ABSTRACT
Rosiglitazone is an activator of nuclear peroxisome proliferator-activated (PPAR) receptor gamma used in the treatment of type 2 diabetes mellitus. The elimination of rosiglitazone occurs mainly via metabolism, with major contribution by enzyme cytochrome P450 (CYP) 2C8. Primary routes of rosiglitazone metabolism are N-demethylation and hydroxylation. Modulation of CYP2C8 activity by co-administered drugs lead to prominent changes in the exposure of rosiglitazone and its metabolites. Here, we attempt to develop mechanistic parent-metabolite physiologically based pharmacokinetic (PBPK) model for rosiglitazone. Our goal is to predict potential drug-drug interaction (DDI) and consequent changes in metabolite N-desmethyl rosiglitazone exposure. The PBPK modeling was performed in the PKSim® software using clinical pharmacokinetics data from literature. The contribution to N-desmethyl rosiglitazone formation by CYP2C8 was delineated using vitro metabolite formation rates from recombinant enzyme system. Developed model was verified for prediction of rosiglitazone DDI potential and its metabolite exposure based on observed clinical DDI studies. Developed model exhibited good predictive performance both for rosiglitazone and N-desmethyl rosiglitazone respectively, evaluated based on commonly acceptable criteria. In conclusion, developed model helps with prediction of CYP2C8 DDI using rosiglitazone as a substrate, as well as changes in metabolite exposure. In vitro data for metabolite formation can be successfully utilized to translate to in vivo conditions.
ABSTRACT
BACKGROUND AND OBJECTIVE: The prediction of pharmacokinetic parameters for drugs metabolised by cytochrome P450 enzymes has been the subject of active research for many years, while the application of in vitro-in vivo extrapolation (IVIVE) techniques for non-cytochrome P450 enzymes has not been thoroughly evaluated. There is still no established quantitative method for predicting hepatic clearance of drugs metabolised by uridine 5'-diphospho-glucuronosyltransferases (UGTs), not to mention those which undergo hepatic uptake. The objective of the study was to predict the human hepatic clearance for telmisartan based on in vitro metabolic stability and hepatic uptake results. METHODS: Telmisartan was examined in liver systems, allowing to estimate intrinsic clearance (CLint, in vitro) based on the substrate disappearance rate with the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Obtained CLint, in vitro values were corrected for corresponding unbound fractions. Prediction of human hepatic clearance was made from scaled unbound CLint, in vitro data with the use of the well-stirred model, and finally referenced to the literature value of observed clearance in humans, allowing determination of the essential scaling factors. RESULTS: The in vitro scaled CLint, in vitro by UGT1A3 was assessed using three systems, human hepatocytes, liver microsomes, and recombinant enzymes. Obtained values were scaled and hepatic metabolism clearance was predicted, resulting in significant clearance underprediction. Utilization of the extended clearance concept (ECC) and hepatic uptake improved prediction of hepatic metabolism clearance. The scaling factors for hepatocytes, assessing the in vitro-in vivo difference, changed from sixfold difference to only twofold difference with the application of the ECC. CONCLUSIONS: The study showed that taking into consideration hepatic uptake of a drug allows us to obtain satisfactory scaling factors, hence enabling the prediction of in vivo hepatic glucuronidation from in vitro data.
Subject(s)
Glucuronides , Glucuronosyltransferase , Microsomes, Liver , Solute Carrier Organic Anion Transporter Family Member 1B3 , Telmisartan , Glucuronosyltransferase/metabolism , Telmisartan/pharmacokinetics , Telmisartan/metabolism , Humans , Microsomes, Liver/metabolism , Glucuronides/metabolism , Solute Carrier Organic Anion Transporter Family Member 1B3/metabolism , Liver/metabolism , Liver/enzymology , Metabolic Clearance Rate , Tandem Mass Spectrometry/methods , Hepatocytes/metabolism , Models, Biological , Chromatography, Liquid/methods , Benzoates/pharmacokinetics , Benzoates/metabolismABSTRACT
Comparative anatomy is an important tool for investigating evolutionary relationships among species, but the lack of scalable imaging tools and stains for rapidly mapping the microscale anatomies of related species poses a major impediment to using comparative anatomy approaches for identifying evolutionary adaptations. We describe a method using synchrotron source micro-x-ray computed tomography (syn-µXCT) combined with machine learning algorithms for high-throughput imaging of Lepidoptera (i.e., butterfly and moth) eyes. Our pipeline allows for imaging at rates of ~15 min/mm3 at 600 nm3 resolution. Image contrast is generated using standard electron microscopy labeling approaches (e.g., osmium tetroxide) that unbiasedly labels all cellular membranes in a species-independent manner thus removing any barrier to imaging any species of interest. To demonstrate the power of the method, we analyzed the 3D morphologies of butterfly crystalline cones, a part of the visual system associated with acuity and sensitivity and found significant variation within six butterfly individuals. Despite this variation, a classic measure of optimization, the ratio of interommatidial angle to resolving power of ommatidia, largely agrees with early work on eye geometry across species. We show that this method can successfully be used to determine compound eye organization and crystalline cone morphology. Our novel pipeline provides for fast, scalable visualization and analysis of eye anatomies that can be applied to any arthropod species, enabling new questions about evolutionary adaptations of compound eyes and beyond.
ABSTRACT
Complex dynamical systems may exhibit multiple steady states, including time-periodic limit cycles, where the final trajectory depends on initial conditions. With tuning of parameters, limit cycles can proliferate or merge at an exceptional point. Here we ask how dynamics in the vicinity of such a bifurcation are influenced by noise. A pitchfork bifurcation can be used to induce bifurcation behavior. We model a limit cycle with the normal form of the Hopf oscillator, couple it to the pitchfork, and investigate the resulting dynamical system in the presence of noise. We show that the generating functional for the averages of the dynamical variables factorizes between the pitchfork and the oscillator. The statistical properties of the pitchfork in the presence of noise in its various regimes are investigated and a scaling theory is developed for the correlation and response functions, including a possible symmetry-breaking field. The analysis is done by perturbative calculations as well as numerical means. Finally, observables illustrating the coupling of a system with a limit cycle to a pitchfork are discussed and the phase-phase correlations are shown to exhibit nondiffusive behavior with universal scaling.
ABSTRACT
BACKGROUND: In predictions about hepatic clearance (CLH), a number of studies explored the role of albumin and transporters in drug uptake by liver cells, challenging the traditional free-drug theory. It was proposed that liver uptake can occur for transporter substrate compounds not only from the drug's unbound form but also directly from the drug-albumin complex, a phenomenon known as uptake facilitated by albumin. In contrast to albumin, dextran does not exhibit binding properties for compounds. However, as a result of its inherent capacity for stabilization, it is widely used to mimic conditions within cells. METHODS: The uptake of eight known substrates of the organic anion-transporting polypeptide 1B3 (OATP1B3) was assessed using a human embryonic kidney cell line (HEK293), which stably overexpresses this transporter. An inert polymer, dextran, was used to simulate cellular conditions, and the results were compared with experiments involving human plasma and human serum albumin (HSA). RESULTS: This study is the first to demonstrate that dextran increases compound uptake in cells with overexpression of the OATP1B3 transporter. Contrary to the common theory that highly protein-bound ligands interact with hepatocytes to increase drug uptake, the results indicate that dextran's interaction with test compounds does not significantly increase concentrations near the cell membrane surface. CONCLUSIONS: We evaluated the effect of dextran on the uptake of known substrates using OATP1B3 overexpressed in the HEK293 cell line, and we suggest that its impact on drug concentrations in liver cells may differ from the traditional role of plasma proteins and albumin.
Subject(s)
Dextrans , Organic Anion Transporters , Humans , Solute Carrier Organic Anion Transporter Family Member 1B3/genetics , Solute Carrier Organic Anion Transporter Family Member 1B3/metabolism , Solute Carrier Organic Anion Transporter Family Member 1B3/pharmacology , Liver-Specific Organic Anion Transporter 1/genetics , Liver-Specific Organic Anion Transporter 1/metabolism , Liver-Specific Organic Anion Transporter 1/pharmacology , HEK293 Cells , Organic Anion Transporters/genetics , Organic Anion Transporters/metabolism , Hepatocytes/metabolism , Liver , Membrane Transport Proteins/metabolism , Albumins , Organic Anion Transporters, Sodium-Independent/genetics , Organic Anion Transporters, Sodium-Independent/metabolismABSTRACT
Cubic energy materials such as thermoelectrics or hybrid perovskite materials are often understood to be highly disordered1,2. In GeTe and related IV-VI compounds, this is thought to provide the low thermal conductivities needed for thermoelectric applications1. Since conventional crystallography cannot distinguish between static disorder and atomic motions, we develop the energy-resolved variable-shutter pair distribution function technique. This collects structural snapshots with varying exposure times, on timescales relevant for atomic motions. In disagreement with previous interpretations3-5, we find the time-averaged structure of GeTe to be crystalline at all temperatures, but with anisotropic anharmonic dynamics at higher temperatures that resemble static disorder at fast shutter speeds, with correlated ferroelectric fluctuations along the <100>c direction. We show that this anisotropy naturally emerges from a Ginzburg-Landau model that couples polarization fluctuations through long-range elastic interactions6. By accessing time-dependent atomic correlations in energy materials, we resolve the long-standing disagreement between local and average structure probes1,7-9 and show that spontaneous anisotropy is ubiquitous in cubic IV-VI materials.
ABSTRACT
In the context of a single-electron two orbital Holstein system coupled to dispersionless bosons, we develop a general method to correct the single-particle Green's function using a power series correction (PSC) scheme. We outline the derivations of various flavors of cumulant approximation through the PSC scheme explaining the assumptions and approximations behind them. Finally, we compare the PSC spectral function with cumulant and exact diagonalized spectral functions and elucidate three regimes of this problem-two where the cumulant explains and one where the cumulant fails. We find that the exact and the PSC spectral functions match within spectral broadening across all three regimes.
ABSTRACT
The COVID-19 pandemic has brought attention to the need for developing effective respiratory support that can be rapidly implemented during critical surge capacity scenarios in healthcare settings. Lung support with bubble continuous positive airway pressure (B-CPAP) is a well-established therapeutic approach for supporting neonatal patients. However, the effectiveness of B-CPAP in larger pediatric and adult patients has not been addressed. Using similar principles of B-CPAP pressure generation, application of intermittent positive pressure inflations above CPAP could support gas exchange and high work of breathing levels in larger patients experiencing more severe forms of respiratory failure. This report describes the design and performance characteristics of the BubbleVent, a novel 3D-printed valve system that combined with commonly found tubes, hoses, and connectors can provide intermittent mandatory ventilation (IMV) suitable for adult mechanical ventilation without direct electrification. Testing of the BubbleVent was performed on a passive adult test lung model and compared with a critical care ventilator commonly used in tertiary care centers. The BubbleVent was shown to deliver stable PIP and PEEP levels, as well as timing control of breath delivery that was comparable with a critical care ventilator.
ABSTRACT
A detailed exploration of thef-atomic orbital occupancy space for UO2is performed using a first principles approach based on density functional theory (DFT), employing a full hybrid functional within a systematic basis set. Specifically, the PBE0 functional is combined with an occupancy biasing scheme implemented in a wavelet-based algorithm which is adapted to large supercells. The results are compared with previous DFT +Ucalculations reported in the literature, while dynamical mean field theory is also performed to provide a further base for comparison. This work shows that the computational complexity of the energy landscape of a correlatedf-electron oxide is much richer than has previously been demonstrated. The resulting calculations provide evidence of the existence of multiple previously unexplored metastable electronic states of UO2, including those with energies which are lower than previously reported ground states.
ABSTRACT
Excellent photovoltaic performance is predicted in a pentagonal covalent network of Si in a hollow structure exhibiting both thermal and dynamical stability. Consisting of a combination of sp2 and sp3 hybridized Si atomic orbitals, the GW0 computed band structure shows an indirect band gap near the zone edge and also a manifold of directly absorbing transitions at frequencies in the window of visible light, in distinction with conventional Si. Hydrogenation of a single sp2 site is predicted to lead to a robust local magnetic moment. We find a low formation energy at low pressure that is compatible with other experimentally known phases, suggesting that a stable phase might be obtained.
ABSTRACT
Out of equilibrium, a lack of reciprocity is the rule rather than the exception. Non-reciprocity occurs, for instance, in active matter1-6, non-equilibrium systems7-9, networks of neurons10,11, social groups with conformist and contrarian members12, directional interface growth phenomena13-15 and metamaterials16-20. Although wave propagation in non-reciprocal media has recently been closely studied1,16-20, less is known about the consequences of non-reciprocity on the collective behaviour of many-body systems. Here we show that non-reciprocity leads to time-dependent phases in which spontaneously broken continuous symmetries are dynamically restored. We illustrate this mechanism with simple robotic demonstrations. The resulting phase transitions are controlled by spectral singularities called exceptional points21. We describe the emergence of these phases using insights from bifurcation theory22,23 and non-Hermitian quantum mechanics24,25. Our approach captures non-reciprocal generalizations of three archetypal classes of self-organization out of equilibrium: synchronization, flocking and pattern formation. Collective phenomena in these systems range from active time-(quasi)crystals to exceptional-point-enforced pattern formation and hysteresis. Our work lays the foundation for a general theory of critical phenomena in systems whose dynamics is not governed by an optimization principle.
ABSTRACT
Multiscale and multimodal imaging of material structures and properties provides solid ground on which materials theory and design can flourish. Recently, KAIST announced 10 flagship research fields, which include KAIST Materials Revolution: Materials and Molecular Modeling, Imaging, Informatics and Integration (M3I3). The M3I3 initiative aims to reduce the time for the discovery, design and development of materials based on elucidating multiscale processing-structure-property relationship and materials hierarchy, which are to be quantified and understood through a combination of machine learning and scientific insights. In this review, we begin by introducing recent progress on related initiatives around the globe, such as the Materials Genome Initiative (U.S.), Materials Informatics (U.S.), the Materials Project (U.S.), the Open Quantum Materials Database (U.S.), Materials Research by Information Integration Initiative (Japan), Novel Materials Discovery (E.U.), the NOMAD repository (E.U.), Materials Scientific Data Sharing Network (China), Vom Materials Zur Innovation (Germany), and Creative Materials Discovery (Korea), and discuss the role of multiscale materials and molecular imaging combined with machine learning in realizing the vision of M3I3. Specifically, microscopies using photons, electrons, and physical probes will be revisited with a focus on the multiscale structural hierarchy, as well as structure-property relationships. Additionally, data mining from the literature combined with machine learning will be shown to be more efficient in finding the future direction of materials structures with improved properties than the classical approach. Examples of materials for applications in energy and information will be reviewed and discussed. A case study on the development of a Ni-Co-Mn cathode materials illustrates M3I3's approach to creating libraries of multiscale structure-property-processing relationships. We end with a future outlook toward recent developments in the field of M3I3.
ABSTRACT
Large scientific projects in genomics and astronomy are influential not because they answer any single question but because they enable investigation of continuously arising new questions from the same data-rich sources. Advances in automated mapping of the brain's synaptic connections (connectomics) suggest that the complicated circuits underlying brain function are ripe for analysis. We discuss benefits of mapping a mouse brain at the level of synapses.
Subject(s)
Brain/physiology , Connectome/methods , Nerve Net/physiology , Neurons/physiology , Synapses/physiology , Animals , MiceABSTRACT
Approximately 75% of xenobiotics are primarily eliminated through metabolism; thus the accurate scaling of metabolic clearance is vital to successful drug development. Yet, when data is scaled from in vitro to in vivo, hepatic metabolic clearance, the primary source of metabolism, is still commonly underpredicted. Over the past decades, with biophysics used as a key component to restore aspects of the in vivo environment, several new cell culture settings have been investigated to improve hepatocyte functionalities. Most of these studies have focused on shear stress, i.e., flow mediated by a pressure gradient. One potential conclusion of these studies is that hepatocytes are naturally "mechanosensitive," i.e., they respond to a change in their biophysical environment. We demonstrate that hepatocytes also respond to an increase in hydrostatic pressure that, we suggest, is directly linked to the lobule geometry and vessel density. Furthermore, we demonstrate that hydrostatic pressure improves albumin production and increases cytochrome P-450 (CYP) 1A2 expression levels in an aryl hydrocarbon-dependent manner in human hepatocytes. Increased albumin production and CYP function are commonly attributed to the impacts of shear stress in microfluidic experiments. Therefore, our results highlight evidence of a novel link between hydrostatic pressure and CYP metabolism and demonstrate that the spectrum of hepatocyte mechanosensitivity might be larger than previously thought.
Subject(s)
Basic Helix-Loop-Helix Transcription Factors/genetics , Cytochrome P-450 CYP1A2/genetics , Liver/metabolism , Mechanotransduction, Cellular/genetics , Receptors, Aryl Hydrocarbon/genetics , Cell Culture Techniques , Gene Expression Regulation/genetics , Hep G2 Cells , Hepatocytes/metabolism , Humans , Hydrostatic Pressure , Inactivation, Metabolic/genetics , Liver/drug effects , Signal Transduction/geneticsABSTRACT
We propose a novel mechanism for a nonequilibrium phase transition in a U(1)-broken phase of an electron-hole-photon system, from a Bose-Einstein condensate of polaritons to a photon laser, induced by the non-Hermitian nature of the condensate. We show that a (uniform) steady state of the condensate can always be classified into two types, namely, arising either from lower or upper-branch polaritons. We prove (for a general model) and demonstrate (for a particular model of polaritons) that an exceptional point where the two types coalesce marks the end point of a first-order-like phase boundary between the two types, similar to a critical point in a liquid-gas phase transition. Since the phase transition found in this paper is not in general triggered by population inversion, our result implies that the second threshold observed in experiments is not necessarily a strong-to-weak-coupling transition, contrary to the widely believed understanding. Although our calculation mainly aims to clarify polariton physics, our discussion is applicable to general driven-dissipative condensates composed of two complex fields.
ABSTRACT
The DNA damage response (DDR) is a DNA damage surveillance and repair mechanism that can limit the effectiveness of radiotherapy and DNA-damaging chemotherapy, commonly used treatment modalities in cancer. Two related kinases, ataxia telangiectasia mutated (ATM) and ATM and Rad3-related kinase (ATR), work together as apical proteins in the DDR to maintain genome stability and cell survival in the face of potentially lethal forms of DNA damage. However, compromised ATM signaling is a common characteristic of tumor cells, which places greater reliance on ATR to mediate the DDR. In such circumstances, ATR inhibition has been shown to enhance the toxicity of DNA damaging chemotherapy to many cancer cells in multiple preclinical studies, while healthy tissue with functional ATM can tolerate ATR inhibition. ATR therefore represents a very attractive anticancer target. Herein we describe the discovery of VX-970/M6620, the first ATR inhibitor to enter clinical studies, which is based on a 2-aminopyrazine core first reported by Charrier ( J. Med. Chem. 2011 , 54 , 2320 - 2330 , DOI: 10.1021/jm101488z ).
Subject(s)
Ataxia Telangiectasia Mutated Proteins/antagonists & inhibitors , Drug Design , Isoxazoles/pharmacology , Protein Kinase Inhibitors/pharmacology , Pyrazines/pharmacology , Animals , Ataxia Telangiectasia Mutated Proteins/chemistry , Ataxia Telangiectasia Mutated Proteins/metabolism , Cell Line , Isoxazoles/pharmacokinetics , Male , Models, Molecular , Protein Conformation , Protein Kinase Inhibitors/pharmacokinetics , Pyrazines/pharmacokinetics , Rats , Rats, Sprague-DawleyABSTRACT
All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.
Subject(s)
Liver/enzymology , Midazolam/pharmacokinetics , Animals , Drug Interactions , Humans , Liver/blood supply , Midazolam/pharmacology , Models, BiologicalABSTRACT
We predict the existence and dynamical stability of heptagraphene, a new graphitic structure formed of rings of 10 carbon atoms bridged by carbene groups yielding seven-membered rings. Despite the rectangular unit cell, the band structure is topologically equivalent to that of strongly distorted graphene. Density-functional-theory calculations demonstrate that heptagraphene has Dirac cones on symmetry lines that are robust against biaxial strain but which open a gap under shear. At high deformation values bond reconstructions lead to different electronic band arrangements in dynamically stable configurations. Within a tight-binding framework this richness of the electronic behavior is identified as a direct consequence of the symmetry breaking within the cell which, unlike other graphitic structures, leads to band gap opening. A combined approach of chemical and physical modification of graphene unit cell unfurls the opportunity to design carbon-based systems in which one aims to tune an electronic band gap.