Hyperglycemia Altered the Fate of Cardiac Stem Cells to Adipogenesis through Inhibiting the β-Catenin/TCF-4 Pathway

Background/Aims: Hyperglycemia is an important risk factor for the most severe cardiovascular diseases in patients with diabetes. It has been demonstrated that cardiac stem cells (CSCs) play a pivotal role in the maintenance of cardiac homeostasis and regeneration. However, the mechanism underlying the influence of diabetes on CSCs remains unclear. This study demonstrated that hyperglycemia might promote adipogenesis in CSCs, which induces a decline in myocardial regeneration capability in diabetes. Methods: CSCs were isolated and cultured in high-glucose medium. The levels of β-catenin and TCF-4 in CSCs were determined by immunofluorescence staining and western blot analysis. Adipogenic transcriptional factors and CSCs markers were also examined by flow cytometry and western blot analysis after adipogenesis induction. In addition, Oil Red O staining was performed to investigate lipid droplet formation during adipogenesis induction with or without LiCl, a potent activator of TCF/β-catenin-dependent transcription. Results: High-glucose conditions inhibited nuclear translocation of β-catenin/TCF-4 and promoted adipogenesis in CSCs. After adipogenesis induction, expression of adipogenic transcriptional factors (PPARγ, ADD1, and C/EBPα) were increased (P < 0.01) and that of CSCs markers (c-Kit, Sca-1, MDR-1, and isl-1) were decreased (P< 0.01) in CSCs in the high-glucose group. Furthermore, lipid droplet formation was increased in CSCs cultured with high glucose, while LiCl attenuated lipid droplet formation in these CSCs (P < 0.01). Conclusion: These results demonstrated that hyperglycemia inhibited the β-catenin/TCF-4 pathway and promoted CSCs adipogenesis. Our findings suggest a new opportunity for future interventional strategie for abnormal myocardial regeneration and epicardial fat in patients with diabetes

Identification of diagnostic hub genes related to neutrophils and infiltrating immune cell alterations in idiopathic pulmonary fibrosis

BackgroundThere is still a lack of specific indicators to diagnose idiopathic pulmonary fibrosis (IPF). And the role of immune responses in IPF is elusive. In this study, we aimed to identify hub genes for diagnosing IPF and to explore the immune microenvironment in IPF.MethodsWe identified differentially expressed genes (DEGs) between IPF and control lung samples using the GEO database. Combining LASSO regression and SVM-RFE machine learning algorithms, we identified hub genes. Their differential expression were further validated in bleomycin-induced pulmonary fibrosis model mice and a meta-GEO cohort consisting of five merged GEO datasets. Then, we used the hub genes to construct a diagnostic model. All GEO datasets met the inclusion criteria, and verification methods, including ROC curve analysis, calibration curve (CC) analysis, decision curve analysis (DCA) and clinical impact curve (CIC) analysis, were performed to validate the reliability of the model. Through the Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm (CIBERSORT), we analyzed the correlations between infiltrating immune cells and hub genes and the changes in diverse infiltrating immune cells in IPF.ResultsA total of 412 DEGs were identified between IPF and healthy control samples, of which 283 were upregulated and 129 were downregulated. Through machine learning, three hub genes (ASPN, SFRP2, SLCO4A1) were screened. We confirmed their differential expression using pulmonary fibrosis model mice evaluated by qPCR, western blotting and immunofluorescence staining and analysis of the meta-GEO cohort. There was a strong correlation between the expression of the three hub genes and neutrophils. Then, we constructed a diagnostic model for diagnosing IPF. The areas under the curve were 1.000 and 0.962 for the training and validation cohorts, respectively. The analysis of other external validation cohorts, as well as the CC analysis, DCA, and CIC analysis, also demonstrated strong agreement. There was also a significant correlation between IPF and infiltrating immune cells. The frequencies of most infiltrating immune cells involved in activating adaptive immune responses were increased in IPF, and a majority of innate immune cells showed reduced frequencies.ConclusionOur study demonstrated that three hub genes (ASPN, SFRP2, SLCO4A1) were associated with neutrophils, and the model constructed with these genes showed good diagnostic value in IPF. There was a significant correlation between IPF and infiltrating immune cells, indicating the potential role of immune regulation in the pathological process of IPF

ATP-dependent dynamic protein aggregation regulates bacterial dormancy depth critical for antibiotic tolerance

Cell dormancy is a widespread mechanism used by bacteria to evade environmental threats including antibiotics. Here we monitored bacterial antibiotic tolerance and regrowth at the single-cell level and found that each individual survival cell shows different ‘dormancy depth’, which in return regulates the lag time for cell resuscitation after removal of antibiotic. We further established that protein aggresome - a collection of endogenous protein aggregates - is an important indicator of bacterial dormancy depth, whose formation is promoted by decreased cellular ATP level. For cells to leave the dormant state and resuscitate, clearance of protein aggresome and recovery of proteostasis are required. We revealed the ability to recruit functional DnaK-ClpB machineries, which facilitate protein disaggregation in an ATP-dependent manner, determines the lag time for bacterial regrowth. Better understanding of the key factors regulating bacterial regrowth after surviving antibiotic attack could lead to new therapeutic strategies for combating bacterial antibiotic tolerance

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

An Analog Baseband Circuit for Wireless Local Area Networks Transceiver in 55 nm CMOS Technology

The design of the analog baseband circuit is based on 55 nm CMOS technology and is integrated in an IEEE 802.11ax concurrent dual band four antenna transceiver. A low-pass filter (LPF) of the receiver was multiplexed with an LPF-transmitter such that the last three stages of the fifth order LPF-receiver were used by the LPF-transmitter, and the first programmable gain amplifier (PGA) of the receiver was partially multiplexed with the PGA-transmitter such that the PGA-receiver and the PGA-transmitter shared the same operational amplifier and input resistance, thereby reducing the power consumption, noise, linearity, and area of intermediate frequency (IF) of the transmitter designed separately. The typical bandwidth of the IF-receiver is 10/20/40 MHz; that of the IF-transmitter is 12/24/50 MHz. The gain range of the IF-receiver and the IF-transmitter is 0.1–65.5 dB and −10.1 to 3.98 dB, respectively. Under the voltage of 1.5 V, the current of the IF-receiver is 3.86 mA. As for the IF-transmitter, the current is 1.78 mA when supply voltage is 1.5 V. The input referred noise (IRN) of the IF-receiver at 10 MHz bandwidth (BW) and 62 dB gain is 14.52 nV/√ Hz, while the IRN of the IF-transmitter at 10 MHz BW and −6 dB gain is 95.16 nV/√ Hz. The suppression ability of the DC offset cancellation circuit is 35.08/80.9/110.1/113 dB. The area of the analog baseband circuit is 0.17 mm2