Multiple Cell Types Research Articles

Maintenance of Cardiac Microenvironmental Homeostasis: A Joint Battle of Multiple Cells.

Various cells such as cardiomyocytes, fibroblasts and endothelial cells constitute integral components of cardiac tissue. The health and stability of cardiac ecosystem are ensured by the action of a certain type of cell and the intricate interactions between multiple cell types. The dysfunctional cells exert a profound impact on the development of cardiovascular diseases by involving in the pathological process. In this paper, we introduce the dynamic activity, cell surface markers as well as biological function of the various cells in the heart. Besides, we discuss the multiple signaling pathways involved in the cardiac injury including Hippo/YAP, TGF-β/Smads, PI3K/Akt, and MAPK signaling. The complexity of different cell types poses a great challenge to the disease treatment. By characterizing the roles of various cell types in cardiovascular diseases, we sought to discuss the potential strategies for preventing and treating cardiovascular diseases.

ELemur: A cellular-resolution 3D atlas of the mouse lemur brain

The gray mouse lemur (Microcebus murinus), one of the smallest living primates, emerges as a promising model organism for neuroscience research. This is due to its genetic similarity to humans, its evolutionary position between rodents and humans, and its primate-like features encapsulated within a rodent-sized brain. Despite its potential, the absence of a comprehensive reference brain atlas impedes the progress of research endeavors in this species, particularly at the microscopic level. Existing references have largely been confined to the macroscopic scale, lacking detailed anatomical information. Here, we present eLemur, a unique resource, comprising a repository of high-resolution brain-wide images immunostained with multiple cell type and structural markers, elucidating the cyto- and chemoarchitecture of the mouse lemur brain. Additionally, it encompasses a segmented two-dimensional reference and 3D anatomical brain atlas delineated into cortical, subcortical, and other vital regions. Furthermore, eLemur includes a comprehensive 3D cell atlas, providing densities and spatial distributions of non-neuronal and neuronal cells across the mouse lemur brain. Accessible via a web-based viewer (https://eeum-brain.com/#/lemurdatasets), the eLemur resource streamlines data sharing and integration, fostering the exploration of different hypotheses and experimental designs using the mouse lemur as a model organism. Moreover, in conjunction with the growing 3D datasets for rodents, nonhuman primates, and humans, our eLemur 3D digital framework enhances the potential for comparative analysis and translation research, facilitating the integration of extensive rodent study data into human studies.

Polyphenol-Scaffolded Modular Assembly of Heterotypic Cell-Cell Assemblies for Potentiating Cancer Immunotherapy.

Cells existing in the form of clusters often exhibit distinct biological functions from their single-cell counterparts. However, the ability to modulate cell-cell interactions among multiple cell types through molecular scaffolds remains an ongoing challenge. Here, a supramolecular phenolic network on surfaces of live cells designed is engineered to act as modular scaffolds that promote intercellular interactions, presenting a universal platform for the construction of cell-cell assemblies (CCAs). Utilizing the inherent cell surface affinity of supramolecular phenolic network modules, a series of heterotypic CCAs is efficiently established by assembling five distinct microorganisms and five types of mammalian cells. A specific application of CCAs with the combination of L. casei and macrophages (L. casei@Mφ) is highlighted for enhanced cancer immunotherapy. Upon intravenous administration, L. casei@Mφ allows the chemotactic Mφ to facilitate the accumulation of L. casei at the tumor. The accumulated L. casei enables the polarization of tumor-associated Mφ toward a pro-inflammatory phenotype, markedly improving the immunotherapeutic response, slowing tumor progression, and mitigating lung metastasis. This work demonstrates the potential of polyphenol-scaffolded modular assembly in manipulating cell-cell interactions to enhance multicellular cooperation, offering a general approach to controlling complex cellular behaviors.

Sexually dimorphic differences in angiogenesis markers are associated with brain aging trajectories in humans.

Aberrant angiogenesis could contribute to the development of cognitive impairment and represent a therapeutic target for preventing dementia. However, most studies addressing angiogenesis and cognitive impairment focus on model organisms. To test the relevance of angiogenesis to human cognitive aging, we evaluated associations of circulating blood markers of angiogenesis with brain aging trajectories in a pooled two-center sample from deeply phenotyped longitudinal human cohorts (n = 435; female = 207, age = 74 ± 9) using cognitive assessments, biospecimens, structural brain imaging, and clinical data. Blood markers included ligands involved in angiogenesis and vascular function such as basic fibroblast growth factor (bFGF), members of the vascular endothelial growth factor family (VEGFA, VEGFB, and VEGFC), and placental growth factor (PlGF), in addition to their receptors VEGF receptor 1 (VEGFR1) and tyrosine kinase with immunoglobulin and EGF homology domain 2 (Tie2). Machine learning and traditional statistics revealed sexually dimorphic associations of plasma angiogenic growth factors with brain aging outcomes, including executive function and gray matter atrophy. Specifically, markers of angiogenesis were associated with higher executive function and less brain atrophy in younger women (not men), a directionality of association that reversed around age 75. Higher concentrations of bFGF, known for pleiotropic effects on multiple cell types, predicted favorable cognitive trajectories in both women and men. An independent sample from a multicenter dataset (MarkVCID; n = 80; female = 30, age = 73 ± 9) was used to externally validate these findings. In conclusion, this analysis demonstrates the association of angiogenesis to human brain aging, with potential therapeutic implications for vascular cognitive impairment and dementia.

A novel human protein-coding locus identified using a targeted RNA enrichment technique.

Accurate and comprehensive genomic annotation, including the full list of protein-coding genes, is vital for understanding the molecular mechanisms of human biology. We have previously shown that the genome contains a multitude of yet hidden functional exons and transcripts, some of which might represent novel mRNAs. These results resonate with those from other groups and strongly argue that two decades after the completion of the first draft of the human genome sequence, the current annotation of human genes and transcripts remains far from being complete. Using a targeted RNA enrichment technique, we showed that one of the novel functional exons previously discovered by us and currently annotated as part of a long non-coding RNA, is actually a part of a novel protein-coding gene, InSETG-4, which encodes a novel human protein with no known homologs or motifs. We found that InSETG-4 is induced by various DNA-damaging agents across multiple cell types and therefore might represent a novel component of DNA damage response. Despite its low abundance in bulk cell populations, InSETG-4 exhibited expression restricted to a small fraction of cells, as demonstrated by the amplification-based single-molecule fluorescence in situ hybridization (asmFISH) analysis. This study argues that yet undiscovered human protein-coding genes exist and provides an example of how targeted RNA enrichment techniques can help to fill this major gap in our knowledge of the information encoded in the human genome.

CD46 Is a Protein Receptor for Human Adenovirus Type 64

Certain species D human adenoviruses (HAdV-D19, -D37, and -D64) are causative agents of epidemic keratoconjunctivitis. HAdV-D37 has previously been shown to bind CD46 (membrane cofactor protein) and sialic acid as adhesion receptors. HAdV-D64 is genetically highly similar to HAdV-D37, with an identical fiber protein sequence, but differs substantially in its penton base and hexon proteins, two other major capsid components, due to genetic recombination. Here, we demonstrate that, like HAdV-D37, HAdV-D64 virions bind directly to CD46 and that CD46 and sialic acid also function as receptors for HAdV-D64 on multiple cell types. Expression of CD46 on CD46-negative cells conferred susceptibility to HAdV-D64 entry. Specifically blocking HAdV-D64 binding to CD46 on the host cell surface strongly inhibits viral entry and gene delivery into multiple cell lines that represent target tissues. We show that CD46 is expressed on human conjunctival epithelial cells and directly binds to the HAdV-D64 virion. Our results suggest that HAdV-D64 may be used to deliver genes to target conjunctival cells and that interrupting HAdV-D64 entry through its interaction with CD46 may prevent or lessen adenovirus-associated ocular disease.

SingletSeeker: an unsupervised clustering approach for automated singlet discrimination in cytometry.

Flow cytometry is a high-throughput, high-dimensional technique that generates large sets of single-cell data. Prior to analyzing this data, it is common to exclude any events that contain two or more cells, multiplets, to ensure downstream analysis and quantification is of single-cell events, singlets, only. The process of singlet discrimination is critical yet fundamentally subjective and time-consuming; it is performed manually by the user, where the proper exclusion of multiplets depends on the user's expertise and often varies from experiment to experiment. To address this problem, we have developed an algorithm to automatically discriminate singlets from other unwanted events such as multiplets and debris. Using parameters derived from imaging, the algorithm first identifies high-density clusters of events using a density-based clustering algorithm, and then classifies the clusters based on their properties. Multiplets are discarded in the first step, while singlets are distinguished from debris in the second step. The algorithm can use different strategies on imaging feature selection-based user's preferences and imaging features available. In addition, the relative importance of singlets precision vs. sensitivity can be further tweaked via a density coefficient adjustment. Twenty-two datasets from various sites and of various cell types acquired on the BD FACSDiscover™ S8 Cell Sorter with CellView™ Image Technology were used to develop and validate the algorithm across multiple imaging feature sets. A consistent singlets precision >97% with a solid >88% sensitivity has been demonstrated with a LightLoss feature set and the default density coefficient. This work yields a high-precision, high-sensitivity algorithm capable of objective and automated singlet discrimination across multiple cell types using various imaging-derived parameters. A free FlowJo™ Software plugin implementation is available for simple and reproducible singlet discrimination for use at the beginning of any user's workflow.

Lactate Dehydrogenase-B Oxidation and Inhibition by Singlet Oxygen and Hypochlorous Acid

Alterations in cellular energy metabolism are a hallmark of cancer and lactate dehydrogenase (LDH) enzymes are overexpressed in many cancers regardless of sufficient oxygen and functional mitochondria. Further, L-lactate plays signaling roles in multiple cell types. We evaluated the effect of singlet oxygen and hypochlorous acid (HOCl) on pig heart LDH-B, which shares 97% homology with human LDH-B. Singlet oxygen was generated photochemically using methylene blue or the chlorophyll metabolites, pheophorbide A and chlorin e6. Singlet oxygen induced protein crosslinks observed by SDS-PAGE under reducing conditions and inhibited LDH-B activity. Ascorbate, hydrocaffeic acid, glutathione and sodium azide were employed as singlet oxygen scavengers and shown to protect LDH-B. Using fluorescein-modified maleimide, no changes in cysteine availability as a result of singlet oxygen damage were observed. This was in contrast to HOCl, which induced the formation of disulfides between LDH-B subunits, thereby decreasing LDH-B labeling with fluorescein. HOCl oxidation inhibited LDH-B activity; however, disulfide reduction did not restore it. LDH-B cysteines were resistant to millimolar H2O2, chloramines and Angeli’s salt. In the absence of pyruvate, LDH-B enhanced NADH oxidation in a chain reaction initiated by singlet oxygen that resulted in H2O2 formation. Once damaged by either singlet oxygen or HOCl, NADH oxidation by LDH-B was impaired.

Study on the therapeutic potential of induced neural stem cells for Alzheimer's disease in mice

Induced neural stem cells (iNSCs), which have similar properties to neural stem cells and are able to self-proliferate and differentiate into neural cell lineages, are expected to be potential cells for the treatment of neurodegeneration disease. However, cell therapy based on iNSCs transplantation is limited by the inability to acquire sufficient quantities of iNSCs. Previous studies have found that mouse and human fibroblasts can be directly reprogrammed into iNSCs with a single factor, Sox2. Here, we induced mouse embryonic fibroblasts (MEFs) into iNSCs by combining valproic acid (VPA) with the induction factor Sox2, and the results showed that VPA significantly improved the conversion efficiency of fibroblasts to iNSCs. The iNSCs exhibited typical neurosphere-like structures that can express NSCs markers, such as Sox2, Nestin, Sox1, and Zbtb16, and could differentiate into neurons, astrocytes, and oligodendrocytes in vitro. Subsequently, the iNSCs were stereotactically transplanted into the hippocampus of APP/PS1 double transgenic mice (AD mice). Post-transplantation, the iNSCs showed long-term survival, migrated over long distances, and differentiated into multiple types of functional neurons and glial cells in vivo. Importantly, the cognitive abilities of APP/PS1 mice transplanted with iNSCs exhibited significant functional recovery. These findings suggest that VPA enhances the conversion efficiency of fibroblasts into iNSCs when used in combination with Sox2, and iNSCs hold promise as a potential donor material for transplantation therapy in Alzheimer’s disease.

CRISPR/CasRx suppresses KRAS-induced brain arteriovenous malformation developed in postnatal brain endothelial cells in mice.

Brain arteriovenous malformations (bAVMs) are anomalies forming vascular tangles connecting the arteries and veins, which cause hemorrhagic stroke in young adults. Current surgical approaches are highly invasive, and alternative therapeutic methods are warranted. Recent genetic studies identified KRAS mutations in endothelial cells of bAVMs; however, the underlying process leading to malformation in the postnatal stage remains unknown. Here we established a mouse model of bAVM developing during the early postnatal stage. Among 4 methods tested, mutant KRAS specifically introduced in brain endothelial cells by brain endothelial cell-directed adeno-associated virus (AAV) and endothelial cell-specific Cdh5-CreERT2 mice successfully induced bAVMs in the postnatal period. Mutant KRAS led to the development of multiple vascular tangles and hemorrhage in the brain with increased MAPK/ERK signaling and growth in endothelial cells. Three-dimensional analyses in cleared tissue revealed dilated vascular networks connecting arteries and veins, similar to human bAVMs. Single-cell RNA-Seq revealed dysregulated gene expressions in endothelial cells and multiple cell types involved in the pathological process. Finally, we employed CRISPR/CasRx to knock down mutant KRAS expression, which efficiently suppressed bAVM development. The present model reveals pathological processes that lead to postnatal bAVMs and demonstrates the efficacy of therapeutic strategies with CRISPR/CasRx.

Spatial dissection of tumour microenvironments in gastric cancers reveals the immunosuppressive crosstalk between CCL2+ fibroblasts and STAT3-activated macrophages

BackgroundA spatially resolved, niche-level analysis of tumour microenvironments (TME) can provide insights into cellular interactions and their functional impacts in gastric cancers (GC).ObjectiveOur goal was to translate the spatial organisation...

Plasma-derived exosomes of Edwardsiella piscicida challenged olive flounder (Paralichthys olivaceus): Characterization and miRNA profiling for potential biomarkers screening

Exosomes are released from multiple cell types as part of their normal physiology as well as during acquired abnormalities. In this study, we investigated the effect of pathogenic Edwardsiella piscicida infection on olive flounder (Paralichthys olivaceus) exosomes at morphometric, physicochemical, and molecular levels. Unique cup-shaped exosomes were isolated from the plasma of non-infected (PBS-Exo) and E. piscicida experimentally challenged (Ep-Exo) olive flounder using ultracentrifugation. The average particle size, concentration, and zeta potential were 150.9 ± 6.9 nm, 5.67 × 1010 particles/mL, and −25.6 ± 1.36 mV for PBS-Exo while 138.7 ± 1.9 nm, 1.22 × 1011 particles/mL, and −35 ± 1.82 mV for Ep-Exo, respectively. Expression of tetraspanin markers (CD81, CD9, and CD63) confirmed the presence of olive flounder exosomes. Differentially expressed (DE) known (9) and novel (29) miRNAs (log2 fold change ≥1; p < 0.05) were identified in the Ep-Exo that could be potential as diagnostic biomarkers for the infection. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that the predicted target genes of the DE miRNAs were highly enriched in metabolic and immune roles. Both PBS-Exo and Ep-Exo were non-toxic in vitro (up to 100 μg/mL) and in vivo (up to 400 μg/mL). Compared to the vehicle, PBS-Exo at 50 μg/mL induced Nf-kB (>1.50-fold) while at 100 μg/mL, Il8, Il10, Nf-kB, P53, and Inf were induced (>1.50-fold) in fathead minnow cells (FHMs). This suggests that the PBS-Exo contains molecules that moderately stimulate gene expression. In the future, validating the exact olive flounder immune response target genes that interact with DE miRNAs in Ep-Exo will be crucial for investigating the host-pathogen interactions, immune defense mechanisms, and therapeutic targets for olive flounder against E. piscicida infection.

A fluorescence and SERS dual-mode biosensor for quantification and imaging of Mucin1 in living cells

Mucin1 (MUC1) is a cell surface transmembrane protein overexpressed in multiple types of tumor cells, which is generally considered as a tumor-associated biomarker. Thus, quantifying and imaging of MUC1 in tumor cells is of great significance for the diagnosis and biological therapy of tumors. Herein, a fluorescence (FL) and surface-enhanced Raman scattering (SERS) dual-mode biosensor was developed for sensitive detection and imaging of MUC1 in living cells. The FL-SERS biosensor was based on self-assembled satellite structures mediated by the competition of MUC1 and complementary DNA modified on Au nanostars (AuNS-cDNA-PEG) with aptamer modified on quantum dots (QD-PDDA-Apt). This biosensor achieved dual-mode quantification and imaging of MUC1 by quenching the FL signal of QD and significantly enhancing the SERS signal of PDDA through the metal FL quenching effect and hotspot effect of AuNS, respectively. The dual-mode biosensor exhibited high sensitivity to MUC1, with a detection limit of 1.19 fg/mL under FL mode and 1.16 fg/mL under SERS mode. Moreover, this biosensor displayed good selectivity, nice biological stability and low cytotoxicity. Importantly, this biosensor possessed an excellent MUC1 dual-mode imaging capability with high specificity in different tumor cells, providing a new idea for clinical diagnosis of tumors.

Mutual information for detecting multi-class biomarkers when integrating multiple bulk or single-cell transcriptomic studies.

Biomarker detection plays a pivotal role in biomedical research. Integrating omics studies from multiple cohorts can enhance statistical power, accuracy and robustness of the detection results. However, existing methods for horizontally combining omics studies are mostly designed for two-class scenarios (e.g., cases versus controls) and are not directly applicable for studies with multi-class design (e.g., samples from multiple disease subtypes, treatments, tissues, or cell types). We propose a statistical framework, namely Mutual Information Concordance Analysis (MICA), to detect biomarkers with concordant multi-class expression pattern across multiple omics studies from an information theoretic perspective. Our approach first detects biomarkers with concordant multi-class patterns across partial or all of the omics studies using a global test by mutual information. A post hoc analysis is then performed for each detected biomarkers and identify studies with concordant pattern. Extensive simulations demonstrate improved accuracy and successful false discovery rate control of MICA compared to an existing MCC method. The method is then applied to two practical scenarios: four tissues of mouse metabolism-related transcriptomic studies, and three sources of estrogen treatment expression profiles. Detected biomarkers by MICA show intriguing biological insights and functional annotations. Additionally, we implemented MICA for single-cell RNA-Seq data for tumor progression biomarkers, highlighting critical roles of ribosomal function in the tumor microenvironment of triple-negative breast cancer and underscoring the potential of MICA for detecting novel therapeutic targets. The source code is available on Figshare at https://doi.org/10.6084/m9.figshare.27635436. Additionally, the R package can be installed directly from GitHub at https://github.com/jianzou75/MICA. Supplementary data are available at Bioinformatics online.

Leveraging Multi-omics to Disentangle the Complexity of Ovarian Cancer.

To better understand ovarian cancer lethality and treatment resistance, sophisticated computational approaches are required that address the complexity of the tumor microenvironment, genomic heterogeneity, and tumor evolution. The ovarian cancer tumor ecosystem consists of multiple tumors and cell types that support disease growth and progression. Over the last two decades, there has been a revolution in -omic methodologies to broadly define components and essential processes within the tumor microenvironment, including transcriptomics, metabolomics, proteomics, genome sequencing, and single-cell analyses. While most of these technologies comprehensively characterize a single biological process, there is a need to understand the biological and clinical impact of integrating multiple -omics platforms. Overall, multi-omics is an intriguing analytic framework that can better approximate biological complexity; however, data aggregation and integration pipelines are not yet sufficient to reliably glean insights that affect clinical outcomes.

Abstract B034: Engineering the tumor microenvironment: Patient-specific microphysiological systems of the head and neck cancer tumor microenvironment

Abstract Introduction: Survival rates in advanced head and neck cancer (HNC) remain poor with no clinically approved biomarkers to predict treatment efficacy. HNC is a highly heterogenous disease and the lack of available models that capture patient heterogeneity and the complexity of the tumor microenvironment (TME) contributes to these poor patient outcomes. Microphysiological systems (MPS) are complex multicellular in vitro models that can recapitulate three-dimensional organ structure and function. The low cell number requirements for MPS permits the creation of patient-specific TME models, where all the cell types can be isolated from a single piece of tumor tissue. These patient-specific MPS represent a promising strategy for elucidating the contribution of the TME to treatment resistance, predicting the best treatment for each patient and improving patient outcomes in HNC. Here, we report a patient-specific MPS that contains multiple TME compartments and recapitulates patient heterogeneity. Methods: Tumor tissue was collected from patients with oral cavity carcinoma undergoing standard of care surgery followed by radiation or chemoradiation. Tissue from each patient was digested and tumor infiltrating leukocytes (TIL) were isolated using CD45 magnetic beads, while epithelial cells and fibroblasts were expanded in culture using specific media formulations. Tissue was also snap frozen for single cell RNA sequencing analysis. To build the MPS, a custom designed microfluidic device was filled with a hydrogel matrix containing patient-matched TIL, fibroblasts and epithelial spheroids to mimic the solid tumor. Lumens molded from the hydrogel were seeded with blood or lymphatic endothelial cells to create vasculature. Multiple replicate MPS can be built from each patient, which are cultured in an optimized media formulation to support the multiple primary cell types. Patient-specific MPS were treated with radiation or cisplatin + radiation to mimic the treatment the patient received. Multiple orthogonal endpoints were measured including tumor cell migration and viability, cytokine secretion and angiogenesis. Single cell sequencing was also performed on the original tumor tissue and matched MPS. Results: We have successfully created patient-specific models of the HNC TME. Single cell RNA sequencing analysis of the MPS suggests that cellular heterogeneity is being retained. Patient characteristics varied between MPS with some patient TME MPS showing highly migratory tumor cells or angiogenic responses. Treatment responses were measured for each patient-specific MPS and ongoing work will characterize the contributions of the TME to treatment resistance. These data demonstrate the feasibility of using patient-specific MPS to investigate the contribution of the TME to treatment response and resistance and lays important groundwork for using MPS to identify patient treatment responses. Citation Format: Adeel Ahmed, Marcos Lares, Fauzan Ahmed, Adam R. Burr, Paul M. Harari, David J. Beebe, Sheena C. Kerr. Engineering the tumor microenvironment: Patient-specific microphysiological systems of the head and neck cancer tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B034.

Uncovering disease-related multicellular pathway modules on large-scale single-cell transcriptomes with scPAFA.

Pathway analysis is a crucial analytical phase in disease research on single-cell RNA sequencing (scRNA-seq) data, offering biological interpretations based on prior knowledge. However, currently available tools for generating cell-level pathway activity scores (PAS) exhibit computational inefficacy in large-scale scRNA-seq datasets. Additionally, disease-related pathways are often identified through cross-condition comparisons within specific cell types, overlooking potential patterns that involve multiple cell types. Here, we present single-cell pathway activity factor analysis (scPAFA), a Python library designed for large-scale single-cell datasets allowing rapid PAS computation and uncovering biologically interpretable disease-related multicellular pathway modules, which are low-dimensional representations of disease-related PAS alterations in multiple cell types. Application on colorectal cancer (CRC) datasets and large-scale lupus atlas over 1.2 million cells demonstrated that scPAFA can achieve over 40-fold reductions in the runtime of PAS computation and further identified reliable and interpretable multicellular pathway modules that capture the heterogeneity of CRC and transcriptional abnormalities in lupus patients, respectively. Overall, scPAFA presents a valuable addition to existing research tools in disease research, with the potential to reveal complex disease mechanisms and support biomarker discovery at the pathway level.

Lymphocyte-based inflammatory markers: Novel predictors of significant coronary artery disease✰,✰✰

BackgroundLymphocyte-based inflammatory indices such as monocyte-to-lymphocyte ratio (MLR) have long been recognized as reliable coronary artery disease (CAD) predictors. More recently, novel indices like the Systemic Inflammatory Index (SII), Systemic Inflammatory Response Index (SIRI), and Systemic Immune-Inflammation Index (SIIRI) have emerged. These newer markers offer a more comprehensive assessment of inflammation by integrating multiple immune cell types, potentially enhancing the prediction of cardiovascular outcomes. ObjectivesWe evaluated the predictive value of novel inflammatory markers in estimating the pretest probability of severe CAD in high-risk patients. MethodsWe enrolled consecutive patients undergoing diagnostic coronary angiography in a single tertiary care hospital. Inflammatory markers were calculated based on pre-procedural complete blood count laboratory measurements. Severe CAD was defined as critical (>70 %) and actionable narrowing of a primary coronary artery. Classification performance was assessed using multivariate logistic regression. ResultsThe study sample included 363 patients (age 58.9± 11 years, 44.9 % females, 30 % severe CAD). In univariate analysis, MLR, SIRI, and SIIRI were significant predictors of severe CAD, with age- and sex-adjusted OR of 1.98 [1.25–3.14], 1.79 [1.24–2.59], and 1.63 [1.11–2.38], respectively. In multivariate analysis, SIRI remained an independent predictor of severe CAD (OR = 1.98, 95 % CI 1.13–3.46, p = 0.02). ConclusionOur results suggest that novel inflammatory markers derived from routine blood tests are predictive of severe CAD in high-risk patients. Such simple, practical, and cost-effective inflammatory markers may enhance cardiac risk stratification and prediction of severe CAD.

Isolation of psychedelic-responsive neurons underlying anxiolytic behavioral states.

Psychedelics hold promise as alternate treatments for neuropsychiatric disorders. However, the neural mechanisms by which they drive adaptive behavioral effects remain unclear. We isolated the specific neurons modulated by a psychedelic to determine their role in driving behavior. Using a light- and calcium-dependent activity integrator, we genetically tagged psychedelic-responsive neurons in the medial prefrontal cortex (mPFC) of mice. Single-nucleus RNA sequencing revealed that the psychedelic drove network-level activation of multiple cell types beyond just those expressing 5-hydroxytryptamine 2A receptors. We labeled psychedelic-responsive mPFC neurons with an excitatory channelrhodopsin to enable their targeted manipulation. We found that reactivation of these cells recapitulated the anxiolytic effects of the psychedelic without driving its hallucinogenic-like effects. These findings reveal essential insight into the cell-type-specific mechanisms underlying psychedelic-induced behavioral states.

Comparison of cell type and disease subset chromatin modifications in SLE

BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease with protean manifestations. There is little understanding of why some organs are specifically impacted in patients and the mechanisms of disease persistence remain unclear. While much work has been done characterizing the DNA methylation status in SLE, there is less information on histone modifications, a more dynamic epigenetic feature. This study identifies two histone marks of activation and the binding of p300 genome-wide in three cell types and three clinical subsets to better understand cell-specific effects and differences across clinical subsets.ResultsWe examined 20 patients with SLE and 8 controls and found that individual chromatin marks varied considerably across T cells, B cells, and monocytes. When pathways were examined, there was far more concordance with conservation of TNF, IL-2/STAT5, and KRAS pathways across multiple cell types and ChIP data sets. Patients with cutaneous lupus and lupus nephritis generally had less dramatically altered chromatin than the general SLE group. Signals also demonstrated significant overlap with GWAS signals in a manner that did not implicate one cell type more than the others.ConclusionsThe pathways identified by altered histone modifications and p300 binding are pathways known to be important from RNA expression studies and recognized pathogenic mechanisms of disease. NFκB and classical inflammatory pathways were strongly associated with increased peak heights across all cell types but were the highest-ranking pathway for all three antibodies in monocytes according to fgsea analysis. IL-6 Jak/STAT3 signaling was the most significant pathway association in T cells marked by H3K27ac change. Therefore, each cell type experiences the disease process distinctly although in all cases there was a strong theme of classical inflammatory pathways. Importantly, this NFκB pathway, so strongly implicated in the patients with generalized SLE, was much less impacted in monocytes when cutaneous lupus was compared to the general SLE cohort and also less impacted in lupus nephritis compared to general SLE. These studies define important cell type differences and emphasize the breadth of the inflammatory effects in SLE.