as ElasticPath2Path, which seamlessly integrates the graph-theoretic and differentialgeometric frameworks. By decomposing a neuron into a set of paths, we derive graph metrics, which are path concurrence and path hierarchy. Next, we model each path as an elastic string to compute the geodesic distance between the paths of a pair of neurons. Later, we formulate the problem of finding the distance between two neurons as a path assignment problem with a cost function combining the graph metrics and the geodesic deformation of paths. ElasticPath2Path is shown to have superior performance over the state of the art.Index Termselastic curves, neuron matching, bioimage analysis, neuron morphology, quantitative image analysis.

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