Sleep EEG signatures in mouse models of 15q11.2-13.1 duplication (Dup15q) syndrome.

BACKGROUND: Sleep disturbances are a prevalent and complex comorbidity in neurodevelopmental disorders (NDDs). Dup15q syndrome (duplications of 15q11.2-13.1) is a genetic disorder highly penetrant for NDDs such as autism and intellectual disability and it is frequently accompanied by significant disruptions in sleep patterns. The 15q critical region harbors genes crucial for brain development, notably UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABAAR) genes. We previously described an electrophysiological biomarker of the syndrome, marked by heightened beta oscillations (12-30 Hz) in individuals with Dup15q syndrome, akin to electroencephalogram (EEG) alterations induced by allosteric modulation of GABAARs. Those with Dup15q syndrome exhibited increased beta oscillations during the awake resting state and during sleep, and they showed profoundly abnormal NREM sleep. This study aims to assess the translational validity of these EEG signatures and to delve into their neurobiological underpinnings by quantifying sleep physiology in chromosome-engineered mice with maternal (matDp/ + mice) or paternal (patDp/ + mice) inheritance of the full 15q11.2-13.1-equivalent duplication, and mice with duplication of just the UBE3A gene (Ube3a overexpression mice; Ube3a OE mice) and comparing the sleep metrics with their respective wildtype (WT) littermate controls. METHODS: We collected 48-h EEG/EMG recordings from 35 (23 male, 12 female) 12-24-week-old matDp/ + , patDp/ + , Ube3a OE mice, and their WT littermate controls. We quantified baseline sleep, sleep fragmentation, spectral power dynamics during sleep states, and recovery following sleep deprivation. Within each group, distinctions between Dup15q mutant mice and WT littermate controls were evaluated using analysis of variance (ANOVA) and student's t-test. The impact of genotype and time was discerned through repeated measures ANOVA, and significance was established at p < 0.05. RESULTS: Our study revealed that across brain states, matDp/ + mice mirrored the elevated beta oscillation phenotype observed in clinical EEGs from individuals with Dup15q syndrome. Time to sleep onset after light onset was significantly reduced in matDp/ + and Ube3a OE mice. However, NREM sleep between Dup15q mutant and WT littermate mice remained unaltered, suggesting a divergence from the clinical presentation in humans. Additionally, while increased beta oscillations persisted in matDp/ + mice after 6-h of sleep deprivation, recovery NREM sleep remained unaltered in all groups, thus suggesting that these mice exhibit resilience in the fundamental processes governing sleep-wake regulation. CONCLUSIONS: Quantification of mechanistic and translatable EEG biomarkers is essential for advancing our understanding of NDDs and their underlying pathophysiology. Our study of sleep physiology in the Dup15q mice underscores that the beta EEG biomarker has strong translational validity, thus opening the door for pre-clinical studies of putative drug targets, using the biomarker as a translational measure of drug-target engagement. The unaltered NREM sleep may be due to inherent differences in neurobiology between mice and humans. These nuanced distinctions highlight the complexity of sleep disruptions in Dup15q syndrome and emphasize the need for a comprehensive understanding that encompasses both shared and distinct features between murine models and clinical populations.

Alteration of synaptic protein composition during developmental synapse maturation.

The postsynaptic density (PSD) is a collection of specialized proteins assembled beneath the postsynaptic membrane of dendritic spines. The PSD proteome comprises ~1000 proteins, including neurotransmitter receptors, scaffolding proteins and signalling enzymes. Many of these proteins have essential roles in synaptic function and plasticity. During brain development, changes are observed in synapse density and in the stability and shape of spines, reflecting the underlying molecular maturation of synapses. Synaptic protein composition changes in terms of protein abundance and the assembly of protein complexes, supercomplexes and the physical organization of the PSD. Here, we summarize the developmental alterations of postsynaptic protein composition during synapse maturation. We describe major PSD proteins involved in postsynaptic signalling that regulates synaptic plasticity and discuss the effect of altered expression of these proteins during development. We consider the abnormality of synaptic profiles and synaptic protein composition in the brain in neurodevelopmental disorders such as autism spectrum disorders. We also explain differences in synapse development between rodents and primates in terms of synaptic profiles and protein composition. Finally, we introduce recent findings related to synaptic diversity and nanoarchitecture and discuss their impact on future research. Synaptic protein composition can be considered a major determinant and marker of synapse maturation in normality and disease.

Transcriptomic dysregulation and autistic-like behaviors in Kmt2c haploinsufficient mice rescued by an LSD1 inhibitor.

Recent studies have consistently demonstrated that the regulation of chromatin and gene transcription plays a pivotal role in the pathogenesis of neurodevelopmental disorders. Among many genes involved in these pathways, KMT2C, encoding one of the six known histone H3 lysine 4 (H3K4) methyltransferases in humans and rodents, was identified as a gene whose heterozygous loss-of-function variants are causally associated with autism spectrum disorder (ASD) and the Kleefstra syndrome phenotypic spectrum. However, little is known about how KMT2C haploinsufficiency causes neurodevelopmental deficits and how these conditions can be treated. To address this, we developed and analyzed genetically engineered mice with a heterozygous frameshift mutation of Kmt2c (Kmt2c+/fs mice) as a disease model with high etiological validity. In a series of behavioral analyses, the mutant mice exhibit autistic-like behaviors such as impairments in sociality, flexibility, and working memory, demonstrating their face validity as an ASD model. To investigate the molecular basis of the observed abnormalities, we performed a transcriptomic analysis of their bulk adult brains and found that ASD risk genes were specifically enriched in the upregulated differentially expressed genes (DEGs), whereas KMT2C peaks detected by ChIP-seq were significantly co-localized with the downregulated genes, suggesting an important role of putative indirect effects of Kmt2c haploinsufficiency. We further performed single-cell RNA sequencing of newborn mouse brains to obtain cell type-resolved insights at an earlier stage. By integrating findings from ASD exome sequencing, genome-wide association, and postmortem brain studies to characterize DEGs in each cell cluster, we found strong ASD-associated transcriptomic changes in radial glia and immature neurons with no obvious bias toward upregulated or downregulated DEGs. On the other hand, there was no significant gross change in the cellular composition. Lastly, we explored potential therapeutic agents and demonstrate that vafidemstat, a lysine-specific histone demethylase 1 (LSD1) inhibitor that was effective in other models of neuropsychiatric/neurodevelopmental disorders, ameliorates impairments in sociality but not working memory in adult Kmt2c+/fs mice. Intriguingly, the administration of vafidemstat was shown to alter the vast majority of DEGs in the direction to normalize the transcriptomic abnormalities in the mutant mice (94.3 and 82.5% of the significant upregulated and downregulated DEGs, respectively, P < 2.2 × 10-16, binomial test), which could be the molecular mechanism underlying the behavioral rescuing. In summary, our study expands the repertoire of ASD models with high etiological and face validity, elucidates the cell-type resolved molecular alterations due to Kmt2c haploinsufficiency, and demonstrates the efficacy of an LSD1 inhibitor that might be generalizable to multiple categories of psychiatric disorders along with a better understanding of its presumed mechanisms of action.

FAM81A is a postsynaptic protein that regulates the condensation of postsynaptic proteins via liquid-liquid phase separation.

Proteome analyses of the postsynaptic density (PSD), a proteinaceous specialization beneath the postsynaptic membrane of excitatory synapses, have identified several thousands of proteins. While proteins with predictable functions have been well studied, functionally uncharacterized proteins are mostly overlooked. In this study, we conducted a comprehensive meta-analysis of 35 PSD proteome datasets, encompassing a total of 5,869 proteins. Employing a ranking methodology, we identified 97 proteins that remain inadequately characterized. From this selection, we focused our detailed analysis on the highest-ranked protein, FAM81A. FAM81A interacts with PSD proteins, including PSD-95, SynGAP, and NMDA receptors, and promotes liquid-liquid phase separation of those proteins in cultured cells or in vitro. Down-regulation of FAM81A in cultured neurons causes a decrease in the size of PSD-95 puncta and the frequency of neuronal firing. Our findings suggest that FAM81A plays a crucial role in facilitating the interaction and assembly of proteins within the PSD, and its presence is important for maintaining normal synaptic function. Additionally, our methodology underscores the necessity for further characterization of numerous synaptic proteins that still lack comprehensive understanding.

End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imaging.

Deep learning is a powerful tool for neural decoding, broadly applied to systems neuroscience and clinical studies. Interpretable and transparent models that can explain neural decoding for intended behaviors are crucial to identifying essential features of deep learning decoders in brain activity. In this study, we examine the performance of deep learning to classify mouse behavioral states from mesoscopic cortex-wide calcium imaging data. Our convolutional neural network (CNN)-based end-to-end decoder combined with recurrent neural network (RNN) classifies the behavioral states with high accuracy and robustness to individual differences on temporal scales of sub-seconds. Using the CNN-RNN decoder, we identify that the forelimb and hindlimb areas in the somatosensory cortex significantly contribute to behavioral classification. Our findings imply that the end-to-end approach has the potential to be an interpretable deep learning method with unbiased visualization of critical brain regions.

Remodeling of the postsynaptic proteome in male mice and marmosets during synapse development.

Postsynaptic proteins play crucial roles in synaptic function and plasticity. During brain development, alterations in synaptic number, shape, and stability occur, known as synapse maturation. However, the postsynaptic protein composition changes during development are not fully understood. Here, we show the trajectory of the postsynaptic proteome in developing male mice and common marmosets. Proteomic analysis of mice at 2, 3, 6, and 12 weeks of age shows that proteins involved in synaptogenesis are differentially expressed during this period. Analysis of published transcriptome datasets shows that the changes in postsynaptic protein composition in the mouse brain after 2 weeks of age correlate with gene expression changes. Proteomic analysis of marmosets at 0, 2, 3, 6, and 24 months of age show that the changes in the marmoset brain can be categorized into two parts: the first 2 months and after that. The changes observed in the first 2 months are similar to those in the mouse brain between 2 and 12 weeks of age. The changes observed in marmoset after 2 months old include differential expression of synaptogenesis-related molecules, which hardly overlap with that in mice. Our results provide a comprehensive proteomic resource that underlies developmental synapse maturation in rodents and primates.

The blues and rhythm.

Most organisms, including humans, show daily rhythms in many aspects of physiology and behavior, and abnormalities in the rhythms are potential risk factors for various diseases. Mood disorders such as depression are no exception. Accumulating evidence suggests strong associations between circadian disturbances and the development of depression. Numerous studies have shown that interventions to circadian rhythms trigger depression-like phenotypes in human cases and animal models. Conversely, mood changes can affect circadian rhythms as symptoms of depression. Our preliminary data suggest that the phosphorylation signal pathway of the clock protein may act as a common pathway for mood and clock regulation. We hypothesize that mood regulation and circadian rhythms may influence each other and may share a common regulatory mechanism. This review provides an overview of circadian disturbances in animal models and human patients with depression.

Comparing the effects of antimicrobial stewardship at primary emergency centers.

BACKGROUND: Antimicrobial prescription rates tend to be high in outpatient settings and Primary Emergency Medical Centers (PECs) in Japan encounter difficulties in implementing antimicrobial stewardship programs (ASPs). While a nudge-based ASP publishing monthly newsletters reduces inappropriate prescription of oral third-generation cephalosporins (3GCs), which requires considerable effort. Therefore, developing more preferable ASP models in PECs is essential. METHODS: We conducted a three-center, retrospective observational study. Himeji City Emergency Medical Center (Site A) introduced a facility-specific guideline for antimicrobial stewardship with reference to national guidelines. The Kobe Children's Primary Emergency Medical Center (Site B) provided the results of monitoring antibiotics prescription in a monthly newsletter. The Hanshin-Kita Children's First-Aid Center (Site C) did not perform a specific ASP. Prescription rates for 3GCs were categorized into pre- and post-intervention and compared using Poisson regression analysis. The difference-in-difference method was used to assess the effect of these interventions. RESULTS: The numbers of patients pre- and post- intervention were 177,126 and 91,251, respectively. The 3GCs prescription rate at Site A, Site B, and Site C decreased from 6.7%, 4.2%, and 6.1% in 2016 to 2.3%, 1.0%, and 2.0% in 2019, respectively. Site B had a greater reduction than Site A and Site C (relative risk [RR] 0.71 [95% confidence interval (CI): 0.62-0.82]; p < 0.001, RR 0.71, [95% CI: 0.62-0.81]; p < 0.001). There was no significant difference between Site A and Site C (RR 1.00 [95% CI 0.88-1.13]; p = 0.963). CONCLUSION: A facility-specific guideline was less effective than a nudge-based ASP for decreasing oral 3GC prescriptions in PECs.

Social circuits and their dysfunction in autism spectrum disorder.

Social behaviors, how individuals act cooperatively and competitively with conspecifics, are widely seen across species. Rodents display various social behaviors, and many different behavioral paradigms have been used for investigating their neural circuit bases. Social behavior is highly vulnerable to brain network dysfunction caused by neurological and neuropsychiatric conditions such as autism spectrum disorders (ASDs). Studying mouse models of ASD provides a promising avenue toward elucidating mechanisms of abnormal social behavior and potential therapeutic targets for treatment. In this review, we outline recent progress and key findings on neural circuit mechanisms underlying social behavior, with particular emphasis on rodent studies that monitor and manipulate the activity of specific circuits using modern systems neuroscience approaches. Social behavior is mediated by a distributed brain-wide network among major cortical (e.g., medial prefrontal cortex (mPFC), anterior cingulate cortex, and insular cortex (IC)) and subcortical (e.g., nucleus accumbens, basolateral amygdala (BLA), and ventral tegmental area) structures, influenced by multiple neuromodulatory systems (e.g., oxytocin, dopamine, and serotonin). We particularly draw special attention to IC as a unique cortical area that mediates multisensory integration, encoding of ongoing social interaction, social decision-making, emotion, and empathy. Additionally, a synthesis of studies investigating ASD mouse models demonstrates that dysfunctions in mPFC-BLA circuitry and neuromodulation are prominent. Pharmacological rescues by local or systemic (e.g., oral) administration of various drugs have provided valuable clues for developing new therapeutic agents for ASD. Future efforts and technological advances will push forward the next frontiers in this field, such as the elucidation of brain-wide network activity and inter-brain neural dynamics during real and virtual social interactions, and the establishment of circuit-based therapy for disorders affecting social functions.

Germ-cell-specific transcriptome analysis illuminates the chromatin and ubiquitin pathway in autism spectrum disorders.

Accumulating epidemiological studies have suggested a positive association between advanced paternal age at conception and the increased risk of neurodevelopmental outcomes such as autism spectrum disorder (ASD) in their children. Recent biological studies using human sperm have identified increased de novo mutations in aged fathers, and hyper- or hypomethylation has been identified in the sperm from aged rodents. Dysregulation of DNA methylation in sperm may explain the transgenerational effects on the pathogenesis of ASD. However, compared to these epigenetic changes in the sperm of aged males, the effects of inherited predisposition from germ cells are largely unknown. Here, we use single-cell transcriptome data sets from 13 cell lines, including 12 ASD-associated CNVs models and control, that are performed neural differentiation from mouse embryonic stem cells. This study performed comprehensive bioinformatic analyses such as gene ontology (GO), network, pathway, and upstream regulator analyses. Through these analyses, we identify several susceptible pathways, such as chromatin and ubiquitin, in addition to translational and oxidative phosphorylation. Our results suggest that dysregulation of epigenetic chromosome remodeling and ubiquitin-proteasome pathway in the germ cell is a possible modulator for subsequent differentiated cells, sperm, and egg, as a risk factor for the neurodevelopmental disorder.

[Analysis of cortical network dynamics in the behavioral state of a mouse model of autism].

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral abnormalities such as poor social communication and stereotyped/repetitive behaviors. Functional dynamics among multiple cortical areas are associated with processing sensory information and planning and executing behavioral expressions. However, the reconfiguration of large-scale functional network dynamics during behaviors remains to be elucidated in ASD. In this review, we describe our virtual reality (VR) based real-time imaging system which allowed us to investigate wide-field cortical activity in voluntarily behaving mice. We previously generated a mouse model of ASD with chromosome 15q11-13 duplication (15q dup), one of the most frequent genomic abnormalities, and reported that 15q dup mice display ASD-like behaviors. Using this system, we examined the functional cortical network during behaviors in 15q dup mice. Pair-wise correlation of cortical area activity on a time scale of a second was calculated to represent the dynamic state of cortical functional connectivity (FC). A graph theoretical network analysis was then conducted to illustrate rapid and robust behavior-state-dependent cortical network reconfiguration. Our VR-based real-time imaging system provides invaluable information to understand FC dynamics linked to a behavioral abnormality of neuropsychiatric disorders.

An old model with new insights: endogenous retroviruses drive the evolvement toward ASD susceptibility and hijack transcription machinery during development.

The BTBR T+Itpr3tf/J (BTBR/J) strain is one of the most valid models of idiopathic autism, serving as a potent forward genetics tool to dissect the complexity of autism. We found that a sister strain with an intact corpus callosum, BTBR TF/ArtRbrc (BTBR/R), showed more prominent autism core symptoms but moderate ultrasonic communication/normal hippocampus-dependent memory, which may mimic autism in the high functioning spectrum. Intriguingly, disturbed epigenetic silencing mechanism leads to hyperactive endogenous retrovirus (ERV), a mobile genetic element of ancient retroviral infection, which increases de novo copy number variation (CNV) formation in the two BTBR strains. This feature makes the BTBR strain a still evolving multiple-loci model toward higher ASD susceptibility. Furthermore, active ERV, analogous to virus infection, evades the integrated stress response (ISR) of host defense and hijacks the transcriptional machinery during embryonic development in the BTBR strains. These results suggest dual roles of ERV in the pathogenesis of ASD, driving host genome evolution at a long-term scale and managing cellular pathways in response to viral infection, which has immediate effects on embryonic development. The wild-type Draxin expression in BTBR/R also makes this substrain a more precise model to investigate the core etiology of autism without the interference of impaired forebrain bundles as in BTBR/J.

Virtual reality-based real-time imaging reveals abnormal cortical dynamics during behavioral transitions in a mouse model of autism.

Functional connectivity (FC) can provide insight into cortical circuit dysfunction in neuropsychiatric disorders. However, dynamic changes in FC related to locomotion with sensory feedback remain to be elucidated. To investigate FC dynamics in locomoting mice, we develop mesoscopic Ca2+ imaging with a virtual reality (VR) environment. We find rapid reorganization of cortical FC in response to changing behavioral states. By using machine learning classification, behavioral states are accurately decoded. We then use our VR-based imaging system to study cortical FC in a mouse model of autism and find that locomotion states are associated with altered FC dynamics. Furthermore, we identify FC patterns involving the motor area as the most distinguishing features of the autism mice from wild-type mice during behavioral transitions, which might correlate with motor clumsiness in individuals with autism. Our VR-based real-time imaging system provides crucial information to understand FC dynamics linked to behavioral abnormality of neuropsychiatric disorders.

Mood phenotypes in rodent models with circadian disturbances.

Many physiological functions with approximately 24-h rhythmicity (circadian rhythms) are generated by an internal time-measuring system of the circadian clock. While sleep/wake cycles, feeding patterns, and body temperature are the most widely known physiological functions under the regulation of the circadian clock, physiological regulation by the circadian clock extends to higher brain functions. Accumulating evidence suggests strong associations between the circadian clock and mood disorders such as depression, but the underlying mechanisms of the functional relationship between them are obscure. This review overviews rodent models with disrupted circadian rhythms on depression-related responses. The animal models with circadian disturbances (by clock gene mutations and artifactual interventions) will help understand the causal link between the circadian clock and depression.

Increased self-triggered vocalizations in an epidermal growth factor-induced rat model for schizophrenia.

Rats elicit two types of ultrasonic vocalizations (USVs), positive (30-80 kHz; high pitch) and negative (10-30 kHz; low pitch) voices. As patients with schizophrenia often exhibit soliloquy-like symptoms, we explored whether an animal model for schizophrenia is similarly characterized by such self-triggered vocalizations. We prepared the animal model by administering an inflammatory cytokine, epidermal growth factor (EGF), to rat neonates, which later develop behavioral and electroencephalographic deficits relevant to schizophrenia. EGF model rats and controls at young (8-10 weeks old) and mature (12-14 weeks old) adult stages were subjected to acclimation, female pairing, and vocalization sessions. In acclimation sessions, low pitch USVs at the mature adult stage were more frequent in EGF model rats than in controls. In the vocalization session, the occurrences of low pitch self-triggered USVs were higher in EGF model rats in both age groups, although this group difference was eliminated by their risperidone treatment. Unlike conventional negative USVs of rats, however, the present low pitch self-triggered USVs had short durations of 10-30 ms. These results suggest the potential that self-triggered vocalization might serve as a translatable pathological trait of schizophrenia to animal models.

Species-specific formation of paraspeckles in intestinal epithelium revealed by characterization of NEAT1 in naked mole-rat.

Paraspeckles are mammalian-specific nuclear bodies built on the long noncoding RNA NEAT1_2 The molecular mechanisms of paraspeckle formation have been mainly studied using human or mouse cells, and it is not known if the same molecular components are involved in the formation of paraspeckles in other mammalian species. We thus investigated the expression pattern of NEAT1_2 in naked mole-rats (nNEAT1_2), which exhibit extreme longevity and lower susceptibility to cancer. In the intestine, nNEAT1_2 is widely expressed along the entire intestinal epithelium, which is different from the expression of mNeat1_2 that is restricted to the cells of the distal tip in mice. Notably, the expression of FUS, a FET family RNA binding protein, essential for the formation of paraspeckles both in humans and mice, was absent in the distal part of the intestinal epithelium in naked mole-rats. Instead, mRNAs of other FET family proteins EWSR1 and TAF15 were expressed in the distal region. Exogenous expression of these proteins in Fus-deficient murine embryonic fibroblast cells rescued the formation of paraspeckles. These observations suggest that nNEAT1_2 recruits a different set of RNA binding proteins in a cell type-specific manner during the formation of paraspeckles in different organisms.

A common epigenetic mechanism across different cellular origins underlies systemic immune dysregulation in an idiopathic autism mouse model.

Immune dysregulation plays a key role in the pathogenesis of autism. Changes occurring at the systemic level, from brain inflammation to disturbed innate/adaptive immune in the periphery, are frequently observed in patients with autism; however, the intrinsic mechanisms behind them remain elusive. We hypothesize a common etiology may lie in progenitors of different types underlying widespread immune dysregulation. By single-cell RNA sequencing (sc-RNA seq), we trace the developmental origins of immune dysregulation in a mouse model of idiopathic autism. It is found that both in aorta-gonad-mesonephros (AGM) and yolk sac (YS) progenitors, the dysregulation of HDAC1-mediated epigenetic machinery alters definitive hematopoiesis during embryogenesis and downregulates the expression of the AP-1 complex for microglia development. Subsequently, these changes result in the dysregulation of the immune system, leading to gut dysbiosis and hyperactive microglia in the brain. We further confirm that dysregulated immune profiles are associated with specific microbiota composition, which may serve as a biomarker to identify autism of immune-dysregulated subtypes. Our findings elucidate a shared mechanism for the origin of immune dysregulation from the brain to the gut in autism and provide new insight to dissecting the heterogeneity of autism, as well as the therapeutic potential of targeting immune-dysregulated autism subtypes.

mTOR-AKT Signaling in Cellular Clock Resetting Triggered by Osmotic Stress.

Aims: The circadian clock oscillates in a cell-autonomous manner with a period of ∼24 h, and the phase is regulated by various time cues such as light and temperature through multiple clock input pathways. We previously found that osmotic and oxidative stress strongly affected the circadian period and phase of cellular rhythms, and triple knockout of apoptosis signal-regulating kinase (ASK) family members, Ask1, Ask2, and Ask3, abolished the phase shift (clock resetting) induced by hyperosmotic pulse treatment. We aimed at exploring a key molecule(s) and signaling events in the clock input pathway dependent on ASK kinases. Results: The phase shift of the cellular clock induced by the hyperosmotic pulse treatment was significantly reduced by combined deficiencies of the clock(-related) genes, Dec1, Dec2, and E4 promoter-binding protein 4 (also known as Nfil3) (E4bp4). In addition, liquid chromatography mass/mass spectrometry (LC-MS/MS)-based proteomic analysis identified hyperosmotic pulse-induced phosphorylation of circadian locomotor output cycles caput (CLOCK) Ser845 in an AKT-dependent manner. We found that AKT kinase was phosphorylated at Ser473 (i.e., activated) in response to the hyperosmotic pulse experiments. Inhibition of mechanistic target of rapamycin (mTOR) kinase by Torin 1 treatment completely abolished the AKT activation, suppressed the phosphorylation of CLOCK Ser845, and blocked the clock resetting induced by the hyperosmotic pulse treatment. Innovation and Conclusions: We conclude that mTOR-AKT signaling is indispensable for the CLOCK Ser845 phosphorylation, which correlates with the clock resetting induced by the hyperosmotic pulse treatment. Immediate early induction of the clock(-related) genes and CLOCK carboxyl-terminal (C-terminal) region containing Ser845 also play important roles in the clock input pathway through redox-sensitive ASK kinases. Antioxid. Redox Signal. 37, 631-646.

Sensing the Sounds of Silence: A Pilot Study on the Detection of Model Mice of Autism Spectrum Disorder from Ultrasonic Vocalisations.

Studying the animal models of human neuropsychiatric disorders can facilitate the understanding of mechanisms of symptoms both physiologically and genetically. Previous studies have shown that ultrasonic vocalisations (USVs) of mice might be efficient markers to distinguish the wild type group and the model of autism spectrum disorder (mASD). Nevertheless, in-depth analysis of these 'silence' sounds by leveraging the power of advanced computer audition technologies (e. g., deep learning) is limited. To this end, we propose a pilot study on using a large-scale pre-trained audio neural network to extract high-level representations from the USVs of mice for the task on detection of mASD. Experiments have shown a best result reaching an unweighted average recall of 79.2 % for the binary classification task in a rigorous subject-independent scenario. To the best of our knowledge, this is the first time to analyse the sounds that cannot be heard by human beings for the detection of mASD mice. The novel findings can be significant to motivate future works with according means on studying animal models of human patients.