The exocyst subunit Sec15 is critical for proper synaptic development and function at the Drosophila NMJ.

The exocyst protein complex is important for targeted vesicle fusion in a variety of cell types, however, its function in neurons is still not entirely known. We found that presynaptic knockdown (KD) of the exocyst component sec15 by transgenic RNAi expression caused a number of unexpected morphological and physiological defects in the synapse. These include the development of active zones (AZ) devoid of essential presynaptic proteins, an increase in the branching of the presynaptic arbor, the appearance of satellite boutons, and a decrease in the amplitude of stimulated postsynaptic currents as well as a decrease in the frequency of spontaneous synaptic vesicle release. We also found the release of extracellular vesicles from the presynaptic neuron was greatly diminished in the Sec15 KDs. These effects were mimicked by presynaptic knockdown of Rab11, a protein known to interact with the exocyst. sec15 RNAi expression caused an increase in phosphorylated Mothers against decapentaplegic (pMad) in the presynaptic terminal, an indication of enhanced bone morphogenic protein (BMP) signaling. Some morphological phenotypes caused by Sec15 knockdown were reduced by attenuation of BMP signaling through knockdown of wishful thinking (Wit), while other phenotypes were unaffected. Individual knockdown of multiple proteins of the exocyst complex also displayed a morphological phenotype similar to Sec15 KD. We conclude that Sec15, functioning as part of the exocyst complex, is critically important for proper formation and function of neuronal synapses. We propose a model in which Sec15 is involved in the trafficking of vesicles from the recycling endosome to the cell membrane as well as possibly trafficking extracellular vesicles for presynaptic release and these processes are necessary for the correct structure and function of the synapse.

Aggressively optimizing validation statistics can degrade interpretability of data-driven materials models.

One of the key factors in enabling trust in artificial intelligence within the materials science community is the interpretability (or explainability) of the underlying models used. By understanding what features were used to generate predictions, scientists are then able to critically evaluate the credibility of the predictions and gain new insights. Here, we demonstrate that ignoring hyperparameters viewed as less impactful to the overall model performance can deprecate model explainability. Specifically, we demonstrate that random forest models trained using unconstrained maximum depths, in accordance with accepted best practices, often can report a randomly generated feature as being one of the most important features in generated predictions for classifying an alloy as being a high entropy alloy. We demonstrate that this is the case for impurity, permutation, and Shapley importance rankings, and the latter two showed no strong structure in terms of optimal hyperparameters. Furthermore, we demonstrate that, for the case of impurity importance rankings, only optimizing the validation accuracy, as is also considered standard in the random forest community, yields models that prefer the random feature in generating their predictions. We show that by adopting a Pareto optimization strategy to model performance that balances validation statistics with the differences between the training and validation statistics, one obtains models that reject random features and thus balance model predictive power and explainability.

Cerebellar contribution to autism-relevant behaviors in fragile X syndrome models.

Cerebellar dysfunction has been linked to autism spectrum disorders (ASDs). Although cerebellar pathology has been observed in individuals with fragile X syndrome (FXS) and in mouse models of the disorder, a cerebellar functional contribution to ASD-relevant behaviors in FXS has yet to be fully characterized. In this study, we demonstrate a critical cerebellar role for Fmr1 (fragile X messenger ribonucleoprotein 1) in ASD-relevant behaviors. First, we identify reduced social behaviors, sensory hypersensitivity, and cerebellar dysfunction, with loss of cerebellar Fmr1. We then demonstrate that cerebellar-specific expression of Fmr1 is sufficient to impact social, sensory, cerebellar dysfunction, and cerebro-cortical hyperexcitability phenotypes observed in global Fmr1 mutants. Moreover, we demonstrate that targeting the ASD-implicated cerebellar region Crus1 ameliorates behaviors in both cerebellar-specific and global Fmr1 mutants. Together, these results demonstrate a critical role for the cerebellar contribution to FXS-related behaviors, with implications for future therapeutic strategies.