Pituitary null cell adenoma is a challenging clinical condition, and its pathogenesis remains to be elucidated. We performed this study to determine the roles of C5orf66-AS1, NORAD, and TINCR in the pathogenesis and invasion of pituitary null cell adenomas. Expression of the three long non-coding RNAs in pituitary null cell adenoma tissues of 11 patients and normal pituitary tissues from four donors was examined by performing quantitative reverse transcription-polymerase chain reaction. We found that C5orf66-AS1 expression was lower in pituitary null cell adenoma tissues than in normal pituitary tissues. Moreover, C5orf66-AS1 expression level was significantly lower in invasive pituitary null cell adenomas than in non-invasive ones. After transfection of C5orf66-AS1 into pituitary adenoma cells, assessment of cell viability and invasion suggested that overexpressed C5orf66-AS1 inhibited cell viability and cell invasion. In silico algorithms predicted several cis- and trans-acting target genes of C5orf66-AS1, including PITX1 and SCGB3A1. In addition, expression of some of the predicted target genes was determined using microarray data of another cohort with pituitary null cell adenomas. It showed that some of these target genes were differentially expressed between pituitary null cell adenoma tissues and normal pituitary tissues as well as between invasive and non-invasive tumors. Co-expression analysis in RNA sequencing data showed that PAQR7 was the most correlated gene of C5orf66-AS1 and that several predicted trans-acting target genes, including SCGB3A1, were highly correlated with C5orf66-AS1. NORAD and TINCR expression was not statistically significant in the complete cohort; however, a negative correlation was observed between NORAD expression and maximum tumor diameter in some subgroups. These results indicate that C5orf66-AS1 suppresses the development and invasion of pituitary null cell adenomas. However, our results do not provide enough statistical evidence to support the roles of NORAD and TINCR in the development and invasion of pituitary null cell adenomas.

Sex is a key modifier of neurological disease outcomes. Microglia are implicated in neurological diseases and modulated by microRNAs, but it is unknown whether microglial microRNAs have sex-specific influences on disease. We show in mice that microglial microRNA expression differs in males and females and that loss of microRNAs leads to sex-specific changes in the microglial transcriptome and tau pathology. These findings suggest that microglial microRNAs influence tau pathogenesis in a sex-specific manner.

The identity and degree of heterogeneity of glial progenitors and their contributions to brain tumor malignancy remain elusive. By applying lineage-targeted single-cell transcriptomics, we uncover an unanticipated diversity of glial progenitor pools with unique molecular identities in developing brain. Our analysis identifies distinct transitional intermediate states and their divergent developmental trajectories in astroglial and oligodendroglial lineages. Moreover, intersectional analysis uncovers analogous intermediate progenitors during brain tumorigenesis, wherein oligodendrocyte-progenitor intermediates are abundant, hyper-proliferative, and progressively reprogrammed toward a stem-like state susceptible to further malignant transformation. Similar actively cycling intermediate progenitors are prominent components in human gliomas with distinct driver mutations. We further unveil lineage-driving networks underlying glial fate specification and identify Zfp36l1 as necessary for oligodendrocyte-astrocyte lineage transition and glioma growth. Together, our results resolve the dynamic repertoire of common and divergent glial progenitors during development and tumorigenesis and highlight Zfp36l1 as a molecular nexus for balancing glial cell-fate decision and controlling gliomagenesis.

Cortical state, defined by population-level neuronal activity patterns, determines sensory perception. While arousal-associated neuromodulators-including norepinephrine (NE)-reduce cortical synchrony, how the cortex resynchronizes remains unknown. Furthermore, general mechanisms regulating cortical synchrony in the wake state are poorly understood. Using in vivo imaging and electrophysiology in mouse visual cortex, we describe a critical role for cortical astrocytes in circuit resynchronization. We characterize astrocytes' calcium responses to changes in behavioral arousal and NE, and show that astrocytes signal when arousal-driven neuronal activity is reduced and bi-hemispheric cortical synchrony is increased. Using in vivo pharmacology, we uncover a paradoxical, synchronizing response to Adra1a receptor stimulation. We reconcile these results by demonstrating that astrocyte-specific deletion of Adra1a enhances arousal-driven neuronal activity, while impairing arousal-related cortical synchrony. Our findings demonstrate that astrocytic NE signaling acts as a distinct neuromodulatory pathway, regulating cortical state and linking arousal-associated desynchrony to cortical circuit resynchronization.

Intermittent hypoxemia (IH) may influence retinopathy of prematurity (ROP) development in preterm infants, however, previous studies had mixed results. This study aims to assess the influence and evaluate the predictive ability of IH measures on Type 1 ROP, a stage beyond which ROP treatment is indicated.

Recent work examining astrocytic physiology centers on fluorescence imaging, due to development of sensitive fluorescent indicators and observation of spatiotemporally complex calcium activity. However, the field remains hindered in characterizing these dynamics, both within single cells and at the population level, because of the insufficiency of current region-of-interest-based approaches to describe activity that is often spatially unfixed, size-varying and propagative. Here we present an analytical framework that releases astrocyte biologists from region-of-interest-based tools. The Astrocyte Quantitative Analysis (AQuA) software takes an event-based perspective to model and accurately quantify complex calcium and neurotransmitter activity in fluorescence imaging datasets. We apply AQuA to a range of ex vivo and in vivo imaging data and use physiologically relevant parameters to comprehensively describe the data. Since AQuA is data-driven and based on machine learning principles, it can be applied across model organisms, fluorescent indicators, experimental modes, and imaging resolutions and speeds, enabling researchers to elucidate fundamental neural physiology.

Intramyocellular (IMCL), extramyocellular lipid (EMCL), and vitamin D deficiency are associated with muscle metabolic dysfunction. This study compared the change in [IMCL]:[EMCL] following the combined treatment of vitamin D and aerobic training (DAT) compared with vitamin D (D), aerobic training (AT), and control (CTL). Male and female subjects aged 60-80 years with a BMI ranging from 18.5-34.9 and vitamin D status of ≤32 ng/mL (25(OH)D) were recruited to randomized, prospective clinical trial double-blinded for supplement with a 2 × 2 factorial design. Cholecalciferol (Vitamin D3) (10,000 IU × 5 days/week) or placebo was provided for 13 weeks and treadmill aerobic training during week 13. Gastrocnemius IMCL and EMCL were measured with magnetic resonance spectroscopy (MRS) and MRI. Hybrid near-infrared diffuse correlation spectroscopy measured hemodynamics. Group differences in IMCL were observed when controlling for baseline IMCL (p = 0.049). DAT was the only group to reduce IMCL from baseline, while a mean increase was observed in all other groups combined (p = 0.008). IMCL reduction and the corresponding increase in rVO2 at study end (p = 0.011) were unique to DAT. Vitamin D, when combined with exercise, may potentiate the metabolic benefits of exercise by reducing IMCL and increasing tissue-level VO2 in healthy, older adults.

Microglia are increasingly recognized for their major contributions during brain development and neurodegenerative disease. It is currently unknown whether these functions are carried out by subsets of microglia during different stages of development and adulthood or within specific brain regions. Here, we performed deep single-cell RNA sequencing (scRNA-seq) of microglia and related myeloid cells sorted from various regions of embryonic, early postnatal, and adult mouse brains. We found that the majority of adult microglia expressing homeostatic genes are remarkably similar in transcriptomes, regardless of brain region. By contrast, early postnatal microglia are more heterogeneous. We discovered a proliferative-region-associated microglia (PAM) subset, mainly found in developing white matter, that shares a characteristic gene signature with degenerative disease-associated microglia (DAM). Such PAM have amoeboid morphology, are metabolically active, and phagocytose newly formed oligodendrocytes. This scRNA-seq atlas will be a valuable resource for dissecting innate immune functions in health and disease.

We investigated the influence of genetic variants on atherosclerosis using whole exome sequencing in cases and controls from the autopsy study "Pathobiological Determinants of Atherosclerosis in Youth (PDAY)". We identified a PDAY case group with the highest total amounts of raised lesions (n = 359) for comparisons with a control group with no detectable raised lesions (n = 626). In addition to the standard exome capture, we included genome-wide proximal promoter regions that contain sequences that regulate gene expression. Our statistical analyses included single variant analysis for common variants (MAF > 0.01) and rare variant analysis for low frequency and rare variants (MAF < 0.05). In addition, we investigated known CAD genes previously identified by meta-analysis of GWAS studies. We did not identify individual common variants that reached exome-wide significance using single variant analysis. In analysis limited to 60 CAD genes, we detected strong associations with COL4A2/COL4A1 that also previously showed associations with myocardial infarction and arterial stiffness, as well as coronary artery calcification. Likewise, rare variant analysis did not identify genes that reached exome-wide significance. Among the 60 CAD genes, the strongest association was with NBEAL1 that was also identified in gene-based analysis of whole exome sequencing for early onset myocardial infarction.

Continuous and longitudinal imaging of cerebral blood flow (CBF) variations provide vital information to investigate pathophysiology and interventions for a variety of neurological and cerebral diseases. An innovative noncontact speckle contrast diffuse correlation tomography (scDCT) system was downscaled and adapted for noninvasive imaging of CBF distributions in rat brain through intact scalp and skull. Algorithms for 2D mapping and 3D image reconstruction of CBF distributions were developed and optimized. The continuous imaging capability of the system was shown by imaging global CBF increases during CO2 inhalations and regional CBF decreases across two hemispheres during sequential unilateral and bilateral common carotid artery ligations. The longitudinal imaging capability was demonstrated by imaging CBF variations over a long recovery period of 14 days after an acute stroke. Compared to the 2D mapping method, the 3D imaging method reduces partial volume effects, but needs more computation time for image reconstruction. Results from this study generally agree with those reported in the literature using similar protocols to induce CBF changes in rats. The scDCT enables a relatively large penetration depth (up to ∼10 mm), which is sufficient for transcranial brain measurements in small animals and human neonates. Ultimately, we expect to provide a noninvasive noncontact cerebral imager for basic neuroscience research in small animal models and clinical applications in human neonates.

Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca2+ indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca2+ signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP.

Conventional differential gene expression analysis by methods such as student's t-test, SAM, and Empirical Bayes often searches for statistically significant genes without considering the interactions among them. Network-based approaches provide a natural way to study these interactions and to investigate the rewiring interactions in disease versus control groups. In this paper, we apply weighted graphical LASSO (wgLASSO) algorithm to integrate a data-driven network model with prior biological knowledge (i.e., protein-protein interactions) for biological network inference. We propose a novel differentially weighted graphical LASSO (dwgLASSO) algorithm that builds group-specific networks and perform network-based differential gene expression analysis to select biomarker candidates by considering their topological differences between the groups.

Recent single-cell RNA sequencing studies have revealed distinct microglial states in development and disease. These include proliferative region-associated microglia (PAM) in developing white matter and disease-associated microglia (DAM) prevalent in various neurodegenerative conditions. PAM and DAM share a similar core gene signature and other functional properties. However, the extent of the dynamism and plasticity of these microglial states, as well as their functional significance, remains elusive, partly due to the lack of specific tools. Here, we report the generation of an inducible Cre driver line, Clec7a-CreERT2, designed to target PAM and DAM in the brain parenchyma. Utilizing this tool, we profile labeled cells during development and in several disease models, uncovering convergence and context-dependent differences in PAM/DAM gene expression. Through long-term tracking, we demonstrate surprising levels of plasticity in these microglial states. Lastly, we specifically depleted DAM in cuprizone-induced demyelination, revealing their roles in disease progression and recovery.

Biological network inference is a major challenge in systems biology. Traditional correlation-based network analysis results in too many spurious edges since correlation cannot distinguish between direct and indirect associations. To address this issue, Gaussian graphical models (GGM) were proposed and have been widely used. Though they can significantly reduce the number of spurious edges, GGM are insufficient to uncover a network structure faithfully due to the fact that they only consider the full order partial correlation. Moreover, when the number of samples is smaller than the number of variables, further technique based on sparse regularization needs to be incorporated into GGM to solve the singular covariance inversion problem. In this paper, we propose an efficient and mathematically solid algorithm that infers biological networks by computing low order partial correlation (LOPC) up to the second order. The bias introduced by the low order constraint is minimal compared to the more reliable approximation of the network structure achieved. In addition, the algorithm is suitable for a dataset with small sample size but large number of variables. Simulation results show that LOPC yields far less spurious edges and works well under various conditions commonly seen in practice. The application to a real metabolomics dataset further validates the performance of LOPC and suggests its potential power in detecting novel biomarkers for complex disease.

Developed herein is a three-dimensional (3D) flow contrast imaging system leveraging advancements in the extension of laser speckle contrast imaging theories to deep tissues along with our recently developed finite-element diffuse correlation tomography (DCT) reconstruction scheme. This technique, termed speckle contrast diffuse correlation tomography (scDCT), enables incorporation of complex optical property heterogeneities and sample boundaries. When combined with a reflectance-based design, this system facilitates a rapid segue into flow contrast imaging of larger, in vivo applications such as humans.

Occlusions of bilateral common carotid arteries (bi-CCA) in mice are popular models for the investigation of transient forebrain ischemia. Currently available technologies for assessing cerebral blood flow (CBF) and oxygenation in ischemic mice have limitations. This study tests a novel near-infrared diffuse correlation spectroscopy (DCS) flow-oximeter for monitoring both CBF and cerebral oxygenation in mice undergoing repeated transient forebrain ischemia. Concurrent flow measurements in a mouse brain were first conducted for validation purposes; DCS measurement was found highly correlated with laser Doppler measurement (R2 = 0.94) and less susceptible to motion artifacts. With unique designs in experimental protocols and fiber-optic probes, we have demonstrated high sensitivities of DCS flow-oximeter in detecting the regional heterogeneity of CBF responses in different hemispheres and global changes of both CBF and cerebral oxygenation across two hemispheres in mice undergoing repeated 2-minute bi-CCA occlusions over 5 days. More than 75% CBF reductions were found during bi-CCA occlusions in mice, which may be considered as a threshold to determine a successful bi-CCA occlusion. With the progress of repeated 2-minute bi-CCA occlusions over days, a longitudinal decline in the magnitudes of CBF reduction was observed, indicating the brain adaptation to cerebral ischemia through the repeated preconditioning.

To identify muscle physiologic properties that may contribute to postexertional fatigue and malaise in women with fibromyalgia (FM).

A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples.

Lengthy use of general anesthetics (GAs) causes neurobehavioral deficits in the developing brain, which has raised significant clinical concerns such that the United States Food and Drug Administration (FDA) is warning on the use of GAs in children younger than 3 years. However, the molecular and cellular mechanisms for GAs-induced neurotoxicity remain largely unknown. Here, we report that sevoflurane (Sevo), a commonly used GA in pediatrics, caused compromised astrocyte morphogenesis spatiotemporally correlated to synaptic overgrowth, with reduced synaptic function in developing cortex in a regional-, exposure-length-, and age-specific manner. Sevo disrupted astrocyte Ca2+ homeostasis both acutely and chronically, which led to the down-regulation of Ezrin, an actin-binding membrane-bound protein, which we found was critically involved in astrocyte morphogenesis in vivo. Importantly, overexpression of astrocyte Ezrin rescued astrocytic and neuronal dysfunctions and fully corrected deficits in social behaviors in developing mice with lengthy Sevo exposure. Our data uncover that, in addition to neurons, astrocytes may represent important targets for GAs to exert toxic effects and that astrocyte morphological integrity is crucial for synaptogenesis and neurological behaviors.

During vertebrate central nervous system development, most oligodendrocyte progenitor cells (OPCs) are specified in the ventral spinal cord and must migrate throughout the neural tube until they become evenly distributed, occupying non-overlapping domains. While this process of developmental OPC migration is well characterized, the nature of the molecular mediators that govern it remain largely unknown. Here, using zebrafish as a model, we demonstrate that Met signaling is required for initial developmental migration of OPCs, and, using cell-specific knock-down of Met signaling, show that Met acts cell-autonomously in OPCs. Taken together, these findings demonstrate in vivo, the role of Met signaling in OPC migration and provide new insight into how OPC migration is regulated during development.