Functional enhancement of neuronal cell behaviors and differentiation by elastin-mimetic recombinant protein presenting Arg-Gly-Asp peptides

Background: Integrin-mediated interaction of neuronal cells with extracellular matrix (ECM) is important for the control of cell adhesion, morphology, motility, and differentiation in both in vitro and in vivo systems. Arg-Gly-Asp (RGD) sequence is one of the most potent integrin-binding ligand found in many native ECM proteins. An elastin-mimetic recombinant protein, TGPG[VGRGD(VGVPG)6]20WPC, referred to as [RGD-V6]20, contains multiple RGD motifs to bind cell-surface integrins. This study aimed to investigate how surface-adsorbed recombinant protein can be used to modulate the behaviors and differentiation of neuronal cells in vitro. For this purpose, biomimetic ECM surfaces were prepared by isothermal adsorption of [RGD-V6]20 onto the tissue culture polystyrene (TCPS), and the effects of protein-coated surfaces on neuronal cell adhesion, spreading, migration, and differentiation were quantitatively measured using N2a neuroblastoma cells.Results: The [RGD-V6]20 was expressed in E. coli and purified by thermally-induced phase transition. N2a cell attachment to either [RGD-V6]20 or fibronectin followed hyperbolic binding kinetics saturating around 2 μM protein concentration. The apparent maximum cell binding to [RGD-V6]20 was approximately 96% of fibronectin, with half-maximal adhesion on [RGD-V6]20 and fibronectin occurring at a coating concentration of 2.4 × 10-7 and 1.4 × 10-7 M, respectively. The percentage of spreading cells was in the following order of proteins: fibronectin (84.3% ± 6.9%) > [RGD-V6]20 (42.9% ± 6.5%) > [V7]20 (15.5% ± 3.2%) > TCPS (less than 10%). The migration speed of N2a cells on [RGD-V6]20 was similar to that of cells on fibronectin. The expression of neuronal marker proteins Tuj1, MAP2, and GFAP was approximately 1.5-fold up-regulated by [RGD-V6]20 relative to TCPS. Moreover, by the presence of both [RGD-V6]20 and RA, the expression levels of NSE, TuJ1, NF68, MAP2, and GFAP were significantly elevated.Conclusion: We have shown that an elastin-mimetic protein consisting of alternating tropoelastin structural domains and cell-binding RGD motifs is able to stimulate neuronal cell behaviors and differentiation. In particular, adhesion-induced neural differentiation is highly desirable for neural development and nerve repair. In this context, our data emphasize that the combination of biomimetically engineered recombinant protein and isothermal adsorption approach allows for the facile preparation of bioactive matrix or coating for neural tissue regeneration. © 2012 Jeon et al.; licensee BioMed Central Ltd.1

Clinical outcomes in patients with persistent atrial fibrillation after technologic advances including contact force-guided and ablation index-guided ablation

We aimed to evaluate the influence of technological advances on ablation outcomes in patients with persistent atrial fibrillation (AF) (PeAF). Radiofrequency ablation for patients with AF has advanced, including contact force (CF)-sensing catheters and the ablation index (AI). Between 2009 and 2018, we analyzed 173 patients with PeAF who underwent catheter ablation. We categorized them into three groups: AF ablation without CF and AI information (no-CF group, n = 63), with CF without AI (CF-only group, n = 49), and with optimal AI-guided ablation (AI group, n = 61). Early (within 3months, ER) and late (from 3months to 1year, LR) AF recurrence after ablation was assessed. Procedure-related complications were also evaluated. The baseline characteristics were similar among the 3 groups, excluding the baseline antiarrhythmic drug history. Additional substrate modification after pulmonary vein isolation was significantly low in frequency in the AI group (71.4%, no-CF; 69.4%, CF-only; 41.0%, AI, p = 0.001). The AI group had a shorter mean procedure-related time than the other groups. Both ER and LR of PeAF showed a trend of reduction with technological advances. With a short experience (less than 1year), the CF-only group showed more ER and LR than that shown by the AI group. However, with a long experience (more than 1year), ER and LR occurred similarly in the two groups. Procedure-related complications improved with technological advances. As ablation technology advanced, favorable clinical outcomes with short procedural times were observed. However, prospective, large multicenter studies are needed to verify these results.This work was supported by the Korea Medical Device Development Fund grant funded by the Korean Government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, Republic of Korea, the Ministry of Food and Drug Safety) (Project Number: 202013B14) and by the Korea National Research Foundation funded by the Ministry of Education, Science and Technology (Grant 2020R1F1A106740)

An Arrhythmia Classification-Guided Segmentation Model for Electrocardiogram Delineation

Accurate delineation of key waveforms in an ECG is a critical initial step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using a segmentation model to locate P, QRS and T waves have shown promising results, their ability to handle signals exhibiting arrhythmia remains unclear. In this study, we propose a novel approach that leverages a deep learning model to accurately delineate signals with a wide range of arrhythmia. Our approach involves training a segmentation model using a hybrid loss function that combines segmentation with the task of arrhythmia classification. In addition, we use a diverse training set containing various arrhythmia types, enabling our model to handle a wide range of challenging cases. Experimental results show that our model accurately delineates signals with a broad range of abnormal rhythm types, and the combined training with classification guidance can effectively reduce false positive P wave predictions, particularly during atrial fibrillation and atrial flutter. Furthermore, our proposed method shows competitive performance with previous delineation algorithms on the Lobachevsky University Database (LUDB)

Roles of peroxiredoxin II in the regulation of proinflammatory responses to LPS and protection against endotoxin-induced lethal shock

Mammalian 2-Cys peroxiredoxin II (Prx II) is a cellular peroxidase that eliminates endogenous H2O2. The involvement of Prx II in the regulation of lipopolysaccharide (LPS) signaling is poorly understood. In this report, we show that LPS induces substantially enhanced inflammatory events, which include the signaling molecules nuclear factor κB and mitogen-activated protein kinase (MAPK), in Prx II–deficient macrophages. This effect of LPS was mediated by the robust up-regulation of the reactive oxygen species (ROS)–generating nicotinamide adenine dinucleotide phosphate (NADPH) oxidases and the phosphorylation of p47phox. Furthermore, challenge with LPS induced greater sensitivity to LPS-induced lethal shock in Prx II–deficient mice than in wild-type mice. Intravenous injection of Prx II–deficient mice with the adenovirus-encoding Prx II gene significantly rescued mice from LPS-induced lethal shock as compared with the injection of a control virus. The administration of catalase mimicked the reversal effects of Prx II on LPS-induced inflammatory responses in Prx II–deficient cells, which suggests that intracellular H2O2 is attributable, at least in part, to the enhanced sensitivity to LPS. These results indicate that Prx II is an essential negative regulator of LPS-induced inflammatory signaling through modulation of ROS synthesis via NADPH oxidase activities and, therefore, is crucial for the prevention of excessive host responses to microbial products

Mycobacterium tuberculosis Eis Regulates Autophagy, Inflammation, and Cell Death through Redox-dependent Signaling

The “enhanced intracellular survival” (eis) gene of Mycobacterium tuberculosis (Mtb) is involved in the intracellular survival of M. smegmatis. However, its exact effects on host cell function remain elusive. We herein report that Mtb Eis plays essential roles in modulating macrophage autophagy, inflammatory responses, and cell death via a reactive oxygen species (ROS)-dependent pathway. Macrophages infected with an Mtb eis-deletion mutant H37Rv (Mtb-Δeis) displayed markedly increased accumulation of massive autophagic vacuoles and formation of autophagosomes in vitro and in vivo. Infection of macrophages with Mtb-Δeis increased the production of tumor necrosis factor-α and interleukin-6 over the levels produced by infection with wild-type or complemented strains. Elevated ROS generation in macrophages infected with Mtb-Δeis (for which NADPH oxidase and mitochondria were largely responsible) rendered the cells highly sensitive to autophagy activation and cytokine production. Despite considerable activation of autophagy and proinflammatory responses, macrophages infected with Mtb-Δeis underwent caspase-independent cell death. This cell death was significantly inhibited by blockade of autophagy and c-Jun N-terminal kinase-ROS signaling, suggesting that excessive autophagy and oxidative stress are detrimental to cell survival. Finally, artificial over-expression of Eis or pretreatment with recombinant Eis abrogated production of both ROS and proinflammatory cytokines, which depends on the N-acetyltransferase domain of the Eis protein. Collectively, these data indicate that Mtb Eis suppresses host innate immune defenses by modulating autophagy, inflammation, and cell death in a redox-dependent manner

Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives

Gene expression profiling technologies have been used in various applications such as cancer biology. The development of gene expression profiling has expanded the scope of target discovery in transcriptomic studies, and each technology produces data with distinct characteristics. In order to guarantee biologically meaningful findings using transcriptomic experiments, it is important to consider various experimental factors in a systematic way through statistical power analysis. In this paper, we review and discuss the power analysis for three types of gene expression profiling technologies from a practical standpoint, including bulk RNA-seq, single-cell RNA-seq, and high-throughput spatial transcriptomics. Specifically, we describe the existing power analysis tools for each research objective for each of the bulk RNA-seq and scRNA-seq experiments, along with recommendations. On the other hand, since there are no power analysis tools for high-throughput spatial transcriptomics at this point, we instead investigate the factors that can influence power analysis

Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives

Gene expression profiling technologies have been used in various applications such as cancer biology. The development of gene expression profiling has expanded the scope of target discovery in transcriptomic studies, and each technology produces data with distinct characteristics. In order to guarantee biologically meaningful findings using transcriptomic experiments, it is important to consider various experimental factors in a systematic way through statistical power analysis. In this paper, we review and discuss the power analysis for three types of gene expression profiling technologies from a practical standpoint, including bulk RNA-seq, single-cell RNA-seq, and high-throughput spatial transcriptomics. Specifically, we describe the existing power analysis tools for each research objective for each of the bulk RNA-seq and scRNA-seq experiments, along with recommendations. On the other hand, since there are no power analysis tools for high-throughput spatial transcriptomics at this point, we instead investigate the factors that can influence power analysis