scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding.

Dynamic compartmentalization of eukaryotic DNA into active and repressed states enables diverse transcriptional programs to arise from a single genetic blueprint, whereas its dysregulation can be strongly linked to a broad spectrum of diseases. While single-cell Hi-C experiments allow for chromosome conformation profiling across many cells, they are still expensive and not widely available for most labs. Here, we propose an alternate approach, scENCORE, to computationally reconstruct chromatin compartments from the more affordable and widely accessible single-cell epigenetic data. First, scENCORE constructs a long-range epigenetic correlation graph to mimic chromatin interaction frequencies, where nodes and edges represent genome bins and their correlations. Then, it learns the node embeddings to cluster genome regions into A/B compartments and aligns different graphs to quantify chromatin conformation changes across conditions. Benchmarking using cell-type-matched Hi-C experiments demonstrates that scENCORE can robustly reconstruct A/B compartments in a cell-type-specific manner. Furthermore, our chromatin confirmation switching studies highlight substantial compartment-switching events that may introduce substantial regulatory and transcriptional changes in psychiatric disease. In summary, scENCORE allows accurate and cost-effective A/B compartment reconstruction to delineate higher-order chromatin structure heterogeneity in complex tissues.

The single-cell opioid responses in the context of HIV (SCORCH) consortium.

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

The Effect of Age on the Regenerative Potential of Adipose Stem-cell-derived Apoptotic Extracellular Vesicles in Rat Skin Wound Healing.

Introduction: Skin, being the body's largest organ, is susceptible to injuries. Despite the adoption of common treatments such as debridement, wound dressing, and infection control measures for skin injuries, the outcomes remain unsatisfactory, especially in diabetic patients or elderly patients. The use of adipose stem cell-derived apoptotic extracellular vesicles (apoEVs-ASCs) has been shown great therapeutic potential in wound repair. The effect of the donor age on the biological properties and functions of apoEVs-ASCs has not been reported. Methods: In this study, we isolated apoEVs-ASCs from young and aged rats. Transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA) were applied for the characteristics of apoEVs-ASCs. For aged and young apoEVs-ASCs groups, the proliferative and migration abilities in vitro, and wound healing function in vivo were contrastively evaluated and quantified for statistical analysis. Results: Our results showed that both young and aged apoEVs-ASCs induced skin healing and reduced scar formation. In addition, young apoEVs-ASCs had significantly higher proliferation, migration of fibroblasts and endothelial cells, and increased neo-angiogenesis ability, when compared with that of aged apoEVs-ASCs. Conclusion: Young apoEVs-ASCs should be employed for wound repair, which is associated with its superior promoting effect on wound healing.

Mitigating Effect of Matricin Against Benzo(a)pyrene-induced Lung Carcinogenesis in Experimental Mice Model.

BACKGROUND: Lung cancer is a life-threatening disease that is still prevalent worldwide. This study aims to evaluate the effects of matricin, a sesquiterpene, on the carcinogenic agent benzo(a)pyrene [B(a)P]-induced lung cancer in Swiss albino mice. METHODS: Lung cancer was induced by oral administration of B(a)P at 50 mg/kg b. wt. in model Swiss-albino mice (group II) as well in experimental group III, and treated with matricin (100 mg/kg b. wt.) in group III. Upon completion of treatment for 18 weeks, the changes in body weight, tumor formation, enzymatic and non-enzymatic antioxidant levels (GSH, SOD, GPx, GR, QR, CAT), lipid peroxidation (LPO) level, pro-inflammatory cytokines (TNF-α, IL-6, IL-1ß), immunoglobulin levels (IgG, IgM), apoptosis markers (Bax, Bcl-xL), tumor markers (carcinoembryogenic antigen (CEA), neuron-specific enolase (NSE)), and histopathological (H&E) alterations were determined. RESULTS: The results indicate that B(a)P caused a significant increase of tumor formation in the lungs, increased tumor markers and inflammatory cytokines in serum, and depletion of enzymatic/ non-enzymatic antioxidants and immunoglobulins, compared to the untreated control group. Matricin treatment significantly reversed the changes caused by B(a)P as evidenced by the biochemical and histopathological assays. CONCLUSION: The changes caused by matricin clearly indicate the cancer-preventive effects of matricin against B(a)P-induced lung cancer in animal models, which can be attributed to the antioxidant activity, immunomodulation, and mitigation of the NF-kß pathway.

Prognostic role of CRABP2 in lung cancer: a meta-analysis.

BACKGROUND: The prognostic value of cellular retinoic acid-binding protein 2 (CRABP2), in lung cancer patients remains to be uncertained. Therefore, our research attempted to assess the relationship between CRABP2 and survival analysis in lung cancer patients through meta-analysis. METHOD: Related literature retrieved from Cochrane Library, Ovid, Embase, PubMed, the CNKI, and the Web of Science. The latest update of the search was May 1, 2023. The outcome indicators included as effective measures in the study were hazard ratio (HR), and 95% confidence interval (CI). The Stata 12.0 software was used to analyze the data. RESULTS: A total of4 studies were finally enrolled in our meta-analysis. The increased plasma level of CRABP2 predicted poor OS in lung cancer patient with a combined HR of 1.14 (95% CI: 1.00-1.30), and were not associated with poor PFS with combined HR: 1.15% CI: 0.63-2.09) in lung cancer patients. CONCLUSIONS: Our meta-analysis found the increased plasma level of CRABP2 was associated with poor OS independently in NSCLC patients. The plasma CRABP2 level may be an indicator of biological aggressiveness of the tumor. Our research was promising regarding the feasibility and utility of plasma CRABP2 as a novel prognostic biomarker in NSCLC, and the findings warrant further investigation.

KLRB1 expression is associated with lung adenocarcinoma prognosis and immune infiltration and regulates lung adenocarcinoma cell proliferation and metastasis through the MAPK/ERK pathway.

Background: Lung cancer is the most common primary malignant tumor of the lung, and as one of the malignant tumors that pose the greatest threat to the health of the population, the incidence rate has remained high in recent years. Previous studies have shown that KLRB1 is transcriptionally repressed in lung adenocarcinoma and correlates with lung adenocarcinoma prognosis. The objective of this study is to investigate the intrinsic mechanisms by which KLRB1 affects the malignant phenotypes of lung adenocarcinoma such as immune infiltration, proliferation, growth and metastasis. Methods: We assessed the expression levels of KLRB1 in publicly available databases and investigated its associations with clinical and pathological variables. Enrichment analysis was subsequently conducted to investigate possible signaling pathways and their associated biological functions. Statistical analysis, including Spearman correlation and the application of multigene prediction models, was utilized to assess the relationship between the expression of KLRB1 and the infiltration of immune cells. The diagnostic and prognostic value of KLRB1 was evaluated using Kaplan-Meier survival curves, diagnostic receptor operating characteristic (ROC) curves, histogram models, and Cox regression analysis. Specimens from lung adenocarcinoma (LUAD) patients were collected, the expression level of KLRB1 was detected by protein blotting analysis, and the expression level of KLRB1 was detected at the mRNA level by real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR). Small interfering RNA (siRNA) was used to silence gene expression, and Transwell, Cell Counting Kit-8 (CCK-8) and colony formation assays were subsequently performed to analyze the effects of KLRB1 on LUAD cell migration, invasion and proliferation. Results: KLRB1 expression was lower in lung cancer tissue than in surrounding healthy tissue. Genes differentially expressed in the low and high KLRB1 expression groups were found to be significantly enriched in pathways related to immunity. KLRB1 exerted an impact on the MAPK/ERK signaling pathway, thereby modulating the growth and proliferation of LUAD cells. KLRB1 expression is linked to prognosis, immune infiltration, and cell migration and proliferation in LUAD. Conclusions: The evidence revealed a correlation between KLRB1 and both prognosis and immune infiltration in LUAD patients.

ScISOr-ATAC reveals convergent and divergent splicing and chromatin specificities between matched cell types across cortical regions, evolution, and in Alzheimer's Disease.

Multimodal measurements have become widespread in genomics, however measuring open chromatin accessibility and splicing simultaneously in frozen brain tissues remains unconquered. Hence, we devised Single-Cell-ISOform-RNA sequencing coupled with the Assay-for-Transposase-Accessible-Chromatin (ScISOr-ATAC). We utilized ScISOr-ATAC to assess whether chromatin and splicing alterations in the brain convergently affect the same cell types or divergently different ones. We applied ScISOr-ATAC to three major conditions: comparing (i) the Rhesus macaque (Macaca mulatta) prefrontal cortex (PFC) and visual cortex (VIS), (ii) cross species divergence of Rhesus macaque versus human PFC, as well as (iii) dysregulation in Alzheimer's disease in human PFC. We found that among cortical-layer biased excitatory neuron subtypes, splicing is highly brain-region specific for L3-5/L6 IT_RORB neurons, moderately specific in L2-3 IT_CUX2.RORB neurons and unspecific in L2-3 IT_CUX2 neurons. In contrast, at the chromatin level, L2-3 IT_CUX2.RORB neurons show the highest brain-region specificity compared to other subtypes. Likewise, when comparing human and macaque PFC, strong evolutionary divergence on one molecular modality does not necessarily imply strong such divergence on another molecular level in the same cell type. Finally, in Alzheimer's disease, oligodendrocytes show convergently high dysregulation in both chromatin and splicing. However, chromatin and splicing dysregulation most strongly affect distinct oligodendrocyte subtypes. Overall, these results indicate that chromatin and splicing can show convergent or divergent results depending on the performed comparison, justifying the need for their concurrent measurement to investigate complex systems. Taken together, ScISOr-ATAC allows for the characterization of single-cell splicing and chromatin patterns and the comparison of sample groups in frozen brain samples.

Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

The emotion prediction of college students with attention LSTM during the COVID19 epidemic.

During the COVID19 pandemic, there is a pronounced collective mental health issue among college students. Forecasting the trend of emotional changes in on-campus students is crucial to effectively address this issue. This study proposes an Attention-LSTM neural network model that performs deep learning on key input sequence information, so as to predict the distribution of emotional states in college students. By testing 60 consecutive days of emotional data, the model successfully predicts students' emotional distribution, triggers and resolution strategies, with an accuracy rate of no less than 99%. Compared with models such as ARIMA, SARIMA and VAR, this model shows significant advantages in accuracy, operational efficiency, and data collection requirements. The integration of deep learning technology with student management in this study offers a novel approach to address emotional issues among students under exceptional circumstances.