Ketogenic diet modifies ribosomal protein dysregulation in KMT2D Kabuki syndrome.

BACKGROUND: Kabuki syndrome (KS) is a genetic disorder caused by DNA mutations in KMT2D, a lysine methyltransferase that methylates histones and other proteins, and therefore modifies chromatin structure and subsequent gene expression. Ketones, derived from the ketogenic diet, are histone deacetylase inhibitors that can 'open' chromatin and encourage gene expression. Preclinical studies have shown that the ketogenic diet rescues hippocampal memory neurogenesis in mice with KS via the epigenetic effects of ketones. METHODS: Single-cell RNA sequencing and mass spectrometry-based proteomics were used to explore molecular mechanisms of disease in individuals with KS (n = 4) versus controls (n = 4). FINDINGS: Pathway enrichment analysis indicated that loss of function mutations in KMT2D are associated with ribosomal protein dysregulation at an RNA and protein level in individuals with KS (FDR <0.05). Cellular proteomics also identified immune dysregulation and increased abundance of other lysine modification and histone binding proteins, representing a potential compensatory mechanism. A 12-year-old boy with KS, suffering from recurrent episodes of cognitive decline, exhibited improved cognitive function and neuropsychological assessment performance after 12 months on the ketogenic diet, with concomitant improvement in transcriptomic ribosomal protein dysregulation. INTERPRETATION: Our data reveals that lysine methyltransferase deficiency is associated with ribosomal protein dysfunction, with secondary immune dysregulation. Diet and the production of bioactive molecules such as ketone bodies serve as a significant environmental factor that can induce epigenetic changes and improve clinical outcomes. Integrating transcriptomic, proteomic, and clinical data can define mechanisms of disease and treatment effects in individuals with neurodevelopmental disorders. FUNDING: This study was supported by the Dale NHMRC Investigator Grant (APP1193648) (R.D), Petre Foundation (R.D), and The Sydney Children's Hospital Foundation/Kids Research Early and Mid-Career Researcher Grant (E.T).

Trans-omic profiling uncovers molecular controls of early human cerebral organoid formation.

Defining the molecular networks orchestrating human brain formation is crucial for understanding neurodevelopment and neurological disorders. Challenges in acquiring early brain tissue have incentivized the use of three-dimensional human pluripotent stem cell (hPSC)-derived neural organoids to recapitulate neurodevelopment. To elucidate the molecular programs that drive this highly dynamic process, here, we generate a comprehensive trans-omic map of the phosphoproteome, proteome, and transcriptome of the exit of pluripotency and neural differentiation toward human cerebral organoids (hCOs). These data reveal key phospho-signaling events and their convergence on transcriptional factors to regulate hCO formation. Comparative analysis with developing human and mouse embryos demonstrates the fidelity of our hCOs in modeling embryonic brain development. Finally, we demonstrate that biochemical modulation of AKT signaling can control hCO differentiation. Together, our data provide a comprehensive resource to study molecular controls in human embryonic brain development and provide a guide for the future development of hCO differentiation protocols.

Multiomics of early epileptogenesis in mice reveals phosphorylation and dephosphorylation-directed growth and synaptic weakening.

To investigate the phosphorylation-based signaling and protein changes occurring early in epileptogenesis, the hippocampi of mice treated with pilocarpine were examined by quantitative mass spectrometry at 4 and 24 h post-status epilepticus at vast depth. Hundreds of posttranscriptional regulatory proteins were the major early targets of increased phosphorylation. At 24 h, many protein level changes were detected and the phosphoproteome continued to be perturbed. The major targets of decreased phosphorylation at 4 and 24 h were a subset of postsynaptic density scaffold proteins, ion channels, and neurotransmitter receptors. Many proteins targeted by dephosphorylation at 4 h also had decreased protein abundance at 24 h, indicating a phosphatase-mediated weakening of synapses. Increased translation was indicated by protein changes at 24 h. These observations, and many additional indicators within this multiomic resource, suggest that early epileptogenesis is characterized by signaling that stimulates both growth and a homeostatic response that weakens excitability.

Global quantitative proteomic analysis of aged mouse hippocampus.

Understanding the molecular changes associated with the aged brain forms the basis for developing potential strategies for slowing cognitive decline associated with normal aging. Focusing on the hippocampus, a critical brain region involved in learning and memory, we employed tandem mass tag methodology to investigate global proteomic changes that occur in advanced-aged (20-month) versus young (3-month) C57BL/6 male mice. Our analysis revealed the upregulation of 236 proteins in the old hippocampal proteome, including those enriched within several age-related processes, such as the adaptive immune response and molecular metabolic pathways, whereas downregulated proteins (88 in total) are mainly involved in axonogenesis and growth cone-related processes. Categorizing proteins by cell-type enrichment in the brain identified a general upregulation of proteins preferentially expressed in microglia, astrocytes, and oligodendrocytes. In contrast, proteins with neuron-specific expression displayed an overall age-related downregulation. By integrating our proteomic with our previously published transcriptomic data, we discovered a mild but significant positive correlation between mRNA and protein expression changes in the aged hippocampus. Therefore, this proteomic data is a valuable additional resource for further understanding age-related molecular mechanisms.

Tau forms synaptic nano-biomolecular condensates controlling the dynamic clustering of recycling synaptic vesicles.

Neuronal communication relies on the release of neurotransmitters from various populations of synaptic vesicles. Despite displaying vastly different release probabilities and mobilities, the reserve and recycling pool of vesicles co-exist within a single cluster suggesting that small synaptic biomolecular condensates could regulate their nanoscale distribution. Here, we performed a large-scale activity-dependent phosphoproteome analysis of hippocampal neurons in vitro and identified Tau as a highly phosphorylated and disordered candidate protein. Single-molecule super-resolution microscopy revealed that Tau undergoes liquid-liquid phase separation to generate presynaptic nanoclusters whose density and number are regulated by activity. This activity-dependent diffusion process allows Tau to translocate into the presynapse where it forms biomolecular condensates, to selectively control the mobility of recycling vesicles. Tau, therefore, forms presynaptic nano-biomolecular condensates that regulate the nanoscale organization of synaptic vesicles in an activity-dependent manner.

Latent Transformer Models for out-of-distribution detection.

Any clinically-deployed image-processing pipeline must be robust to the full range of inputs it may be presented with. One popular approach to this challenge is to develop predictive models that can provide a measure of their uncertainty. Another approach is to use generative modelling to quantify the likelihood of inputs. Inputs with a low enough likelihood are deemed to be out-of-distribution and are not presented to the downstream predictive model. In this work, we evaluate several approaches to segmentation with uncertainty for the task of segmenting bleeds in 3D CT of the head. We show that these models can fail catastrophically when operating in the far out-of-distribution domain, often providing predictions that are both highly confident and wrong. We propose to instead perform out-of-distribution detection using the Latent Transformer Model: a VQ-GAN is used to provide a highly compressed latent representation of the input volume, and a transformer is then used to estimate the likelihood of this compressed representation of the input. We demonstrate this approach can identify images that are both far- and near- out-of-distribution, as well as provide spatial maps that highlight the regions considered to be out-of-distribution. Furthermore, we find a strong relationship between an image's likelihood and the quality of a model's segmentation on it, demonstrating that this approach is viable for filtering out unsuitable images.

Migration and Migrant Labour in the Gig Economy: An Intervention.

In urban gig economies around the world, platform labour is predominantly migrant labour, yet research on the intersection of the gig economy and labour migration remains scant. Our experience with two action research projects, spanning six cities on four continents, has taught us how platform work impacts the structural vulnerability of migrant workers. This leads us to two claims that should recalibrate the gig economy research agenda. First, we argue that platform labour simultaneously degrades working conditions while offering migrants much-needed opportunities to improve their livelihoods. Second, we contend that the reclassification of gig workers as employees is by itself not sufficient to counter the precarisation of migrant gig work. Instead, we need ambitious policies at the intersection of immigration, social welfare, and employment regulation that push back against the digitally mediated commodification of migrant labour worldwide.

Classification of Features across Five CURE Networks Reveals Opportunities to Improve Course Design, Instruction, and Equity.

Course-based undergraduate research experiences (CUREs) are tools used to introduce students to authentic participation in science. Several specific CUREs have been shown to benefit students' interest and retention in the biological sciences. Nevertheless, CUREs vary greatly in terms of their context, methodology, and degree of research authenticity, so different types of CUREs may differently influence student outcomes. This programmatic diversity poses a challenge to educators who want to better understand which course components and features are reliably present in a CURE curriculum. To address these issues, we identified, catalogued, and classified 112 potential features of CUREs across the biosciences. To develop the list, we interviewed instructors experienced with teaching individual and large networked CUREs across a diversity of the biological disciplines, including: Squirrel-Net (field-based animal behavior), SEA-PHAGES (wet lab microbiology and computational microbiology), Tiny Earth (environmental and wet lab microbiology), PARE (environmental microbiology), and the Genomics Education Partnership (eukaryotic computational biology). Twenty-five interviewees contributed expert content in terms of CURE features and classification of those items into an organized list. The resulting list's categories encompasses student experiences with the following: (i) the scientific process; (ii) technical aspects of science; (iii) the professional development associated with research; and (iv) building scientific identity. The most striking insight was that CUREs vary widely in terms of which features they contain, since different CUREs will by necessity have different approaches to science and student involvement. We also identified several features commonly thought to be crucial to CUREs yet have ambiguous definitions. This ambiguity can potentially confound efforts to make CUREs research-authentic and aligned with the central goals of science. We disambiguate these terms and represent their varied meanings throughout the classification. We also provide instructor-friendly supplementary worksheets along with considerations for instructors interested in expanding their CURE course design, instruction, and equity.

Minimal expression of dysferlin prevents development of dysferlinopathy in dysferlin exon 40a knockout mice.

Dysferlin is a Ca2+-activated lipid binding protein implicated in muscle membrane repair. Recessive variants in DYSF result in dysferlinopathy, a progressive muscular dystrophy. We showed previously that calpain cleavage within a motif encoded by alternatively spliced exon 40a releases a 72 kDa C-terminal minidysferlin recruited to injured sarcolemma. Herein we use CRISPR/Cas9 gene editing to knock out murine Dysf exon 40a, to specifically assess its role in membrane repair and development of dysferlinopathy. We created three Dysf exon 40a knockout (40aKO) mouse lines that each express different levels of dysferlin protein ranging from ~ 90%, ~ 50% and ~ 10-20% levels of wild-type. Histopathological analysis of skeletal muscles from all 12-month-old 40aKO lines showed virtual absence of dystrophic features and normal membrane repair capacity for all three 40aKO lines, as compared with dysferlin-null BLAJ mice. Further, lipidomic and proteomic analyses on 18wk old quadriceps show all three 40aKO lines are spared the profound lipidomic/proteomic imbalance that characterises dysferlin-deficient BLAJ muscles. Collective results indicate that membrane repair does not depend upon calpain cleavage within exon 40a and that ~ 10-20% of WT dysferlin protein expression is sufficient to maintain the muscle lipidome, proteome and membrane repair capacity to crucially prevent development of dysferlinopathy.

Subcellular analysis of blood-brain barrier function by micro-impalement of vessels in acute brain slices.

The blood-brain barrier (BBB) is a tightly and actively regulated vascular barrier. Answering fundamental biological and translational questions about the BBB with currently available approaches is hampered by a trade-off between accessibility and biological validity. We report an approach combining micropipette-based local perfusion of capillaries in acute brain slices with multiphoton microscopy. Micro-perfusion offers control over the luminal solution and allows application of molecules and drug delivery systems, whereas the bath solution defines the extracellular milieu in the brain parenchyma. Here we show, that this combination allows monitoring of BBB transport at the cellular level, visualization of BBB permeation of cells and molecules in real-time and resolves subcellular details of the neurovascular unit. In combination with electrophysiology, it permits comparison of drug effects on neuronal activity following luminal versus parenchymal application. We further apply micro-perfusion to the human and mouse BBB of epileptic hippocampi highlighting its utility for translational research and analysis of therapeutic strategies.

Circuit-selective cell-autonomous regulation of inhibition in pyramidal neurons by Ste20-like kinase.

Maintaining an appropriate balance between excitation and inhibition is critical for neuronal information processing. Cortical neurons can cell-autonomously adjust the inhibition they receive to individual levels of excitatory input, but the underlying mechanisms are unclear. We describe that Ste20-like kinase (SLK) mediates cell-autonomous regulation of excitation-inhibition balance in the thalamocortical feedforward circuit, but not in the feedback circuit. This effect is due to regulation of inhibition originating from parvalbumin-expressing interneurons, while inhibition via somatostatin-expressing interneurons is unaffected. Computational modeling shows that this mechanism promotes stable excitatory-inhibitory ratios across pyramidal cells and ensures robust and sparse coding. Patch-clamp RNA sequencing yields genes differentially regulated by SLK knockdown, as well as genes associated with excitation-inhibition balance participating in transsynaptic communication and cytoskeletal dynamics. These data identify a mechanism for cell-autonomous regulation of a specific inhibitory circuit that is critical to ensure that a majority of cortical pyramidal cells participate in information coding.

The global polarisation of remote work.

The Covid-19 pandemic has led to the rise of digitally enabled remote work with consequences for the global division of labour. Remote work could connect labour markets, but it might also increase spatial polarisation. However, our understanding of the geographies of remote work is limited. Specifically, in how far could remote work connect employers and workers in different countries? Does it bring jobs to rural areas because of lower living costs, or does it concentrate in large cities? And how do skill requirements affect competition for employment and wages? We use data from a fully remote labour market-an online labour platform-to show that remote platform work is polarised along three dimensions. First, countries are globally divided: North American, European, and South Asian remote platform workers attract most jobs, while many Global South countries participate only marginally. Secondly, remote jobs are pulled to large cities; rural areas fall behind. Thirdly, remote work is polarised along the skill axis: workers with in-demand skills attract profitable jobs, while others face intense competition and obtain low wages. The findings suggest that agglomerative forces linked to the unequal spatial distribution of skills, human capital, and opportunities shape the global geography of remote work. These forces pull remote work to places with institutions that foster specialisation and complex economic activities, i. e. metropolitan areas focused on information and communication technologies. Locations without access to these enabling institutions-in many cases, rural areas-fall behind. To make remote work an effective tool for economic and rural development, it would need to be complemented by local skill-building, infrastructure investment, and labour market programmes.

Politics by Automatic Means? A Critique of Artificial Intelligence Ethics at Work.

Calls for "ethical Artificial Intelligence" are legion, with a recent proliferation of government and industry guidelines attempting to establish ethical rules and boundaries for this new technology. With few exceptions, they interpret Artificial Intelligence (AI) ethics narrowly in a liberal political framework of privacy concerns, transparency, governance and non-discrimination. One of the main hurdles to establishing "ethical AI" remains how to operationalize high-level principles such that they translate to technology design, development and use in the labor process. This is because organizations can end up interpreting ethics in an ad-hoc way with no oversight, treating ethics as simply another technological problem with technological solutions, and regulations have been largely detached from the issues AI presents for workers. There is a distinct lack of supra-national standards for fair, decent, or just AI in contexts where people depend on and work in tandem with it. Topics such as discrimination and bias in job allocation, surveillance and control in the labor process, and quantification of work have received significant attention, yet questions around AI and job quality and working conditions have not. This has left workers exposed to potential risks and harms of AI. In this paper, we provide a critique of relevant academic literature and policies related to AI ethics. We then identify a set of principles that could facilitate fairer working conditions with AI. As part of a broader research initiative with the Global Partnership on Artificial Intelligence, we propose a set of accountability mechanisms to ensure AI systems foster fairer working conditions. Such processes are aimed at reshaping the social impact of technology from the point of inception to set a research agenda for the future. As such, the key contribution of the paper is how to bridge from abstract ethical principles to operationalizable processes in the vast field of AI and new technology at work.

The mental health burden of racial and ethnic minorities during the COVID-19 pandemic.

Racial/ethnic minorities have been disproportionately impacted by COVID-19. The effects of COVID-19 on the long-term mental health of minorities remains unclear. To evaluate differences in odds of screening positive for depression and anxiety among various racial and ethnic groups during the latter phase of the COVID-19 pandemic, we performed a cross-sectional analysis of 691,473 participants nested within the prospective smartphone-based COVID Symptom Study in the United States (U.S.) and United Kingdom (U.K). from February 23, 2021 to June 9, 2021. In the U.S. (n=57,187), compared to White participants, the multivariable odds ratios (ORs) for screening positive for depression were 1·16 (95% CI: 1·02 to 1·31) for Black, 1·23 (1·11 to 1·36) for Hispanic, and 1·15 (1·02 to 1·30) for Asian participants, and 1·34 (1·13 to 1·59) for participants reporting more than one race/other even after accounting for personal factors such as prior history of a mental health disorder, COVID-19 infection status, and surrounding lockdown stringency. Rates of screening positive for anxiety were comparable. In the U.K. (n=643,286), racial/ethnic minorities had similarly elevated rates of positive screening for depression and anxiety. These disparities were not fully explained by changes in leisure time activities. Racial/ethnic minorities bore a disproportionate mental health burden during the COVID-19 pandemic. These differences will need to be considered as health care systems transition from prioritizing infection control to mitigating long-term consequences.

Broadening Access to STEM through the Community College: Investigating the Role of Course-Based Research Experiences (CREs).

Broadening access to science, technology, engineering, and mathematics (STEM) professions through the provision of early-career research experiences for a wide range of demographic groups is important for the diversification of the STEM workforce. The size and diversity of the community college system make it a prime educational site for achieving this aim. However, some evidence shows that women and Black, Latinx, and Native American student groups have been hindered in STEM at the community college level. One option for enhancing persistence in STEM is to incorporate the course-based research experiences (CREs) into the curriculum as a replacement for the prevalent traditional laboratory. This can be achieved through the integration of community colleges within extant, multi-institutional CREs such as the SEA-PHAGES program. Using a propensity score-matching technique, students in a CRE and traditional laboratory were compared on a range of psychosocial variables (project ownership, self-efficacy, science identity, scientific community values, and networking). Results revealed higher ratings for women and persons excluded because of their ethnicity or race (PEERs) in the SEA-PHAGES program on important predictors of persistence such as project ownership and science identity. This suggests that the usage of CREs at community colleges could have positive effects in addressing the gender gap for women and enhance inclusiveness for PEER students in STEM.

COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2: a prospective observational cohort study.

The Delta (B.1.617.2) variant was the predominant UK circulating SARS-CoV-2 strain between May and December 2021. How Delta infection compares with previous variants is unknown. This prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly the predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) the predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. 3581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta versus Alpha infection (including fever, sore throat, and headache) and some vice versa (dyspnoea). Symptom burden in the first week was higher with Delta versus Alpha infection; however, the odds of any given symptom lasting ≥ 7 days was either lower or unchanged. Illness duration ≥ 28 days was lower with Delta versus Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1.49) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly reduced the risk of Delta infection (by 69-84%). We conclude that COVID-19 from Delta or Alpha infections is similar. The Delta variant is more transmissible than Alpha; however, current vaccines showed good efficacy against disease. This research framework can be useful for future comparisons with new emerging variants.

Differentiation of brain and retinal organoids from confluent cultures of pluripotent stem cells connected by nerve-like axonal projections of optic origin.

Advances in the study of neurological conditions have been possible because of pluripotent stem cell technologies and organoids. Studies have described the generation of neural ectoderm-derived retinal and brain structures from pluripotent stem cells. However, the field is still troubled by technical challenges, including high culture costs and variability. Here, we describe a simple and economical protocol that reproducibly gives rise to the neural retina and cortical brain regions from confluent cultures of stem cells. The spontaneously generated cortical organoids are transcriptionally comparable with organoids generated by other methods. Furthermore, these organoids showed spontaneous functional network activity and proteomic analysis confirmed organoids maturity. The generation of retinal and brain organoids in close proximity enabled their mutual isolation. Suspension culture of this complex organoid system demonstrated the formation of nerve-like structures connecting retinal and brain organoids, which might facilitate the investigation of neurological diseases of the eye and brain.

Illness Characteristics of COVID-19 in Children Infected with the SARS-CoV-2 Delta Variant.

BACKGROUND: The Delta (B.1.617.2) SARS-CoV-2 variant was the predominant UK circulating strain between May and November 2021. We investigated whether COVID-19 from Delta infection differed from infection with previous variants in children. METHODS: Through the prospective COVID Symptom Study, 109,626 UK school-aged children were proxy-reported between 28 December 2020 and 8 July 2021. We selected all symptomatic children who tested positive for SARS-CoV-2 and were proxy-reported at least weekly, within two timeframes: 28 December 2020 to 6 May 2021 (Alpha (B.1.1.7), the main UK circulating variant) and 26 May to 8 July 2021 (Delta, the main UK circulating variant), with all children unvaccinated (as per national policy at the time). We assessed illness profiles (symptom prevalence, duration, and burden), hospital presentation, and presence of long (≥28 day) illness, and calculated odds ratios for symptoms presenting within the first 28 days of illness. RESULTS: 694 (276 younger (5-11 years), 418 older (12-17 years)) symptomatic children tested positive for SARS-CoV-2 with Alpha infection and 706 (227 younger and 479 older) children with Delta infection. Median illness duration was short with either variant (overall cohort: 5 days (IQR 2-9.75) with Alpha, 5 days (IQR 2-9) with Delta). The seven most prevalent symptoms were common to both variants. Symptom burden over the first 28 days was slightly greater with Delta compared with Alpha infection (in younger children, 3 (IQR 2-5) symptoms with Alpha, 4 (IQR 2-7) with Delta; in older children, 5 (IQR 3-8) symptoms with Alpha, 6 (IQR 3-9) with Delta infection ). The odds of presenting several symptoms were higher with Delta than Alpha infection, including headache and fever. Few children presented to hospital, and long illness duration was uncommon, with either variant. CONCLUSIONS: COVID-19 in UK school-aged children due to SARS-CoV-2 Delta strain B.1.617.2 resembles illness due to the Alpha variant B.1.1.7., with short duration and similar symptom burden.

App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden.

The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74-0.83) in an external dataset. These individual probabilities are employed to estimate daily regional COVID-19 prevalence, which are in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We show that this hospital prediction model demonstrates a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates are similar. When we apply the same model to an English dataset, not including local COVID-19 test data, we observe MdAPEs of 22.3% and 19.0% during the first and second pandemic waves, respectively, highlighting the transferability of the prediction model.

A presynaptic phosphosignaling hub for lasting homeostatic plasticity.

Stable function of networks requires that synapses adapt their strength to levels of neuronal activity, and failure to do so results in cognitive disorders. How such homeostatic regulation may be implemented in mammalian synapses remains poorly understood. Here we show that the phosphorylation status of several positions of the active-zone (AZ) protein RIM1 are relevant for synaptic glutamate release. Position RIMS1045 is necessary and sufficient for expression of silencing-induced homeostatic plasticity and is kept phosphorylated by serine arginine protein kinase 2 (SRPK2). SRPK2-induced upscaling of synaptic release leads to additional RIM1 nanoclusters and docked vesicles at the AZ and is not observed in the absence of RIM1 and occluded by RIMS1045E. Our data suggest that SRPK2 and RIM1 represent a presynaptic phosphosignaling hub that is involved in the homeostatic balance of synaptic coupling of neuronal networks.