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Cardioprotective effect of prostaglandin-E2 receptor-4 (EP4) stimulation on the ischemic heart has been demonstrated. Its effect on the heart affected by myocarditis, however, remains uncertain. In this study, we investigated therapeutic effect of EP4 stimulant using a mouse model of autoimmune myocarditis (EAM) that progresses to dilated cardiomyopathy (DCM). EP4 was present in the hearts of EAM mice. Treatment with EP4 agonist (ONO-0260164: 20 mg/kg/day) improved an impaired left ventricular (LV) contractility and reduction of blood pressure on day 21, a peak myocardial inflammation. Alternatively, DCM phenotype, characterized by LV dilation, LV systolic dysfunction, and collagen deposition, without inflammatory profiles was observed on day 56, along with activation of matrix metalloproteinase (MMP) 2 critical for myocardial extracellular matrix disruption, indicating an important molecular mechanism underlying adverse ventricular remodeling after myocarditis. Continued treatment with ONO-0260164 alleviated the DCM phenotype, but this effect was counteracted by its combination with a EP4 antagonist. Moreover, ONO-0260164 inhibited in vivo proteolytic activity of MMP2 in association with up-regulation of tissue inhibitor of metalloproteinase (TIMP)-3. EP4 stimulant may be a promising and novel therapeutic agent that rescues cardiac malfunction during myocarditis and prevents adverse ventricular remodeling after myocarditis by promoting the TIMP3/MMP2 axis.

Therapeutic efficacy of steroids on acute respiratory distress syndrome (ARDS) requiring mechanical ventilation (MV) has been reported. However, predictive indicators of early weaning from MV in such cases have not yet been defined. Our aim was to clarify clinical utility of interleukin (IL)-6 level in ventilated patients with established ARDS. Clinical, treatment, and outcome data were evaluated in 119 invasively ventilated patients with ARDS caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Plasma levels of IL-6 and C-reactive protein (CRP) were measured on days 1, 4, and 7 after intubation. Fifty-two patients received dexamethasone (steroid group) and the remaining 67 did not (non-steroid group). Duration of MV use was significantly shorter in the steroid group compared to non-steroid group (11.5±0.6 vs. 16.1±1.0 days, P = 0.0005, respectively). Even when restricted to the steroid group, among the post-MV variables, the IL-6 level on day 7 was most closely correlated with the duration of MV use and showed the highest accuracy for withdrawal from MV within 11 days (AUC: 0.88), with optimal cutoff value of 20.6 pg/mL. Collectively, in intubated patients with ARDS due to SARS-CoV-2 who received dexamethasone, plasma IL-6 levels served as a predictor of early withdrawal from MV.

BackgroundTherapeutic effects of steroids on acute respiratory distress syndrome (ARDS) requiring mechanical ventilation (MV) have been reported. However, predictive indicators of early weaning from MV post-treatment have not yet been defined, making treating established ARDS challenging. Interleukin (IL)-6 has been associated with the pathogenesis of ARDS.ObjectiveOur aim was to clarify clinical utility of IL-6 level in ventilated patients with established ARDS.MethodsClinical, treatment, and outcome data were evaluated in 119 invasively ventilated patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-mediated ARDS. Plasma levels of IL-6 and C-reactive protein (CRP) were measured on days 1, 4, and 7 after intubation.ResultsFifty-two patients were treated with dexamethasone (steroid group), while the remaining 67 patients were not (non-steroid group). Duration of MV use was significantly shorter in the steroid group compared to non-steroid group (11.5±0.6 vs. 16.1±1.0 days, P = 0.0005, respectively) along with significantly decreased levels of IL-6 and CRP. Even when restricted to the steroid group, among variables post-MV, IL-6 level on day 7 was most closely correlated with duration of MV use (Spearman’s rank correlation coefficient [ρ] = 0.73, P < 0.0001), followed by CRP level on day 7 and the percentage change in IL-6 or CRP levels between day 1 and day 7. Moreover, among these variables, IL-6 levels on day 7 showed the highest accuracy for withdrawal from MV within 11 days (AUC: 0.88), with optimal cutoff value of 20.6 pg/mL. Consistently, the rate of MV weaning increased significantly earlier in patients with low IL-6 (≤ 20.6 pg/mL) than in those with high IL-6 (> 20.6 pg/mL) (log-rank test P < 0.0001).ConclusionsIn invasively ventilated patients with established ARDS due to SARS-CoV-2, plasma IL-6 levels served as a predictor of early withdrawal from MV after dexamethasone administration.

Background Prostaglandin E2 receptor 4 (EP4) plays a crucial role in inflammatory diseases. Inflammatory cardiomyopathy often leads to refractory heart failure. Purpose We aimed to evaluate the role of EP4 in the development of inflammatory cardiomyopathy. Methods Experimental autoimmune myocarditis (EAM) was induced by immunization with cardiac myosin in balb/c mice. EP4 selective antagonist (CJ-42794, Cayman Chemical: 30 mg/kg/day), EP4 selective agonist (20 mg/kg/day), both, or vehicle alone was daily administrated after the immunization. Cardiac function and dimensions were assessed by echocardiography. Blood pressure and heart rate were assessed with tail-cuff method. Cardiac inflammation and fibrosis were immunohistologically examined. Molecular examination was performed by RT-PCR and immunoblotting. Results Cardiac dysfunction and dilatation were worsened on day 21 in EP4 antagonist-treated group compared with in the vehicle-treated group, accompanied by an increase in cellular infiltration area (21.7±1.9 vs. 11.0±2.7%, P=0.0367, respectively). Conversely, cardiac dysfunction and dilatation were improved in EP4 agonist-treated group compared with in the vehicle-treated group (Left ventricular fractional shortening: 69±3% vs. 40±4%, P Conclusions EP4 activation negatively regulated the induction of cardiac autoimmunity, which alleviated cardiac dysfunction, dilatation, and fibrosis. EP4 may be a therapeutic target for preventing the development of inflammatory cardiomyopathy. Funding Acknowledgement Type of funding sources: None.

Background: Coronavirus disease (COVID-19) pneumonitis associated with severe respiratory failure has a high mortality rate. Based on recent reports, the most severely ill patients present with coagulopathy, and disseminated intravascular coagulation (DIC)-like massive intravascular clot formation is frequently observed. Coagulopathy has emerged as a significant contributor to thrombotic complications. Although recommendations have been made for anticoagulant use for COVID-19, no guidelines have been specified.Case presentation: We describe four cases of critical COVID-19 with thrombosis detected by enhanced CT scan. The CT findings of all cases demonstrated typical findings of COVID-19 and pulmonary embolism or deep venous thrombus without critical exacerbation. Two patients died of respiratory failure due to COVID-19.Discussion: Previous reports have suggested coagulopathy with thrombotic signs as the main pathological feature of COVID-19, but no previous reports have focused on coagulopathy evaluated by whole-body enhanced CT scan. Changes in hemostatic biomarkers, represented by an increase in D-dimer and fibrin/fibrinogen degradation products, indicated that the essence of coagulopathy was massive fibrin formation. Although there were no clinical symptoms related to their prognosis, critical COVID-19-induced systemic thrombus formation was observed. Conclusions: Therapeutic dose anticoagulants should be considered for critical COVID-19 because of induced coagulopathy, and aggressive follow-up by whole body enhanced CT scan for systemic venous thromboembolism (VTE) is necessary.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has resulted in global pandemic. There is currently no effective therapeutic strategy for the management of mechanical ventilation or antiviral drugs for the treatment of this disease. As such, the development of a therapeutic strategy is urgently needed and should be established as soon as possible. In this case series, a therapeutic strategy was initially developed based on previous treatment methods used for the treatment of SARS and MERS in the absence of treatment options for COVID-19 due to a lack of information. During the search for a potential treatment, clinical findings were obtained from patients with severe COVID-19, and one therapeutic strategy was established. This therapeutic strategy was then applied to severe COVID-19 patients. In addition, we can require some interesting clinical features and characteristics of COVID-19 from blood analysis and physical findings. Here, we reported on the clinical features and characteristics of a therapeutic strategy for the treatment of severe COVID-19 pneumonia at our institution.

Background Although some predictors of COVID-19 pneumonia severity and mortality have been identified, much of the pathophysiology of this emerging infectious disease remains unclear. We hypothesized that a patient’s cholinesterase level on admission could predict COVID-19 pneumonia severity and mortality. Methods We retrospectively collected data of 26 COVID-19 pneumonia patients from February–May 2020. Outcomes were aggravation of symptoms and in-hospital mortality. We compared receiver operating curves of cholinesterase, C-reactive protein, lymphocytes, albumin, D-dimer, and PaO2/FiO2 ratio and examined prediction accuracy. Regarding the interaction between cholinesterase and other variables, each independent variable was divided into two groups using cutoff values, and interaction terms were created. Results Cholinesterase levels on admission were significantly lower in the severe group than in the mild-to-moderate group (326 vs. 218 IU/L, p = 0.006; area under the curve: 0.81; 95% confidence interval 0.61–0.94). When comparing the area under the curve, cholinesterase was comparable to C-reactive protein, albumin, lymphocytes, and PaO2/FiO2 ratio other than D-dimer in the prediction accuracy of severe cases and mortality. Cholinesterase levels on admission were significantly lower in the death group than in the survival group (274 vs. 187.5 IU/L, p = 0.028; area under the curve: 0.79; 95% interval 0.58–0.93). Regarding the interaction between cholinesterase and established predictors, the prediction accuracy of both severity and death was higher when cholinesterase was combined with each predictor than when cholinesterase was used alone. Conclusions Cholinesterase may reflect the disease state of COVID-19 pneumonia, suggesting that a patient’s cholinesterase level on admission may be useful as a predictor of severity and prognosis.

The ability to operate in a variety of environments is an important topic in humanoid robotics research. One of the ultimate goals of this research is smooth operation in everyday environments. However, movement in a real-world environment such as a family's house is challenging because the viscous friction and elasticity of each floor, which directly influence the robot's motion and are difficult to immediately measure, differ from place to place. There has been a lot of previous research into ways for the robots to recognize the environment. For instance, Fennema et al. (Fennema et al., 1987) and Yamamoto et al. (Yamamoto et al., 1999) proposed environment recognition methods based on range and visual information for wheeled robot navigation. Regarding humanoid robots, Kagami et al. (Kagami et al., 2003) proposed a method to generate motions for obstacle avoidance based on visual information. They measured features of the environment precisely before moving or fed back sensor information to a robot's controller with a short sampling period. It is still difficult to measure the viscous friction or elasticity of the floor before moving or by using short term sampling data, and they did not deal with such features. Thus, we propose a method for recognizing the features of environments and selecting appropriate behaviours based on the histories of simple sensor outputs, in order to achieve a humanoid robot able to move around a house. Figure 1 shows how our research differs from previous research according to length of the sensor history and number of types of sensors. The key idea of our method is to use a long sensor history to determine the features of the environment. To measure such features, almost all previous research (Shats et al., 1991; Holweg et al., 1996) proposed methods that used several kinds of sensors with a large amount of calculations to quickly process the sensor outputs. However, such approaches are unreasonable because the robot lacks sufficient space on its body for the attached sensors and processors. Hence we propose using sensor history to measure them because there are close relationships between sensor histories, motions, and environments. When the robot performs specific motions in specific environments, we can see those features in the sensor history that describe the motion and the environment. Furthermore, such features as viscous friction or floor elasticity do not change quickly. Thus we can use a long history of sensor data to measure them.