Probes for INS

Hepatoblastoma (HB) is one of the most common liver malignancies in children, while the molecular basis of the disease is largely unknown. Therefore, this study aims to explore the key genes and molecular mechanisms of the pathogenesis of HB using a bioinformatics approach. The gene expression dataset GSE131329 was used to find differentially expressed genes (DEGs). Functional and enrichment analyses of the DEGs were performed by the EnrichR. Then, the protein-protein interaction (PPI) network of the up-regulated genes was constructed and visualized using STRING database and Cytoscape software, respectively. MCODE was used to detect the significant modules of the PPI network, and cytoHubba was utilized to rank the important nodes (genes) of the PPI modules. Overall, six ranking methods were employed and the results were validated by the Oncopression database. Moreover, the upstream regulatory network and the miRNA-target interactions of the up-regulated DEGs were analyzed by the X2K web and the miRTarBase respectively. A total of 594 DEGs, including 221 up- and 373 down-regulated genes, were obtained, which were enriched in different cellular and metabolic processes, human diseases, and cancer. Furthermore, 15 hub genes were screened, out of which, 11 were validated. Top 10 transcription factors, kinases, and miRNAs were also determined. To the best of our knowledge, the association of RACGAP1, MKI67, FOXM1, SIN3A, miR-193b, and miR-760 with HB was reported for the first time. Our findings may be used to shed light on the underlying mechanisms of HB and provide new insights for better prognosis and therapeutic strategies.

Single-cell analysis has emerged over the past decade as a transformative technology informative for the systematic analysis of complex cell populations such as in cancers and the tumor immune microenvironment. The methodologic and analytical advancements in this realm have evolved rapidly, scaling from but a few cells at its outset to the current capabilities of processing and analyzing hundreds of thousands of individual cells at a time. The types of profiling attainable at individual cell resolution now range from genetic and transcriptomic characterization and extend to epigenomic and spatial analysis. Additionally, the increasing ability to achieve multiomic integration of these data layers now yields ever richer insights into diverse molecular disease subtypes and the patterns of cellular circuitry on a per-cancer basis. Over the years, chronic lymphocytic leukemia (CLL) consistently has been at the forefront of genomic investigation, given the ready accessibility of pure leukemia cells and immune cells from circulating blood of patients with this disease. Herein, we review the recent forays into the application of single-cell analysis to CLL, which are already revealing a new understanding of the natural progression of CLL, the impact of novel therapies, and the interactions with coevolving nonmalignant immune cell populations. As we emerge from the end of the beginning of this technologic revolution, CLL stands poised to reap the benefits of single-cell analysis from the standpoints of uncovering fresh fundamental biological knowledge and of providing a path to devising regimens of personalized diagnosis, treatment, and monitoring.

Intracellular pathogens have evolved to utilize normal cellular processes to complete their replicative cycles. Pathogens that interface with proliferative cell signaling pathways risk infections that can lead to cancers, but the factors that influence malignant outcomes are incompletely understood. Human papillomaviruses (HPVs) predominantly cause benign hyperplasia in stratifying epithelial tissues. However, a subset of carcinogenic or "high-risk" HPV (hr-HPV) genotypes are etiologically linked to nearly 5% of all human cancers. Progression of hr-HPV-induced lesions to malignancies is characterized by increased expression of the E6 and E7 oncogenes and the oncogenic functions of these viral proteins have been widely studied. Yet, the mechanisms that regulate hr-HPV oncogene transcription and suppress their expression in benign lesions remain poorly understood. Here, we demonstrate that EGFR/MEK/ERK signaling, influenced by epithelial contact inhibition and tissue differentiation cues, regulates hr-HPV oncogene expression. Using monolayer cells, epithelial organotypic tissue models, and neoplastic tissue biopsy materials, we show that cell-extrinsic activation of ERK overrides cellular control to promote HPV oncogene expression and the neoplastic phenotype. Our data suggest that HPVs are adapted to use the EGFR/MEK/ERK signaling pathway to regulate their productive replicative cycles. Mechanistic studies show that EGFR/MEK/ERK signaling influences AP-1 transcription factor activity and AP-1 factor knockdown reduces oncogene transcription. Furthermore, pharmacological inhibitors of EGFR, MEK, and ERK signaling quash HPV oncogene expression and the neoplastic phenotype, revealing a potential clinical strategy to suppress uncontrolled cell proliferation, reduce oncogene expression and treat HPV neoplasia.

METHODS : To induce OIR, C57BL/6J mice were exposed to 75% oxygen from postnatal day (p) 7 to p12 and then maintained under normal room air conditions. Control mice were kept under room air conditions throughout. At p12, p17, and p25, one eye of each mouse was harvested to prepare retinal flatmounts to analyze retinal vascular changes. From the contralateral eye, total RNA was isolated and reverse transcribed into cDNA for relative quantification of miRNA expression using qRT-PCR. An in situ hybridization technique (miRNAscopeTM) was used to visualize miR-21-5p expression on formalin-fixed, paraffin-embedded mouse eye tissue sections.

Research on adeno-associated virus (AAV) and its recombinant vectors as well as on fluorescence microscopy imaging is rapidly progressing driven by clinical applications and new technologies, respectively. The topics converge, since high and super-resolution microscopes facilitate the study of spatial and temporal aspects of cellular virus biology. Labeling methods also evolve and diversify. We review these interdisciplinary developments and provide information on the technologies used and the biological knowledge gained. The emphasis lies on the visualization of AAV proteins by chemical fluorophores, protein fusions and antibodies as well as on methods for the detection of adeno-associated viral DNA. We add a short overview of fluorescent microscope techniques and their advantages and challenges in detecting AAV.

We describe a modified BaseScope Assay protocol (ACDBio) for RNA in situ hybridization on fixed-frozen human brain tissue. The original protocol caused tissue detachment due to harsh tissue pre-treatment. We therefore optimized it to improve tissue stability while providing high stain quality in fragile post-mortem tissue from aged donors with advanced neurodegeneration. The main changes include two additional fixation steps and modifications to the pre-treatment protocol. We also describe tissue imaging and stain quantification using the open-source QuPath software. For complete details on the use and execution of this protocol, please refer to Hornsby et al. (2020).

Tumor growth depends on angiogenesis. The complex tissue environment surrounding tumor cells, which is composed of a variety of resident and infiltrating host cells, secreted factors and extracellular matrix proteins, influences tumor angiogenesis and progression. Moreover, the tumor microenvironment contributes to determining therapeutic responses and resistance to therapy. The ability to block tumor resistance is related to the understanding of the cellular and molecular pathways activated in the tumor microenvironment. Novel emerging targeted therapeutic strategies are based on the combination of different antitumor approaches with the aim of resolving refractory tumors and improving cancer treatment efficiency.

We present an automated method to track and identify neurons in C. elegans, called 'fast Deep Neural Correspondence' or fDNC, based on the transformer network architecture. The model is trained once on empirically derived semi-synthetic data and then predicts neural correspondence across held-out real animals. The same pre-trained model both tracks neurons across time and identifies corresponding neurons across individuals. Performance is evaluated against hand-annotated datasets, including NeuroPAL [1]. Using only position information, the method achieves 79.1% accuracy at tracking neurons within an individual and 64.1% accuracy at identifying neurons across individuals. Accuracy at identifying neurons across individuals is even higher (78.2%) when the model is applied to a dataset

Protocadherin-19 (PCDH19) mutations cause early-onset seizures and cognitive impairment. The PCDH19 gene is on the X-chromosome. Unlike most X-linked disorders, PCDH19 mutations affect heterozygous females (PCDH19HET♀ ) but not hemizygous males (PCDH19HEMI♂ ); however, the reason why remains to be elucidated. We demonstrate that PCDH19, a cell-adhesion molecule, is enriched at hippocampal mossy fiber synapses. Pcdh19HET♀ but not Pcdh19HEMI♂ mice show impaired mossy fiber synaptic structure and physiology. Consistently, Pcdh19HET♀ but not Pcdh19HEMI♂ mice exhibit reduced pattern completion and separation abilities, which require mossy fiber synaptic function. Furthermore, PCDH19 appears to interact with N-cadherin at mossy fiber synapses. In Pcdh19HET♀ conditions, mismatch between PCDH19 and N-cadherin diminishes N-cadherin-dependent signaling and impairs mossy fiber synapse development; N-cadherin overexpression rescues Pcdh19HET♀ phenotypes. These results reveal previously unknown molecular and cellular mechanisms underlying the female-specific PCDH19 disorder phenotype.

The accurate localization of transgene expression after viral vector delivery is essential to the interpretation of experiments based on genetic-based approaches, such as chemo- or optogenetics. Postmortem histological analysis can be used to examine the injection target, the extent of the virus transduction, the types of cells expressing the transgene, and the subcellular localization of the protein. In this chapter, we will provide a general description of methods to identify transgene expression, immunocytochemistry protocols, and examples of specific protocols. We close the chapter with an example of an application of electron microscopy to identify the localization of transgene expression.

O-GlcNAc is a dynamic post-translational modification (PTM) that regulates protein functions. In studying the regulatory roles of O-GlcNAc, a major roadblock is the inability to change O-GlcNAcylation on a single protein at a time. Herein, we developed a dual RNA-aptamer-based approach that simultaneously targeted O-GlcNAc transferase (OGT) and β-catenin, the key transcription factor of the Wnt signaling pathway, to selectively increase O-GlcNAcylation of the latter without affecting other OGT substrates. Using the OGT/β-catenin dual-specificity aptamers, we found that O-GlcNAcylation of β-catenin stabilizes the protein by inhibiting its interaction with β-TrCP. O-GlcNAc also increases β-catenin's interaction with EZH2, recruits EZH2 to promoters, and dramatically alters the transcriptome. Further, by coupling riboswitches or an inducible expression system to aptamers, we enabled inducible regulation of protein-specific O-GlcNAcylation. Together, our findings demonstrate the efficacy and versatility of dual-specificity aptamers for regulating O-GlcNAcylation on individual proteins.

High dimensional single-cell analysis such as single cell and single nucleus RNA sequencing (sc/snRNAseq) are currently being widely applied to explore microglia diversity. The use of sc/snRNAseq provides a powerful and unbiased approach to deconvolve heterogeneous cellular populations. However, sc/snRNAseq and analyses pipelines are designed to find heterogeneity. Indeed, cellular heterogeneity is often the most frequently reported finding. In this Perspective, we consider the ubiquitous concept of heterogeneity focusing on its application to microglia research and its influence on the field of neuroimmunology. We suggest that a clear understanding of the semantic and biological implications of microglia heterogeneity is essential for mitigating confusion among researchers.