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Quantifying RNAs in their spatial context is crucial to understanding gene expression and regulation in complex tissues. In situ transcriptomic methods generate spatially resolved RNA profiles in intact tissues. However, there is a lack of a unified computational framework for integrative analysis of in situ transcriptomic data. Here, we introduce an unsupervised and annotation-free framework, termed ClusterMap, which incorporates the physical location and gene identity of RNAs, formulates the task as a point pattern analysis problem, and identifies biologically meaningful structures by density peak clustering (DPC). Specifically, ClusterMap precisely clusters RNAs into subcellular structures, cell bodies, and tissue regions in both two- and three-dimensional space, and performs consistently on diverse tissue types, including mouse brain, placenta, gut, and human cardiac organoids. We demonstrate ClusterMap to be broadly applicable to various in situ transcriptomic measurements to uncover gene expression patterns, cell niche, and tissue organization principles from images with high-dimensional transcriptomic profiles. In situ transcriptomics maps RNA expression patterns across intact tissues taking our understanding of gene expression to a new level. Here, the authors present a computational method that uncovers gene expression, cell niche, and tissue region patterns from 2D and 3D spatial transcriptomics.

Complex diseases are characterized by spatiotemporal cellular and molecular changes that may be difficult to comprehensively capture. However, understanding the spatiotemporal dynamics underlying pathology can shed light on disease mechanisms and progression. Here we introduce STARmap PLUS, a method that combines high-resolution spatial transcriptomics with protein detection in the same tissue section. As proof of principle, we analyze brain tissues of a mouse model of Alzheimer’s disease at 8 and 13 months of age. Our approach provides a comprehensive cellular map of disease progression. It reveals a core–shell structure where disease-associated microglia (DAM) closely contact amyloid-β plaques, whereas disease-associated astrocyte-like (DAA-like) cells and oligodendrocyte precursor cells (OPCs) are enriched in the outer shells surrounding the plaque-DAM complex. Hyperphosphorylated tau emerges mainly in excitatory neurons in the CA1 region and correlates with the local enrichment of oligodendrocyte subtypes. The STARmap PLUS method bridges single-cell gene expression profiles with tissue histopathology at subcellular resolution, providing a tool to pinpoint the molecular and cellular changes underlying pathology. Understanding the spatiotemporal dynamics underlying pathology can shed light on its mechanisms. Here the authors introduce STARmap PLUS, a method that combines high-resolution spatial transcriptomics with protein detection.

Background A possible relationship between periodontitis and Alzheimer’s disease (AD) has been reported. However, there is limited information on the association between the Porphyromonas gingivalis ( P. gingivalis ) periodontal infection and the pathological features of AD. The hypothesis that P. gingivalis periodontal infection may cause cognitive impairment via age-dependent neuroinflammation was tested. Results Thirty 4-week-old (young) female C57BL/6 J mice were randomly divided into two groups, the control group and the experimental group. Thirty 12-month-old (middle-aged) were grouped as above. The mouth of the mice in the experimental group was infected with P. gingivalis . Morris water maze(MWM) was performed to assess the learning and memory ability of mice after 6 weeks. Moreover, the expression levels of the pro-inflammatory cytokines TNF-α, IL-6, and IL-1β in the mice brain tissues were determined by Quantitative real-time polymerase chain reaction (qRT-PCR), Enzyme Linked Immunosorbent Assay(ELISA) and immunohistochemistry. Our results showed that the learning and memory abilities of the middle-aged P. gingivalis infected mice were impaired. Moreover, the expression levels of the pro-inflammatory cytokines TNF-α, IL-6, and IL-1β in the brain tissues of the middle-aged P. gingivalis infected mice were increased. Conclusions These results suggest that P. gingivalis periodontal infection may cause cognitive impairment via the release of the pro-inflammatory cytokines TNF-α, IL-6, and IL-1β in the brain tissues of middle-aged mice.

Streptococcus oralis , belonging to the viridans group streptococci (VGS), has been considered a member of normal flora mainly inhabiting the oral cavity. However, more recently, there has been growing recognition of its role as a causative agent in various life-threatening infectious diseases such as infective endocarditis (IE) and meningitis. Additionally, the differences in the prevalence, clinical features, and prognosis of opportunistic infections between S. oralis and other VGS species have been addressed. Particularly the predominance of S. oralis in IE has drawn critical attention. In potentially fatal infections, clinical neglect of S. oralis as an instigating agent might significantly impede early diagnosis and treatment. Nevertheless, to date, the infectious diseases associated with S. oralis have not yet been comprehensively described. Therefore, this review will give an overview of infectious diseases caused by S. oralis to uncover its hidden role as an opportunistic pathogen.

MicroRNAs (miRNAs) play important roles in the pathogenesis of cardiovascular diseases. Circulating miRNAs were recently identified as biomarkers for various physiological and pathological conditions. In this study, we aimed to identify the circulating miRNA fingerprint of vulnerable coronary artery disease (CAD) and explore its potential as a novel biomarker for this disease. The Taqman low-density miRNA array and coexpression network analyses were used to identify distinct miRNA expression profiles in the plasma of patients with typical unstable angina (UA) and angiographically documented CAD (UA group, n = 13) compared to individuals with non-cardiac chest pain (control group, n = 13). Significantly elevated expression levels of miR-106b/25 cluster, miR-17/92a cluster, miR-21/590-5p family, miR-126*, and miR-451 were observed in UA patients compared to controls. These findings were validated by real-time PCR in another 45 UA patients, 31 stable angina patients, and 37 controls. In addition, miR-106b, miR-25, miR-92a, miR-21, miR-590-5p, miR-126* and miR-451 were upregulated in microparticles (MPs) isolated from the plasma of UA patients (n = 5) compared to controls (n = 5). Using flow cytometry and immunolabeling, we further found that Annexin V(+) MPs were increased in the plasma samples of UA patients compared to controls, and the majority of the increased MPs in plasma were shown to be Annexin V(+) CD31(+) MPs. The findings suggest that Annexin V(+) CD31(+) MPs may contribute to the elevated expression of the selected miRNAs in the circulation of patients with vulnerable CAD. The circulating miRNA signature, consisting of the miR-106b/25 cluster, miR-17/92a cluster, miR-21/590-5p family, miR-126* and miR-451, may be used as a novel biomarker for vulnerable CAD. Chinese Clinical Trial Register, ChiCTR-OCH-12002349.

Objective Chronic kidney disease (CKD) patients with coronary artery disease (CAD) in the intensive care unit (ICU) have higher in-hospital mortality and poorer prognosis than patients with either single condition. The objective of this study is to develop a novel model that can predict the in-hospital mortality of that kind of patient in the ICU using machine learning methods. Methods Data of CKD patients with CAD were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Boruta algorithm was conducted for the feature selection process. Eight machine learning algorithms, such as logistic regression (LR), random forest (RF), Decision Tree, K-nearest neighbors (KNN), Gradient Boosting Decision Tree Machine (GBDT), Support Vector Machine (SVM), Neural Network (NN), and Extreme Gradient Boosting (XGBoost), were conducted to construct the predictive model for in-hospital mortality and performance was evaluated by average precision (AP) and area under the receiver operating characteristic curve (AUC). Shapley Additive Explanations (SHAP) algorithm was applied to explain the model visually. Moreover, data from the Telehealth Intensive Care Unit Collaborative Research Database (eICU-CRD) were acquired as an external validation set. Results 3590 and 1657 CKD patients with CAD were acquired from MIMIC-IV and eICU-CRD databases, respectively. A total of 78 variables were selected for the machine learning model development process. Comparatively, GBDT had the highest predictive performance according to the results of AUC (0.946) and AP (0.778). The SHAP method reveals the top 20 factors based on the importance ranking. In addition, GBDT had good predictive value and a certain degree of clinical value in the external validation according to the AUC (0.865), AP (0.672), decision curve analysis, and calibration curve. Conclusion Machine learning algorithms, especially GBDT, can be reliable tools for accurately predicting the in-hospital mortality risk for CKD patients with CAD in the ICU. This contributed to providing optimal resource allocation and reducing in-hospital mortality by tailoring precise management and implementation of early interventions.

Histone acetylation, balanced by histone acetyltransferase (HAT) and histone deacetylase (HDAC) complexes, affects dynamic transitions of chromatin structure to regulate transcriptional accessibility. However, little is known about the interplay between HAT and HDAC complexes in Fusarium graminearum , a causal agent of Fusarium Head Blight (FHB) that uniquely contains chromosomal regions enriched for house-keeping or infection-related genes. In this study, we identified the ortholog of the human inhibitor of growth (ING1) gene in F . graminearum ( FNG1 ) and found that it specifically interacts with the FgEsa1 HAT of the NuA4 complex. Deletion of FNG1 led to severe growth defects and blocked conidiation, sexual reproduction, DON production, and plant infection. The fng1 mutant was normal in H3 acetylation but significantly reduced in H4 acetylation. A total of 34 spontaneous suppressors of fng1 with faster growth rate were isolated. Most of them were still defective in sexual reproduction and plant infection. Thirty two of them had mutations in orthologs of yeast RPD3 , SIN3 , and SDS3 , three key components of the yeast Rpd3L HDAC complex. Four mutations in these three genes were verified to suppress the defects of fng1 mutant in growth and H4 acetylation. The rest two suppressor strains had a frameshift or nonsense mutation in a glutamine-rich hypothetical protein that may be a novel component of the FgRpd3 HDAC complex in filamentous fungi. FgRpd3, like Fng1, localized in euchromatin. Deletion of FgRPD3 resulted in severe growth defects and elevated H4 acetylation. In contract, the Fgsds3 deletion mutant had only a minor reduction in growth rate but FgSIN3 appeared to be an essential gene. RNA-seq analysis revealed that 48.1% and 54.2% of the genes with altered expression levels in the fng1 mutant were recovered to normal expression levels in two suppressor strains with mutations in FgRPD3 and FgSDS3 , respectively. Taken together, our data showed that Fng1 is important for H4 acetylation as a component of the NuA4 complex and functionally related to the FgRpd3 HDAC complex for transcriptional regulation of genes important for growth, conidiation, sexual reproduction, and plant infection in F . graminearum .

IntroductionExposure to fine particulate matter (PM2.5) is known to be associated with cardiovascular diseases. Sesamin (Ses) is a natural phenolic compound found in sesame seeds and sesame oil. Ferroptosis is a novel mode of cell death characterised by iron-dependent lipid peroxidation. This study aims to explore whether PM2.5 can induce ferroptosis in H9C2 cells and to investigate the precise protective mechanism of Ses.MethodsBased on transcriptomic data, PM2.5 may induce ferroptosis in cardiomyocytes. The ferroptosis inducer erastin and ferroptosis inhibitor ferrostatin-1 (Fer-1) were used to illustrate the mechanisms involved in PM2.5-induced H9C2 cell injury. Using network pharmacology, the pharmacological mechanism and potential therapy targets of Ses were explored for the treatment of PM2.5-induced cardiomyocyte injury. H9C2 cells were cultured and pretreated with Fer-1 or different concentrations of Ses, and then cardiomyocyte injury model was established using erastin or PM2.5. Indicators of oxidative responses, including total superoxide dismutase, reduced glutathione, glutathione peroxidase and malondialdehyde, were measured. The expression levels of ferroptosis-related proteins were determined through Western blot analysis.ResultsResults demonstrate that PM2.5 induces ferroptosis in H9C2 cells and Ses exerts a protective effect by suppressing ACSL4-mediated ferroptosis.DiscussionOverall, these findings elucidate a novel mechanism by which Ses ameliorates the detrimental effects of PM2.5 on cardiomyocytes.

Three-dimensional (3D) printing dental applications are broadly applied in multiple specialties of dentistry facilitating diagnosis and treatment greatly. However, the current photopolymer materials for 3D printing dental applications often fail to yield the required quality due to their inferior mechanical properties. Thus, this study aims to explore the effects of silanized nano-Al2O3 fillers on the mechanical properties and printing accuracy of one of the most commonly used photopolymer resins, polyurethane acrylate (PUA). The modification of nano-Al2O3 particles by the silane coupling agent was characterized by Fourier-transform infrared spectroscopy (FTIR) and thermogravimetric (TGA) analysis. Then, specimens were fabricated using PUA resins with 0 wt% (control), 2 wt%, 4 wt%, and 6 wt% silanized nano-Al2O3 fillers. The effects of silanized nano-Al2O3 fillers on the mechanical properties of the photopolymer resins were evaluated by Shore D hardness, tensile strength, and flexural strength tests. Moreover, the printing accuracy was assessed by the root-mean-square error (RMS) analysis. The results showed that the mechanical properties of the photopolymer resins were significantly improved when loaded with silanized nano-Al2O3 fillers. The highest values were observed in the resin with 4 wt% filler content, improving hardness, tensile strength, and flexural strength by 11.7%, 31.1%, and 39.9%, respectively. For printing accuracy, loading 2 wt% and 4 wt% fillers did not influence the printing accuracy significantly. However, the incorporation of 6 wt% fillers compromised the printing accuracy. Within the limits, this study has demonstrated that the incorporation of silanized nano-Al2O3 fillers can enhance the mechanical performance of photopolymer resins, indicating the potential of this material for improved quality of 3D printing dental applications.

Background Long-term exposure of humans to air pollution is associated with an increasing risk of cardiovascular diseases (CVDs). Astaxanthin (AST), a naturally occurring red carotenoid pigment, was proved to have multiple health benefits. However, whether or not AST also exerts a protective effect on fine particulate matter (PM 2.5 )-induced cardiomyocyte damage and its underlying mechanisms remain unclear. Methods In vitro experiments, the H9C2 cells were subjected to pretreatment with varying concentrations of AST, and then cardiomyocyte injury model induced by PM 2.5 was established. The cell viability and the ferroptosis-related proteins expression were measured in different groups. In vivo experiments, the rats were pretreated with different concentrations of AST for 21 days. Subsequently, a rat model of myocardial PM 2.5 injury was established by intratracheal instillation every other day for 1 week. The effects of AST on myocardial tissue injury caused by PM 2.5 indicating by histological, serum, and protein analyses were examined. Results AST significantly ameliorated PM 2.5 -induced myocardial tissue injury, inflammatory cell infiltration, the release of inflammatory factors, and cardiomyocyte H9C2 cell damage. Mechanistically, AST pretreatment increased the expression of SLC7A11, GPX4 and down-regulated the expression of TfR1, FTL and FTH1 in vitro and in vivo. Conclusions Our study suggest that ferroptosis plays a significant role in the pathogenesis of cardiomyocyte injury induced by PM 2.5 . AST may serve as a potential therapeutic agent for mitigating cardiomyocyte injury caused by PM 2.5 through the inhibition of ferroptosis.