Endothelial cells adopt a pro-reparative immune responsive signature during cardiac injury.

Modulation of the heart's immune microenvironment is crucial for recovery after ischemic events such as myocardial infarction (MI). Endothelial cells (ECs) can have immune regulatory functions; however, interactions between ECs and the immune environment in the heart after MI remain poorly understood. We identified an EC-specific IFN responsive and immune regulatory gene signature in adult and pediatric heart failure (HF) tissues. Single-cell transcriptomic analysis of murine hearts subjected to MI uncovered an EC population (IFN-ECs) with immunologic gene signatures similar to those in human HF. IFN-ECs were enriched in regenerative-stage mouse hearts and expressed genes encoding immune responsive transcription factors (Irf7, Batf2, and Stat1). Single-cell chromatin accessibility studies revealed an enrichment of these TF motifs at IFN-EC signature genes. Expression of immune regulatory ligand genes by IFN-ECs suggests bidirectional signaling between IFN-ECs and macrophages in regenerative-stage hearts. Our data suggest that ECs may adopt immune regulatory signatures after cardiac injury to accompany the reparative response. The presence of these signatures in human HF and murine MI models suggests a potential role for EC-mediated immune regulation in responding to stress induced by acute injury in MI and chronic adverse remodeling in HF.

SCREENER: Streamlined collaborative learning of NER and RE model for discovering gene-disease relations.

Finding relations between genes and diseases is essential in developing a clinical diagnosis, treatment, and drug design for diseases. One successful approach for mining the literature is the document-based relation extraction method. Despite recent advances in document-level extraction of entity-entity, there remains a difficulty in understanding the relations between distant words in a document. To overcome the above limitations, we propose an AI-based text-mining model that learns the document-level relations between genes and diseases using an attention mechanism. Furthermore, we show that including a direct edge (DE) and indirect edges between genetic targets and diseases when training improves the model's performance. Such relation edges can be visualized as graphs, enhancing the interpretability of the model. For the performance, we achieved an F1-score of 0.875, outperforming state-of-the-art document-level extraction models. In summary, the SCREENER identifies biological connections between target genes and diseases with superior performance by leveraging direct and indirect target-disease relations. Furthermore, we developed a web service platform named SCREENER (Streamlined CollaboRativE lEarning of NEr and Re), which extracts the gene-disease relations from the biomedical literature in real-time. We believe this interactive platform will be useful for users to uncover unknown gene-disease relations in the world of fast-paced literature publications, with sufficient interpretation supported by graph visualizations. The interactive website is available at: https://ican.standigm.com.

Beads- and oil-free single molecule assay with immuno-rolling circle amplification for detection of SARS-CoV-2 from saliva.

Digital enzyme linked immunosorbent assays (ELISA) can be used to detect various antigens such as spike (S) or nucleocapsid (N) proteins of SARS-CoV-2, with much higher sensitivity compared to that achievable using conventional antigen tests. However, the use of microbeads and oil for compartmentalization in these assays limits their user-friendliness and causes loss of assay information due to the loss of beads during the process. To improve the sensitivity of antigen test, here, we developed an oil- and bead-free single molecule counting assay, with rolling circle amplification (RCA) on a substrate. With RCA, the signal is localized at the captured region of an antigen, and the signal from a single antigen molecule can be visualized using the same immune-reaction procedures as in the conventional ELISA. Substrate-based single molecule assay was theoretically evaluated for kd value, and the concentration of capture and detection antibodies. As a feasibility test, biotin-conjugated primer and mouse IgG conjugates were detected even at femto-molar concentrations with this digital immuno-RCA. Using this method, we detected the N protein of SARS-CoV-2 with a limit of detection less than 1 pg/mL more than 100-fold improvement compared to the detection using conventional ELISA. Furthermore, testing of saliva samples from COVID-19 patients and healthy controls (n = 50) indicated the applicability of the proposed method for detection of SARS-CoV-2 with 99.5% specificity and 90.9% sensitivity.

Emotional discourse analysis of COVID-19 patients and their mental health: A text mining study.

COVID-19 has caused negative emotional responses in patients, with significant mental health consequences for the infected population. The need for an in-depth analysis of the emotional state of COVID-19 patients is imperative. This study employed semi-structured interviews and the text mining method to investigate features in lived experience narratives of COVID-19 patients and healthy controls with respect to five basic emotions. The aim was to identify differences in emotional status between the two matched groups of participants. The results indicate generally higher complexity and more expressive emotional language in healthy controls than in COVID-19 patients. Specifically, narratives of fear, happiness, and sadness by COVID-19 patients were significantly shorter as compared to healthy controls. Regarding lexical features, COVID-19 patients used more emotional words, in particular words of fear, disgust, and happiness, as opposed to those used by healthy controls. Emotional disorder symptoms of COVID-19 patients at the lexical level tended to focus on the emotions of fear and disgust. They narrated more in relation to self or family while healthy controls mainly talked about others. Our automatic emotional discourse analysis potentially distinguishes clinical status of COVID-19 patients versus healthy controls, and can thus be used to predict mental health disorder symptoms in COVID-19 patients.

Multinomial Convolutions for Joint Modeling of Regulatory Motifs and Sequence Activity Readouts.

A common goal in the convolutional neural network (CNN) modeling of genomic data is to discover specific sequence motifs. Post hoc analysis methods aid in this task but are dependent on parameters whose optimal values are unclear and applying the discovered motifs to new genomic data is not straightforward. As an alternative, we propose to learn convolutions as multinomial distributions, thus streamlining interpretable motif discovery with CNN model fitting. We developed MuSeAM (Multinomial CNNs for Sequence Activity Modeling) by implementing multinomial convolutions in a CNN model. Through benchmarking, we demonstrate the efficacy of MuSeAM in accurately modeling genomic data while fitting multinomial convolutions that recapitulate known transcription factor motifs.

Emotional Experiences of COVID-19 Patients in China: A Qualitative Study.

This study explored the emotional experiences of COVID-19 patients in China. Thirty-four patients diagnosed with COVID-19 participated in semi-structured telephone interviews. We used qualitative methods to investigate the distribution patterns and characteristics of patients' emotional experiences. The results indicated that emotional experiences showed different characteristics at different stages during isolation and treatment. COVID-19 patients' emotional discourse encompassed eight main themes, namely, feelings of shock at the diagnosis, yearning for future life, attachment to one's family, depression during the treatment, self-restriction due to probable contagiousness, powerlessness about the disease, open-mindedness about death, and faith in the joint efforts to fight COVID-19. These themes related to experiences concerning infection, isolation, outlook on life and death, stigma, and macro-identity. The findings suggest that the unexpected experience of COVID-19 infection exacerbated patients' negative emotions. COVID-19 patients' emotional stress stemmed from isolated environments, physiological effects of the disease, panic about the unknown, and realistic economic pressure. The government, medical staff, family members of patients, and the media should therefore work together to ensure proper emotional care for COVID-19 patients.

Decoding the PITX2-controlled genetic network in atrial fibrillation.

Atrial fibrillation (AF), the most common sustained cardiac arrhythmia and a major risk factor for stroke, often arises through ectopic electrical impulses derived from the pulmonary veins (PVs). Sequence variants in enhancers controlling expression of the transcription factor PITX2, which is expressed in the cardiomyocytes (CMs) of the PV and left atrium (LA), have been implicated in AF predisposition. Single nuclei multiomic profiling of RNA and analysis of chromatin accessibility combined with spectral clustering uncovered distinct PV- and LA-enriched CM cell states. Pitx2-mutant PV and LA CMs exhibited gene expression changes consistent with cardiac dysfunction through cell type-distinct, PITX2-directed, cis-regulatory grammars controlling target gene expression. The perturbed network targets in each CM were enriched in distinct human AF predisposition genes, suggesting combinatorial risk for AF genesis. Our data further reveal that PV and LA Pitx2-mutant CMs signal to endothelial and endocardial cells through BMP10 signaling with pathogenic potential. This work provides a multiomic framework for interrogating the basis of AF predisposition in the PVs of humans.

CuCrO2 Nanoparticles Incorporated into PTAA as a Hole Transport Layer for 85 °C and Light Stabilities in Perovskite Solar Cells.

High-mobility inorganic CuCrO2 nanoparticles are co-utilized with conventional poly(bis(4-phenyl)(2,5,6-trimethylphenyl)amine) (PTAA) as a hole transport layer (HTL) for perovskite solar cells to improve device performance and long-term stability. Even though CuCrO2 nanoparticles can be readily synthesized by hydrothermal reaction, it is difficult to form a uniform HTL with CuCrO2 alone due to the severe agglomeration of nanoparticles. Herein, both CuCrO2 nanoparticles and PTAA are sequentially deposited on perovskite by a simple spin-coating process, forming uniform HTL with excellent coverage. Due to the presence of high-mobility CuCrO2 nanoparticles, CuCrO2/PTAA HTL demonstrates better carrier extraction and transport. A reduction in trap density is also observed by trap-filled limited voltages and capacitance analyses. Incorporation of stable CuCrO2 also contributes to the improved device stability under heat and light. Encapsulated perovskite solar cells with CuCrO2/PTAA HTL retain their efficiency over 90% after ~900-h storage in 85 °C/85% relative humidity and under continuous 1-sun illumination at maximum-power point.

Anti-Adipogenic Effects of Ethanol Extracts Prepared from Selected Medicinal Herbs in 3T3-L1 Cells.

Obesity is a major risk factor for various metabolic diseases such as cardiovascular disease, hypertension, and type 2 diabetes mellitus. In this study, we prepared ethanol extracts from Agastache rugosa (ARE), Chrysanthemum zawadskii (CZE), Mentha arvensis (MAE), Perilla frutescens (PFE), Leonurus sibiricus (LSE), Gardenia jasminoides (GJE), and Lycopus coreanus (LCE). The anti-oxidant and anti-adipogenic effects were evaluated. The IC50 values for ascorbic acid and LCE against 2,2-diphenyl-1-picrylhydrazyl radicals were 246.2 µg/mL and 166.2 µg/mL, respectively, followed by ARE (186.6 µg/mL), CZE (198.6 µg/mL), MAE (337.1 µg/mL), PFE (415.3 µg/mL), LSE (548.2 µg/mL), and GJE (626.3 µg/mL). In non-toxic concentration ranges, CZE had a strong inhibitory effect against 3T3-L1 adipogenes (84.5%) than those of the other extracts. Furthermore, the anti-adipogenic effect of CZE is largely limited in the early stage of adipogenesis, and we revealed that the inhibitory role of CZE in adipogenesis is required for the activation of Wnt signaling. Our results provide scientific evidence that the anti-adipogenic effect of CZE can be applied as an ingredient for the development of functional foods and nutri-cosmetics for obesity prevention.

Real-time detection of chlorine gas using Ni/Si shell/core nanowires.

We demonstrate the selective adsorption of Ni/Si shell/core nanowires (Ni-Si NWs) with a Ni outer shell and a Si inner core on molecularly patterned substrates and their application to sensors for the detection of chlorine gas, a toxic halogen gas. The molecularly patterned substrates consisted of polar SiO2 regions and nonpolar regions of self-assembled monolayers of octadecyltrichlorosilane (OTS). The NWs showed selective adsorption on the polar SiO2 regions, avoiding assembly on the nonpolar OTS regions. Utilizing these assembled Ni-Si NWs, we demonstrate a sensor for the detection of chlorine gas. The utilization of Ni-Si NWs resulted in a much larger sensor response of approximately 23% to 5 ppm of chlorine gas compared to bare Ni NWs, due to the increased surface-to-volume ratio of the Ni-Si shell/core structure. We expect that our sensor will be utilized in the future for the real-time detection of halogen gases including chlorine with high sensitivity and fast response.