Tuesday, December 26th, 2023

Time	Event
12:32a	Neural circuits underlying context-dependent competition between defensive actions in Drosophila larva To ensure their survival, animals must be able to respond adaptively to threats within their environment. However, the precise neural circuit mechanisms that underlie such flexible defensive behaviors remain poorly understood. Using neuronal manipulations, machine-learning-based behavioral detection, Electron Microscopy (EM) connectomics and calcium imaging in Drosophila larva, we have mapped the second-order interneurons differentially involved in the competition between different defensive actions and the main pathways to the motor side putatively involved in inhibiting startle-type behaviors and promoting escape behaviors in a context dependent manner. We found that mechanosensory stimulation modulates the nociceptive escape sequences and inhibits C-shape bends and Rolls in favor of startle-like behaviors. This suggests a competition between mechanosensory-induced startle responses and escape behaviors. Structural and functional connectivity revealed that the second order interneurons receive their main input from projection neurons that integrate mechanosensory and nociceptive stimuli. The analysis of their postsynaptic connectivity in EM revealed that they make indirect connections to the pre-motor and motor neurons. Finally, we identify a pair of descending neurons that could promote modulate the escape sequence and promote startle behaviors. Altogether, these results characterize the pathways involved in the Startle and Escape competition, modulated by the sensory context. (Comment on this)
12:32a	Transcriptional analysis of neuronal ensembles of alcohol memories within the nucleus accumbens Alcohol-associated memories play an important role in relapse in alcohol use disorder. Disrupting these memories, which become labile upon retrieval, through interference with their reconsolidation process, could reduce relapse. Memories are thought to be encoded within specific patterns of sparsely distributed neurons, called neuronal ensembles. Here, we explored the role of neuronal ensembles in alcohol-memory reconsolidation and relapse and characterized their transcriptional signature. Upon retrieving alcohol-related memories, we observed increased neuronal activation in the nucleus accumbens (NAc). We established the causal role of these NAc ensembles in alcohol-memory reconsolidation using the Daun02 method with the Fos-LacZ transgenic rat, which expresses {beta}-galactosidase ({beta}-gal) under the Fos promoter, allowing the selective ablation of activated neurons. Selective inactivation of the active NAc neuronal ensemble produced a long-lasting attenuation of relapse. Through fluorescence-activated cell sorting (FACS) and RNA sequencing, we found a unique transcriptional fingerprint in activated Fos-positive neuronal ensembles in NAc following alcohol memory retrieval (vs. no retrieval controls) that was not present in the Fos-negative neurons. Our findings underscore the critical role of NAc neuronal ensembles in alcohol-associated memory reconsolidation. These neurons have a unique transcriptional profile that can provide novel targets for reducing alcohol relapse. (Comment on this)
12:32a	Glucocorticoids rapidly modulate CaV1.2-mediated calcium signals through Kv2.1 channel clusters in hippocampal neurons The precise regulation of Ca2+ signals plays a crucial role in the physiological functions of neurons. Here, we investigated the rapid effect of glucocorticoids on Ca2+ signals in hippocampal neurons. In cultured hippocampal neurons, glucocorticoids inhibited the spontaneous somatic Ca2+ spikes generated by Kv2.1-organized Ca2+ microdomains. Furthermore, glucocorticoids rapidly reduced the cell surface expressions of Kv2.1 and CaV1.2 channels in hippocampal neurons. In HEK293 cells transfected with Kv2.1 alone, glucocorticoids significantly reduced the surface expression of Kv2.1 with little effect on K+ currents. Glucocorticoids inhibited CaV1.2 currents but had no effect on the cell surface expression of CaV1.2 in HEK293 cells transfected with CaV1.2 alone. Notably, in the presence of wild-type Kv2.1, glucocorticoids caused a decrease in the surface expression of CaV1.2 channels in HEK293 cells. However, this effect was not observed in the presence of non-clustering Kv2.1S586A mutant channels. Live cell imaging showed that glucocorticoids rapidly decreased Kv2.1 clusters on the plasma membrane. Correspondingly, western blot results indicated a significant increase in the cytoplasmic level of Kv2.1, suggesting the endocytosis of Kv2.1 clusters. Glucocorticoids rapidly decreased the intracellular cAMP concentration and the phosphorylation level of PKA in hippocampal neurons. The PKA inhibitor H89 mimicked the effect of glucocorticoids on Kv2.1, while the PKA agonist forskolin abrogated the effect. In conclusion, glucocorticoids rapidly regulate CaV1.2-mediated Ca2+ signals in hippocampal neurons by promoting the endocytosis of Kv2.1 channel clusters through reducing PKA activity. (Comment on this)
12:32a	A neurotransmitter atlas of the nervous system of C.elegans males and hermaphrodites Assigning neurotransmitter identity to neurons is key to understanding information flow in a nervous system. It also provides valuable entry points for studying the development and plasticity of neuronal identity features. Neurotransmitter identities have been assigned to most neurons in the C. elegans nervous system through the expression pattern analysis of neurotransmitter pathway genes that encode neurotransmitter biosynthetic enzymes or transporters. However, many of these assignments have relied on multicopy reporter transgenes that may lack relevant cis-regulatory information and therefore may not provide an accurate picture of neurotransmitter usage. We analyzed the expression patterns of 13 CRISPR/Cas9-engineered reporter knock-in strains, which report on the deployment of all main types of neurotransmitters in C. elegans (glutamate, acetylcholine, GABA, serotonin, tyramine, and octopamine) throughout the entire nervous system of both the hermaphrodite and the male. Our analysis reveals novel sites of expression of these neurotransmitter systems within both neurons and glia and defines neurons that may be exclusively neuropeptidergic. Furthermore, we also identified unusual combinations of expression of monoaminergic synthesis pathway genes, suggesting the existence of novel monoaminergic transmitters. Our analysis results in what constitutes the most extensive nervous system-wide map of neurotransmitter usage to date, paving the way for a better understanding of neuronal communication in C. elegans. (Comment on this)
12:32a	Classification of iPSC-Derived Cultures Using Convolutional Neural Networks to Identify Single Differentiated Neurons for Isolation or Measurement Understanding neurodegenerative disease pathology depends on a close examination of neurons and their processes. However, image-based single-cell analyses of neurons often require laborious and time-consuming manual classification tasks. Here, we present a machine learning approach leveraging convolutional neural network (CNN) models that have the capability to accurately identify various classes of neuronal images, including single neurons. We developed the Single Neuron Identification Model (SNIM20) which was trained on a dataset of induced pluripotent stem cell (iPSC)-derived motor neurons, containing over 12,000 images from 20 distinct classes. SNIM20 is built in TensorFlow and trained on images of differentiated iPSC cultures stained for nuclei and microtubules. This classifier demonstrated high predictive accuracy (AUC = 0.99) for distinguishing single neurons. Additionally, the 2-stage training framework can be used more broadly for cellular classification tasks. A variation was successfully trained on images of a human osteosarcoma cell line (U2OS) for single-cell classification (AUC = 0.99). While this system was primarily designed for single-cell microraft-based identification and capture, it also works with cells in standard formats. We additionally explore the impact of specific fluorescent channels and brightfield images, class groupings, and transfer learning on the quality of the classification. This framework can both assist in high throughput neuronal or cellular identification and be used to train a custom classifier for the user's needs. (Comment on this)
3:16a	Visual information is broadcast among cortical areas in discrete channels The authors have withdrawn this manuscript due to a duplicate posting of manuscript number BIORXIV/2018/469114. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. The correct preprint can be found at doi: 10.1101/469114 (Comment on this)

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