Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain.

In the human brain, the dorsal anterior cingulate cortex (dACC) plays key roles in various components of cognitive control, and is particularly relevant for reward processing and conflict monitoring. The dACC regulates expression of fear and pain, and its dysfunction is implicated in a number of neuropsychiatric disorders. Compared to more recently specialized neocortical areas, such as the dorsolateral prefrontal cortex (dlPFC), the dACC is evolutionarily older.

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.

Cell types in the hippocampus with unique morphology, physiology and connectivity serve specialized functions associated with cognition and mood. These cell types are spatially organized, necessitating molecular profiling strategies that retain cytoarchitectural organization. Here we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from anterior human hippocampus in ten adult neurotypical donors.

lute: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression.

Background: Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. While there exist algorithms to estimate the cell type proportions in tissues, a major challenge is the algorithms can show reduced performance if using tissues that have varying cell sizes, such as in brain tissue. In this way, without adjusting for differences in cell sizes, computational algorithms estimate the relative fraction of RNA attributable to each cell type, rather than the relative fraction of cell types, leading to potentially biased estimates in cellular composition.

Risk factor analysis and clinical experience of treating red breast syndrome in acellular dermal matrix and implant-based breast reconstruction.

Background: Red breast syndrome (RBS) is represented as idiopathic cutaneous erythema overlying the acellular dermal matrix (ADM) after implant-based breast reconstruction without other signs and symptoms of infection. Although a number of etiologies including lymphatic disruption, delayed hypersensitivity reaction to ADM, and residual DNA within ADM have been suggested for RBS, consensus regarding risk factors and treatment for RBS has been reached yet. Thus, the aim of this study was to find risk factors for RBS and introduce our experience of successful treatment of RBS.

Benchmark of cellular deconvolution methods using a multi-assay dataset from postmortem human prefrontal cortex.

Cellular deconvolution of bulk RNA-sequencing data using single cell/nuclei RNA-seq reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as the human brain. Here, we generate a multi-assay dataset in postmortem human dorsolateral prefrontal cortex from 22 tissue blocks, including bulk RNA-seq, reference snRNA-seq, and orthogonal measurement of cell type proportions with RNAScope/ImmunoFluorescence. We use this dataset to evaluate six deconvolution algorithms.

Integrating Spatially-Resolved Transcriptomics Data Across Tissues and Individuals: Challenges and Opportunities.

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. The lowering cost of SRT data generation presents an unprecedented opportunity to create large-scale spatial atlases and enable population-level investigation, integrating SRT data across multiple tissues, individuals, species, or phenotypes. Here, unique challenges are described in the SRT data integration, where the analytic impact of varying spatial and biological resolutions is characterized and explored.

Mature microRNA-binding protein QKI suppresses extracellular microRNA let-7b release.

Argonaute (AGO), a component of RNA-induced silencing complexes (RISCs), is a representative RNA-binding protein (RBP) known to bind with mature microRNAs (miRNAs) and is directly involved in post-transcriptional gene silencing. However, despite the biological significance of miRNAs, the roles of other miRNA-binding proteins (miRBPs) remain unclear in the regulation of miRNA loading, dissociation from RISCs and extracellular release. In this study, we performed protein arrays to profile miRBPs and identify 118 RBPs that directly bind to miRNAs.

Integrating spatially-resolved transcriptomics data across tissues and individuals: challenges and opportunities.

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. As the cost of generating these data decreases, these technologies provide an exciting opportunity to create large-scale atlases that integrate SRT data across multiple tissues, individuals, species, or phenotypes to perform population-level analyses. Here, we describe unique challenges of varying spatial resolutions in SRT data, as well as highlight the opportunities for standardized preprocessing methods along with computational algorithms amenable to atlas-scale datasets leading to improved sensitivity and reproducibility in the future.

Quantitative analysis of radiosensitizing effect for magnetic hyperthermia-radiation combined therapy on prostate cancer cells.

Background: Magnetic hyperthermia (MHT) has emerged as a promising therapeutic approach in the field of radiation oncology due to its superior precision in controlling temperature and managing the heating area compared to conventional hyperthermia. Recent studies have proposed solutions to address clinical safety concerns associated with MHT, which arise from the use of highly concentrated magnetic nanoparticles and the strong magnetic field needed to induce hyperthermic effects. Despite these efforts, challenges remain in quantifying therapeutic outcomes and developing treatment plan systems for combining MHT with radiation therapy (RT).

: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression.

Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. Current computational tools estimate relative RNA abundances rather than cell type proportions in tissues with varying cell sizes, leading to biased estimates. We present , a computational tool to accurately deconvolute cell types with varying sizes.

The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics.

Norepinephrine (NE) neurons in the locus coeruleus (LC) make long-range projections throughout the central nervous system, playing critical roles in arousal and mood, as well as various components of cognition including attention, learning, and memory. The LC-NE system is also implicated in multiple neurological and neuropsychiatric disorders. Importantly, LC-NE neurons are highly sensitive to degeneration in both Alzheimer's and Parkinson's disease.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets.

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions.

Autophagy activates EGR1 via MAPK/ERK to induce FGF2 in renal tubular cells for fibroblast activation and fibrosis during maladaptive kidney repair.

Macroautophagy/autophagy contributes to maladaptive kidney repair by inducing pro-fibrotic factors such as FGF2 (fibroblast growth factor 2), but the underlying mechanism remains elusive. Here, we show that EGR1 (early growth response 1) was induced in injured proximal tubules after ischemic acute kidney injury (AKI) and this induction was suppressed by autophagy deficiency in inducible, renal tubule-specific (autophagy related 7) knockout (iRT- KO) mice. In cultured proximal tubular cells, TGFB1 (transforming growth factor beta 1) induced EGR1 and this induction was also autophagy dependent.

Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue.

We define and identify a new class of control genes for next-generation sequencing called total RNA expression genes (TREGs), which correlate with total RNA abundance in cell types of different sizes and transcriptional activity. We provide a data-driven method to identify TREGs from single-cell RNA sequencing data, allowing the estimation of total amount of RNA when restricted to quantifying a limited number of genes. We demonstrate our method in postmortem human brain using multiplex single-molecule fluorescent in situ hybridization and compare candidate TREGs against classic housekeeping genes.

Analysis of the Outcomes of Immediate Recurrent Laryngeal Nerve Reconstruction During Thyroid Surgery for Prevention of Vocal Fold Paralysis.

Background: Recurrent laryngeal nerve (RLN) injury and the resulting paralysis is the most common and known complication of thyroid surgery. Several surgical techniques, such as medialization thyroplasty with or without arytenoid adduction and injection laryngoplasty, have been developed to treat RLN injury, but these procedures have specific limitations and complications. In this study, we present the outcomes for our patients who underwent immediate RLN reconstruction during thyroid surgery by analyzing both subjective and objective outcomes.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single cell RNA-sequencing datasets.

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding the pathologies of diseases. However, several experimental and computational challenges remain in developing and implementing transcriptomics-based deconvolution approaches, especially those using a single cell/nuclei RNA-seq reference atlas, which are becoming rapidly available across many tissues. Notably, deconvolution algorithms are frequently developed using samples from tissues with similar cell sizes.

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex.

Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture.

SUFI: an automated approach to spectral unmixing of fluorescent multiplex images captured in mouse and post-mortem human brain tissues.

Background: Multispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample. Multiple fluorescent dyes, each measuring a unique molecule, are simultaneously measured and subsequently "unmixed" to provide a read-out for each molecular signal. This strategy allows for measuring highly multiplexed signals in a single data capture session, such as multiple proteins or RNAs in tissue slices or cultured cells, but can often result in mixed signals and bleed-through problems across dyes.

Ascorbate peroxidase-mediated in situ labelling of proteins in secreted exosomes.

The extracellular vesicle exosome mediates intercellular communication by transporting macromolecules such as proteins and ribonucleic acids (RNAs). Determining cargo contents with high accuracy will help decipher the biological processes that exosomes mediate in various contexts. Existing methods for probing exosome cargo molecules rely on a prior exosome isolation procedure.