ABSTRACT
Resonant oscillators with stable frequencies and large quality factors help us to keep track of time with high precision. Examples range from quartz crystal oscillators in wristwatches to atomic oscillators in atomic clocks, which are, at present, our most precise time measurement devices1. The search for more stable and convenient reference oscillators is continuing2-6. Nuclear oscillators are better than atomic oscillators because of their naturally higher quality factors and higher resilience against external perturbations7-9. One of the most promising cases is an ultra-narrow nuclear resonance transition in 45Sc between the ground state and the 12.4-keV isomeric state with a long lifetime of 0.47 s (ref. 10). The scientific potential of 45Sc was realized long ago, but applications require 45Sc resonant excitation, which in turn requires accelerator-driven, high-brightness X-ray sources11 that have become available only recently. Here we report on resonant X-ray excitation of the 45Sc isomeric state by irradiation of Sc-metal foil with 12.4-keV photon pulses from a state-of-the-art X-ray free-electron laser and subsequent detection of nuclear decay products. Simultaneously, the transition energy was determined as [Formula: see text] with an uncertainty that is two orders of magnitude smaller than the previously known values. These advancements enable the application of this isomer in extreme metrology, nuclear clock technology, ultra-high-precision spectroscopy and similar applications.
ABSTRACT
MOTIVATION: Cell-type annotation is fundamental in revealing cell heterogeneity for single-cell data analysis. Although a host of works have been developed, the low signal-to-noise-ratio single-cell RNA-sequencing data that suffers from batch effects and dropout still poses obstacles in discovering grouped patterns for cell types by unsupervised learning and its alternative-semi-supervised learning that utilizes a few labeled cells as guidance for cell-type annotation. RESULTS: We propose a robust cell-type annotation method scSemiGCN based on graph convolutional networks. Built upon a denoised network structure that characterizes reliable cell-to-cell connections, scSemiGCN generates pseudo labels for unannotated cells. Then supervised contrastive learning follows to refine the noisy single-cell data. Finally, message passing with the refined features over the denoised network structure is conducted for semi-supervised cell-type annotation. Comparison over several datasets with six methods under extremely limited supervision validates the effectiveness and efficiency of scSemiGCN for cell-type annotation. AVAILABILITY AND IMPLEMENTATION: Implementation of scSemiGCN is available at https://github.com/Jane9898/scSemiGCN.
Subject(s)
Neural Networks, Computer , Single-Cell Analysis , Signal-To-Noise Ratio , Supervised Machine LearningABSTRACT
Learning node representation is a fundamental problem in biological network analysis, as compact representation features reveal complicated network structures and carry useful information for downstream tasks such as link prediction and node classification. Recently, multiple networks that profile objects from different aspects are increasingly accumulated, providing the opportunity to learn objects from multiple perspectives. However, the complex common and specific information across different networks pose challenges to node representation methods. Moreover, ubiquitous noise in networks calls for more robust representation. To deal with these problems, we present a representation learning method for multiple biological networks. First, we accommodate the noise and spurious edges in networks using denoised diffusion, providing robust connectivity structures for the subsequent representation learning. Then, we introduce a graph regularized integration model to combine refined networks and compute common representation features. By using the regularized decomposition technique, the proposed model can effectively preserve the common structural property of different networks and simultaneously accommodate their specific information, leading to a consistent representation. A simulation study shows the superiority of the proposed method on different levels of noisy networks. Three network-based inference tasks, including drug-target interaction prediction, gene function identification and fine-grained species categorization, are conducted using representation features learned from our method. Biological networks at different scales and levels of sparsity are involved. Experimental results on real-world data show that the proposed method has robust performance compared with alternatives. Overall, by eliminating noise and integrating effectively, the proposed method is able to learn useful representations from multiple biological networks.
Subject(s)
Learning , Neural Networks, Computer , Computer Simulation , DiffusionABSTRACT
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe and fatal disease. Although mesenchymal stem cell (MSC)-based therapy has shown remarkable efficacy in treating ARDS in animal experiments, clinical outcomes have been unsatisfactory, which may be attributed to the influence of the lung microenvironment during MSC administration. Extracellular vesicles (EVs) derived from endothelial cells (EC-EVs) are important components of the lung microenvironment and play a crucial role in ARDS. However, the effect of EC-EVs on MSC therapy is still unclear. In this study, we established lipopolysaccharide (LPS) - induced acute lung injury model to evaluate the impact of EC-EVs on the reparative effects of bone marrow-derived MSC (BM-MSC) transplantation on lung injury and to unravel the underlying mechanisms. METHODS: EVs were isolated from bronchoalveolar lavage fluid of mice with LPS - induced acute lung injury and patients with ARDS using ultracentrifugation. and the changes of EC-EVs were analysed using nanoflow cytometry analysis. In vitro assays were performed to establish the impact of EC-EVs on MSC functions, including cell viability and migration, while in vivo studies were performed to validate the therapeutic effect of EC-EVs on MSCs. RNA-Seq analysis, small interfering RNA (siRNA), and a recombinant lentivirus were used to investigate the underlying mechanisms. RESULTS: Compared with that in non-ARDS patients, the quantity of EC-EVs in the lung microenvironment was significantly greater in patients with ARDS. EVs derived from lipopolysaccharide-stimulated endothelial cells (LPS-EVs) significantly decreased the viability and migration of BM-MSCs. Furthermore, engrafting BM-MSCs pretreated with LPS-EVs promoted the release of inflammatory cytokines and increased pulmonary microvascular permeability, aggravating lung injury. Mechanistically, LPS-EVs reduced the expression level of isocitrate dehydrogenase 2 (IDH2), which catalyses the formation of α-ketoglutarate (α-KG), an intermediate product of the tricarboxylic acid (TCA) cycle, in BM-MSCs. α-KG is a cofactor for ten-eleven translocation (TET) enzymes, which catalyse DNA hydroxymethylation in BM-MSCs. CONCLUSIONS: This study revealed that EC-EVs in the lung microenvironment during ARDS can affect the therapeutic efficacy of BM-MSCs through the IDH2/TET pathway, providing potential strategies for improving the therapeutic efficacy of MSC-based therapy in the clinic.
Subject(s)
Endothelial Cells , Extracellular Vesicles , Isocitrate Dehydrogenase , Mesenchymal Stem Cell Transplantation , Mesenchymal Stem Cells , Respiratory Distress Syndrome , Extracellular Vesicles/metabolism , Extracellular Vesicles/transplantation , Animals , Mesenchymal Stem Cells/metabolism , Mesenchymal Stem Cells/cytology , Respiratory Distress Syndrome/therapy , Respiratory Distress Syndrome/metabolism , Endothelial Cells/metabolism , Humans , Mice , Mesenchymal Stem Cell Transplantation/methods , Isocitrate Dehydrogenase/genetics , Isocitrate Dehydrogenase/metabolism , Mice, Inbred C57BL , Male , Lipopolysaccharides/pharmacology , Signal Transduction , Acute Lung Injury/therapy , Acute Lung Injury/metabolism , Cell MovementABSTRACT
Cardiorenal syndrome type 4 (CRS4), a progressive deterioration of cardiac function secondary to chronic kidney disease (CKD), is a leading cause of death in patients with CKD. In this study, we aimed to investigate the cardioprotective effect of emodin on CRS4. C57BL/6 mice with 5/6 nephrectomy and HL-1 cells stimulated with 5% CKD mouse serum were used for in vivo and in vitro experiments. To assess the cardioprotective potential of emodin, we employed a comprehensive array of methodologies, including echocardiography, tissue staining, immunofluorescence staining, biochemical detection, flow cytometry, real-time quantitative PCR, and western blot analysis. Our results showed that emodin exerted protective effects on the function and structure of the residual kidney. Emodin also reduced pathologic changes in the cardiac morphology and function of these mice. These effects may have been related to emodin-mediated suppression of reactive oxygen species production, reduction of mitochondrial oxidative damage, and increase of oxidative metabolism via restoration of PGC1α expression and that of its target genes. In contrast, inhibition of PGC1α expression significantly reversed emodin-mediated cardioprotection in vivo. In conclusion, emodin protects the heart from 5/6 nephrectomy-induced mitochondrial damage via activation of the PGC1α signaling. The findings obtained in our study can be used to develop effective therapeutic strategies for patients with CRS4.
Subject(s)
Cardio-Renal Syndrome , Emodin , Renal Insufficiency, Chronic , Humans , Mice , Animals , Emodin/pharmacology , Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha/metabolism , Apoptosis , Mice, Inbred C57BLABSTRACT
BACKGROUND: Epigenetic modifications that exhibit circadian oscillations also promote circadian oscillations of gene expression. Brassica napus is a heterozygous polyploid species that has undergone distant hybridization and genome doubling events and has a young and distinct species origin. Studies incorporating circadian rhythm analysis of epigenetic modifications can offer new insights into differences in diurnal oscillation behavior among subgenomes and the regulation of diverse expressions of homologous gene rhythms in biological clocks. RESULTS: In this study, we created a high-resolution and multioscillatory gene expression dataset, active histone modification (H3K4me3, H3K9ac), and RNAPII recruitment in Brassica napus. We also conducted the pioneering characterization of the diurnal rhythm of transcription and epigenetic modifications in an allopolyploid species. We compared the evolution of diurnal rhythms between subgenomes and observed that the Cn subgenome had higher diurnal oscillation activity in both transcription and active histone modifications than the An subgenome. Compared to the A subgenome in Brassica rapa, the An subgenome of Brassica napus displayed significant changes in diurnal oscillation characteristics of transcription. Homologous gene pairs exhibited a higher proportion of diurnal oscillation in transcription than subgenome-specific genes, attributed to higher chromatin accessibility and abundance of active epigenetic modification types. We found that the diurnal expression of homologous genes displayed diversity, and the redundancy of the circadian system resulted in extensive changes in the diurnal rhythm characteristics of clock genes after distant hybridization and genome duplication events. Epigenetic modifications influenced the differences in the diurnal rhythm of homologous gene expression, and the diurnal oscillation of homologous gene expression was affected by the combination of multiple histone modifications. CONCLUSIONS: Herein, we presented, for the first time, a characterization of the diurnal rhythm characteristics of gene expression and its epigenetic modifications in an allopolyploid species. Our discoveries shed light on the epigenetic factors responsible for the diurnal oscillation activity imbalance between subgenomes and homologous genes' rhythmic expression differences. The comprehensive time-series dataset we generated for gene expression and epigenetic modifications provides a valuable resource for future investigations into the regulatory mechanisms of protein-coding genes in Brassica napus.
Subject(s)
Brassica napus , Brassica napus/genetics , Polyploidy , Circadian Rhythm/genetics , Genome, PlantABSTRACT
Unidirectional magnetoresistance (UMR) has been intensively studied in ferromagnetic systems, which is mainly induced by spin-dependent and spin-flip electron scattering. Yet, UMR in antiferromagnetic (AFM) systems has not been fully understood to date. In this work, we reported UMR in a YFeO3/Pt heterostructure where YFeO3 is a typical AFM insulator. Magnetic-field dependence and temperature dependence of transport measurements indicate that magnon dynamics and interfacial Rashba splitting are two individual origins for AFM UMR, which is consistent with the UMR theory in ferromagnetic systems. We further established a comprehensive theoretical model that incorporates micromagnetic simulation, density functional theory calculation, and the tight-binding model, which explain the observed AFM UMR phenomenon well. Our work sheds light on the intrinsic transport property of the AFM system and may facilitate the development of AFM spintronic devices.
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With the extensive industrialization and urbanization taking place in China during the recent decades, land use throughout the country has experienced profound changes influenced not only by the demand for population growth and living standard improvement but also by the constraints of series of land use policies. However, whether the conflict between the expansion of settlement land (SL) and the loss of cultivated land (CL) have been resolved at the national scale or transferred between the local regions remains unclear. Based on yearly ESA CCI land use and land cover products from 1992 to 2020, the long-term trends of quantity and spatial pattern of SL expansion and CL change in China from national and local views were investigated using trend statistic methods, and finally a comprehensive zoning framework was proposed to recognize the trade-off and synergies relationships between SL expansion and CL change. There are a continuous expansion of SL with global linear trends showing three breakpoints in 2000, 2005, and 2012, and a fluctuation decline of CL presented with four breakpoints in 1997, 2002, 2006, and 2013. Aggregation and dispersion tendencies with linear characteristics of SL expansion and CL change were found with breakpoints in 2001, 2008, 2012, and 2016 and breakpoints in 2001 and 2010, respectively. A spotty spatial pattern of SL was shown spatially coincident with urban agglomerations in China while the planar continuous characteristic was found for CL. Local counties were classified into five tradeoff and synergies zones (TSZs), where general synergies (G-S) and decoupling (D) of SL expansion and CL change were rare cases and the different change in quantity and trend of SL expansion and CL change in local counties was concealed by the national trend. A few scattered counties were belonging to G-S and D TSZs, while most of the counties in the central-east and western China were in General-Tradeoff (G-T) and Superior-Tradeoff (S-T) TSZs. Counties in south and north China with higher percentages of CL were more prevalent in Superior-Synergy (S-S) TSZ. Our findings explicated the complex relationships between SL expansion and CL change of China at the national scale and in local counties, which pointed out the differences of unified land use management activities across scales and could provide insights for future policy-making and management measures of land use to both ensure the national food security and promote regional sustainable development more synchronously.
Subject(s)
Conservation of Natural Resources , Urbanization , China , Agriculture , HumansABSTRACT
In this paper, Cu-BTC derived mesoporous CuS nanomaterial (m-CuS) was synthesized via a two-step process involving carbonization and sulfidation of Cu-BTC for colorimetric glutathione detection. The Cu-BTC was constructed by 1,3,5-benzenetri-carboxylic acid (H3BTC) and Cu2+ ions. The obtained m-CuS showed a large specific surface area (55.751 m2/g), pore volume (0.153 cm3/g), and pore diameter (15.380 nm). In addition, the synthesized m-CuS exhibited high peroxidase-like activity and could catalyze oxidation of the colorless substrate 3,3',5,5'-tetramethylbenzidine to a blue product. Peroxidase-like activity mechanism studies using terephthalic acid as a fluorescent probe proved that m-CuS assists H2O2 decomposition to reactive oxygen species, which are responsible for TMB oxidation. However, the catalytic activity of m-CuS for the oxidation of TMB by H2O2 could be potently inhibited in the presence of glutathione. Based on this phenomenon, the colorimetric detection of glutathione was demonstrated with good selectivity and high sensitivity. The linear range was 1-20 µM and 20-300 µM with a detection limit of 0.1 µM. The m-CuS showing good stability and robust peroxidase catalytic activity was applied for the detection of glutathione in human urine samples.
Subject(s)
Colorimetry , Copper , Glutathione , Hydrogen Peroxide , Nanostructures , Glutathione/analysis , Glutathione/chemistry , Colorimetry/methods , Copper/chemistry , Nanostructures/chemistry , Catalysis , Hydrogen Peroxide/chemistry , Hydrogen Peroxide/analysis , Porosity , Oxidation-Reduction , Phthalic Acids/chemistry , Humans , Benzidines/chemistry , Limit of DetectionABSTRACT
A morphologic examination is essential for the diagnosis of hematological diseases. However, its conventional manual operation is time-consuming and laborious. Herein, we attempt to establish an artificial intelligence (AI)-aided diagnostic framework integrating medical expertise. This framework acts as a virtual hematological morphologist (VHM) for diagnosing hematological neoplasms. Two datasets were established as follows: An image dataset was used to train the Faster Region-based Convolutional Neural Network to develop an image-based morphologic feature extraction model. A case dataset containing retrospective morphologic diagnostic data was used to train a support vector machine algorithm to develop a feature-based case identification model based on diagnostic criteria. Integrating these 2 models established a whole-process AI-aided diagnostic framework, namely, VHM, and a 2-stage strategy was applied to practice case diagnosis. The recall and precision of VHM in bone marrow cell classification were 94.65% and 93.95%, respectively. The balanced accuracy, sensitivity, and specificity of VHM were 97.16%, 99.09%, and 92%, respectively, in the differential diagnosis of normal and abnormal cases, and 99.23%, 97.96%, and 100%, respectively, in the precise diagnosis of chronic myelogenous leukemia in chronic phase. This work represents the first attempt, to our knowledge, to extract multimodal morphologic features and to integrate a feature-based case diagnosis model for designing a comprehensive AI-aided morphologic diagnostic framework. The performance of our knowledge-based framework was superior to that of the widely used end-to-end AI-based diagnostic framework in terms of testing accuracy (96.88% vs 68.75%) or generalization ability (97.11% vs 68.75%) in differentiating normal and abnormal cases. The remarkable advantage of VHM is that it follows the logic of clinical diagnostic procedures, making it a reliable and interpretable hematological diagnostic tool.
Subject(s)
Artificial Intelligence , Hematologic Neoplasms , Humans , Retrospective Studies , Neural Networks, Computer , Algorithms , Hematologic Neoplasms/diagnosisABSTRACT
The mechanical properties (compressibility or deformability) of cells are closely related to their death, migration, and differentiation. Accurate separation and manipulation of bioparticles based on these mechanical properties are still a challenging in the field of acoustofluidics. In this work, based on surface acoustic waves (SAW) and divergent microchannels, we developed a new method for separating and detecting particles or cells with different compressibility. The difference in acoustic radiation force (Fr) caused by compressibility are gradually amplified and accumulated by decreasing the flow velocity, and they are finally reflected in the particle migration distance. During the transverse migration process, the alternating dominance of the acoustic radiation force and the Stokes resistance force (Fs) drives the particles to create three typical migration patterns: intermittent migration, compound migration, and near-wall migration. In the present tilted SAW device, a 91% separation success rate of â¼10 µm polystyrene (PS) and polydimethylsiloxane (PDMS) particles can be achieved by optimizing the acoustic field input power and the fluid velocity. The application potential of the present divergent microchannel is validated by separating the myelogenous leukemia cell K562 and the natural killer cell NK92 that have similar densities and sizes (â¼15 µm) but different compressibility. The results of this work are expected to provide valuable insights into the acoustofluidics separation and detection of the cells that are with different compressibility.
Subject(s)
Acoustics , Sound , PolystyrenesABSTRACT
BACKGROUND: Time to reperfusion is the key to the treatment of patients with ST-elevation myocardial infarction (STEMI). It is uncertain whether adjunctive thrombolytic therapy combined with contemporary antiplatelet agent ticagrelor improves outcomes as administered prior to primary percutaneous coronary intervention (PCI) expected to be performed within 120 minutes. METHODS: OPTIMA-6 is a multicenter, randomized, double-blind, placebo-controlled, and superiority trial to evaluate the efficacy of a bolus of half-dose recombinant staphylokinase (r-SAK) vs placebo prior to timely primary PCI in patients with STEMI. Enrollment began in April 2023 and is expected to enroll 2,260 patients at approximately 50 centers. Patients with acute STEMI presenting ≤12 hours of symptom onset and expected to undergo primary PCI within 120 minutes but more than 30 minutes are to be randomized to a bolus of half-dose r-SAK or placebo. All recruited patients will be mandatory to take aspirin and ticagrelor and receive a bolus of loading dose heparin before the thrombolytic therapy. The primary efficacy endpoint is major adverse cardiovascular events (MACE) within 90 days, and the MACE is defined as a composite of all-cause death, reinfarction, unplanned target vessel revascularization, heart failure or cardiogenic shock, and major ventricular arrhythmia. The primary safety endpoints are major bleeding events (BARC 3, 5) within 90 days. CONCLUSIONS: OPTIMA-6 will reveal the efficacy and safety of a contemporary facilitated PCI with a bolus of half-dose r-SAK in combination with ticagrelor in patients with STEMI.
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With diverse types of omics data widely available, many computational methods have been recently developed to integrate these heterogeneous data, providing a comprehensive understanding of diseases and biological mechanisms. But most of them hardly take noise effects into account. Data-specific patterns unique to data types also make it challenging to uncover the consistent patterns and learn a compact representation of multi-omics data. Here we present a multi-omics integration method considering these issues. We explicitly model the error term in data reconstruction and simultaneously consider noise effects and data-specific patterns. We utilize a denoised network regularization in which we build a fused network using a denoising procedure to suppress noise effects and data-specific patterns. The error term collaborates with the denoised network regularization to capture data-specific patterns. We solve the optimization problem via an inexact alternating minimization algorithm. A comparative simulation study shows the method's superiority at discovering common patterns among data types at three noise levels. Transcriptomics-and-epigenomics integration, in seven cancer cohorts from The Cancer Genome Atlas, demonstrates that the learned integrative representation extracted in an unsupervised manner can depict survival information. Specially in liver hepatocellular carcinoma, the learned integrative representation attains average Harrell's C-index of 0.78 in 10 times 3-fold cross-validation for survival prediction, which far exceeds competing methods, and we discover an aggressive subtype in liver hepatocellular carcinoma with this latent representation, which is validated by an external dataset GSE14520. We also show that DeFusion is applicable to the integration of other omics types.
Subject(s)
Carcinoma, Hepatocellular/genetics , Carcinoma, Hepatocellular/mortality , Epigenomics/methods , Liver Neoplasms/genetics , Liver Neoplasms/mortality , Transcriptome , Algorithms , Bayes Theorem , Cohort Studies , DNA Methylation/genetics , Deep Learning , Humans , MicroRNAs/genetics , Prognosis , RNA, Messenger/geneticsABSTRACT
MOTIVATION: Drug repositioning that aims to find new indications for existing drugs has been an efficient strategy for drug discovery. In the scenario where we only have confirmed disease-drug associations as positive pairs, a negative set of disease-drug pairs is usually constructed from the unknown disease-drug pairs in previous studies, where we do not know whether drugs and diseases can be associated, to train a model for disease-drug association prediction (drug repositioning). Drugs and diseases in these negative pairs can potentially be associated, but most studies have ignored them. RESULTS: We present a method, springD2A, to capture the uncertainty in the negative pairs, and to discriminate between positive and unknown pairs because the former are more reliable. In springD2A, we introduce a spring-like penalty for the loss of negative pairs, which is strong if they are too close in a unit sphere, but mild if they are at a moderate distance. We also design a sequential sampling in which the probability of an unknown disease-drug pair sampled as negative is proportional to its score predicted as positive. Multiple models are learned during sequential sampling, and we adopt parameter- and feature-based ensemble schemes to boost performance. Experiments show springD2A is an effective tool for drug-repositioning. AVAILABILITY AND IMPLEMENTATION: A python implementation of springD2A and datasets used in this study are available at https://github.com/wangyuanhao/springD2A. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Algorithms , Drug Repositioning , Uncertainty , Probability , Drug DiscoveryABSTRACT
BACKGROUND: Swallowing is one of the most important activities in our life and serves the dual roles of nutritional intake and eating enjoyment. OBJECTIVE: The study aimed to conduct a meta-analysis to investigate the brain activity of swallowing. METHODS: Studies of swallowing using functional magnetic resonance imaging were reviewed in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP) and Wan Fang before 30 November 2021. Two authors analysed the studies for eligibility criteria. The final inclusion of studies was decided by consensus. An activation likelihood estimation (ALE) meta-analysis of these studies was performed with GingerALE, including 16 studies. RESULTS: For swallowing, clusters with high activation likelihood were found in the bilateral insula, bilateral pre-central gyrus, bilateral post-central gyrus, left transverse temporal gyrus, right medial front gyrus, bilateral inferior frontal gyrus and bilateral cingulate gyrus. For water swallowing, clusters with high activation likelihood were found in the bilateral inferior frontal gyrus and the left pre-central gyrus. For saliva swallowing, clusters with high activation likelihood were found in the bilateral cingulate gyrus, bilateral pre-central gyrus, left post-central gyrus and left transverse gyrus. CONCLUSION: This meta-analysis reflects that swallowing is regulated by both sensory and motor cortex, and saliva swallowing activates more brain areas than water swallowing, which would promote our knowledge of swallowing and provide some direction for clinical and other research.
Subject(s)
Brain Mapping , Deglutition , Humans , Deglutition/physiology , Magnetic Resonance Imaging , Brain/diagnostic imaging , WaterABSTRACT
Self-renewal and differentiation of embryonic stem cells (ESCs) are influenced by protein O-linked ß-N-acetylglucosamine (O-GlcNAc) modification, but the underlying mechanism remains incompletely understood. Herein, we report the identification of 979 O-GlcNAcylated proteins and 1340 modification sites in mouse ESCs (mESCs) by using a chemoproteomics method. In addition to OCT4 and SOX2, the third core pluripotency transcription factor (PTF) NANOG was found to be modified and functionally regulated by O-GlcNAc. Upon differentiation along the neuronal lineage, the O-GlcNAc stoichiometry at 123 sites of 83 proteins-several of which were PTFs-was found to decline. Transcriptomic profiling reveals 2456 differentially expressed genes responsive to OGT inhibition during differentiation, of which 901 are target genes of core PTFs. By acting on the core PTF network, suppression of O-GlcNAcylation upregulates neuron-related genes, thus contributing to mESC fate determination.
Subject(s)
Mouse Embryonic Stem Cells , Transcriptome , Animals , Mice , Acetylglucosamine/metabolism , Cell Differentiation , Embryonic Stem Cells , Gene Expression Regulation , Mouse Embryonic Stem Cells/metabolism , Cell LineageABSTRACT
BACKGROUND: Thin endometrium (TE) is a challenging clinical issue in the reproductive medicine characterized by inadequate endometrial thickness, poor response to estrogen and no effective treatments currently. At present, the precise pathogenesis of thin endometria remains to be elucidated. We aimed to explore the related molecular mechanism of TE by comparing the transcriptome profiles of late-proliferative phase endometria between TE and matched controls. METHODS: We performed a bulk RNA-Seq (RNA-sequencing) of endometrial tissues in the late-proliferative phase in 7 TE and 7 matched controls for the first time. Differential gene expression analysis, gene ontology enrichment analysis and protein-protein interactions (PPIs) network analysis were performed. Immunohistochemistry was used for molecular expression and localization in endometria. Human endometrial stromal cells (HESCs) were isolated and cultured for verifying the functions of hub gene. RESULTS: Integrative data mining of our RNA-seq data in endometria revealed that most genes related to cell division and cell cycle were significantly inhibited, while inflammation activation, immune response and reactive oxygen species associated genes were upregulated in TE. PBK was identified as a hub of PPIs network, and its expression level was decreased by 2.43-fold in endometria of TE patients, particularly reduced in the stromal cells, which was paralleled by the decreased expression of Ki67. In vitro experiments showed that the depletion of PBK reduced the proliferation of HESCs by 50% and increased the apoptosis of HESCs by 1 time, meanwhile PBK expression was inhibited by oxidative stress (reduced by 76.2%), hypoxia (reduced by 51.9%) and inflammatory factors (reduced by approximately 50%). These results suggested that the insufficient expression of PBK was involved in the poor endometrial thickness in TE. CONCLUSIONS: The endometrial transcriptome in late-proliferative phase showed suppressed cell proliferation in women with thin endometria and decreased expression of PBK in human endometrial stromal cells (HESCs), to which inflammation and reactive oxygen species contributed.
Subject(s)
Cell Proliferation/genetics , Endometrium/pathology , Proto-Oncogene Proteins c-akt/genetics , Adult , Case-Control Studies , Cells, Cultured , Down-Regulation/genetics , Endometrium/metabolism , Female , Humans , Organ Size/genetics , Proto-Oncogene Proteins c-akt/metabolism , RNA-Seq , Sequence Analysis, RNA , Stromal Cells/metabolism , Stromal Cells/pathology , TranscriptomeABSTRACT
ABSTRACT: This study aimed to investigate the role of ginsenoside Rh1 in regulating the proliferation, apoptosis, and oxidative stress in oxidized low-density lipoprotein (ox-LDL)-treated human vascular endothelial cells (VECs) and the underlying mechanisms. VECs were treated with ox-LDL to generate an in vitro atherosclerosis model. The effect of ginsenoside Rh1 on cell viability and proliferation was examined by MTT and colony formation assays, respectively, and cell apoptosis was determined by flow cytometry and transferase dUTP nick end-labeling assay. The levels of reactive oxygen species, malondialdehyde, and superoxide dismutase activity were detected using biological assays. Finally, the effect of ginsenoside Rh1 on the levels of BAX and BCL-2 and the nuclear erythroid 2-related factor-2/heme oxygenase (HO)-1 signaling pathway was determined by quantitative real-time polymerase chain reaction and western blot assays. Treatment with ginsenoside Rh1 significantly increased the proliferation and decreased the apoptosis of ox-LDL-treated VECs in a dose-dependent manner. Moreover, ginsenoside Rh1 also relieved oxidative stress in ox-LDL-treated VECs by activating the Nrf2/HO-1 signaling pathway. Thus, ginsenoside Rh1 affects the proliferation, apoptosis, and oxidative stress in ox-LDL-treated VECs by activating the Nrf2/HO-1 signaling pathway.
Subject(s)
Heme Oxygenase (Decyclizing) , NF-E2-Related Factor 2 , Apoptosis , Cell Proliferation , Endothelial Cells/metabolism , Ginsenosides , Heme Oxygenase (Decyclizing)/metabolism , Heme Oxygenase-1/genetics , Heme Oxygenase-1/metabolism , Humans , Lipoproteins, LDL/metabolism , NF-E2-Related Factor 2/metabolism , NFI Transcription Factors/metabolism , NFI Transcription Factors/pharmacology , Oxidative Stress , Signal TransductionABSTRACT
Herein, we develop a novel strategy for preparing all-inorganic cesium lead halide (CsPbX3, X = Cl, Br, I) perovskite nanocrystals (NCs)@Zn-based metal-organic framework (MOF) composites through interfacial synthesis. The successful embedding of fluorescent perovskite NCs in Zn-MOFs is due to thein situconfined growth, which is attributed to the re-nucleation of water-triggered phase transformation from Cs4PbBr6to CsPbBr3. The controllable synthesis of mixed-halide based composites with various emission wavelength can be achieved by adding the desired amount of halide (Cl or I) salts in the re-nucleation process. More importantly, the anion exchange reaction is inhibited among various composites with different halogen atoms by being trapped in MOFs. Besides, a white light-emitting diode (WLED) is produced using a blue LED chip with the green-emitting and red-emitting composites, which has a color coordinate of (0.3291, 0.3272) and a wide color gamut. This work provides a novel route to achieving perovskite NCs growth in MOFs, which also can be extended to the other NCs embedded in frames as well.
ABSTRACT
Emerging evidence indicates that circular RNA (circRNA) is implicated in the development of atherosclerosis (AS). This study investigated the effect of circ_0003204 on endothelial cell function and explored the functional mechanism of circ_0003204 in AS progression. AS cell models were constructed by treating human umbilical vein endothelial cells (HUVEC) with oxidized low-density lipoprotein (ox-LDL). The expression of circ_0003204 was detected by quantitative real-time PCR (qPCR). The releases of pro-inflammatory factors were determined by ELISA. Cell viability was checked by CCK-8 assay. Cell apoptosis was monitored by flow cytometry assay. The ability of angiogenesis was assessed by tube formation assay. The protein levels of cell development- and apoptosis-related markers were measured by western blot. The binding relationship between miR-491-5p and circ_0003204 or intercellular adhesion molecule 1 (ICAM1) was verified by dual-luciferase reporter assay or RIP assay. The expression of circ_0003204 was strengthened in ox-LDL-treated HUVECs. Circ_0003204 knockdown inhibited ox-LDL-induced inflammation and cell apoptosis, and promoted ox-LDL-depleted cell viability and tube formation ability in HUVECs. MiR-491-5p was a target of circ_0003204, and miR-491-5p directly bound to ICAM1 3'UTR. Accordingly, circ_0003204 positively regulated ICAM1 expression by targeting miR-491-5p. Rescue experiments presented that miR-491-5p inhibition reversed the effects of circ_0003204 knockdown, and ICAM1 overexpression abolished the effects of miR-491-5p restoration. Circ_0003204 knockdown protects HUVECs against ox-LDL-induced injuries by targeting the miR-491-5p-ICAM1 pathway, hinting that circ_0003204 inhibition might prevent AS development.