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Decidualization of the endometrial stromal cells (ESCs) is essential for successful embryo implantation. It involves the transformation of fibroblastic cells into epithelial-like cells that secrete cytokines, growth factors, and proteins necessary for implantation. Previous studies have revealed altered expression of miR-375 in the endometrium of patients with recurrent implantation failure and the ectopic stromal cells of patients with endometriosis. However, the exact molecular mechanisms, particularly the role of microRNAs (miRNAs) in the regulation of decidualization, remain elusive. In this study, we investigated whether decidualization is affected by miR-375 and its potential target(s). The findings demonstrated the downregulation of the expression of miR-375 in the secretory phase compared to its expression in the proliferative phase of the endometrium in normal donors. In contrast, it was upregulated in the secretory phase of the endometrium in infertility patients. Furthermore, during decidualization of ESCs in vitro, overexpression of miR-375 significantly reduced the transcript-level expression of forkhead box protein O1 (FOXO1), prolactin (PRL), and insulin-like growth factor binding protein-1 (IGFBP1), the well-known decidual cell markers. Overexpression of miR-375 also resulted in reduced decidualization-derived intracellular and mitochondrial reactive oxygen species (ROS) levels. Using the luciferase assay, we confirmed that NADPH oxidase 4 (NOX4) is a direct target of miR-375. Collectively, the study showed that the miR-375-mediated NOX4 downregulation reduced ROS production and attenuated the decidualization of ESCs. It provides evidence that miR-375 is a negative regulator of decidualization and could serve as a potential target for combating infertility.

Many researchers have suggested evaluation methods and Torsades de Pointes (TdP) metrics to assess the proarrhythmic risk of a drug based on the in silico simulation, as part of the Comprehensive in-vitro Proarrhythmia Assay (CiPA) project. In the previous study, we validated the robustness of 12 in silico features using the ordinal logistic regression (OLR) model by comparing the classification performances of metrics according to the in-vitro experimental datasets used; however, the OLR model using 12 in silico features did not provide desirable results. This study proposed a convolutional neural network (CNN) model using the variability of promising in silico TdP metrics hypothesizing that the variability of in silico features based on beats has more information than the single value of in silico features. We performed the action potential (AP) simulation using a human ventricular myocyte model to calculate seven in silico features representing the electrophysiological cell states of drug effects over 1,000 beats: qNet, qInward, intracellular calcium duration at returning to 50% baseline (CaD50) and 90% baseline (CaD90), AP duration at 50% repolarization (APD50) and 90% repolarization (APD90), and dVm/dtMax_repol. The proposed CNN classifier was trained using 12 train drugs and tested using 16 test drugs among CiPA drugs. The torsadogenic risk of drugs was classified as high, intermediate, and low risks. We determined the CNN classifier by comparing the classification performance according to the variabilities of seven in silico biomarkers computed from the in silico drug simulation using the Chantest dataset. The proposed CNN classifier performed the best when using qInward variability to classify the TdP-risk drugs with 0.94 AUC for high risk and 0.93 AUC for low risk. In addition, the final CNN classifier was validated using the qInward variability obtained after merging three in-vitro datasets, but the model performance decreased to a moderate level of 0.75 and 0.78 AUC. These results suggest the need for the proposed CNN model to be trained and tested using various types of drugs.

Action potential duration (APD) alternans, an alternating phenomenon between action potentials in cardiomyocytes, causes heart arrhythmia when the heart rate is high. However, some of the APD alternans observed in clinical trials occurs under slow heart rate conditions of 100 to 120 bpm, increasing the likelihood of heart arrhythmias such as atrial fibrillation. Advanced studies have identified the occurrence of this type of APD alternans in terms of electrophysiological ion channel currents in cells. However, they only identified physiological phenomena, such as action potential due to random changes in a particular ion channel’s conductivity through ion models specializing in specific ion channel currents. In this study, we performed parameter sensitivity analysis via population modeling using a validated human ventricular physiology model to check the sensitivity of APD alternans to ion channel conductances. Through population modeling, we expressed the changes in alternans onset cycle length (AOCL) and mean APD in AOCL (AO meanAPD) according to the variations in ion channel conductance. Finally, we identified the ion channel that maximally affected the occurrence of APD alternans. AOCL and AO meanAPD were sensitive to changes in the plateau Ca2+ current. Accordingly, it was expected that APD alternans would be vulnerable to changes in intracellular calcium concentration.

Endometrial receptivity is essential for successful pregnancy, and its impairment is a major cause of embryo-implantation failure. MicroRNAs (miRNAs) that regulate epigenetic modifications have been associated with endometrial receptivity. However, the molecular mechanisms whereby miRNAs regulate endometrial receptivity remain unclear. Therefore, we investigated whether miR-182 and its potential targets influence trophoblast cell attachment. miR-182 was expressed at lower levels in the secretory phase than in the proliferative phase of endometrium tissues from fertile donors. However, miR-182 expression was upregulated during the secretory phase in infertile women. Transfecting a synthetic miR-182-5p mimic decreased spheroid attachment of human JAr choriocarcinoma cells and E-cadherin expression (which is important for endometrial receptivity). miR-182-5p also downregulated N-Myc downstream regulated 1 (NDRG1), which was studied further. NDRG1 was upregulated in the secretory phase of the endometrium tissues and induced E-cadherin expression through the nuclear factor-κΒ (NF-κΒ)/zinc finger E-box binding homeobox 1 (ZEB1) signaling pathway. NDRG1-overexpressing or -depleted cells showed altered attachment rates of JAr spheroids. Collectively, our findings indicate that miR-182-5p-mediated NDRG1 downregulation impaired embryo implantation by upregulating the NF-κΒ/ZEB1/E-cadherin pathway. Hence, miR-182-5p is a potential biomarker for negative selection in endometrial receptivity and a therapeutic target for successful embryo implantation.

Since the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiation, many studies have suggested various in silico features based on ionic charges, action potentials (AP), or intracellular calcium (Ca) to assess proarrhythmic risk. These in silico features are computed through electrophysiological simulations using in vitro experimental datasets as input, therefore changing with the quality of in vitro experimental data; however, research to validate the robustness of in silico features for proarrhythmic risk assessment of drugs depending on in vitro datasets has not been conducted. This study aims to verify the availability of in silico features commonly used in assessing the cardiac toxicity of drugs through an ordinal logistic regression model and three in vitro datasets measured under different experimental environments and with different purposes. We performed in silico drug simulations using the Tomek-Ohara Rudy (ToR-ORD) ventricular myocyte model and computed 12 in silico features comprising six AP features, four Ca features, and two ion charge features, which reflected the effect and characteristics of each in vitro data for CiPA 28 drugs. We then compared the classific performances of ordinal logistic regressions according to these 12 in silico features and used in vitro datasets to validate which in silico feature is the best for assessing the proarrhythmic risk of drugs at high, intermediate, and low levels. All 12 in silico features helped determine high-risky torsadogenic drugs, regardless of the in vitro datasets used in the in silico simulation as input. In the three types of in silico features, AP features were the most reliable for determining the three Torsade de Pointes (TdP) risk standards. Among AP features, AP duration at 50% repolarization (APD50) was the best when individually using in silico features per in vitro dataset. In contrast, the AP repolarization velocity (dVm/dtMax_repol) was the best when merging all in silico features computed through three in vitro datasets.

The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) signal and the systolic peak of photoplethysmography (PPG) signal, is an indicator that enables noninvasive and continuous blood pressure estimation. However, it is difficult to accurately measure PAT from ECG and PPG signals because they have inconsistent shapes owing to patient-specific physical characteristics, pathological conditions, and movements. Accordingly, complex preprocessing is required to estimate blood pressure based on PAT. In this paper, as an alternative solution, we propose a noninvasive continuous algorithm using the difference between ECG and PPG as a new feature that can include PAT information. The proposed algorithm is a deep CNN–LSTM-based multitasking machine learning model that outputs simultaneous prediction results of systolic (SBP) and diastolic blood pressures (DBP). We used a total of 48 patients on the PhysioNet website by splitting them into 38 patients for training and 10 patients for testing. The prediction accuracies of SBP and DBP were 0.0 ± 1.6 mmHg and 0.2 ± 1.3 mmHg, respectively. Even though the proposed model was assessed with only 10 patients, this result was satisfied with three guidelines, which are the BHS, AAMI, and IEEE standards for blood pressure measurement devices.

Since the Comprehensive

Comprehensive in vitro Proarrhythmia Assay (CiPA) projects for assessing proarrhythmic drugs suggested a logistic regression model using qNet as the Torsades de Pointes (TdP) risk assessment biomarker, obtained from in silico simulation. However, using a single in silico feature, such as qNet, cannot reflect whole characteristics related to TdP in the entire action potential (AP) shape. Thus, this study proposed a deep convolutional neural network (CNN) model using differential action potential shapes to classify three proarrhythmic risk levels: high, intermediate, and low, considering both characteristics related to TdP not only in the depolarization phase but also the repolarization phase of AP shape. We performed an in silico simulation and got AP shapes with drug effects using half-maximal inhibitory concentration and Hill coefficients of 28 drugs released by CiPA groups. Then, we trained the deep CNN model with the differential AP shapes of 12 drugs and tested it with those of 16 drugs. Our model had a better performance for classifying the proarrhythmic risk of drugs than the traditional logistic regression model using qNet. The classification accuracy was 98% for high-risk level drugs, 94% for intermediate-risk level drugs, and 89% for low-risk level drugs.

Background and Objectives: This retrospective study evaluated the clinical impact of enhanced personal protective equipment (PPE) on the clinical outcomes in patients with out-of-hospital cardiac arrest. Moreover, by focusing on the use of a powered air-purifying respirator (PAPR), we investigated the medical personnel’s perceptions of wearing PAPR during cardiopulmonary resuscitation. Materials and Methods: According to the arrival time at the emergency department, the patients were categorized into a conventional PPE group (1 August 2019 to 20 January 2020) and an enhanced PPE group (21 January 2020, to 31 August 2020). The primary outcomes of this analysis were the return of spontaneous circulation (ROSC) rate. Additionally, subjective perception of the medical staff regarding the effect of wearing enhanced PPE during cardiopulmonary resuscitation (CPR) was evaluated by conducting a survey. Results: This study included 130 out-of-hospital cardiac arrest (OHCA) patients, with 73 and 57 patients in the conventional and enhanced PPE groups, respectively. The median time intervals to first intubation and to report the first arterial blood gas analysis results were longer in the enhanced PPE group than in the conventional PPE group (3 min vs. 2 min; p = 0.020 and 8 min vs. 3 min; p < 0.001, respectively). However, there were no significant differences in the ROSC rate (odds ratio (OR) = 0.79, 95% confidence interval (CI): 0.38–1.67; p = 0.542) and 1 month survival (OR 0.38, 95% CI: 0.07–2.10; p = 0.266) between the two groups. In total, 67 emergent department (ED) professionals responded to the questionnaire. Although a significant number of respondents experienced inconveniences with PAPR use, they agreed that PAPR was necessary during the CPR procedure for protection and reduction of infection transmission. Conclusion: The use of enhanced PPE, including PAPR, affected the performance of CPR to some extent but did not alter patient outcomes. PAPR use during the resuscitation of OHCA patients might positively impact the psychological stability of the medical staff.

Several lines of evidence indicated that generation of NADPH oxidase (Nox)-mediated reactive oxygen species are associated with neuronal inflammation, leading to Parkinson's disease (PD). Novel benzylidene-1-methyl-2-thioxoimidazolidin-one derivatives as Nox inhibitors were designed and synthesized in order to increase blood-brain barrier (BBB) permeability to target Nox in brain cells. In lucigenin chemiluminescence assay, eight compounds showed excellent inhibition activity against NADPH oxidases and parallel artificial membrane permeability assay (PAMPA) identified compound 11 with high passive permeability. To validate the effect of compound 11 on neuronal inflammation, we tested the regulatory activity of compound 11 in lipopolysaccharide (LPS)-induced production of pro-inflammatory cytokines in BV-2 microglial cells and LPS-mediated microglial migration. Treatment of BV2 cells with compound 11 resulted in suppressed production of pro-inflammatory cytokines and migration activity of BV2 cells in response to LPS. To evaluate the therapeutic efficacy of compound 11 in PD animal model, compound 11 was applied to MPTP-induced PD mouse model. Oral administration of compound 11 (30 mg/kg/daily, 4 weeks) into the mice resulted in suppression of dopaminergic neuronal death in substantia nigra (SN) and in striatum as well as inhibition of microglial migration into SN. These results implicate compound 11 as a novel therapeutic agent for the treatment of PD.

As part of the Comprehensive in vitro Proarrhythmia Assay initiative, methodologies for predicting the occurrence of drug-induced torsade de pointes via computer simulations have been developed and verified recently. However, their predictive performance still requires improvement. Herein, we propose an artificial neural networks (ANN) model that uses nine multiple input features, considering the action potential morphology, calcium transient morphology, and charge features to further improve the performance of drug toxicity evaluation. The voltage clamp experimental data for 28 drugs were augmented to 2,000 data entries using an uncertainty quantification technique. By applying these data to the modified O’Hara Rudy in silico model, nine features (dVm/dtmax, APresting, APD90, APD50, Caresting, CaD90, CaD50, qNet, and qInward) were calculated. These nine features were used as inputs to an ANN model to classify drug toxicity into high-risk, intermediate-risk, and low-risk groups. The model was trained with data from 12 drugs and tested using the data of the remaining 16 drugs. The proposed ANN model demonstrated an AUC of 0.92 in the high-risk group, 0.83 in the intermediate-risk group, and 0.98 in the low-risk group. This was higher than the classification performance of the method proposed in previous studies.

Osteoarthritis (OA) is an incurable joint disease affecting 240 million elderly population, and major unmet medical needs exist for better therapeutic options for OA. During skeletal development, Nkx3.2 has been shown to promote chondrocyte differentiation and survival, but to suppress cartilage hypertrophy and blood vessel invasion. Here we show that Nkx3.2 plays a key role in osteoarthritis (OA) pathogenesis. Marked reduction of Nkx3.2 expression was observed in three different murine OA models. Consistent with these findings, analyses of surgery-induced and age-driven OA models revealed that cartilage-specific post-natal induction of Nkx3.2 can suppress OA progression in mice. These results suggest that Nkx3.2 may serve as a promising target for OA drug development.

Successful embryo implantation is the first step for establishing natural pregnancy and is dependent on the crosstalk between the embryo and a receptive endometrium. However, the molecular signaling events for successful embryo implantation are not entirely understood. To identify differentially expressed transcripts [long-noncoding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs] and competing endogenous RNA (ceRNA) networks associated with endometrial receptivity, the current study analyzed gene expression profiles between proliferative and mid-secretory endometria in fertile women. A total of 247 lncRNAs, 67 miRNAs and 2,154 mRNAs were identified as differentially expressed between proliferative and mid-secretory endometria. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that these differentially expressed genes were significantly enriched for 'cell adhesion molecules.' Additionally, 98 common mRNAs were significantly involved in tryptophan metabolism, metabolic pathways and FoxO signaling. From the differentially expressed lncRNA/miRNA/mRNA ceRNA network, hub RNAs that formed three axes were identified: The DLX6-AS1/miR-141 or miR-200a/OLFM1 axis, the WDFY3-AS2/miR-135a or miR-183/STC1 axis, and the LINC00240/miR-182/NDRG1 axis. These may serve important roles in the regulation of endometrial receptivity. The hub network of the current study may be developed as a candidate marker for endometrial receptivity.

Many studies have revealed changes in specific protein channels due to physiological causes such as mutation and their effects on action potential duration changes. However, no studies have been conducted to predict the type of protein channel abnormalities that occur through an action potential (AP) shape. Therefore, in this study, we aim to predict the ion channel conductance that is altered from various AP shapes using a machine learning algorithm. We perform electrophysiological simulations using a single-cell model to obtain AP shapes based on variations in the ion channel conductance. In the AP simulation, we increase and decrease the conductance of each ion channel at a constant rate, resulting in 1,980 AP shapes and one standard AP shape without any changes in the ion channel conductance. Subsequently, we calculate the AP difference shapes between them and use them as the input of the machine learning model to predict the changed ion channel conductance. In this study, we demonstrate that the changed ion channel conductance can be predicted with high prediction accuracy, as reflected by an F1 score of 0.985, using only AP shapes and simple machine learning.

Methodologies for predicting the occurrence of torsade de pointes by drugs via computer simulations have been developed and verified recently, as part of the Comprehensive in vitro Proarrhythmia Assay initiative. However, the predictive performance still requires improvement. Herein, we propose a deep learning algorithm based on artificial neural networks that receives nine multiple features and ​considers the action potential morphology, calcium concentration morphology, and charge characteristics to further improve drug toxicity evaluation performance. The voltage clamp experimental data for 28 drugs were augmented to 2,000 data entries using an uncertainty quantification technique. By applying these data to the modified Ohara Rudy in silico model, nine features (dVm/dtmax, APresting, APD90, APD50, Caresting, CaD90, CaD50, qNet, and qInward) were predicted. These nine features were used as inputs to an artificial neural network (ANN) model to classify drug toxicity into high-risk, intermediate, and low-risk groups. The model was trained with data of 12 drugs and tested with the data of the remaining 16 drugs. The proposed ANN model demonstrated an AUC of 0.94 in the high-risk group, 0.73 in the intermediate group, and 0.91 in the low-risk group. This is higher than the classification performance of the method proposed in previous studies.

Natural killer (NK) cells are key immune cells engaged in fighting infection and malignant transformation. In this study, we found that canine NK cell-derived exosomes (NK-exosomes) separated from activated cytotoxic NK cell supernatants express specific markers including CD63, CD81, Alix, HSP70, TSG101, Perforin 1, and Granzyme B. We examined the antitumor effects of NK-exosomes in an experimental murine mammary tumor model using REM134 canine mammary carcinoma cell line. We observed changes in tumor size, tumor initiation, progression, and recurrence-related markers in the control, tumor group, and NK-exosome-treated tumor group. We found that the tumor size in the NK-exosome-treated tumor group decreased compared with that of the tumor group in the REM134-driven tumorigenic mouse model. We observed significant changes including the expression of tumorigenesis-related markers, such as B cell-specific Moloney murine leukemia virus insertion site 1 (Bmi-1), vascular endothelial growth factor (VEGF), matrix metallopeptidase-3 (MMP-3), interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF-α), multidrug resistance protein (MDR), tumor suppressor protein p53 (p53), proliferating cell nuclear antigen (PCNA), and the apoptotic markers, B cell lymphoma-2 associated X (Bax) and B cell lymphoma-extra large (Bcl-xL) belonging to the Bcl-2 family, in the tumor group compared with those in the control group. The expression of CD133, a potent cancer stem cell marker, was significantly higher than that of the control. By contrast, the NK-exosome-treated tumor group exhibited a significant reduction in Bmi-1, MMP-3, IL-1β, IL-6, TNF-α, Bax, Bcl-xL, and PCNA expression compared with that in the tumor group. Furthermore, the expression of CD133, which mediates tumorigenesis, was significantly decreased in the NK-exosome-treated tumor group compared with that in the tumor group. These findings indicate that canine NK-exosomes represent a promising therapeutic tool against canine solid tumors, including mammary carcinoma.

Ventricular fibrillation (VF) is a cardiovascular disease that is one of the major causes of mortality worldwide, according to the World Health Organization. Heart rate variability (HRV) is a biomarker that is used for detecting and predicting life-threatening arrhythmias. Predicting the occurrence of VF in advance is important for saving patients from sudden death. We extracted features from seven HRV data lengths to predict the onset of VF before nine different forecast times and observed the prediction accuracies. By using only five features, an artificial neural network classifier was trained and validated based on 10-fold cross-validation. Maximum prediction accuracies of 88.18% and 88.64% were observed at HRV data lengths of 10 and 20 s, respectively, at a forecast time of 0 s. The worst prediction accuracy was recorded at an HRV data length of 70 s and a forecast time of 80 s. Our results showed that features extracted from HRV signals near the VF onset could yield relatively high VF prediction accuracies.

In ventricular tachyarrhythmia, electrical instability features including action potential duration, dominant frequency, phase singularity, and filaments are associated with mechanical contractility. However, there are insufficient studies on estimated mechanical contractility based on electrical features during ventricular tachyarrhythmia using a stochastic model. In this study, we predicted cardiac mechanical performance from features of electrical instability during ventricular tachyarrhythmia simulation using machine learning algorithms, including support vector regression (SVR) and artificial neural network (ANN) models. We performed an electromechanical tachyarrhythmia simulation and extracted 12 electrical instability features and two mechanical properties, including stroke volume and the amplitude of myocardial tension (ampTens). We compared predictive performance according to kernel types of the SVR model and the number of hidden layers of the ANN model. In the SVR model, the prediction accuracies of stroke volume and ampTens were the highest when using the polynomial kernel and linear kernel, respectively. The predictive performance of the ANN model was better than that of the SVR model. The prediction accuracies were the highest when the ANN model consisted of three hidden layers. Accordingly, we propose the ANN model with three hidden layers as an optimal model for predicting cardiac mechanical contractility in ventricular tachyarrhythmia. The results of this study are expected to be used to indirectly estimate the hemodynamic response from the electrical cardiac map measured by the optical mapping system during cardiac surgery, as well as cardiac contractility under normal sinus rhythm conditions.

Mesenchymal stem cells (MSCs) possess the ability to differentiate into multiple cell lineages, and thus, confer great potential for use in regenerative medicine and biotechnology. In the present study, we attempted to isolate and characterize bovine tongue tissue epithelium-derived MSCs (boT-MSCs) and investigate the culture conditions required for long-term culturing of boT-MSCs. boT-MSCs were successfully isolated by the collagenase digestion method and their proliferative capacity was maintained for up to 20 or more passages. We observed a significant increase in the proliferation of boT-MSCs during the 20 consecutive passages under low-glucose Dulbecco’s modified Eagle’s medium culture condition among the three culture conditions. These boT-MSCs presented pluripotency markers (octamer-binding transcription factor 3/4 (Oct3/4) and sex determining region Y-box2 (Sox2)) and cell surface markers, which included CD13, CD29, CD44, CD73, CD90, CD105, CD166, and major histocompatibility complex (MHC) class I (MHC-I) but not CD11b, CD14, CD31, CD34, CD45, CD80, CD86, CD106, CD117, and MHC-II at third passage. Moreover, these boT-MSCs could differentiate into mesodermal (adipocyte, osteocyte, and chondrocyte) cell lineages. Thus, the present study suggests that the tongue of bovines could be used as a source of bovine MSCs.

Choi, J.U.; Lee, Y.G.; Jeong, D.U.; Choi, Y.H., and Woo, H.J., 2018. Effects of Abalone Farming Cage Removal on the Benthic Foraminiferal Assemblages. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 321–325. Coconut Creek (Florida), ISSN 0749-0208. To improve the aquaculture environment of an abalone farm near the Bogil Island, relocation was executed via the partial relocation of cages. The surface sediments were collected from nine stations to analyze the grain size, geochemical characteristics, and benthic foraminiferal assemblages in May (before) and August (after) 2015. Although no distinct environmental changes in the cage area were observed, the relocation area had an increased sand content caused by water circulation. In addition, despite the increase in the sediment temperature, the ignition loss decreased while the dissolved oxygen in the se...

There are representative electrical parameters for understanding the mechanism of reentrant waves in studies on tachyarrhythmia, namely the action potential duration (APD), dominant frequency, phase singularity, and filament. However, there are no studies that have directly identified the correlation between these electrophysiological parameters and cardiac contractility. Therefore, we have identified individual and integrative correlations between these electrical phenomena and contractility during tachyarrhythmia by deriving regression equations and also investigated the electrophysiological parameters affecting cardiac contractility during tachyarrhythmia. We simulated ventricular tachyarrhythmia with 48 types of electrical patterns by applying four reentry generation methods and changing the electrical conductivity of the potassium channel, which has the greatest effect on ventricular tissue. The mechanical responses reflecting electrical complexity were obtained through deterministic simulations of excitation–contraction coupling. We used the stroke volume and amplitude of myocardial tension (ampTens) as the variables representing contractility. We derived stochastic models through single- and multivariable regression analyses to identify the electrical parameters affecting contractility during tachyarrhythmia. In single-variable regression analysis, the APD, dominant frequency, and filament, excluding phase singularity, have statistically significant correlations with the stroke volume and ampTens. Among them, the APD has the maximum influence on these two mechanical parameters (standard beta coefficient: 0.859 for stroke volume, 0.930 for ampTens). The stochastic model using all four electrical parameters fails to accurately predict contractility owing to the multicollinearity between the APD and dominant frequency. We have rederived the multi-variable stochastic model using three electrical parameters without the APD. The filament has the greatest effect on the stroke volume stochastically (standard beta coefficient: 0.853 and 0.752). The dominant frequency has the greatest effect on ampTens statistically (standard beta coefficient: −0.813). We conclude that among the electrical parameters, the APD has the highest individual influence on mechanical contraction, and the filament has the highest integrative influence in both statistical terms.

Background Atrial arrhythmia is a cardiac disorder caused by abnormal electrical signaling and transmission, which can result in atrial fibrillation and eventual death. Genetic defects in ion channels can cause myocardial repolarization disorders. Arrhythmia-associated gene mutations, including KCNH2 gene mutations, which are one of the most common genetic disorders, have been reported. This mutation causes abnormal QT intervals by a gain of function in the rapid delayed rectifier potassium channel (IKr). In this study, we demonstrated that mutations in the KCNH2 gene cause atrial arrhythmia. Methods The N588K and L532P mutations were induced in the Courtemanche-Ramirez-Nattel (CRN) cell model, which was subjected to two-dimensional and three-dimensional simulations to compare the electrical conduction patterns of the wild-type and mutant-type genes. Results In contrast to the early self-termination of the wild-type conduction waveforms, the conduction waveform of the mutant-type retained the reentrant wave (N588K) and caused a spiral break-up, resulting in irregular wave generation (L532P). Conclusion The present study confirmed that the KCNH2 gene mutation increases the vulnerability of the atrial tissue for arrhythmia., Graphical Abstract

Background Atrial arrhythmia is a cardiac disorder caused by abnormal electrical signaling and transmission, which can result in atrial fibrillation and eventual death. Genetic defects in ion channels can cause myocardial repolarization disorders. Arrhythmia-associated gene mutations, including KCNH2 gene mutations, which are one of the most common genetic disorders, have been reported. This mutation causes abnormal QT intervals by a gain of function in the rapid delayed rectifier potassium channel (IKr). In this study, we demonstrated that mutations in the KCNH2 gene cause atrial arrhythmia. Methods The N588K and L532P mutations were induced in the Courtemanche-Ramirez-Nattel (CRN) cell model, which was subjected to two-dimensional and three-dimensional simulations to compare the electrical conduction patterns of the wild-type and mutant-type genes. Results In contrast to the early self-termination of the wild-type conduction waveforms, the conduction waveform of the mutant-type retained the reentrant wave (N588K) and caused a spiral break-up, resulting in irregular wave generation (L532P). Conclusion The present study confirmed that the KCNH2 gene mutation increases the vulnerability of the atrial tissue for arrhythmia.

The KCNJ2 gene mutations induce short QT syndrome (SQT3) by directly increasing the IK1 current. There have been many studies on the electrophysiological effects of mutations such as the KCNJ2 D172N that cause the SQT3. However, the KCNJ2 E299V mutation is distinguished from other representative gene mutations that can induce the short QT syndrome (SQT3) in that it increased IK1 current by impairing the inward rectification of K+ channels. The studies of the electromechanical effects on myocardial cells and mechanisms of E299V mutations are limited. Therefore, we investigated the electrophysiological changes and the concomitant mechanical responses according to the expression levels of the KCNJ2 E299V mutation during sinus rhythm and ventricular fibrillation. We performed excitation-contraction coupling simulations using a human ventricular model with both electrophysiological and mechanical properties. In order to observe the electromechanical changes due to the expression of KCNJ2 E299V mutation, the simulations were performed under normal condition (WT), heterogeneous mutation condition (WT/E299V), and pure mutation condition (E299V). First, a single-cell simulation was performed in three types of ventricular cells (endocardial cell, midmyocardial cell, and epicardial cell) to confirm the electrophysiological changes and arrhythmogenesis caused by the KCNJ2 E299V mutation. In three-dimensional sinus rhythm simulations, we compared electrical changes and the corresponding changes in mechanical performance caused by the expression level of E299V mutation. Then, we observed the electromechanical properties of the E299V mutation during ventricular fibrillation using the three-dimensional reentry simulation. The KCNJ2 E299V mutation accelerated the opening of the IK1 channel and increased IK1 current, resulting in a decrease in action potential duration. Accordingly, the QT interval was reduced by 48% and 60% compared to the WT condition, for the WT/E299V and E299V conditions, respectively. During sustained reentry, the wavelength was reduced due to the KCNJ2 E299V mutation. Furthermore, there was almost no ventricular contraction in both WT/E299V and E299V conditions. We concluded that in both sinus rhythm and fibrillation, the KCNJ2 E299V mutation results in very low contractility regardless of the expression level of mutation and increases the risk of cardiac arrest and cardiac death.

Spinal cord injury (SCI) results in permanent loss of motor and sensory function due to developmentally-related and injured-induced changes in the extrinsic microenvironment and intrinsic neuronal biochemistry that limit plasticity and axonal regeneration. Our long term goal is to develop cationic, amphiphilic copolymers (poly (lactide-co-glycolide)-g-polyethylenimine, PgP) for combinatorial delivery of therapeutic nucleic acids (TNAs) and drugs targeting these different barriers. In this study, we evaluated the ability of PgP to deliver siRNA targeting RhoA, a critical signaling pathway activated by multiple extracellular inhibitors of axonal regeneration. After generation of rat compression SCI model, PgP/siRhoA polyplexes were locally injected into the lesion site. Relative to untreated injury only, PgP/siRhoA polyplexes significantly reduced RhoA mRNA and protein expression for up to 4 weeks post-injury. Histological analysis at 4 weeks post-injury showed that RhoA knockdown was accompanied by reduced apoptosis, cavity size, and astrogliosis and increased axonal regeneration within the lesion site. These studies demonstrate that PgP is an efficient non-viral delivery carrier for therapeutic siRhoA to the injured spinal cord and may be a promising platform for the development of combinatorial TNA/drug therapy.

Tidal current survey as well as geochemical and benthic foraminiferal analyses of sediment cores were conducted in an abalone farm and a Zostera bed to understand the degree to which the abalone farm facilities installed along a channel in a shallow sea affect the benthic environment and ecology. In the abalone farm, Ammonia beccarii-Pseudoparrella naraensis-Elphidium somaense-Rosalina globularis-Trochammina hadai and P. naraensis-E. somaense-A. beccarii-T. hadai assemblages appeared owing to an increase in the total nitrogen content from the biodeposits. The Zostera bed consisted of A. beccarii-P. naraensis-Buccella frigida-T. hadai assemblage owing to the gradual expansion of a brackish shallow-water environment by the rapidly decreasing current speed, and it may have flourished. Moreover, the total sulfur, Zn, Cr, and Cu contents in the sediments decreased remarkably more than those of the pre-abalone farming did, caused by the vigorous activity of Zostera marina physiology.

Nkx3.2, the vertebrate homologue of Drosophila bagpipe, has been implicated as playing a role in chondrogenic differentiation. In brief, Nkx3.2 is initially expressed in chondrocyte precursor cells and later during cartilage maturation, its expression is diminished in hypertrophic chondrocytes. In addition to Nkx3.2 expression analyses, previous studies using ex vivo chick embryo cultures and in vitro cell cultures have suggested that Nkx3.2 can suppress chondrocyte hypertrophy. However, it has never been demonstrated that Nkx3.2 functions in regulating chondrocyte hypertrophy during cartilage development in vivo. Here, we show that cartilage-specific and Cre-dependent Nkx3.2 overexpression in mice results in significant postnatal dwarfism in endochondral skeletons, while intramembranous bones remain unaltered. Further, we observed significant delays in cartilage hypertrophy in conditional transgenic ciTg-Nkx3.2 mice. Together, these findings confirm that Nkx3.2 is capable of controlling hypertrophic maturation of cartilage in vivo, and this regulation plays a significant role in endochondral ossification and longitudinal bone growth. J. Cell. Physiol. 232: 78-90, 2017. © 2016 Wiley Periodicals, Inc.

Excessive and prolonged neuroinflammation leads to neuronal cell death and limits functional recovery after traumatic brain injury (TBI). Dexamethasone (DX) is a steroidal anti-inflammatory agent that is known to attenuate early expression of pro-inflammatory cytokines associated with activated microglia/macrophages. In this study, we investigated the effect of dexamethasone-conjugated hyaluronic acid (HA-DXM) incorporated in a hydrolytically degradable, photo-cross-linkable poly (ethylene) glycol-bis-(acryloyloxy acetate) (PEG-bis-AA) hydrogel on the inflammatory response, apoptosis, and functional recovery in a controlled cortical impact (CCI) rat TBI model. In vitro, DX release from PEG-bis-AA/HA-DXM hydrogel was slow in phosphate-buffered saline without enzymes, but significantly increased in the presence of hyauronidase/esterase enzymes. TBI was generated by a CCI device armed with a 3 mm tip (3.5 m s−1, depth: 2 mm) and treated immediately with PEG-bis-AA/HA-DXM hydrogel. PEG-bis-AA/HA hydrogel without DX was used for comparison and untreated TBI group was used as a control. Significant reductions in cavity size, inflammatory response, and apoptosis were observed in animals treated with PEG-bis-AA/HA-DXM compared to those receiving PEG-bis-AA/HA and untreated. Animals receiving the PEG-bis-AA/HA-DXM hydrogel also exhibited higher neuronal cell survival and improved motor functional recovery compared to the other two groups.

The KCNQ1 S140G mutation, which is involved in IKs current, affects atrial fibrillation. However, little is known about its effect on the mechanical behavior of the heart. Therefore, we assessed the influence of the KCNQ1 S140G mutation on ventricular electrophysiological stability and mechanical pumping performance using a multi-scale model of cardiac electromechanics. An image-based electromechanical model was used to assess the effect on electrical propagation and arrhythmogenesis of the KCNQ1 S140G mutation. In addition, it was used to compare the mechanical response under the wild-type (WT) and S140G mutation conditions. The intracellular calcium transient obtained from the electrophysiological model was applied as an input parameter to a mechanical model to implement excitation–contraction coupling. The IKs current equation was modified to account for expression of the KCNQ1 S140G mutation, and it included a scaling factor (ϕ) for mutant expressivity. The WT and S140G mutation conditions were compared at the single-cell and three-dimensional (3D) tissue levels. The action potential duration (APD) was reduced by 60% by the augmented IKs current under the S140G mutation condition, which resulted in shorter QT interval. This reduced the 3D sinus rhythm wavelength by 60% and the sustained re-entry by 56%. However, pumping efficiency of mutant ventricles was superior in sinus rhythm condition. In addition, the shortened wavelength in cardiac tissue allowed a re-entrant circuit to form and increased the probability of sustaining ventricular tachycardia and ventricular fibrillation. In contrast, under the WT condition, a normal wavelength (20.8 cm) was unlikely to initiate and sustain re-entry in the cardiac tissue. Subsequently, the S140G mutant ventricles developed a higher dominant frequency distribution range (2.0–5.3 Hz) than the WT condition (2.8–3.7 Hz). In addition, stroke volume of mutant ventricles was reduced by 65% in sustained re-entry compared to the WT condition. In conclusion, signs of the S140G mutation might be difficult to identify in sinus rhythm even though the mutant ventricles show shortened QT interval. This suggests that the KCNQ1 S140G mutation increases the risk of death by sudden cardiac arrest. In addition, the KCNQ1 S140G mutation can induce ventricular arrhythmia and lessen ventricular contractility under re-entrant conditions.

Analyses of the compositions of benthic foraminifera and sediment, observations of tidal level and salinity, and a geographic survey of the tidal salt marsh in Suncheon Bay were conducted to examine the vertical distribution of foraminifera and evaluate their potential use for sea level studies. The salt marsh is composed mainly of fine-grained silty clay sediment and its salinity is below approximately 11 psu. The tidal current flows in the southwest-tonortheast direction with an average velocity of 26.57 cm/s. A total of 33 species of foraminifera (17 agglutinated and 16 calcareoushyaline) belonging to 24 genera was identified. The species diversity (1.1 on average) was relatively low. Dominant species were Ammonia beccarii, Miliammina fusca, Haplophragmoides wilberti, and Jadammina macrescens. Calcareous foraminifera (29.5%) were dominantly represented by the Ammonia beccarii assemblage, which characterized the region between mean tide level and mean low high water (MLHW). Agglutinated species (70.5%) were represented mostly by Miliammina fusca, Miliammina fusca-Haplophragmoides wilberti, and Haplophragmoides wilberti assemblages, which characterized the MLHW–mean high water (MHW), MHW–mean highest high water (MHHW), and MHHW–Approx. highest high water tide levels, respectively. In particular, the Haplophragmoides wilberti assemblage is believed to represent the highest elevation zone of foraminifera in the salt marshes of Suncheon Bay and is considered to be a reliable indicator of sea level as a result of its narrow vertical range.

In this study, to improve the in vitro development of various cells including cloned embryos, the effects that isoproterenol and melatonin have on in vitro development of porcine parthenogenetic oocytes were investigated. Parthenogenetic activation was induced with electrical stimulation, BSA and 6-DMAP treatment. 10-7 M of melatonin and isoproterenol (10-10, 10-12 and 10-14 M) were supplemented for in vitro maturation (IVM) and in vitro culture (IVC) medium, with different concentrations. When isoproterenol and melatonin were supplemented in IVM medium with different concentrations, there was no significant (p