Microglia are macrophages present in the brain that function as the primary and most important source of immune response in the central nervous system (CNS). Regardless of their multitasking role, our knowledge regarding their molecular heterogeneity is limited; due to technical restrictions, it is only possible to measure gene expression in cell populations, not individual cells, with the results reflecting average mRNA levels. Therefore, recent scientific approaches have focused on single-cell techniques such as single-cell RNA sequencing (scRNAseq), a powerful technique that enables the delineation of transcriptomic cell-to-cell differences, revealing subpopulations with distinct molecular and functional characteristics. Here, we summarize recent studies that focused on transcriptomic microglial subpopulation clustering and classify them into three distinct groups based on age, spatial distribution, and disease. Additionally, we cross-compare populations from different studies to identify expressional and functional overlaps between them.

(1) Background: A proposed approach to promote periodontal tissue regeneration in cases of peri-implantitis is the local administration of growth factors at the implant site. Recombinant human bone morphogenetic protein-2 (rh-BMP-2) can effectively promote bone regeneration and osseointegration and the development of appropriate carriers for its delivery is of paramount importance. The aim of the present study was to develop SBA-15 mesoporous nanoparticles (MSNs) with varying porosity, evaluate their biocompatibility with human Periodontal Ligament Cells (hPDLCs) and to investigate their effectiveness as carriers of rh-BMP-2. (2) Methods: SBA-15 type mesoporous silicas were synthesized via sol–gel reaction. The calcined SBA-15 samples were characterized by N₂ porosimetry, Fourier transform–infrared spectrometry (FTIR), Scanning (SEM) and Transmission Electron Microscopy (TEM). Rh-BMP-2 loading and release kinetics were evaluated by UV spectroscopy. (3) Results: MSNs presented hexagonally arranged, tubular pores of varying length and diameter. Slightly higher loading capacity was achieved for SBA-15 with large pores that presented good hemocompatibility. MTT assay revealed no cytotoxic effects for all the tested materials, while SBA-15 with large pores induced a significant upregulation of cell viability at day 5. (4) Conclusions: SBA-15 MSNs may prove a valuable delivery platform towards the effective release of bone-inducing proteins.

Background: Amyotrophic lateral sclerosis (ALS) is a rare progressive neurodegenerative disease that affects upper and lower motor neurons. As the molecular basis of the disease is still elusive, the development of high-throughput sequencing technologies, combined with data mining techniques and machine learning methods, could provide remarkable results in identifying pathogenetic mechanisms. High dimensionality is a major problem when applying machine learning techniques in biomedical data analysis, since a huge number of features is available for a limited number of samples. The aim of this study was to develop a methodology for training interpretable machine learning models in the classification of ALS and ALS-subtypes samples, using gene expression datasets. Methods: We performed dimensionality reduction in gene expression data using a semi-automated preprocessing systematic gene selection procedure using Statistically Equivalent Signature (SES), a causality-based feature selection algorithm, followed by Boosted Regression Trees (XGBoost) and Random Forest to train the machine learning classifiers. The SHapley Additive exPlanations (SHAP values) were used for interpretation of the machine learning classifiers. The methodology was developed and tested using two distinct publicly available ALS RNA-seq datasets. We evaluated the performance of SES as a dimensionality reduction method against: (a) Least Absolute Shrinkage and Selection Operator (LASSO), and (b) Local Outlier Factor (LOF). Results: The proposed methodology achieved 85.18% accuracy for the classification of cerebellum or frontal cortex samples as C9orf72-related familial ALS, sporadic ALS or healthy samples. Importantly, the genes identified as the most determinative have also been reported as disease-associated in ALS literature. When tested in the evaluation dataset, the methodology achieved 88.89% accuracy for the classification of sporadic ALS motor neuron samples. When LASSO was used as feature selection method instead of SES, the accuracy of the machine learning classifiers ranged from 74.07 to 96.30%, depending on tissue assessed, while LOF underperformed significantly (77.78% accuracy for the classification of pooled cerebellum and frontal cortex samples). Conclusions: Using SES, we addressed the challenge of high dimensionality in gene expression data analysis, and we trained accurate machine learning ALS classifiers, specific for the gene expression patterns of different disease subtypes and tissue samples, while identifying disease-associated genes.

Prion diseases are transmissible encephalopathies associated with the conversion of the physiological form of the prion protein (PrP^C) to the disease-associated (PrP^Sc). Despite intense research, no therapeutic or prophylactic agent is available. The catechol-type diterpene Carnosic acid (CA) and its metabolite Carnosol (CS) from Rosmarinus officinalis have well-documented anti-oxidative and neuroprotective effects. Since oxidative stress plays an important role in the pathogenesis of prion diseases, we investigated the potential beneficial role of CA and CS in a cellular model of prion diseases (N2a22L cells) and in a cell-free prion amplification assay (RT-QuIC). The antioxidant effects of the compounds were confirmed when N2a22L were incubated with CA or CS. Furthermore, CA and CS reduced the accumulation of the disease-associated form of PrP, detected by Western Blotting, in N2a22L cells. This effect was validated in RT-QuIC assays, indicating that it is not associated with the antioxidant effects of CA and CS. Importantly, cell-free assays revealed that these natural products not only prevent the formation of PrP aggregates but can also disrupt already formed aggregates. Our results indicate that CA and CS have pleiotropic effects against prion diseases and could evolve into useful prophylactic and/or therapeutic agents against prion and other neurodegenerative diseases.

RNA editing is an epitranscriptomic modification, leading to targeted changes in RNA transcripts. It is mediated by the action of ADAR (adenosine deaminases acting on double-stranded (ds) RNA and APOBEC (apolipoprotein B mRNA editing enzyme catalytic polypeptide-like) deaminases and appears to play a major role in the pathogenesis of many diseases. Here, we assessed its role in experimental autoimmune encephalomyelitis (EAE), a widely used non-clinical model of autoimmune inflammatory diseases of the central nervous system (CNS), which resembles many aspects of human multiple sclerosis (MS). We have analyzed in silico data from microglia isolated at different timepoints through disease progression to identify the global editing events and validated the selected targets in murine tissue samples. To further evaluate the functional role of RNA editing, we induced EAE in transgenic animals lacking expression of APOBEC-1. We found that RNA-editing events, mediated by the APOBEC and ADAR deaminases, are significantly reduced throughout the course of disease, possibly affecting the protein expression necessary for normal neurological function. Moreover, the severity of the EAE model was significantly higher in APOBEC-1 knock-out mice, compared to wild-type controls. Our results implicate regulatory epitranscriptomic mechanisms in EAE pathogenesis that could be extrapolated to MS and other neurodegenerative disorders (NDs) with common clinical and molecular features.

RNA editing contributes to transcriptome diversification through RNA modifications in relation to genome-encoded information (RNA–DNA differences, RDDs). The deamination of Adenosine (A) to Inosine (I) or Cytidine (C) to Uridine (U) is the most common type of mammalian RNA editing. It occurs as a nuclear co- and/or post-transcriptional event catalyzed by ADARs (Adenosine deaminases acting on RNA) and APOBECs (apolipoprotein B mRNA editing enzyme catalytic polypeptide-like genes). RNA editing may modify the structure, stability, and processing of a transcript. This review focuses on RNA editing in psychiatric, neurological, neurodegenerative (NDs), and autoimmune brain disorders in humans and rodent models. We discuss targeted studies that focus on RNA editing in specific neuron-enriched transcripts with well-established functions in neuronal activity, and transcriptome-wide studies, enabled by recent technological advances. We provide comparative editome analyses between human disease and corresponding animal models. Data suggest RNA editing to be an emerging mechanism in disease development, displaying common and disease-specific patterns. Commonly edited RNAs represent potential disease-associated targets for therapeutic and diagnostic values. Currently available data are primarily descriptive, calling for additional research to expand global editing profiles and to provide disease mechanistic insights. The potential use of RNA editing events as disease biomarkers and available tools for RNA editing identification, classification, ranking, and functional characterization that are being developed will enable comprehensive analyses for a better understanding of disease(s) pathogenesis and potential cures.