Analytical Pyrolysis of Soluble Bio-Tar from Steam Pretreatment of Bamboo by Using TG-FTIR and Py-GC/MS.

Steam pretreatment at high temperatures enables fresh bamboo to possess antifungal and antiseptic properties. The process produces a large amount of wastewater that urgently needs to be recycled. Soluble bio-tars derived from wastewater under low-temperature (LTS-tar) and high-temperature (HTS-tar) steam pretreatments of moso bamboo were studied with a thermogravimetric analyzer coupled with Fourier transform infrared spectroscopy (TG-FTIR) and pyrolysis-gas-chromatography/mass spectrometry (Py-GC/MS). Thermogravimetric analysis showed that in the three stages of the thermal decomposition process, the final residue of the bamboo and HTS-tar had two main peaks of 0.88 wt% and 6.85 wt%. The LTS-tar had much more complicated thermal decomposition behavior, with six steps and a high residue yield of 23.86 wt%. A large quantity of CH4 was observed at the maximum mass loss rates of the bamboo and bio-tars. Acids, aldehydes, ketones, esters, and phenolic compounds were found in the pyrolysis products of the bamboo and soluble bio-tars. Both bio-tars contained carbohydrates and lignin fragments, but the LTS-tar under mild steam conditions had more saccharides and was much more sensitive to temperature. The lignin in the bamboo degraded under harsh steam conditions, resulting in high aromatic and polymeric features for the HTS-tar. The significant differences between LTS-tar and HTS-tar require different techniques to achieve the resource utilization of wastewater in the bamboo industry.

Early Detection of Novel SARS-CoV-2 Variants from Urban and Rural Wastewater through Genome Sequencing and Machine Learning.

Genome sequencing from wastewater has emerged as an accurate and cost-effective tool for identifying SARS-CoV-2 variants. However, existing methods for analyzing wastewater sequencing data are not designed to detect novel variants that have not been characterized in humans. Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns leading to the identification of SARS-CoV-2 variants. To build our model, we sequenced 3,659 wastewater samples collected over a span of more than two years from urban and rural locations in Southern Nevada. We then developed a multivariate independent component analysis (ICA)-based pipeline to transform mutation frequencies into independent sources with co-varying and time-evolving patterns and compared variant predictions to >5,000 SARS-CoV-2 clinical genomes isolated from Nevadans. Using the source patterns as data-driven reference "barcodes", we demonstrated the model's accuracy by successfully detecting the Delta variant in late 2021, Omicron variants in 2022, and emerging recombinant XBB variants in 2023. Our approach revealed the spatial and temporal dynamics of variants in both urban and rural regions; achieved earlier detection of most variants compared to other computational tools; and uncovered unique co-varying mutation patterns not associated with any known variant. The multivariate nature of our pipeline boosts statistical power and can support accurate and early detection of SARS-CoV-2 variants. This feature offers a unique opportunity for novel variant and pathogen detection, even in the absence of clinical testing.

Science Education for the Youth (SEFTY): A Neuroscience Outreach Program for High School Students in Southern Nevada during the COVID-19 Pandemic.

Laboratory outreach programs for K-12 students in the United States from 2020 to 2022 were suspended or delayed due to COVID-19 restrictions. While Southern Nevada also observed similar closures for onsite programs, we and others hypothesized that in-person laboratory activities could be prioritized after increasing vaccine doses were available to the public and masking was encouraged. Here, we describe how the Laboratory of Neurogenetics and Precision Medicine at the University of Nevada Las Vegas (UNLV) collaborated with administrators from a local school district to conduct training activities for high school students during the COVID-19 pandemic. The Science Education for the Youth (SEFTY) program's curriculum was constructed to incorporate experiential learning, fostering collaboration and peer-to-peer knowledge exchange. Leveraging neuroscience tools from our UNLV laboratory, we engaged with 117 high school applicants from 2021 to 2022. Our recruitment efforts yielded a diverse cohort, with >41% Pacific Islander and Asian students, >9% African American students, and >12% multiracial students. We assessed the impact of the SEFTY program through pre- and postassessment student evaluations, revealing a significant improvement of 20.3% in science proficiency (p < 0.001) after participating in the program. Collectively, our laboratory curriculum offers valuable insights into the capacity of an outreach program to actively foster diversity and cultivate opportunities for academic excellence, even in the challenging context of a global pandemic.

Science Education for the Youth (SEFTY): A Neuroscience Outreach Program for High School Students in Southern Nevada During the COVID-19 Pandemic.

Laboratory outreach programs for K-12 students in the United States from 2020-2022 were suspended or delayed due to COVID-19 restrictions. While Southern Nevada also observed similar closures for onsite programs, we and others hypothesized that in-person laboratory activities could be prioritized after increasing vaccine doses were available to the public and masking was encouraged. Here, we describe how the Laboratory of Neurogenetics and Precision Medicine at the University of Nevada Las Vegas (UNLV) collaborated with administrators from a local school district to conduct training activities for high school students during the COVID-19 pandemic. The Science Education for the Youth (SEFTY) program's curriculum was constructed to incorporate experiential learning, fostering collaboration and peer-to-peer knowledge exchange. Leveraging neuroscience tools from our UNLV laboratory, we engaged with 117 high school applicants from 2021-2022. Our recruitment efforts yielded a diverse cohort, with >41% Pacific Islander and Asian students, >9% African American students, and >12% multiracial students. We assessed the impact of the SEFTY program through pre- and post-assessment student evaluations, revealing a significant improvement of 20.3% in science proficiency ( p <0.001) after participating in the program. Collectively, our laboratory curriculum offers valuable insights into the capacity of an outreach program to actively foster diversity and cultivate opportunities for academic excellence, even in the challenging context of a global pandemic. Significance Statement: The Science Education for the Youth (SEFTY) program at UNLV successfully engaged 117 diverse high school students in neuroscience-based experiential learning, demonstrating the viability of in-person education during a pandemic. Significant improvements in science proficiency (20.3% increase) underscore the program's effectiveness in fostering academic excellence and diversity. This initiative potentially serves as a model for maintaining high-quality, inclusive science education in challenging times.

Spatial and Temporal Drug Usage Patterns in Wastewater Correlate with Socioeconomic and Demographic Indicators in Southern Nevada.

Evaluating drug use within populations in the United States poses significant challenges due to various social, ethical, and legal constraints, often impeding the collection of accurate and timely data. Here, we aimed to overcome these barriers by conducting a comprehensive analysis of drug consumption trends and measuring their association with socioeconomic and demographic factors. From May 2022 to April 2023, we analyzed 208 wastewater samples from eight sampling locations across six wastewater treatment plants in Southern Nevada, covering a population of 2.4 million residents with 50 million annual tourists. Using bi-weekly influent wastewater samples, we employed mass spectrometry to detect 39 analytes, including pharmaceuticals and personal care products (PPCPs) and high risk substances (HRS). Our results revealed a significant increase over time in the level of stimulants such as cocaine (pFDR=1.40×10-10) and opioids, particularly norfentanyl (pFDR =1.66×10-12), while PPCPs exhibited seasonal variation such as peak usage of DEET, an active ingredient in insect repellents, during the summer (pFDR =0.05). Wastewater from socioeconomically disadvantaged or rural areas, as determined by Area Deprivation Index (ADI) and Rural-Urban Commuting Area Codes (RUCA) scores, demonstrated distinct overall usage patterns, such as higher usage/concentration of HRS, including cocaine (p=0.05) and norfentanyl (p=1.64×10-5). Our approach offers a near real-time, comprehensive tool to assess drug consumption and personal care product usage at a community level, linking wastewater patterns to socioeconomic and demographic factors. This approach has the potential to significantly enhance public health monitoring strategies in the United States.

Molecularly defined and spatially resolved cell atlas of the whole mouse brain.

In mammalian brains, millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells have impeded our understanding of the molecular and cellular basis of brain function. Recent advances in spatially resolved single-cell transcriptomics have enabled systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3, including several brain regions (for example, refs. 1-11). However, a comprehensive cell atlas of the whole brain is still missing. Here we imaged a panel of more than 1,100 genes in approximately 10 million cells across the entire adult mouse brains using multiplexed error-robust fluorescence in situ hybridization12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating multiplexed error-robust fluorescence in situ hybridization and single-cell RNA sequencing data. Using this approach, we generated a comprehensive cell atlas of more than 5,000 transcriptionally distinct cell clusters, belonging to more than 300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of this atlas to the mouse brain common coordinate framework allowed systematic quantifications of the cell-type composition and organization in individual brain regions. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes of cells. Finally, this high-resolution spatial map of cells, each with a transcriptome-wide expression profile, allowed us to infer cell-type-specific interactions between hundreds of cell-type pairs and predict molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a foundation for functional investigations of neural circuits and their dysfunction in health and disease.

Cell-type-specific 3D-genome organization and transcription regulation in the brain.

3D organization of the genome plays a critical role in regulating gene expression. However, it remains unclear how chromatin organization differs among different cell types in the brain. Here we used genome-scale DNA and RNA imaging to investigate 3D-genome organization in transcriptionally distinct cell types in the primary motor cortex of the mouse brain. We uncovered a wide spectrum of differences in the nuclear architecture and 3D-genome organization among different cell types, ranging from the physical size of the cell nucleus to the active-inactive chromatin compartmentalization and radial positioning of chromatin loci within the nucleus. These cell-type-dependent variations in nuclear architecture and chromatin organization exhibited strong correlation with both total transcriptional activity of the cell and transcriptional regulation of cell-type-specific marker genes. Moreover, we found that the methylated-DNA-binding protein MeCP2 regulates transcription in a divergent manner, depending on the nuclear radial positions of chromatin loci, through modulating active-inactive chromatin compartmentalization.

Detecting time-varying genetic effects in Alzheimer's disease using a longitudinal GWAS model.

Background: The development and progression of Alzheimer's disease (AD) is a complex process that can change over time, during which genetic influences on phenotypes may also fluctuate. Incorporating longitudinal phenotypes in genome wide association studies (GWAS) could help unmask genetic loci with time-varying effects. In this study, we incorporated a varying coefficient test in a longitudinal GWAS model to identify single nucleotide polymorphisms (SNPs) that may have time- or age-dependent effects in AD. Methods: Genotype data from 1,877 participants in the Alzheimer's Neuroimaging Data Initiative (ADNI) were imputed using the Haplotype Reference Consortium (HRC) panel, resulting in 9,573,130 SNPs. Subjects' longitudinal impairment status at each visit was considered as a binary and clinical phenotype. Participants' composite standardized uptake value ratio (SUVR) derived from each longitudinal amyloid PET scan was considered as a continuous and biological phenotype. The retrospective varying coefficient mixed model association test (RVMMAT) was used in longitudinal GWAS to detect time-varying genetic effects on the impairment status and SUVR measures. Post-hoc analyses were performed on genome-wide significant SNPs, including 1) pathway analyses; 2) age-stratified genotypic comparisons and regression analyses; and 3) replication analyses using data from the National Alzheimer's Coordinating Center (NACC). Results: Our model identified 244 genome-wide significant SNPs that revealed time-varying genetic effects on the clinical impairment status in AD; among which, 12 SNPs on chromosome 19 were successfully replicated using data from NACC. Post-hoc age-stratified analyses indicated that for most of these 244 SNPs, the maximum genotypic effect on impairment status occurred between 70 to 80 years old, and then declined with age. Our model further identified 73 genome-wide significant SNPs associated with the temporal variation of amyloid accumulation. For these SNPs, an increasing genotypic effect on PET-SUVR was observed as participants' age increased. Functional pathway analyses on significant SNPs for both phenotypes highlighted the involvement and disruption of immune responses- and neuroinflammation-related pathways in AD. Conclusion: We demonstrate that longitudinal GWAS models with time-varying coefficients can boost the statistical power in AD-GWAS. In addition, our analyses uncovered potential time-varying genetic variants on repeated measurements of clinical and biological phenotypes in AD.

Topological reorganization of functional hubs in patients with Parkinson's disease with freezing of gait.

BACKGROUND AND PURPOSE: Resting-state functional MRI (rs-fMRI) studies in Parkinson's disease (PD) patients with freezing of gait (FOG) have implicated dysfunctional connectivity over multiple resting-state networks (RSNs). While these findings provided network-specific insights and information related to the aberrant or altered regional functional connectivity (FC), whether these alterations have any effect on topological reorganization in PD-FOG patients is incompletely understood. Understanding the higher order functional organization, which could be derived from the "hub" and the "rich-club" organization of the functional networks, could be crucial to identifying the distinct and unique pattern of the network connectivity associated with PD-FOG. METHODS: In this study, we use rs-fMRI data and graph theoretical approaches to explore the reorganization of RSN topology in PD-FOG when compared to those without FOG. We also compared the higher order functional organization derived using the hub and rich-club measures in the FC networks of these PD-FOG patients to understand whether there is a topological reorganization of these hubs in PD-FOG. RESULTS: We found that the PD-FOG patients showed a noticeable reorganization of hub regions. Regions that are part of the prefrontal cortex, primary somatosensory, motor, and visuomotor coordination areas were some of the regions exhibiting altered hub measures in PD-FOG patients. We also found a significantly altered feeder and local connectivity in PD-FOG. CONCLUSIONS: Overall, our findings demonstrate a widespread topological reorganization and disrupted higher order functional network topology in PD-FOG that may further assist in improving our understanding of functional network disturbances associated with PD-FOG.

Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF).

Tissue biology involves an intricate balance between cell-intrinsic processes and interactions between cells organized in specific spatial patterns, which can be respectively captured by single-cell profiling methods, such as single-cell RNA-seq (scRNA-seq), and histology imaging data, such as Hematoxylin-and-Eosin (H&E) stains. While single-cell profiles provide rich molecular information, they can be challenging to collect routinely and do not have spatial resolution. Conversely, histological H&E assays have been a cornerstone of tissue pathology for decades, but do not directly report on molecular details, although the observed structure they capture arises from molecules and cells. Here, we leverage adversarial machine learning to develop SCHAF (Single-Cell omics from Histology Analysis Framework), to generate a tissue sample's spatially-resolved single-cell omics dataset from its H&E histology image. We demonstrate SCHAF on two types of human tumors-from lung and metastatic breast cancer-training with matched samples analyzed by both sc/snRNA-seq and by H&E staining. SCHAF generated appropriate single-cell profiles from histology images in test data, related them spatially, and compared well to ground-truth scRNA-Seq, expert pathologist annotations, or direct MERFISH measurements. SCHAF opens the way to next-generation H&E2.0 analyses and an integrated understanding of cell and tissue biology in health and disease.

A molecularly defined and spatially resolved cell atlas of the whole mouse brain.

In mammalian brains, tens of millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells in the brain have so far hindered our understanding of the molecular and cellular basis of its functions. Recent advances in spatially resolved single-cell transcriptomics have allowed systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3. However, these approaches have only been applied to a few brain regions1-11 and a comprehensive cell atlas of the whole brain is still missing. Here, we imaged a panel of >1,100 genes in ~8 million cells across the entire adult mouse brain using multiplexed error-robust fluorescence in situ hybridization (MERFISH)12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating MERFISH and single-cell RNA-sequencing (scRNA-seq) data. Using this approach, we generated a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to ~300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of the MERFISH images to the common coordinate framework (CCF) of the mouse brain further allowed systematic quantifications of the cell composition and organization in individual brain regions defined in the CCF. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes in the gene-expression profiles of cells. Finally, this high-resolution spatial map of cells, with a transcriptome-wide expression profile associated with each cell, allowed us to infer cell-type-specific interactions between several hundred pairs of molecularly defined cell types and predict potential molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a valuable resource for future functional investigations of neural circuits and their dysfunction in diseases.

China's Ambitious Policy Experiment with Social Long-Term Care Insurance: Promises, Challenges, and Prospects.

In 2016, China launched long-term care insurance (LTCI) pilot programs in 15 cities across the country. In this Commentary, we provide an overview of these pilots regarding the target insured population, sources of financing, beneficiary eligibility criteria, and benefit design. We offer perspectives on the strengths and limitations, implementation challenges, and future prospects of these ongoing pilots. Also, we highlight the needs for addressing several key policy issues and challenges before further expanding these programs toward national implementation. These include solidifying the LTCI financing pool for independence and self-sustainability, balancing national priorities and local needs in LTCI design, reducing coverage gaps and disparities, ensuring quality of care through pay-for-performance and regulatory oversight, and strengthening independent evaluation of LTCI implementation and impacts.

China is piloting public social insurance as its core long-term care financing strategy.Current long-term care insurance pilots vary greatly in program design across pilot sites.Long-term care insurance financing should move away from current over-reliance on existing health insurance funds toward independence and self-sustainability.While balancing national priorities, it is essential to design and implement appropriate long-term care insurance programs locally.China should dedicate time and resources to allow for sufficient policy learning, adaption, and evaluation through ongoing pilot programs.

Molecular and spatial signatures of mouse brain aging at single-cell resolution.

The diversity and complex organization of cells in the brain have hindered systematic characterization of age-related changes in its cellular and molecular architecture, limiting our ability to understand the mechanisms underlying its functional decline during aging. Here, we generated a high-resolution cell atlas of brain aging within the frontal cortex and striatum using spatially resolved single-cell transcriptomics and quantified changes in gene expression and spatial organization of major cell types in these regions over the mouse lifespan. We observed substantially more pronounced changes in cell state, gene expression, and spatial organization of non-neuronal cells over neurons. Our data revealed molecular and spatial signatures of glial and immune cell activation during aging, particularly enriched in the subcortical white matter, and identified both similarities and notable differences in cell-activation patterns induced by aging and systemic inflammatory challenge. These results provide critical insights into age-related decline and inflammation in the brain.

Spatially resolved epigenomic profiling of single cells in complex tissues.

The recent development of spatial omics methods has enabled single-cell profiling of the transcriptome and 3D genome organization with high spatial resolution. Expanding the repertoire of spatial omics tools, a spatially resolved single-cell epigenomics method will accelerate understanding of the spatial regulation of cell and tissue functions. Here, we report a method for spatially resolved epigenomic profiling of single cells using in situ tagmentation and transcription followed by multiplexed imaging. We demonstrated the ability to profile histone modifications marking active promoters, putative enhancers, and silent promoters in individual cells, and generated high-resolution spatial atlas of hundreds of active promoters and putative enhancers in embryonic and adult mouse brains. Our results suggested putative promoter-enhancer pairs and enhancer hubs regulating developmentally important genes. We envision this approach will be generally applicable to spatial profiling of epigenetic modifications and DNA-binding proteins, advancing our understanding of how gene expression is spatiotemporally regulated by the epigenome.

Longitudinal Changes in Cognitive Functioning and Brain Structure in Professional Boxers and Mixed Martial Artists After They Stop Fighting.

OBJECTIVE: This study compares longitudinal changes in cognitive functioning and brain structures in male fighters who transitioned to an inactive fighting status without any further exposure to repetitive head impacts (RHI) and fighters remaining active with continual exposure to RHI. METHODS: Participants were recruited from the Professional Fighters Brain Health Study. At time point 1 (TP1), all fighters were active, with continual exposure to RHI. At time point 2 (TP2), fighters were considered "transitioned" if they had no sanctioned professional fights and had not been sparring for the past 2 years. Fighters were considered "active" if they continued to train and compete. All fighters underwent cognitive testing and 3T magnetic resonance imaging (MRI) at both TPs. A subset of our fighters (50%) underwent blood sampling for characterization of neurofilament light (NfL) levels at both TPs. Linear mixed effect models were applied to investigate the potentially different longitudinal trajectories (interaction effect between group and time) of cognitive function measures, NfL levels and regional thickness measures (derived from structural MRI) between transitioned and active fighters. RESULTS: 45 male transitioned fighters (31.69±6.27 years old (TP1), 22 boxers, 22 mixed martial artists, 1 martial artist) and 45 demographically matched male active fighters (30.24±5.44 years old (TP1); 17 boxers, 27 mixed martial artists, 1 martial artist) were included in the analyses. Significantly different longitudinal trajectories between transitioned and active fighters were observed in verbal memory (p FDR =4.73E-04), psychomotor speed (p FDR =4.73E-04), processing speed (p FDR =3.90E-02) and NfL levels (p=0.02). Transitioned fighters demonstrated longitudinally improved cognitive functioning and decreased NfL levels, and active fighters demonstrated declines in cognitive performance and stable NfL levels. Out of 68 cortical regions inspected, 54 regions demonstrated a consistently changing trajectory, with thickness measures stabilizing on a group level for transitioned fighters and subtly declining over time for active fighters. CONCLUSION: After fighters' cessation of RHI exposure, cognitive function and brain thickness measures may stabilize and blood NfL levels may decline. This study could be a starting point to identify potential predictors of individuals who are at a higher risk of RHI-related long-term neurological conditions.

Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH.

The human cerebral cortex has tremendous cellular diversity. How different cell types are organized in the human cortex and how cellular organization varies across species remain unclear. In this study, we performed spatially resolved single-cell profiling of 4000 genes using multiplexed error-robust fluorescence in situ hybridization (MERFISH), identified more than 100 transcriptionally distinct cell populations, and generated a molecularly defined and spatially resolved cell atlas of the human middle and superior temporal gyrus. We further explored cell-cell interactions arising from soma contact or proximity in a cell type-specific manner. Comparison of the human and mouse cortices showed conservation in the laminar organization of cells and differences in somatic interactions across species. Our data revealed human-specific cell-cell proximity patterns and a markedly increased enrichment for interactions between neurons and non-neuronal cells in the human cortex.

A preoptic neuronal population controls fever and appetite during sickness.

During infection, animals exhibit adaptive changes in physiology and behaviour aimed at increasing survival. Although many causes of infection exist, they trigger similar stereotyped symptoms such as fever, warmth-seeking, loss of appetite and fatigue1,2. Yet exactly how the nervous system alters body temperature and triggers sickness behaviours to coordinate responses to infection remains unknown. Here we identify a previously uncharacterized population of neurons in the ventral medial preoptic area (VMPO) of the hypothalamus that are activated after sickness induced by lipopolysaccharide (LPS) or polyinosinic:polycytidylic acid. These neurons are crucial for generating a fever response and other sickness symptoms such as warmth-seeking and loss of appetite. Single-nucleus RNA-sequencing and multiplexed error-robust fluorescence in situ hybridization uncovered the identity and distribution of LPS-activated VMPO (VMPOLPS) neurons and non-neuronal cells. Gene expression and electrophysiological measurements implicate a paracrine mechanism in which the release of immune signals by non-neuronal cells during infection activates nearby VMPOLPS neurons. Finally, we show that VMPOLPS neurons exert a broad influence on the activity of brain areas associated with behavioural and homeostatic functions and are synaptically and functionally connected to circuit nodes controlling body temperature and appetite. Together, these results uncover VMPOLPS neurons as a control hub that integrates immune signals to orchestrate multiple sickness symptoms in response to infection.

Proteomic and functional analyses of the periodic membrane skeleton in neurons.

Actin, spectrin, and associated molecules form a membrane-associated periodic skeleton (MPS) in neurons. The molecular composition and functions of the MPS remain incompletely understood. Here, using co-immunoprecipitation and mass spectrometry, we identified hundreds of potential candidate MPS-interacting proteins that span diverse functional categories. We examined representative proteins in several of these categories using super-resolution imaging, including previously unknown MPS structural components, as well as motor proteins, cell adhesion molecules, ion channels, and signaling proteins, and observed periodic distributions characteristic of the MPS along the neurites for ~20 proteins. Genetic perturbations of the MPS and its interacting proteins further suggested functional roles of the MPS in axon-axon and axon-dendrite interactions and in axon diameter regulation, and implicated the involvement of MPS interactions with cell adhesion molecules and non-muscle myosin in these roles. These results provide insights into the interactome of the MPS and suggest previously unknown functions of the MPS in neurons.