Computational assessment of the effects of a pulsatile pump on toxin removal in blood purification

<p>Abstract</p> <p>Background</p> <p>For blood purification systems using a semipermeable membrane, the convective mass transfer by ultrafiltration plays an important role in toxin removal. The increase in the ultrafiltration rate can improve the toxin removal efficiency of the device, ultimately reducing treatment time and cost. In this study, we assessed the effects of pulsatile flow on the efficiency of the convective toxin removal in blood purification systems using theoretical methods.</p> <p>Methods</p> <p>We devised a new mathematical lumped model to assess the toxin removal efficiency of blood purification systems in patients, integrating the mass transfer model for a human body with a dialyser. The human body model consists of a three-compartment model of body fluid dynamics and a two-compartment model of body solute kinetics. We simulated three types of blood purification therapy with the model, hemofiltration, hemodiafiltration, and high-flux dialysis, and compared the simulation results in terms of toxin (urea and beta-2 microglobulin) clearance and the treatment dose delivered under conditions of pulsatile and non-pulsatile pumping. <it>In vivo </it>experiments were also performed to verify the model results.</p> <p>Results</p> <p>Simulation results revealed that pulsatile flow improved the convective clearance of the dialyser and delivered treatment dose for all three types of therapy. Compared with the non-pulsatile pumping method, the increases in the clearance of urea and beta-2 microglobulin with pulsatile pumping were highest with hemofiltration treatment (122.7% and 122.7%, respectively), followed by hemodiafiltration (3.6% and 8.3%, respectively), and high-flux dialysis (1.9% and 4.7%, respectively). EKRc and std Kt/V averaged 28% and 23% higher, respectively, in the pulsatile group than in the non-pulsatile group with hemofiltration treatment.</p> <p>Conclusions</p> <p>The pulsatile effect was highly advantageous for all of the toxins in the hemofiltration treatment and for β₂-microglobulin in the hemodiafiltration and high-flux dialysis treatments.</p

qInward variability-based in-silico proarrhythmic risk assessment of drugs using deep learning model

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

Machine learning approach to evaluate TdP risk of drugs using cardiac electrophysiological model including inter-individual variability

Introduction: Predicting ventricular arrhythmia Torsade de Pointes (TdP) caused by drug-induced cardiotoxicity is essential in drug development. Several studies used single biomarkers such as qNet and Repolarization Abnormality (RA) in a single cardiac cell model to evaluate TdP risk. However, a single biomarker may not encompass the full range of factors contributing to TdP risk, leading to divergent TdP risk prediction outcomes, mainly when evaluated using unseen data. We addressed this issue by utilizing multi-in silico features from a population of human ventricular cell models that could capture a representation of the underlying mechanisms contributing to TdP risk to provide a more reliable assessment of drug-induced cardiotoxicity.Method: We generated a virtual population of human ventricular cell models using a modified O’Hara-Rudy model, allowing inter-individual variation. IC50 and Hill coefficients from 67 drugs were used as input to simulate drug effects on cardiac cells. Fourteen features (dVmdtrepol, dVmdtmax, Vmpeak, Vmresting, APDtri, APD90, APD50, Capeak, Cadiastole, Catri, CaD90, CaD50, qNet, qInward) could be generated from the simulation and used as input to several machine learning models, including k-nearest neighbor (KNN), Random Forest (RF), XGBoost, and Artificial Neural Networks (ANN). Optimization of the machine learning model was performed using a grid search to select the best parameter of the proposed model. We applied five-fold cross-validation while training the model with 42 drugs and evaluated the model’s performance with test data from 25 drugs.Result: The proposed ANN model showed the highest performance in predicting the TdP risk of drugs by providing an accuracy of 0.923 (0.908–0.937), sensitivity of 0.926 (0.909–0.942), specificity of 0.921 (0.906–0.935), and AUC score of 0.964 (0.954–0.975).Discussion and conclusion: According to the performance results, combining the electrophysiological model including inter-individual variation and optimization of machine learning showed good generalization ability when evaluated using the unseen dataset and produced a reliable drug-induced TdP risk prediction system

Influence of the KCNQ1 S140G Mutation on Human Ventricular Arrhythmogenesis and Pumping Performance: Simulation Study

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

V241F KCNQ1 Mutation Shortens Electrical Wavelength and Reduces Ventricular Pumping Capabilities: A Simulation Study With an Electro-Mechanical Model

Death due to ventricular fibrillation (VF) can occur over a relatively short time period. During the first stage, an irregular heartbeat or arrhythmia of the heart may occur. Therefore, studying arrhythmia could reveal important insights relevant to the prevention of VF. One of the factors known to cause arrhythmia is the generation of mutations in the ion channels of myocytes. The current experimental methods to monitor and observe subjects with arrhythmia are invasive, and could possibly harm the subject with no guarantee of obtaining good results. These limitations could be overcome by using an extensively validated computational simulation study. This study aims to enhance our understanding of the effect of the V241F mutation on electromechanical behavior in the heart. We simulated three conditions; wild-type (WT), heterozygous/intermediate V241F, and pure V241F conditions in an electrophysiological single cell model and three-dimensional electro-mechanics ventricular model. The electro-mechanics model is a one-way coupling of the electrical compartment to the mechanical compartment by Ca2+ transient concentration. Consistent with a previous study, the V241F mutation significantly shortened the action potential duration at 90% repolarization (APD90) under pure V241F mutation conditions, due to the gain of function of the slow delayed rectifier potassium (IKs) channel. This APD90 shortening is associated with a short electrical wavelength, which shortens the Ca2+ activation time as well. The hemodynamic responses showed that the V241F mutation lowered ventricular contraction under normal sinus rhythm conditions by decreasing the stroke volume, stroke work, and ejection fraction. During reentry, the V241F mutation significantly reduced the ventricular contractility compared with the WT condition. In conclusions, the effect of the two variants of V241F (intermediate and pure) mutation not only disturbed the electrophysiological events but also affected the mechanical behavior significantly. The result of this study can be used as a reference for the cardiovascular expert to decide the appropriate pharmacology of IKs conductance block for the patient

Assessment of the proarrhythmic effects of repurposed antimalarials for COVID-19 treatment using a comprehensive in vitro proarrhythmia assay (CiPA)

Due to the outbreak of the SARS-CoV-2 virus, drug repurposing and Emergency Use Authorization have been proposed to treat the coronavirus disease 2019 (COVID-19) during the pandemic. While the efficiency of the drugs has been discussed, it was identified that certain compounds, such as chloroquine and hydroxychloroquine, cause QT interval prolongation and potential cardiotoxic effects. Drug-induced cardiotoxicity and QT prolongation may lead to life-threatening arrhythmias such as torsades de pointes (TdP), a potentially fatal arrhythmic symptom. Here, we evaluated the risk of repurposed pyronaridine or artesunate-mediated cardiac arrhythmias alone and in combination for COVID-19 treatment through in vitro and in silico investigations using the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative. The potential effects of each drug or in combinations on cardiac action potential (AP) and ion channels were explored using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and Chinese hamster ovary (CHO) cells transiently expressing cardiac ion channels (Nav1.5, Cav1.2, and hERG). We also performed in silico computer simulation using the optimized O’Hara-Rudy human ventricular myocyte model (ORd model) to classify TdP risk. Artesunate and dihydroartemisinin (DHA), the active metabolite of artesunate, are classified as a low risk of inducing TdP based on the torsade metric score (TMS). Moreover, artesunate does not significantly affect the cardiac APs of hiPSC-CMs even at concentrations up to 100 times the maximum serum concentration (Cmax). DHA modestly prolonged at APD90 (10.16%) at 100 times the Cmax. When considering Cmax, pyronaridine, and the combination of both drugs (pyronaridine and artesunate) are classified as having an intermediate risk of inducing TdP. However, when considering the unbound concentration (the free fraction not bound to carrier proteins or other tissues inducing pharmacological activity), both drugs are classified as having a low risk of inducing TdP. In summary, pyronaridine, artesunate, and a combination of both drugs have been confirmed to pose a low proarrhythmogenic risk at therapeutic and supratherapeutic (up to 4 times) free Cmax. Additionally, the CiPA initiative may be suitable for regulatory use and provide novel insights for evaluating drug-induced cardiotoxicity

Theoretical Estimation of Cannulation Methods for Left Ventricular Assist Device Support as a Bridge to Recovery

Left ventricular assist device (LVAD) support under cannulation connected from the left atrium to the aorta (LA-AA) is used as a bridge to recovery in heart failure patients because it is non-invasive to ventricular muscle. However, it has serious problems, such as valve stenosis and blood thrombosis due to the low ejection fraction of the ventricle. We theoretically estimated the effect of the in-series cannulation, connected from ascending aorta to descending aorta (AA-DA), on ventricular unloading as an alternative to the LA-AA method. We developed a theoretical model of a LVAD-implanted cardiovascular system that included coronary circulation. Using this model, we compared hemodynamic responses according to various cannulation methods such as LA-AA, AA-DA, and a cannulation connected from the left ventricle to ascending aorta (LV-AA), under continuous and pulsatile LVAD supports. The AA-DA method provided 14% and 18% less left ventricular peak pressure than the LA-AA method under continuous and pulsatile LVAD conditions, respectively. The LA-AA method demonstrated higher coronary flow than AA-DA method. Therefore, the LA-AA method is more advantageous in increasing ventricular unloading whereas the AA-DA method is a better choice to increase coronary perfusion

Relationship between Vitamin D, Parathyroid Hormone, and Bone Mineral Density in Elderly Koreans

There is controversy regarding definition of vitamin D inadequacy. We analyzed threshold 25-hydroxyvitamin D (25[OH]D) below which intact parathyroid hormone (iPTH) increases, and examined age- and sex-specific changes of 25(OH)D and iPTH, and association of 25(OH)D and iPTH with bone mineral density (BMD) in elderly Koreans. Anthropometric parameters, serum 25(OH)D and iPTH, lumbar spine and femur BMD by dual-energy radiography absorptiometry (DXA) were measured in 441 men and 598 postmenopausal women. iPTH increased below serum 25(OH) of 36.7 ng/mL in men, but failed to reach plateau in women. Femur neck BMD above and below threshold differed when threshold 25(OH)D concentrations were set at 15-27.5 ng/mL in men, and 12.5-20 ng/mL in postmenopausal women. Vitamin D-inadequate individuals older than 75 yr had higher iPTH than those aged ≤ 65 yr. In winter, age-associated iPTH increase in women was steeper than in summer. In conclusion, vitamin D inadequacy threshold cannot be estimated based on iPTH alone, and but other factors concerning bone health should also be considered. Older people seemingly need higher 25(OH)D levels to offset age-associated hyperparathyroidism. Elderly vitamin D-inadequate women in the winter are most vulnerable to age-associated hyperparathyroidism

Comparison of Monthly Ibandronate Versus Weekly Risedronate in Preference, Convenience, and Bone Turnover Markers in Korean Postmenopausal Osteoporotic Women

Patient preferences, convenience, and bone turnover markers were evaluated for the monthly ibandronate over the weekly risedronate regimen in Korean postmenopausal osteoporotic women. This was a 6-month, prospective, randomized, open-label, multicenter study with a two-period and two-sequence crossover treatment design. After a 30-day screening period, eligible participants with postmenopausal osteoporosis were randomized to receive either monthly oral ibandronate 150 mg for 3 months followed by weekly oral risedronate 35 mg for 12 weeks (sequence A) or the same regimen in reverse order (sequence B). Patient preference and convenience were evaluated by questionnaire. The changes in serum C-telopeptide after 3 months of treatment were analyzed. A total of 365 patients were enrolled in this study (sequence A 182, sequence B 183). Of patients expressing a preference (83.4%), 74.8% preferred the monthly ibandronate regimen over the weekly regimen (25.2%). More women stated that the monthly ibandronate regimen was more convenient (84.2%) than the weekly regimen (15.8%). There was no significant difference in the change in bone turnover marker between the two treatments. The two regimens were similarly tolerable. There were fewer adverse events in the monthly ibandronate group compared to the weekly risedronate group in terms of gastrointestinal side effects (nausea and abdominal distension). This study revealed a strong preference and convenience for monthly ibandronate over weekly risedronate in Korean postmenopausal osteoporotic women. There was no significant difference in change of bone turnover marker and safety profile between the two regimens

Proteostasis Dysregulation in Pancreatic Cancer

The most common form of pancreatic cancer, pancreatic ductal adenocarcinoma (PDAC), has a dismal 5-year survival rate of less than 5%. Radical surgical resection, in combination with adjuvant chemotherapy, provides the best option for long-term patient survival. However, only approximately 20% of patients are resectable at the time of diagnosis, due to locally advanced or metastatic disease. There is an urgent need for the identification of new, specific, and more sensitive biomarkers for diagnosis, prognosis, and prediction to improve the treatment options for pancreatic cancer patients. Dysregulation of proteostasis is linked to many pathophysiological conditions, including various types of cancer. In this review, we report on findings relating to the main cellular protein degradation systems, the ubiquitin-proteasome system (UPS) and autophagy, in pancreatic cancer. The expression of several components of the proteolytic network, including E3 ubiquitinligases and deubiquitinating enzymes, are dysregulated in PDAC, which accounts for approximately 90% of all pancreatic malignancies. In the future, a deeper understanding of the emerging role of proteostasis in pancreatic cancer has the potential to provide clinically relevant biomarkers and new strategies for combinatorial therapeutic options to better help treat the patients.Peer reviewe