Finding line of action of the force exerted on erect spine based on lateral bending test in personalization of scoliotic spine models

In multi-body models of scoliotic spine, personalization of mechanical properties of joints significantly improves reconstruction of the spine shape. In personalization methods based on lateral bending test, simulation of bending positions is an essential step. To simulate, a force is exerted on the spine model in the erect position. The line of action of the force affects the moment of the force about the joints and thus, if not correctly identified, causes over/underestimation of mechanical properties. Therefore, we aimed to identify the line of action, which has got little attention in previous studies. An in-depth analysis was performed on the scoliotic spine movement from the erect to four spine positions in the frontal plane by using pre-operative X-rays of 18 adolescent idiopathic scoliosis (AIS) patients. To study the movement, the spine curvature was considered as a 2D chain of micro-scale motion segments (MMSs) comprising rigid links and 1-degree-of-freedom (DOF) rotary joints. It was found that two MMSs representing the inflection points of the erect spine had almost no rotation (0.0028° ± 0.0021°) in the movement. The small rotation can be justified by weak moment of the force about these MMSs due to very small moment arm. Therefore, in the frontal plane, the line of action of the force to simulate the left/right bending position was defined as the line that passes through these MMSs in the left/right bending position. Through personalization of a 3D spine model for our patients, we demonstrated that our line of action could result in good estimates of the spine shape in the bending positions and other positions not included in the personalization, supporting our proposed line of action.     

Uridine diphosphate–glucose/P2Y14R axis is a nonchemokine pathway that selectively promotes eosinophil accumulation

Allergic asthma is a chronic inflammatory airway disease characterized by dysregulated type 2 immune responses, including degranulating airway eosinophils that induce tissue damage and airway hyperresponsiveness (AHR). The type 2 cytokines interleukin 5 (IL-5) and IL-13 and the eosinophil-specific chemokine CCL11/CCL24/CCL26 axis recruit, activate, and regulate eosinophils in the airways. In this issue of the JCI, Karcz et al. identified a mechanism involving the nucleotide sugar UDP-glucose (UDP-G) and the purinergic receptor P2Y₁₄R in amplifying eosinophil accumulation in the lung. During type 2 inflammation, UDP-G activates P2Y₁₄R on eosinophils, inducing the cells to move and migrate into the lung. Pharmacologically or genetically inhibiting P2Y₁₄R on eosinophils attenuated eosinophil infiltration and AHR. Future experiments, including identifying additional type 2 factors regulating P2Y₁₄R expression on lung eosinophils, are necessary to ascertain the impact of targeting P2Y₁₄R as an alternative or adjunctive therapy to current type 2 biologics for the treatment of asthma.     

Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score

ABSTRACT: INTRODUCTION: A key aim of triage is to identify those with high risk of cardiac arrest, as they require intensive monitoring, resuscitation facilities, and early intervention. We aim to validate a novel machine learning (ML) score incorporating heart rate variability (HRV) for triage of critically ill patients presenting to the emergency department by comparing the area under the curve, sensitivity and specificity with the modified early warning score (MEWS). METHODS: We conducted a prospective observational study of critically ill patients (Patient Acuity Category Scale 1 and 2) in an emergency department of a tertiary hospital. At presentation, HRV parameters generated from a 5-minute electrocardiogram recording are incorporated with age and vital signs to generate the ML score for each patient. The patients are then followed up for outcomes of cardiac arrest or death. RESULTS: From June 2006 to June 2008 we enrolled 925 patients. The area under the receiver operating characteristic curve (AUROC) for ML scores in predicting cardiac arrest within 72 hours is 0.781, compared with 0.680 for MEWS (difference in AUROC: 0.101, 95% confidence interval: 0.006 to 0.197). As for in-hospital death, the area under the curve for ML score is 0.741, compared with 0.693 for MEWS (difference in AUROC: 0.048, 95% confidence interval: -0.023 to 0.119). A cutoff ML score ≥ 60 predicted cardiac arrest with a sensitivity of 84.1%, specificity of 72.3% and negative predictive value of 98.8%. A cutoff MEWS ≥ 3 predicted cardiac arrest with a sensitivity of 74.4%, specificity of 54.2% and negative predictive value of 97.8%. CONCLUSION: We found ML scores to be more accurate than the MEWS in predicting cardiac arrest within 72 hours. There is potential to develop bedside devices for risk stratification based on cardiac arrest prediction.     

Motion correction and frequency stabilization for MRS of the human spinal cord

Subject motion is challenging for MRS, because it can falsify results. For spinal cord MRS in particular, subject movement is critical, since even a small movement > 1 mm) can lead to a voxel shift out of the desired measurement region. Therefore, the identification of motion corrupted MRS scans is essential. In this investigation, MR navigators acquired simultaneously with the MRS data are used to identify a displacement of the spinal cord due to subject motion. It is shown that navigators are able to recognize substantial subject motion (>1 mm) without impairing the MRS measurement. In addition, navigators are easy to apply to the measurement, because no additional hardware and just a minor additional user effort are needed. Moreover, no additional scan time is required, because navigators can be applied in the deadtime of the MRS sequence. Furthermore, in this work, retrospective motion correction combined with frequency stabilization is presented by combining navigators with non‐water‐suppressed ¹H‐MRS, resulting in an improved spectral quality of the spinal cord measurements. Copyright © 2016 John Wiley & Sons, Ltd.     

Three-dimensional asymmetrical modeling of the mitral valve: a finite element study with dynamic boundaries

BACKGROUND AND AIM OF THE STUDY: Previous computational studies of the normal mitral valve have been limited because they assumed symmetrical modeling and artificial boundary conditions. The study aim was to model the mitral valve complex asymmetrically with three-dimensional (3-D) dynamic boundaries obtained from in-vivo experimental data. METHODS: Distance tracings between ultrasound crystals placed in the sheep mitral valve were converted into 3-D coordinates to reconstruct an initial asymmetric mitral model and subsequent dynamic boundary conditions. The non-linear, real-time left ventricular and aortic pressure loads were acquired synchronously. A quasi-static solution was applied over one cardiac cycle. RESULTS: The mitral valve leaflet stress was heterogeneous. The trigones experienced highest stresses, while the mid-anterior annulus between trigones experienced low stress. High leaflet stress was observed during peak pressure loading. During isovolumic relaxation, the leaflets were highly stretched between the anterolateral trigone and the posteromedial commissure, resulting in a prominent secondary leaflet stress re-increment. This has not been observed previously, as symmetric models with artificial boundary conditions were studied only in the ejection phase. CONCLUSION: Here, the first asymmetrical mitral valve model synchronized with 3-D dynamic boundaries and non-linear pressure loadings over the whole cardiac cycle based on in vivo experimental data is described. Despite its limitations, this model provides new insights into the distribution of leaflet stress in the mitral valve.     

Activated protein C induces the release of microparticle-associated endothelial protein C receptor

Activated protein C (APC) treatment is now used for patients with severe sepsis. We investigated its effect in vitro on primary, physiologically relevant cells and demonstrate a novel mechanism of endothelial protein C receptor (EPCR) release that is not inhibited by metalloproteinase inhibitors. Exposure of human umbilical vein endothelial cells or monocytes to APC (6.25-100 nM) results in the release of EPCR-containing microparticles, as demonstrated by confocal microscopy and characterized through flow cytometry, enzyme-linked immunosorbent assay quantitation of isolated microparticles, and Western blotting. The phenomenon is time- and concentration-dependent and requires the APC active site, EPCR, and protease activated receptor 1 (PAR1) on endothelial cells. Neither protein C nor boiled or D-Phe-Pro-Arg-chloromethylketone-blocked APC can induce microparticle formation and antibody blockade of EPCR or PAR1 cleavage and activation abrogates this APC action. Coincubation with hirudin does not alter the APC effect. The released microparticle bound is full-length EPCR (49 kDa) and APC retains factor V-inactivating activity. Although tumor necrosis factor-alpha (10 ng/mL) can also induce microparticle-associated EPCR release to a similar extent as APC (100 nM), it is only APC-induced microparticles that contain bound APC. This novel observation could provide new insights into the consequences of APC therapy in the septic patient.