Cystatin C is a predictor for long-term All-Cause and Cardiovascular Mortality in US Adults with Metabolic Syndrome.

OBJECTIVE: This study examined the relationship between Cystatin C (CysC) levels and all-cause, CVD, and cancer mortality in US metabolic syndrome (MetS) patients. METHODS: The 1999-2002 National Health and Nutrition Examination Survey (NHANES) prospective cohort research included 1,980 MetS participants. To assess CysC levels and all-cause, CVD, and cancer mortality, fitted curves, Kaplan-Meier survival curves, cox regression analysis, and ROC curves were performed. RESULTS: During a mean follow-up of 15.3 ± 5.4 years, a total of 819 deaths occurred. The fitted and Kaplan-Meier survival curves revealed that greater CysC levels were linked to higher all-cause, CVD, and cancer mortality rates (P<0.05). After adjusting for variables, CysC level was associated with all-cause, CVD, and cancer mortality at 1.63 (1.42-1.88), 1.53 (1.19-1.95), and 1.53 (1∼2.32), respectively (P<0.05). Later tertile models showed consistent results. High CysC tertile participants showed higher risk of all-cause mortality (HR 1.87; 1.43-2.45), CVD mortality (HR 1.97, 1.15∼3.38), and cancer mortality (HR 1.72, 1.01∼2.91) compared to those in the lowest tertile (P<0.05). Subgroup studies by sex and other characteristics confirmed the findings. CysC demonstrated the higher predictive efficacy across mortality outcomes, followed by eGFR, outperforming Urea nitrogen, Creatinine, Uric acid, and CRP. CysC alone exhibited substantial predictive value for all-cause (AUC 0.773; P<0.05) and CVD mortality (AUC 0.726; P<0.05). Combining CysC with age enhanced the predictive value for all-cause mortality to 0.861 and CVD mortality to 0.771 (P<0.05). CONCLUSION: MetS patients with elevated CysC levels have a higher risk of all-cause, CVD, and cancer death. CysC may predict MetS all-cause and CVD mortality.

Dendrobine regulates STAT3 to attenuate mitochondrial dysfunction and senescence in vascular endothelial cells triggered by oxidized low-density lipoprotein.

Our previous studies have highlighted the potential therapeutic efficacy of dendrobine, an alkaloid, in atherosclerosis (AS), nevertheless, the underlying mechanism remains unclear. This study employs a combination of network pharmacology and in vitro experiments to explore the regulatory pathways involved. Through network pharmacology, the biological function for intersection targets between dendrobine and AS were identified. Molecular docking was conducted to investigate the interaction between the dominant target and dendrobine. Human umbilical vein endothelial cells (HUVECs) were treated with oxidized low-density lipoprotein (ox-LDL) to mimic AS, and the effects of dendrobine on cell viability, lipid deposition, mitochondrial function, and cellular senescence were evaluated. Subsequently, cells were treated with the mitophagy inhibitor Mdivi-1 and the STAT3 agonist colivelin to assess the role of mitophagy and STAT3 signaling in dendrobine regulation. Intersection targets were associated with biological processes, including reactive oxygen species production. Dendrobine attenuated the effects of ox-LDL treatment on HUVECs, mitigating changes in cell activity, lipid deposition, mitochondrial function, and cellular senescence. Both Mdivi-1 and colivelin treatments resulted in decreased cell viability and increased cellular senescence, with colivelin suppressing mitophagy. Cotreatment with Mdivi-1 and colivelin further aggravated cellular senescence and inhibited FoxO signaling. Together, this study indicated that dendrobine regulated the STAT3/FoxO signaling pathway, alleviating mitochondrial dysfunction and cellular senescence. This study contributes valuable insights to the potential clinical application of dendrobine.

Coptisine prevents angiotensin II­induced endothelial cell injury and senescence via the lncRNA SNHG12/miR­603/NAMPT pathway.

Atherosclerosis (AS) is a major health problem and targeting the associated molecular pathways is critical for developing therapies. The present study investigated the effect of coptisine on human umbilical vein endothelial cells (HUVECs) in response to angiotensin II (Ang II) induction by focusing on cellular senescence, apoptosis and inflammation. HUVECs were treated with different Ang II concentrations and long non-coding RNA small nucleolar RNA host gene 12 (SNHG12), microRNA (miRNA/miR)-603 and nicotinamide phosphoribosyltransferase (NAMPT) expressions were assessed. Cell viability, nicotinamide adenine dinucleotide (NAD+) levels, senescence, apoptosis and inflammation were assessed. The interactions among SNHG12, miR-603 and NAMPT were investigated using dual-luciferase reporter gene assays and RNA pull-down experiments. Coptisine treatment increased SNHG12 expression and attenuated Ang II-induced adverse effects in HUVECs. SNHG12 silencing abrogated coptisine's protective effects, indicating that SNHG12 is a key mediator. SNHG12 targets miR-603, which then directly targets NAMPT, an age-related gene involved in NAD(+) regulation. Coptisine modulated the SNHG12/miR-603/NAMPT pathway and miR-603 inhibition enhanced the protective effects of coptisine. NAMPT overexpression reversed the negative effects of miR-603 and enhanced the protective effect of the miR-603 inhibitor. Finally, the protective mechanism of coptisine is linked to the regulation of NAD(+), sirtuin 3 (SIRT3) and p53. Coptisine treatment counteracted the AngII-induced increase in SIRT3 and p53 protein levels, whereas the miR-603 inhibitor potentiated the effect of coptisine. SNHG12 knockdown partially abolished these effects, which were reversed by NAMPT overexpression. In conclusion, the present study revealed a novel protective mechanism involving the SNHG12/miR-603/NAMPT pathway in HUVECs exposed to Ang II, highlighting the potential therapeutic application of coptisine in treating atherosclerosis. These results suggested that coptisine exerts its protective effects by modulating the SNHG12/miR-603/NAMPT axis, which ultimately affects the regulation of NAD(+), SIRT3 and p53. Future studies should explore the potential of the SNHG12/miR-603/NAMPT pathway as a target for developing novel AS therapies.

Fabrication of resveratrol-loaded soy protein isolate-glycyrrhizin nanocomplex for improving bioavailability via pH-responsive hydrogel properties.

Resveratrol (RES) is a functional polyphenol that suffers from low water solubility and poor bioavailability. A novel RES-loaded soy protein isolate-dipotassium glycyrrhizinate (SPI-DG) nanocomplex (RES@SPI-DG) was designed and evaluated in this study. RES@SPI-DG was prepared using a simple but novel self-assembly ultrasonic-assisted pH-driven method. The interactions between RES and SPI-DG were non-covalent bonds, including hydrophobic interactions, hydrogen bonds, and van der Waals interactions. RES@SPI-DG exhibited high encapsulation efficiency (97.60 ± 0.38 %) and loading capacity (8.74 ± 0.03 %) of RES with a uniform small size (68.39 ± 1.10 nm). RES in RES@SPI-DG was in an amorphous state and demonstrated a 24-h apparent solubility 482.53-fold higher than bare RES. RES@SPI-DG also showed strong in vitro antioxidant properties. The pH-responsive hydrogel character of SPI-DG makes it an effective intestine-targeted delivery system that could retard the release of RES in a simulated stomach and accelerate it in a simulated intestine. In animal experiments, the bioavailability of RES@SPI-DG was 5.17 times higher than that of bare RES, and the biodistribution was also significantly improved. RES@SPI-DG demonstrated a strong hepatoprotective effect against overdose acetaminophen-induced liver injury. The SPI-DG complex might be a promising nano-platform for enhancing the bioavailability and efficacy of hydrophobic polyphenols such as RES.

Multi-omics integration analysis unveils heterogeneity in breast cancer at the individual level.

Identifying robust breast cancer subtypes will help to reveal the cancer heterogeneity. However, previous breast cancer subtypes were based on population-level quantitative gene expression, which is affected by batch effects and cannot be applied to individuals. We detected differential gene expression, genomic, and epigenomic alterations to identify driver differential expression at the individual level. The individual driver differential expression reflected the breast cancer patients' heterogeneity and revealed four subtypes. Mesenchymal subtype as the most aggressive subtype harbored deletion and downregulated expression of genes in chromosome 11q23 region. Specifically, silencing of the SDHD gene in 11q23 promoted the invasion and migration of breast cancer cells in vitro by the epithelial-mesenchymal transition. The immunologically hot subtype displayed an immune-hot microenvironment, including high T-cell infiltration and upregulated PD-1 and CTLA4. Luminal and genomic-unstable subtypes showed opposite macrophage polarization, which may be regulated by the ligand-receptor pairs of CD99. The integration of multi-omics data at the individual level provides a powerful framework for elucidating the heterogeneity of breast cancer.

A study on the long-term effects and mechanisms of internet information behavior on poverty alleviation among smallholder farmers: Evidence from China.

China has historically accomplished the task of eradicating absolute poverty, however, as a result of multiple external constraints and a lack of their own endogenous motivation, there is a general lack of viability among farmers who have been lifted out of poverty, with some of those who have been lifted out of poverty at risk of returning to poverty and marginalized populations at risk of becoming poor, and there are certain challenges to the longevity and stability of the poverty eradication of smallholder farmers. In the era of rapid development of information technology, the use of Internet information has become an important way to change the information asymmetry in rural areas, narrow the urban-rural digital divide and reduce the vulnerability of poverty at present. Based on this, this paper puts forward the corresponding research hypotheses on the theoretical basis of how Internet information behavior affects the long-term effects of poverty alleviation of smallholder farmers, and this paper is based on the empirical analysis of the household survey data of 240 smallholder farmers in 3 cities and 3 counties of H Province, in an attempt to explore empirical testing of the impact of Internet information behavior on the long-term effects of poverty alleviation of smallholder farmers, and to further reveal the intrinsic mechanism of the role of the internal mechanism of the transformation between the smallholder farmers' Internet information behavior and poverty alleviation of the long-term effects of poverty alleviation. This study found that (1) Internet information usage would be positively related to the long-term poverty alleviation of smallholder farmers; (2) Among the mechanisms of Internet information usage on the long-term poverty alleviation of smallholder farmers, agricultural income opportunities, employment opportunities and entrepreneurial business opportunities have significant mediating effects; (3) Formal social support and informal social support, all play a significant positive moderating role in the process of transformation of development opportunities carried out by smallholder farmers. The findings of the study have important practical implications for accelerating the poverty alleviation effect of the Internet and achieving sustainable poverty alleviation among small farmers to promote common prosperity.

Graph Signal Smoothness Based Feature Learning of Brain Functional Networks in Schizophrenia.

In this paper we study the brain functional network of schizophrenic patients based on resting-state fMRI data. Different from the region of interest (ROI)-level brain networks that describe the connectivity between brain regions, this paper constructs a subject-level brain functional network that describes the similarity between subjects from a graph signal processing (GSP) perspective. Based on the subject graph, we introduce the concept of graph signal smoothness to analyze the abnormal brain regions (feature brain regions) in which schizophrenic patients produce abnormal functional connections and to quantitatively rank the degree of abnormality of brain regions. We find that in the patients' brain networks, many new connections appear and some common connections are strengthened. The feature brain regions can be easily found according to the value of connection differences. Finally, we validate the learned feature brain regions by the results of two types of statistical analyses (ROI-to-ROI analysis and seed-to-voxel analysis), and the feature brain regions derived from graph signal smoothness are indeed the brain regions with significant differences in the statistical analysis, which illustrates the potential of graph signal smoothness for use in quantitative analysis of brain networks.

Brain Network Analysis of Schizophrenia Patients Based on Hypergraph Signal Processing.

Since high-order relationships among multiple brain regions-of-interests (ROIs) are helpful to explore the pathogenesis of neurological diseases more deeply, hypergraph-based brain networks are more suitable for brain science research. Unlike the existing hypergraph based brain network (brain hypernetwork), where hyperedges containing the same number of ROIs are assumed to have equal weights (to some extent, the network is unweighted), and the underlying structure is described only by an incidence/adjacency matrix, in this paper, we propose a framework for constructing a truly weighted brain hypernetwork described by an adjacency tensor. Considering the relationships among vertices within a hyperedge, we propose a novel hyperedge weight estimation method and convert the incidence matrix into a weighted adjacency tensor. On the basis of tensor decomposition, we apply hypergraph signal processing tools, such as hypergraph Fourier transform, to analyze and compare the spectrum between schizophrenia patients and normal controls. It is found that there are more high frequency components in the spectrum of patients than controls, and the average amplitude is significantly greater than that of controls. Instead of extracting some simple topological features from brain hypernetworks for classification, we innovatively use the hypergraph spectrum and the spectral signal as classification features, and the classification results on two public datasets demonstrate the effectiveness of our proposed method.

Long non-coding RNA PFI inhibits apoptosis of alveolar epithelial cells to alleviate lung injury via miR-328-3p/Creb1 axis.

Acute lung injury (ALI), a common clinical type of critical illness, is an acute hypoxic respiratory insufficiency caused by the damage of alveolar epithelial cells and capillary endothelial cells. In a previous study, we reported a novel lncRNA, lncRNA PFI, which could protect against pulmonary fibrosis in pulmonary fibroblasts. The present study demonstrated that lncRNA PFI was downregulated in alveolar epithelial cell of mice injury lung tissues, and further investigated the role of lncRNA PFI in regulating inflammation-induced alveolar epithelial cell apoptosis. Overexpression of lncRNA PFI could partially abrogated bleomycin induced type II AECs injured. Subsequently, bioinformatic prediction revealed that lncRNA PFI might directly bind to miR-328-3p, and further AGO-2 RNA binding protein immunoprecipitation (RIP) assay confirmed their binding relationship. Furthermore, miR-328-3p promoted apoptosis in MLE-12 cells by limiting the activation of the Creb1, a protein correlated with cell apoptosis, whereas AMO-328-3p ablated the pro-apoptosis effect of silencing lncRNA PFI in MLE-12 cells. While miR-328-3p could also ablate the function of lncRNA PFI in bleomycin treated human lung epithelial cells. Enhanced expression of lncRNA PFI reversed the LPS-induced lung injury in mice. Overall, these data reveal that lncRNA PFI mitigated acute lung injury through miR-328-3p/Creb1 pathway in alveolar epithelial cells.

Angelica sinensis polysaccharides prevents hematopoietic regression in D-Galactose-Induced aging model via attenuation of oxidative stress in hematopoietic microenvironment.

BACKGROUND: Extrinsic molecular mechanisms that regulate hematopoietic stem/progenitor cell (HSPC) aging are still poorly understood, and a potential protective medication needs to be explored. MATERIALS AND METHODS: The senescent parameters of hematopoietic cells and bone marrow stromal cells (BMSCs) including cell cycle analysis, senescence-associated SA-ß-gal staining and signals, hematopoietic factors and cellular junction were analyzed in femur and tibia of rats. Furthermore, Sca-1+ HSPCs and BMSCs co-culture system was established to evaluate the direct effects of BMSC feeder layer to HSPCs. Oxidative DNA damage indicators in Sca-1+ HSCs and senescence-associated secretory phenotype (SASP) of BMSCs, gap junction intercellular communication between BMSCs, osteogenesis/adipogenisis differentiation balance of BMSCs were detected. RESULTS: In the D-gal pre-administrated rats, ASP treatment rescued senescence of hematopoietic cells and BMSCs, reserved CFU-GEMM; also, ASP treatment attenuated stromal oxidative load, ameliorated SCF, CXCL12, and GM-CSF production, increased Connexin-43 (Cx43) expression. BMSCs and Sca-1+ HSPCs co-cultivation demonstrated that ASP treatment prevented oxidative DNA damage response in co-cultured Sca-1+ HSPCs induced by D-gal pre-administration of feeder layer and the underlying mechanism may be related to ASP ameliorating feeder layer dysfunction due to D-gal induced senescence via inhibiting secretion of IL-1, IL-6, TNF-α, and RANTES, enhancing Cx43-mediated intercellular communication, improving Runx2 expression whereas decreasing PPARγ expression in BMSCs. CONCLUSION: The antioxidant property of ASP may provide a stroma-mediated potential therapeutic strategy for HSPC aging.

Discovery of Type II Interlayer Trions.

In terms of interlayer trions, electronic excitations in van der Waals heterostructures (vdWHs) can be classified into Type I (i.e., two identical charges in the same layer) and Type II (i.e., two identical charges in the different layers). Type I interlayer trions are investigated theoretically and experimentally. By contrast, Type II interlayer trions remain elusive in vdWHs, due to inadequate free charges, unsuitable band alignment, reduced Coulomb interactions, poor interface quality, etc. Here, the first observation of Type II interlayer trions is reported by exploring band alignments and choosing an atomically thin organic-inorganic system-monolayer WSe2 /bilayer pentacene heterostructure (1L + 2L HS). Both positive and negative Type II interlayer trions are electrically tuned and observed via PL spectroscopy. In particular, Type II interlayer trions exhibit in-plane anisotropic emission, possibly caused by their unique spatial structure and anisotropic charge interactions, which is highly correlated with the transition dipole moment of pentacene. The results pave the way to develop excitonic devices and all-optical circuits using atomically thin organic-inorganic bilayers.

Analysis on the linguistic features of conflict discourse in mathematical cooperation problem solving in China.

Classroom teaching is a kind of social activity system. Thus, as a form of classroom learning, collaborative problem solving has a strong social attribute. It is extremely common to choose the conflict discourse in the context of cooperation. The verbal characteristics of the conflicting discourse level in cooperative mathematics problem solving directly affects the cooperative learning between students and the classroom teaching of teachers. This article focuses on the overall linguistic characteristics of conflict discourse in solving cooperative problems and the discourse style and language characteristics of the three stages of conflict discourse. The main research conclusions are as follows: (1) The classification of language features of conflict discourse includes extreme summaries, negation, discourse markers, and so on. Among them, the frequency of Indexical 2nd-person pronouns is the highest. (2) The language expressions at the "initial stage of conflict" include Explanatory statement Negative response, instruct refuse and Seditious inquiry Confrontational answer. The language shows the characteristics of using emphatic words or phrases, negative words, imperative sentences and so on. Meanwhile, rebuttal questions, direct responses, explanations, and negative avoidance are the main forms language expressions at the "conflict stage." It also exhibits the verbal characteristics of rhetorical questions, negative comments, and direct negation. Lastly, topic-shifting, compromise, third-party intervention, and one-sided wins are the linguistic expressions at the "end of conflict." The language features are the appearance of tone relaxation and language easing, and the conflict ending utterances reflect cooperation.

Possible functions of CobW domain-containing (CBWD) genes in dinoflagellates using Karlodinium veneficum as a representative.

Since > 91% of dinoflagellates are proven auxotrophs of vitamin B12 and the cobalamin synthetase W (CobW) is a key gene involved in vitamin B12 synthesis pathway, a number of CobW domain-containing (CBWD) genes in dinoflagellates (DinoCBWDs) were surprisedly found from our transcriptomic and meta-transcriptomic studies. A total of 88 DinoCBWD genes were identified from the genomes and transcriptomes of four dinoflagellates, with five being cloned for full-lengths and characterized using the cosmopolitan and ecologically-important dinoflagellates Karlodinium veneficum and Scrippsiella trochoidea (synonym of Scrippsiella acuminata). DinoCBWDs were verified being irrelevant to vitamin B12 biosynthesis due to their transcriptions irresponsive to vitamin B12 levels and their phylogenetic positions. A comprehensive phylogenetic analysis demonstrated 75 out of the 88 DinoCBWD genes identified belong to three subfamilies of COG0523 protein family, of which most prokaryotic members are reported to be metallochaperones and the eukaryotic members are ubiquitously found but mostly unknown for their functions. Our results from K. veneficum demonstrated DinoCBWDs are associated with metal homeostasis and other divergent functions, with four KvCBWDs involving in zinc homeostasis and KvCBWD1 likely functioning as Fe-type nitrile hydratase activator. In addition, conserved motif analysis revealed the structural foundation of KvCBWD proteins that are consistent with previously described CBWD proteins with GTPase activity and metal binding. Our results provide a stepping-stone toward better understanding the functions of DinoCBWDs and the COG0523 family.

Graph-Based Motion Artifacts Detection Method from Head Computed Tomography Images.

Computed tomography (CT) images play an important role due to effectiveness and accessibility, however, motion artifacts may obscure or simulate pathology and dramatically degrade the diagnosis accuracy. In recent years, convolutional neural networks (CNNs) have achieved state-of-the-art performance in medical imaging due to the powerful learning ability with the help of the advanced hardware technology. Unfortunately, CNNs have significant overhead on memory usage and computational resources and are labeled 'black-box' by scholars for their complex underlying structures. To this end, an interpretable graph-based method has been proposed for motion artifacts detection from head CT images in this paper. From a topological perspective, the artifacts detection problem has been reformulated as a complex network classification problem based on the network topological characteristics of the corresponding complex networks. A motion artifacts detection method based on complex networks (MADM-CN) has been proposed. Firstly, the graph of each CT image is constructed based on the theory of complex networks. Secondly, slice-to-slice relationship has been explored by multiple graph construction. In addition, network topological characteristics are investigated locally and globally, consistent topological characteristics including average degree, average clustering coefficient have been utilized for classification. The experimental results have demonstrated that the proposed MADM-CN has achieved better performance over conventional machine learning and deep learning methods on a real CT dataset, reaching up to 98% of the accuracy and 97% of the sensitivity.

Direct observation of contact resistivity for monolayer TMD based junctions via PL spectroscopy.

Monolayer transition metal dichalcogenides (mTMDs) possess a direct band gap and strong PL emission that is highly sensitive to doping level and interfaces, laying the foundation for investigating the contact between mTMD and metal via PL spectroscopy. Currently, electrical methods have been utilized to measure the contact resistance (RC), but they are complicated, time-consuming, high-cost and suffer from inevitable chemical disorders and Fermi level pinning. In addition, previously reported contact resistances comprise both Schottky barrier and tunnel barrier components. Here, we report a simple, rapid and low-cost method to study the tunnel barrier dominated contact resistance of mTMD based junctions through PL spectroscopy. These junctions are free from chemical disorders and Fermi level pinning. Excluding the Schottky barrier component, solely tunnel barrier dominated contact resistances of 1 L MoSe2/Au and 1 L MoSe2/graphene junctions were estimated to be 147.8 Ω µm and 54.9 Ω µm, respectively. Density functional theory (DFT) simulations revealed that the larger RC of the former was possibly due to the existence of intrinsic effective potential difference (Φbarrier) between mTMD and metal. Both junctions exhibit an increasing tendency of RC as temperature decreases, which is probably attributed to the thermal expansion coefficient (TEC) mismatch-triggered interlayer spacing (d) increase and temperature-induced doping. Remarkably, a significant change of RC was observed in 1 L MoSe2/Au junctions, which is possibly ascribed to the changes of their orbital overlaps. Our results open new avenues for exploring fundamental metal-semiconductor contact principles and constructing high-performance devices.

Systematic analyses identify the anti-fibrotic role of lncRNA TP53TG1 in IPF.

Long non-coding RNA (lncRNA) was reported to be a critical regulator of cellular homeostasis, but poorly understood in idiopathic pulmonary fibrosis (IPF). Here, we systematically identified a crucial lncRNA, p53-induced long non-coding RNA TP53 target 1 (TP53TG1), which was the dysregulated hub gene in IPF regulatory network and one of the top degree genes and down-regulated in IPF-drived fibroblasts. Functional experiments revealed that overexpression of TP53TG1 attenuated the increased expression of fibronectin 1 (Fn1), Collagen 1α1, Collagen 3α1, ACTA2 mRNA, Fn1, and Collagen I protein level, excessive fibroblasts proliferation, migration and differentiation induced by TGF-ß1 in MRC-5 as well as PMLFs. In vivo assays identified that forced expression of TP53TG1 by adeno-associated virus 5 (AAV5) not only prevented BLM-induced experimental fibrosis but also reversed established lung fibrosis in the murine model. Mechanistically, TP53TG1 was found to bind to amount of tight junction proteins. Importantly, we found that TP53TG1 binds to the Myosin Heavy Chain 9 (MYH9) to inhibit its protein expression and thus the MYH9-mediated activation of fibroblasts. Collectively, we identified the TP53TG1 as a master suppressor of fibroblast activation and IPF, which could be a potential hub for targeting treatment of the disease.

Critical role of PAFR/YAP1 positive feedback loop in cardiac fibrosis.

Aberrant activation of cardiac fibroblasts is the main cause and character of cardiac fibrosis, and inhibition of cardiac fibrosis becomes a promising treatment for cardiac diseases. Platelet-activating factor (PAF) and Hippo pathway is recently recognized as key signaling mechanisms in cardiovascular diseases. In this study we explored the potential roles of PAF and Hippo signaling pathway in cardiac fibrosis. Myocardial infarction (MI) was induced in mice by left anterior descending artery ligation. After 28 days, the mice were sacrificed, and the hearts were collected for analyses. We showed that PAF receptor (PAFR) and yes-associated protein 1 (YAP1, a key effector in the Hippo pathway) were significantly increased in the heart of MI mice. Increased expression of PAFR and YAP1 was also observed in angiotensin II (Ang II)-treated mouse cardiac fibroblasts. In mouse cardiac fibroblasts, forced expression of YAP1 increased cell viability, resulted in collagen deposition and promoted fibroblast-myofibroblast transition. We showed that PAF induced fibrogenesis through activation of YAP1 and promoted its nuclear translocation via interacting with PAFR, while YAP1 promoted the expression of PAFR by binding to and activating transcription factor TEAD1. More importantly, silencing PAFR or YAP1 by shRNA, or using transgenic mice to induce the conditional deletion of YAP1 in cardiac fibroblasts, impeded cardiac fibrosis and improved cardiac function in MI mice. Taken together, this study elucidates the role and mechanisms of PAFR/YAP1 positive feedback loop in cardiac fibrosis, suggesting a potential role of this pathway as novel therapeutic targets in cardiac fibrosis.

Endothelial progenitor cells-derived exosomes transfer microRNA-30e-5p to regulate Erastin-induced ferroptosis in human umbilical vein endothelial cells via the specificity protein 1/adenosine monophosphate-activated protein kinase axis.

Ferroptosis is a kind of cell death triggered by intracellular phospholipid peroxidation. Human umbilical vein blood endothelial progenitor cells-Exosomes (EPCs-Exos) affect ferroptosis. This study sought to explore the mechanism of EPCs-Exos in human umbilical vein endothelial cell (HUVEC) ferroptosis. EPCs-Exos were isolated and identified. HUVECs were treated with Erastin at IC50 concentration. Ferroptosis-related indexes and iron ion content were detected using kits. HUVEC migration and angiogenesis before/after ferroptosis inhibitor treatment were observed by cell scratch and angiogenesis assays. After Erastin induction, HUVECs were transfected with miR-30e-5p mimic, or treated with EPCs-Exos and EPCs-Exos transfected with miR-30e-5p inhibitor. miR-30e-5p expression was detected by RT-qPCR. The binding relationship between miR-30e-5p and specificity protein 1 (SP1) was verified by dual-luciferase assay. SP1 expression was detected by Western blot. HUVECs treated with Erastin and EPCs-Exos were transfected with pcDNA3.1-SP1. Protein levels of adenosine monophosphate-activated protein kinase (AMPK) and p-AMPK were detected by Western blot. EPCs-Exos inhibited Erastin-induced HUVEC ferroptosis and endothelial injury. Erastin inhibited miR-30e-5p and EPCs-Exo treatment recovered miR-30e-5p expression. miR-30e-5p was encapsulated in EPCs-Exos. After inhibiting miR-30e-5p in EPCs, the inhibitory effect of EPCs-Exos on HUVEC ferroptosis was attenuated. miR-30e-5p targeted SP1. Overexpression of SP1 partially reversed the effect of EPCs-Exos on improving HUVEC ferroptosis and increasing phosphorylation levels of AMPK. Collectively, EPCs-Exos inhibited Erastin-induced HUVEC ferroptosis by upregulating miR-30e-5p, inhibiting SP1, and activating the AMPK pathway.

Graph Signal Processing Approach to QSAR/QSPR Model Learning of Compounds.

Quantitative relationship between the activity/property and the structure of compound is critical in chemical applications. To learn this quantitative relationship, hundreds of molecular descriptors have been designed to describe the structure, mainly based on the properties of vertices and edges of molecular graph. However, many descriptors degenerate to the same values for different compounds with the same molecular graph, resulting in model failure. In this paper, we design a multidimensional signal for each vertex of the molecular graph to derive new descriptors with higher discriminability. We treat the new and traditional descriptors as the signals on the descriptor graph learned from the descriptor data, and enhance descriptor dissimilarity using the Laplacian filter derived from the descriptor graph. Combining these with model learning techniques, we propose a graph signal processing based approach to obtain reliable new models for learning the quantitative relationship and predicting the properties of compounds. We also provide insights from chemistry for the boiling point model. Several experiments are presented to demonstrate the validity, effectiveness and advantages of the proposed approach.