Special Issue on Solitons in Quantum Physics.

This is an Editorial for the Special Issue on Solitons in Quantum Physics.

Kinetic modeling of the plasma pharmacokinetic profiles of ADAMTS13 fragment and its Fc-fusion counterpart in mice.

Introduction: Fusion of the fragment crystallizable (Fc) to protein therapeutics is commonly used to extend the circulation time by enhancing neonatal Fc-receptor (FcRn)-mediated endosomal recycling and slowing renal clearance. This study applied kinetic modeling to gain insights into the cellular processing contributing to the observed pharmacokinetic (PK) differences between the novel recombinant ADAMTS13 fragment (MDTCS) and its Fc-fusion protein (MDTCS-Fc). Methods: For MDTCS and MDTCS-Fc, their plasma PK profiles were obtained at two dose levels following intravenous administration of the respective proteins to mice. The plasma PK profiles of MDTCS were fitted to a kinetic model with three unknown protein-dependent parameters representing the fraction recycled (FR) and the rate constants for endocytosis (kup, for the uptake into the endosomes) and for the transfer from the plasma to the interstitial fluid (kpi). For MDTCS-Fc, the model was modified to include an additional parameter for binding to FcRn. Parameter optimization was done using the Cluster Gauss-Newton Method (CGNM), an algorithm that identifies multiple sets of approximate solutions ("accepted" parameter sets) to nonlinear least-squares problems. Results: As expected, the kinetic modeling results yielded the FR of MDTCS-Fc to be 2.8-fold greater than that of MDTCS (0.8497 and 0.3061, respectively). In addition, MDTCS-Fc was predicted to undergo endocytosis (the uptake into the endosomes) at a slower rate than MDTCS. Sensitivity analyses identified the association rate constant (kon) between MDTCS-Fc and FcRn as a potentially important factor influencing the plasma half-life in vivo. Discussion: Our analyses suggested that Fc fusion to MDTCS leads to changes in not only the FR but also the uptake into the endosomes, impacting the systemic plasma PK profiles. These findings may be used to develop recombinant protein therapeutics with extended circulation time.

Altered gut microbiome plays an important role in AKI to CKD transition in aged mice.

Introduction: This study investigated the role of renal-intestinal crosstalk in the transition from acute kidney injury (AKI) to chronic kidney disease (CKD) in elderly individuals. Methods: Using young and aged mice, we induced bilateral ischemia-reperfusion injury (IRI) and compared intestinal and kidney inflammation over 28 days. To determine the role of the microbiome in gut-kidney crosstalk, we analyzed the microbiome of fecal samples of the young vs. aged mice and examined the effects of probiotic supplementation. Results: In the post-IRI recovery phase, prolonged intestinal and renal inflammation along with dysbiosis were evident in aged vs. younger mice that was associated with severe renal dysfunction and fibrosis progression in aged mice. Probiotic supplementation with Bifidobacterium bifidum BGN4 and Bifidobacterium longum BORI alleviated intestinal inflammation but not intestinal leakage, characterized by decreased inflammatory cytokine levels and decreased infiltration of macrophages, neutrophils, and Th17 cells. This was associated with improved M1-dominant renal inflammation and ultimately improved renal function and fibrosis, suggesting that renal-intestinal crosstalk in aged mice contributes to the transition from AKI to CKD. Discussion: Our study findings suggest that exacerbation of chronic inflammation through the gut-kidney axis might be an important mechanism in the transition from AKI to CKD in the elderly.

Practical Approach for Determining Material Parameters When Predicting Austenite Grain Growth under Isothermal Heat Treatment.

An investigation of austenite grain growth (AGG) during the isothermal heat treatment of low-alloy steel is conducted. The goal is to uncover the effect of time, temperature, and initial grain size on SA508-III steel grain growth. Understanding this relationship enables the optimization of the time and temperature of the heat treatment to achieve the desired grain size in the studied steel. A modified Arrhenius model is used to model austenite grain size (AGS) growth distributions. With this model, it is possible to predict how grain size will change depending on heat treatment conditions. Then, the generalized reduced gradient (GRG) optimization method is employed under adiabatic conditions to characterize the model's parameters, providing a more precise solution than traditional methods. With optimal model parameters, predicted AGS agree well with measured values. The model shows that AGS increases faster as temperature and time increase. Similarly, grain size grows directly in proportion to the initial grain size. The optimized parameters are then applied to a practical case study with a similar specimen size and material properties, demonstrating that our approach can efficiently and accurately predict AGS growth via GRG optimization.

Prediction of the Time to Reach Equilibrium for Improved Estimation of the Unbound Fraction of Compounds in Equilibrium Dialysis Using kinetic Modeling.

Equilibrium dialysis (ED) is widely used in pharmacokinetics to determine the fraction of unbound (fu) compounds in plasma; however, the kinetics of drugs in the ED system with respect to their permeation across semi-permeable membranes has not been systemically studied. Here, the kinetics of the ED system, including the binding of drugs to plasma proteins, non-specific binding, and permeation across the membrane, was described to enable verification of the equilibrium, prediction of the time to reach equilibrium, and estimations of fu with data obtained during pre-equilibrium. Using data obtained during pre-equilibrium, the time to reach 90% equilibrium (t90%) and fu were estimated with reasonable accuracy. Notably, fu could be estimated reasonably well using one-time-point data for the calculation. Furthermore, the current modeling approach allowed concurrent estimations of fu and the decomposition rate of compounds that were metabolically unstable in the plasma. Reasonable metabolic rate constants were determined for cefadroxil and diltiazem, demonstrating the practicality of this method for determining kinetics related to fu characterization. Because the determination of fu of compounds with 'unfavorable' physicochemical properties is known to be experimentally challenging, the current method may be useful in determining the fu of compounds in vitro.

Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans.

Enavogliflozin is a sodium-dependent glucose cotransporter 2 (SGLT2) inhibitor approved for clinical use in South Korea. As SGLT2 inhibitors are a treatment option for patients with diabetes, enavogliflozin is expected to be prescribed in various populations. Physiologically based pharmacokinetic (PBPK) modelling can rationally predict the concentration-time profiles under altered physiological conditions. In previous studies, one of the metabolites (M1) appeared to have a metabolic ratio between 0.20 and 0.25. In this study, PBPK models for enavogliflozin and M1 were developed using published clinical trial data. The PBPK model for enavogliflozin incorporated a non-linear urinary excretion in a mechanistically arranged kidney model and a non-linear formation of M1 in the liver. The PBPK model was evaluated, and the simulated pharmacokinetic characteristics were in a two-fold range from those of the observations. The pharmacokinetic parameters of enavogliflozin were predicted using the PBPK model under pathophysiological conditions. PBPK models for enavogliflozin and M1 were developed and validated, and they seemed useful for logical prediction.

Involvement of CYP3A4 and MDR1 in altered metabolism and transport of indinavir in 1,25(OH)2D3-treated Caco-2 cells.

Altered drug concentrations may induce unexpected toxicity or treatment failure; thus, understanding the factors that alter the pharmacokinetic profiles of drugs is crucial for optimal disease treatment. Vitamin D receptor (VDR), a nuclear receptor, regulates the expression of cytochrome P450 3A4 (CYP3A4) and multidrug resistance protein 1 (MDR1), which are crucial determinants of drug pharmacokinetics. In this study, we investigated the effects of 1α,25-dihydroxyvitamin D3 [1,25(OH)2D3], a VDR ligand, on the metabolism, transport, and pharmacokinetics of indinavir, a dual substrate of CYP3A4 and MDR1. 1,25(OH)2D3 treatment for three days upregulated the expression levels of CYP3A4 and MDR1 in Caco-2 cells and consequently led to an increase in the level of a metabolite formed via CYP3A4 (indinavir M6) and the efflux ratio of indinavir in transport study. The increase in the metabolic reaction was also confirmed through a metabolism assay performed using the lysate of 1,25(OH)2D3-treated Caco-2 cells. In the Ussing chamber study conducted with the rat intestine, 1,25(OH)2D3 treatment did not alter the transport of indinavir into the basolateral side but increased indinavir M6 formation. Similarly, plasma levels of the metabolite increased in 1,25(OH)2D3-treated rats; however, systemic exposure to indinavir led to insignificant alterations. Considering the overlapping substrate specificities for CYP3A4 and MDR1 and their significant roles in drug pharmacokinetics, VDR may play an important role in drug interactions of CYP3A4 and MDR1 substrates for accessing more effective and safe disease treatments.

Pretreatment of rhesus monkeys with transdermal patches containing physostigmine and procyclidine: implications of the delivery system for the potential application against VX nerve agent intoxication in humans.

Physostigmine (Phs) is a reversible inhibitor of acetylcholinesterase (AChE) that penetrates the blood-brain barrier (BBB) and could be used to protect the central nervous system (CNS) against the effects of nerve agents. For prophylactic effectiveness, long, steady, and adequate inhibition of AChE activity by Phs is needed to broadly protect against the CNS effects of nerve agents. Here, we evaluated the efficacy of transdermal patches containing Phs and procyclidine (PC) as prophylactic agents. Patches (25 cm2) containing 4.4 mg Phs and 17.8 mg PC had a protective ratio of approximately 78.6-fold in rhesus monkeys challenged with VX nerve agent and given an antidote. Physiologically based pharmacokinetic model in conjunction with an indirect pharmacodynamic (PBPK/PD) was developed for Phs and scaled to rhesus monkeys. The model was able to reproduce the concentration profile and inhibitory effect on AChE of Phs in monkeys, as evidenced by correlation coefficients of 0.994 and 0.992 for 25 cm2 and 49 cm2 patches, respectively (i.e., kinetic data), and 0.989 and 0.968 for 25 cm2 and 49 cm2 patches, respectively (i.e., dynamic data). By extending the monkey PBPK/ PD model to humans, the effective human dose was predicted to be five applications of a 25 cm2 patch (i.e., 22 mg Phs), and two applications of a 49 cm2 patch (i.e., 17.4 mg Phs). Therefore, given that patch application of Phs in rhesus monkeys has a prolonged effect (namely, AChE inhibition of 19.6% for the 25 cm2 patch and 23.0% for the 49 cm2 patch) for up to 216 h, patch formulation of Phs may provide similar protection against nerve agent intoxication in humans.

Real-time monitoring of work-at-height safety hazards in construction sites using drones and deep learning.

INTRODUCTION: The construction field is considered one of the most dangerous industries. Accidents and fatalities take place on a daily basis in construction projects. Globally, different levels of government have implemented strict rules and regulations to protect workers on job sites. However, despite the efforts to implement the rules and regulations, accidents occur frequently. Falling from heights is considered the most common cause of death in construction. This study developed a novel system integrating deep learning and drones to monitor workers in real-time when performing at-height activities. METHOD: Specifically, a pre-trained deep learning model was used to detect Personal Fall Arrest System components (e.g., safety harness, lifeline, and helmet). The drone was utilized to take images and videos from the construction site, and the data were relayed to the model to detect safety violations. The system was tested and validated in real construction sites and in a controlled lab environment to verify the model's effectiveness under different light and weather conditions. RESULTS: The overall accuracy of the system was 90%. The model's precision and recall were 97.2 % and 90.2%, respectively. The average time taken to detect a violation was around 12 seconds. CONCLUSIONS: Moreover, the Area Under Curve - Receiver Operating Characteristics chart showed that the trained model was very good and precise in detecting and differentiating the desired objects. PRACTICAL APPLICATIONS: This fast, reliable, and economical system can aid in saving many lives if implemented and utilized properly in real construction sites.

Determination of the Number of Tissue Groups of Kinetically Distinct Transit Time in Whole-Body Physiologically Based Pharmacokinetic (PBPK) Models I: Theoretical Consideration of Bottom-Up Approach of Lumping Tissues in Whole-Body PBPK.

Minimal physiologically based pharmacokinetic (mPBPK) models, consisting of system-specific (e.g., tissue volume and blood flow) and drug-related (e.g., tissue-to-plasma partition coefficient) parameters, are practically useful for pharmacokinetic analyses. However, biopharmaceutical principles were not clear on how peripheral tissues, adopted in whole-body physiologically based pharmacokinetic (WB-PBPK) models, could be kinetically consolidated into one or two tissue groups in the mPBPK models. In this theoretical examination, we studied the relationship between the progressive tissue lumping in the direction from the longest mean transit time (MTTmax) to the shorter one(s) and the slopes of the terminal (λter)/distributional phases, assuming tissues with comparable MTTs are kinetically combined. The appropriateness of lumping was ascertained by evaluating the impact of difference in tissue MTTs during the lumping on the analytical solution of WB-PBPK models. We found that the ratio of MTTmax to the mean residence time in the body, viz., Kdet, is related to the change in λter by the progressive lumping and can serve as an index for the robustness of λter. Calculations with two extreme cases revealed that, for caffeine at Kdet < 0.03, the change in λter was minimal even when all peripheral tissues were collectively lumped, whereas for artesunic acid at Kdet > 50, the tissue of MTTmax could not be kinetically combined even with the tissue having the second-longest MTT without significantly affecting λter. Therefore, we proposed Kdet as an index for the robustness of λter during tissue lumping and for the number of tissue groups with distinct transit times in WB-PBPK.

Determination of the Number of Tissue Groups of Kinetically Distinct Transit Time in Whole-Body Physiologically Based Pharmacokinetic (PBPK) Models II: Practical Application of Tissue Lumping Theories for Pharmacokinetics of Various Compounds.

In our companion paper, we described the theoretical basis for tissue lumping in whole-body physiologically based pharmacokinetic (WB-PBPK) models and found that Kdet, a coefficient for determining the number of tissue groups of distinct transit time in WB-PBPK models, was related to the fractional change in the terminal slope (FCT) when tissues were progressively lumped from the longest transit time to shorter ones. This study was conducted to identify the practical threshold of Kdet by applying the lumping theory to plasma/blood concentration-time relationships of 113 model compounds collected from the literature. We found that drugs having Kdet < 0.3 were associated with FCT < 0.1 even when all peripheral tissues were lumped, resulting in comparable plasma concentration-time profiles between one-tissue minimal PBPK (mPBPK) and WB-PBPK models. For drugs with Kdet ≥ 1, WB-PBPK profiles appeared similar with two-tissue mPBPK models by applying the rule of FCT < 0.1 for lumping slowly equilibrating tissues. The two-tissue mPBPK model also appeared appropriate in terms of concentration-time profiles for drugs with 0.3 ≤ Kdet < 1, although, some compounds (15.9% of the total cases), but not all, in this range showed a slight (maximum of 18.9% of the total AUC) deviation from WB-PBPK models, indicating that the two-tissue model, with caution, could still be used for those cases. Comparison of kinetic parameters between traditional (model-fitting) and current (theoretical calculation) mPBPK analyses revealed their significant correlations. Collectively, these observations suggest that the number of tissue groups could be determined based on the Kdet/FCT criteria, and plasma concentration-time profiles from WB-PBPK could be calculated using equations significantly less complex.

Model-Based Prediction of Acid Suppression and Proposal of a New Dosing Regimen of Fexuprazan in Humans.

Fexuprazan is a potassium-competitive acid blocker (P-CAB). The compounds in this newly developed drug family suppress intragastric acidity. As there are already other acid-suppressing drugs on the market, such as H2 antagonists and proton pump inhibitors (PPIs), it would be informative to compare the biological effects of fexuprazan against another approved drug with the same indication. The drug concentration predicted by the pharmacokinetic (PK) model could serve as an input function for a pharmacodynamic (PD) model. The apparent pharmacokinetics of fexuprazan could be described by a simpler model. However, a physiologically based pharmacokinetic (PBPK) model was developed in a previous study. A one-compartment model was also proposed in the present study. Both the newly suggested model and the previously validated PBPK model were used as input functions of the PD models. Our simulation revealed that the effects of fexuprazan could be effectively simulated by the proposed PK-PD models. A PK-PD model was also proposed for the oral administration of the PPI reference drug esomeprazole. A model-based analysis was then performed for intragastric pH using several dosing methods. The expected pH could be predicted for both drugs under several dosing regimens using the proposed PK-PD models.

Prediction of Pharmacokinetics of IDP-73152 in Humans Using Physiologically-Based Pharmacokinetics.

IDP-73152, a novel peptide deformylase inhibitor with an antibacterial effect against Gram-positive bacteria, is in phase I development. The objective of this study was to develop a physiologically-based pharmacokinetic model (PBPK) for IDP-73152 in animals, and to extend the model to humans. Biopharmaceutical properties of IDP-73152 are determined using in vitro/in vivo experimentations for the PBPK model. A transit model consisting of gastrointestinal segments is applied for an estimation of the intestinal absorption kinetics. The PBPK model of IDP-73152 in rats is able to appropriately predict the plasma concentration-time profiles after the administration of IDP-73152 at different doses and by different routes (combined absolute average fold error (cAAFE), 1.77). The model is also found to be adequate in predicting the plasma concentration-time profiles of IDP-73152 in mice (cAAFE 1.59) and dogs (cAAFE 1.42). Assuming the oral administration of IDP-73152 to humans at doses of 640 and 1280 mg, the model is able to reproduce the concentration-time profiles obtained in humans (cAAFE 1.38); therefore, these observations indicate that the PBPK model used for IDP-73152 is applicable to animal species and humans. This model may be useful in predicting efficacious doses of IDP-73152 for the management of infectious disease in humans.

Metronomic dose-finding approach in oral chemotherapy by experimentally-driven integrative mathematical modeling.

In conventional chemotherapy, maximum tolerated dose approach is considered as a first-line medication for cancer treatment in clinics. In contrast to the conventional chemotherapy which has heavy tumor burdens arising from high dose treatment, metronomic chemotherapy (MCT) engages relatively low dose without drug-free breaks, and is recognized as a promising strategy for a long-term management of the disease. Although doxorubicin (DOX), an anthracycline anti-cancer drug, showed a potential of maintenance effect in vitro, further study on in vivo-relevant concentration to achieve tumor suppression with no toxicity is required to apply the MCT in clinicals. Therefore, the objective of this study was to identify an optimal MCT regimen of DOX by determining concentration-response relationships of tumor suppression (pharmacodynamic; PD) and cardiac toxicity (toxicodynamic; TD). Utilizing an oral DOX formulation complexed with deoxycholic acid (DOX/DOCA complex) which has enhanced bioavailability, physiologically-based pharmacokinetic (PBPK) model was linked to TD and PD models to generate drug profiles from the combined PK, TD, and PD parameters. The integrated model was validated for various scenarios of administration route, formulation, dose, and frequency. The established mathematical model facilitated calculations of adequate in vivo-relevant dosages and intervals, suggesting the optimum oral metronomic regimen of DOX. It is expected to serve as a useful guideline for the design and evaluation of oral DOX formulations in future preclinical/clinical studies.

Role of the efflux transporters Abcb1 and Abcg2 in the brain distribution of olaparib in mice.

Olaparib is a first-in-class poly (ADP-ribose) polymerase oral inhibitor used to treat various tumors. In this study, we clarified the roles of ABCB1/Abcb1 and ABCG2/Abcg2 transporters in restricting olaparib distribution to the brain. Olaparib was efficiently transported by human ABCG2, human ABCB1, and mouse Abcg2 in vitro. In the in vivo disposition study of olaparib using single or combination knockout mice, the systemic exposure of olaparib did not differ significantly between the strains over an 8-h period. However, the brain-to-plasma unbound concentration ratio of olaparib increased 5.6- and 8.1-fold in Abcb1a/1b and Abcb1a/1b;Abcg2 knockout mice, respectively, compared with wild-type mice. The Abcg2 single knockout mice exhibited a similar brain-to-plasma unbound concentration ratio to wild-type mice. Moreover, the brain distribution of olaparib could be modulated by the ABCB1/ABCG2 dual inhibitor elacridar to reach a similar degree of inhibition to Abcb1a/1b-/-. These findings suggest that olaparib is actively transported by both human and mouse ABCB1/Abcb1 and ABCG2/Abcg2; while Abcb1a/1b is a major determinant of olaparib brain penetration in mice, Abcg2 is likely to be a minor contributor. Concomitant treatment with temozolomide slightly increased the brain distribution of olaparib in mouse, but the clinical impact of the interaction was expected to be limited.

A Review of Carbon Footprint Reduction in Construction Industry, from Design to Operation.

Construction is among the leading industries/activities contributing the largest carbon footprint. This review paper aims to promote awareness of the sources of carbon footprint in the construction industry, from design to operation and management during manufacturing, transportation, construction, operations, maintenance and management, and end-of-life deconstruction phases. In addition, it summarizes the latest studies on carbon footprint reduction strategies in different phases of construction by the use of alternative additives in building materials, improvements in design, recycling construction waste, promoting the utility of alternative water resources, and increasing efficiencies of water technologies and other building systems. It was reported that the application of alternative additives/materials or techniques/systems can reduce up to 90% of CO2 emissions at different stages in the construction and building operations. Therefore, this review can be beneficial at the stage of conceptualization, design, and construction to assist clients and stakeholders in selecting materials and systems; consequently, it promotes consciousness of the environmental impacts of fabrication, transportation, and operation.

Emergence of topological superconductivity in doped topological Dirac semimetals under symmetry-lowering lattice distortions.

Recently, unconventional superconductivity having a zero-bias conductance peak is reported in doped topological Dirac semimetal (DSM) with lattice distortion. Motivated by the experiments, we theoretically study the possible symmetry-lowering lattice distortions and their effects on the emergence of unconventional superconductivity in doped topological DSM. We find four types of symmetry-lowering lattice distortions that reproduce the crystal symmetries relevant to experiments from the group-theoretical analysis. Considering inter-orbital and intra-orbital electron density-density interactions, we calculate superconducting phase diagrams. We find that the lattice distortions can induce unconventional superconductivity hosting gapless surface Andreev bound states (SABS). Depending on the lattice distortions and superconducting pairing interactions, the unconventional inversion-odd-parity superconductivity can be either topological nodal superconductivity hosting a flat SABS or topological crystalline superconductivity hosting a gapless SABS. Remarkably, the lattice distortions increase the superconducting critical temperature, which is consistent with the experiments. Our work opens a pathway to explore and control pressure-induced topological superconductivity in doped topological semimetals.

Effects of 1α,25-Dihydroxyvitamin D3 on the Pharmacokinetics of Procainamide and Its Metabolite N-Acetylprocainamide, Organic Cation Transporter Substrates, in Rats with PBPK Modeling Approach.

In this study, possible changes in the expression of rat organic cationic transporters (rOCTs) and rat multidrug and toxin extrusion proteins (rMATEs) following treatment with 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3) were investigated. Rats received intraperitoneal administrations of 1,25(OH)2D3 for four consecutive days, and the tissues of interest were collected. The mRNA expression of rOCT1 in the kidneys was significantly increased in 1,25(OH)2D3-treated rats compared with the control rats, while the mRNA expressions of rOCT2 and rMATE1 in the kidneys, rOCT1 and N-acetyltransferase-II (NAT-II) in the liver, and rOCT3 in the heart were significantly decreased. Changes in the protein expression of hepatic rOCT1 and renal rOCT2 and rMATE1 were confirmed by western blot analysis. We further evaluated the pharmacokinetics of procainamide (PA) hydrochloride and its major metabolite N-acetyl procainamide (NAPA) in the presence of 1,25(OH)2D3. When PA hydrochloride was administered intravenously at a dose 10 mg/kg to 1,25(OH)2D3-treated rats, a significant decrease in renal and/or non-renal clearance of PA and NAPA was observed. A physiological model for the pharmacokinetics of PA and NAPA in rats was useful for linking changes in the transcriptional and translational expressions of rOCTs and rMATE1 transporters to the altered pharmacokinetics of the drugs.

Development of Physiologically Based Pharmacokinetic Model for Orally Administered Fexuprazan in Humans.

Fexuprazan is a new drug candidate in the potassium-competitive acid blocker (P-CAB) family. As proton pump inhibitors (PPIs), P-CABs inhibit gastric acid secretion and can be used to treat gastric acid-related disorders such as gastroesophageal reflux disease (GERD). Physiologically based pharmacokinetic (PBPK) models predict drug interactions as pharmacokinetic profiles in biological matrices can be mechanistically simulated. Here, we propose an optimized and validated PBPK model for fexuprazan by integrating in vitro, in vivo, and in silico data. The extent of fexuprazan tissue distribution in humans was predicted using tissue-to-plasma partition coefficients in rats and the allometric relationships of fexuprazan distribution volumes (VSS) among preclinical species. Urinary fexuprazan excretion was minimal (0.29-2.02%), and this drug was eliminated primarily by the liver and metabolite formation. The fraction absorbed (Fa) of 0.761, estimated from the PBPK modeling, was consistent with the physicochemical properties of fexuprazan, including its in vitro solubility and permeability. The predicted oral bioavailability of fexuprazan (38.4-38.6%) was within the range of the preclinical datasets. The Cmax, AUClast, and time-concentration profiles predicted by the PBPK model established by the learning set were accurately predicted for the validation sets.

Superconducting Sr2RuO4 Thin Films without Out-of-Phase Boundaries by Higher-Order Ruddlesden-Popper Intergrowth.

Ruddlesden-Popper (RP) phases (An+1BnO3n+1, n = 1, 2,···) have attracted intensive research with diverse functionalities for device applications. However, the realization of a high-quality RP-phase film is hindered by the formation of out-of-phase boundaries (OPBs) that occur at terrace edges, originating from lattice mismatch in the c-axis direction with the A'B'O3 (n = ∞) substrate. Here, using strontium ruthenate RP-phase Sr2RuO4 (n = 1) as a model system, an experimental approach for suppressing OPBs was developed. By tuning the growth parameters, the Sr3Ru2O7 (n = 2) phase was formed in a controlled manner near the film-substrate interface. This higher-order RP-phase then blocked the subsequent formation of OPBs, resulting in nearly defect-free Sr2RuO4 layer at the upper region of the film. Consequently, the Sr2RuO4 thin films exhibited superconductivity up to 1.15 K, which is the highest among Sr2RuO4 films grown by pulsed laser deposition. This work paves the way for synthesizing pristine RP-phase heterostructures and exploring their unique physical properties.