We investigate the mass-radius relation of neutron star (NS) with hyperons inside its core by using the Eddington-inspired Born-Infeld (EiBI) theory of gravity. The equation of state of the star is calculated by using the relativistic mean field model under which the standard SU(6) prescription and hyperons potential depths are used to determine the hyperon coupling constants. We found that, for 4×10 6 m 2 κ 6×10 6 m 2 , the corresponding NS mass and radius predicted by the EiBI theory of gravity is compatible with observational constraints of maximum NS mass and radius. The corresponding κ value is also compatible with the κ range predicted by the astrophysical-cosmological constraints. We also found that the parameter κ could control the size and the compactness of a neutron star.
Abstract. We propose the disappearance of "the hyperon puzzle" in neutron star (NS) by invoking two new-physics prescriptions: modified gravity theory and braneworld scenario. By assuming that NS lives on a 3-brane within a 5d empty AdS bulk, gravitationally governed by Eddington-inspired Born-Infeld (EiBI) theory, the field equations can be effectively cast into the usual Einstein's with "apparent" anisotropic energy-momentum tensor. Solving the corresponding brane-TOV equations numerically, we study its mass-radius relation. It is known that the appearance of finite brane tension λ reduces the compactness of the star. The compatibility of the braneworld results with observational constraints of NS mass and radius can be restored in our model by varying the EiBI's coupling constant, κ. We found that within the astrophysically-accepted range of parameters (0 < κ < 6 × 10 6 m 2 and λ 1 MeV 4 ) the NS can have mass ∼ 2.1 M and radius ∼ 10 km.
We investigate the effect of the inclusion of relativistic Coulomb terms in a confined-isospindensity-dependent-mass (CIDDM) model of strange quark matter (SQM). We found that if we include Coulomb term in scalar density form, SQM equation of state (EOS) at high densities is stiffer but if we include Coulomb term in vector density form is softer than that of standard CIDDM model. We also investigate systematically the role of each term of the extended CIDDM model. Compared with what was reported in Ref. [14], we found the stiffness of SQM EOS is controlled by the interplay among the the oscillator harmonic, isospin asymmetry and Coulomb contributions depending on the parameter's range of these terms. We have found that the absolute stable condition of SQM and the mass of 2 M⊙ pulsars can constrain the parameter of oscillator harmonic κ1 ≈ 0.53 in the case Coulomb term excluded. If the Coulomb term is included, for the models with their parameters are consistent with SQM absolute stability condition, the 2.0 M⊙ constraint more prefer the maximum mass prediction of model with scalar Coulomb term than that of model with vector Coulomb term. On contrary, the high densities EOS predicted by model with vector Coulomb is more compatible with recent pQCD result [19] than that predicted by model with scalar Coulomb. Furthermore, we also observed the quark composition in a very high density region depends quite sensitively on the kind of Coulomb term used.
It is well known that cardiac electromechanical delay (EMD) can cause dyssynchronous heart failure (DHF), a prominent cardiovascular disease (CVD). This work computationally assesses the conductance variation of every ion channel on the cardiac cell to give rise to EMD prolongation. The electrical and mechanical models of human ventricular tissue were simulated, using a population approach with four conductance reductions for each ion channel. Then, EMD was calculated by determining the difference between the onset of action potential and the start of cell shortening. Finally, EMD data were put into the optimized conductance dimensional stacking to show which ion channel has the most influence in elongating the EMD. We found that major ion channels, such as L-type calcium (CaL), slow-delayed rectifier potassium (Ks), rapid-delayed rectifier potassium (Kr), and inward rectifier potassium (K1), can significantly extend the action potential duration (APD) up to 580 ms. Additionally, the maximum intracellular calcium (Cai) concentration is greatly affected by the reduction in channel CaL, Ks, background calcium, and Kr. However, among the aforementioned major ion channels, only the CaL channel can play a superior role in prolonging the EMD up to 83 ms. Furthermore, ventricular cells with long EMD have been shown to inherit insignificant mechanical response (in terms of how strong the tension can grow and how far length shortening can go) compared with that in normal cells. In conclusion, despite all variations in every ion channel conductance, only the CaL channel can play a significant role in extending EMD. In addition, cardiac cells with long EMD tend to have inferior mechanical responses due to a lack of Cai compared with normal conditions, which are highly likely to result in a compromised pump function of the heart.
Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines’ TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when limited drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models on several ion channels for various drug pairs. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as biomarker features. The drug combination maps were also used to illustrate combined medicines' TdP risk. We found that the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations.
The SCN5A mutations have been long associated with long QT variant 3 (LQT3). Recent experimental and computation studies have reported that mexiletine effectively treats LQT3 patients associated with the A1656D mutation. However, they have primarily focused on cellular level evaluations and have only looked at the effects of mexiletine on action potential duration (APD) or QT interval reduction. We further investigated mexiletine’s effects on cardiac cells through simulations of single-cell (behavior of alternant occurrence) and 3D (with and without mexiletine). We discovered that mexiletine could shorten the cell’s APD and change the alternant’s occurrence to a shorter basic cycle length (BCL) between 350 and 420 ms. The alternant also appeared at a normal heart rate under the A1656D mutation. Furthermore, the 3D ventricle simulations revealed that mexiletine could reduce the likelihood of a greater spiral wave breakup in the A1656D mutant condition by minimizing the appearance of rotors. In conclusion, we found that mexiletine could provide extra safety features during therapy for LQT3 patients because it can change the alternant occurrence from a normal to a faster heart rate, and it reduces the chance of a spiral wave breakup. Therefore, these findings emphasize the promising efficacy of mexiletine in treating LQT3 patients under the A1656D mutation.
Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines’ TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when a limited number of drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models for various two-drug combinations. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as features. The drug combination maps were also utilized to illustrate the impact of DDIs on the TdP risk of combined medicines. We found that the DDIs of the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations.
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