Kinetic Mathematical Model Research Articles

Neuro‐fuzzy interface and mathematical modeling of rehydration kinetics and dynamic vapor sorption behavior of novel no‐cooking rice

A novel no-cooking rice was developed from a low-amylose paddy using instant controlled pressure drop (ICPD) assisted novel parboiling method with an improvisation of the traditional method of production of the no-cooking rice named as “komal chawal.” Autoclaving and ICPD treatments were employed for the preparation of no-cooking rice. Autoclaving involved the treatment of rice at 1 atm(g) pressure for the preparation of pressure-parboiled rice, while ICPD treatment with instant decompression was carried out within an experimental setup at treatment pressures (TP) of .2–.4 MPa(g) to produce ICPD treated rice. The step of soaking was omitted for the samples parboiled by the ICPD treatment. Effects of ICPD treatment pressure were assessed for obtaining better milling yield, color, texture, microstructure, and other properties. Paddy treated at .4 MPa(g) with instant decompression yielded the best quality rice in terms of those quality parameters. The rehydration behavior of the optimized rice samples was analyzed by applying the neuro-fuzzy interface and mathematical modeling. In addition, dynamic vapor sorption-based isotherm kinetics was investigated using the enthalpy–entropy compensation theory, demonstrating adequate sigmoid isotherm behavior of the rice. Practical Applications Application of instant control pressure drop (ICPD) has shown improvement in the rehydration properties of komal chawal with an increased head rice yield as compared to similar product produced by conventional parboiling. When freshly harvested low amylose paddy with relatively high moisture are used, the ICPD treatment permitted komal chawal production without the initial paddy soaking step, which is otherwise essential in a conventional parboiling process of komal chawal production. Hence, ICPD treatment as a novel technological intervention has the potential to shorten the komal chawal production process, and yield products with better rehydration and better chances of acceptance in market.

Efficient Leaching Process of Valuable Elements from Gibbsite Ore Materials in Talet Seleim, Southwestern, Sinai, Egypt Using Green and Ecofriendly Lixiviant Agent: Optimization, Kinetic and Thermodynamic Study

Here, valuable elements in Talet Seleim, Southwestern, Sinai, Egypt was leaching using methanesulfonic acid (MSA) as an environmental-friendly and ecofriendly lixiviant agent. The effects of methane sulfonic acid (MSA) concentration, time of leaching reaction, temperature, liquid/solid ratio (L/S) and stirring speed on dissolution of valuable elements in MSA were studied. The optimized conditions for dissolution of various metals were: methane sulfonic acid concentration; 150g/L, dissolution time; 300 min, temperature; 363K, liquid to solid ratio; 4 ml/g and stirring speed; 400 rpm/min. The dissolution efficiency of Zn, Cu, Ni and Pb are 81.8%, 79.47%, 76.6%, and 70.7%, respectively under the optimal conditions. Different mathematical kinetic models for the dissolution process in MSA were studied since it is very important for economic metal dissolution. The experimental data were best fitted by fitted by pseudo-second-order homogeneous reaction model, whilst lead (Pb) was best fitted the diffusion through the product or ash layer. The activation energies of the dissolution processes of different metals were evaluated. Overall, the MSA leaching system provides an efficient, clean and environmental-friendly method for dissolution of valuable metals. It can be a promising alternative for inorganic acids.

Mathematical modeling of the early modeled CA-125 longitudinal kinetics (KELIM-PARP) as a pragmatic indicator of rucaparib efficacy in patients with recurrent ovarian carcinoma in ARIEL2 & STUDY 10.

PARP inhibitors (PARPi) have revolutionized the management of advanced ovarian carcinoma, and were investigated as forefront treatment in recurrent disease. The objective was to explore if mathematical modeling of the early longitudinal CA-125 kinetics could be used as a pragmatic indicator of the subsequent rucaparib efficacy, like it is for platinum-based chemotherapy. The datasets of ARIEL2 and Study 10 involving recurrent HGOC patients treated with rucaparib were retrospectively investigated. The same strategy as those successfully developed for platinum chemotherapy, based on CA-125 ELIMination rate constant K (KELIM™), was implemented. Individual values of rucaparib-adjusted KELIM (KELIM-PARP) were estimated based on the longitudinal CA-125 kinetics during the first 100 treatment days, and then scored as favorable (KELIM-PARP ≥1.0) or unfavorable (KELIM-PARP <1.0). The prognostic value of KELIM-PARP regarding treatment efficacy (radiological response, and progression-free survival (PFS)) was assessed using univariable/multivariable analyses, with respect to platinum-sensitivity and homologous recombination deficiency (HRD) status. The data from 476 patients were assessed. The CA-125 longitudinal kinetics during the first 100-treatment days could be accurately assessed using the KELIM-PARP model. In patients with platinum-sensitive diseases, BRCA mutational status KELIM-PARP score and were associated with subsequent complete/partial radiological responses (KELIM-PARP: odds-ratio=2.81, 95% CI 1.86-4.52), and PFS (KELIM-PARP: hazard-ratio=0.67, 95% CI 0.50-0.91). The patients with BRCA-wild type cancer and favorable KELIM-PARP experienced long PFS with rucaparib regardless of HRD. In platinum-resistant disease patients, KELIM-PARP was associated with subsequent radiological response (odds-ratio=2.80, 95% CI 1.82-4.72). This proof-of-concept study confirms the early CA-125 longitudinal kinetics during rucaparib in recurrent HGOC patients are assessable by mathematical modeling, to generate individual a KELIM-PARP score associated with the subsequent efficacy. This pragmatic strategy might be useful for selecting the patients for PARPi-based combination regimens, when identifying efficacy biomarker is challenging. Further assessment of this hypothesis is warranted. The present study was supported by Clovis Oncology with a grant to academic research association.

Using tumor growth rate to inform treatment efficacy in pancreatic adenocarcinoma: From the metastatic to the neoadjuvant setting.

726 Background: The development of new treatments in oncology is a long, costly, and, too often, unsuccessful process. Methods for screening agents earlier in development and strategies for conducting smaller randomized controlled trials are needed. Methods: We used a mathematical model of tumor growth kinetics fit to serial radiographic tumor measurements or CA19-9 values to estimate rates of exponential tumor growth [g] and decay [d] during treatment for pancreatic ductal adenocarcinoma (PDAC). Results: We retrospectively collected and analyzed data from 2691 patients with stage III-IV PDAC who were enrolled in five clinical trials or were included in two large real-world data sets from Columbia University Irving Medical Center and Veterans Administration Medical Centers. Using log-rank comparison of Kaplan-Meier plots by quartile of g, we found that in patients with metastatic PDAC g correlates highly with overall (OS) and progression-free survival (PFS) (p&lt;0.001), with slower g associated with improved survival in this population. Pairwise comparisons showed significantly slower median g in the experimental arm versus control arm in the pivotal trials analyzed (p&lt;0.001). At the individual patient level, g was significantly faster for liver metastases as compared to primary pancreatic tumors and g consistently increased towards the end of therapy (often a threefold increase) suggesting development of chemoresistance. In addition to utility in the metastatic setting, a pilot analysis of data from a prospective study of patients treated with gemcitabine + docetaxel + capecitabine (GTX) in the neoadjuvant setting suggests that the emergence of a detectable g during neoadjuvant therapy may portend worse OS following surgery though sample size was small (n=45, median OS with detectable g 13.6 m v 33.1 without detectable g, p =0.35). Conclusions: We applied a tumor growth model to the data of over 2500 patients with PDAC and showed that g is inversely associated with survival in this population. Given the strong association between g and survival, g could be useful in clinical trials as an informative endpoint to expedite the assessment of novel therapies for the treatment of PDAC. Furthermore, g offers valuable patient-level data, including trends in resistance and variations in growth rate by metastatic disease site We plan to evaluate whether the emergence of g during neoadjuvant therapy should be considered a prompt to change treatment regimens.

Research of the Solutions Proximity of Linearized and Nonlinear Problems of the Biogeochemical Process Dynamics in Coastal Systems

The article considers a non-stationary three-dimensional spatial mathematical model of biological kinetics and geochemical processes with nonlinear coefficients and source functions. Often, the step of analytical study in models of this kind is skipped. The purpose of this work is to fill this gap, which will allow for the application of numerical modeling methods to a model of biogeochemical cycles and a computational experiment that adequately reflects reality. For this model, an initial-boundary value problem is posed and its linearization is carried out; for all the desired functions, their final spatial distributions for the previous time step are used. As a result, a chain of initial-boundary value problems is obtained, connected by initial–final data at each step of the time grid. To obtain inequalities that guarantee the convergence of solutions of a chain of linearized problems to the solution of the original nonlinear problems, the energy method, Gauss’s theorem, Green’s formula, and Poincaré’s inequality are used. The scientific novelty of this work lies in the proof of the convergence of solutions of a chain of linearized problems to the solution of the original nonlinear problems in the norm of the Hilbert space L2 as the time step τ tends to zero at the rate O(τ).

Inhalation of virus-loaded droplets as a clinically plausible pathway to deep lung infection.

Respiratory viruses, such as SARS-CoV-2, preliminarily infect the nasopharyngeal mucosa. The mechanism of infection spread from the nasopharynx to the deep lung-which may cause a severe infection-is, however, still unclear. We propose a clinically plausible mechanism of infection spread to the deep lung through droplets, present in the nasopharynx, inhaled and transported into the lower respiratory tract. A coupled mathematical model of droplet, virus transport and virus infection kinetics is exercised to demonstrate clinically observed times to deep lung infection. The model predicts, in agreement with clinical observations, that severe infection can develop in the deep lung within 2.5-7days of initial symptom onset. Results indicate that while fluid dynamics plays an important role in transporting the droplets, infection kinetics and immune responses determine infection growth and resolution. Immune responses, particularly antibodies and T-lymphocytes, are observed to be critically important for preventing infection severity. This reinforces the role of vaccination in preventing severe infection. Managing aerosolization of infected nasopharyngeal mucosa is additionally suggested as a strategy for minimizing infection spread and severity.

Heterogenous Iron Oxide Assemblages for Use in Catalytic Ozonation: Reactivity, Kinetics, and Reaction Mechanism.

Heterogeneous catalytic ozonation (HCO) has gained increasing attention as an effective process to remove refractory organic pollutants from industrial effluents. However, widespread application of HCO is still limited due to the typically low efficacy of catalysts used and matrix passivation effects. To this end, we prepared an Al2O3-supported Fe catalyst with high reactivity via a facile urea-based heterogeneous precipitation method. Due to the nonsintering nature of the preparation method, a heterogeneous catalytic layer comprised of γ-FeOOH and α-Fe2O3 is formed on the Al2O3 support (termed NS-Fe-Al2O3). On treatment of a real industrial effluent by HCO, the presence of NS-Fe-Al2O3 increased the removal of organics by ∼100% compared to that achieved with a control catalyst (i.e., α-Fe2O3/Al2O3 or γ-FeOOH/Al2O3) that was prepared by a conventional impregnation and calcination method. Furthermore, our results confirmed that the novel NS-Fe-Al2O3 catalyst demonstrated resistance to the inhibitory effect of high concentration of chloride and sulfate ions usually present in industrial effluent. A mathematical kinetic model was developed that adequately describes the mechanism of HCO process in the presence of NS-Fe-Al2O3. Overall, the results presented here provide valuable guidance for the synthesis of effective and robust catalysts that will facilitate the wider industrial application of HCO.

Kinetic Modeling of the Anodic Degradation of Ni-EDTA Complexes: Insights into the Reaction Mechanism and Products

In this study, an electrochemical advanced oxidation process (EAOP) was employed to effectively degrade complexes of nickel and ethylenediaminetetraacetic acid (EDTA) present in electroless nickel plating wastewaters. Our results show that Ni-EDTA complexes can be effectively degraded by an EAOP with degradation of the complexes occurring at/near the anode surface via interaction with hydroxyl radicals generated on water splitting. Our results further show that the rate of Ni-EDTA degradation is not a function of the rate of any particular chemical reaction but, rather, is controlled by the rate of transport of Ni-EDTA to the anode surface. The oxidation of EDTA to smaller noncomplexing entities releases Ni2+, which is subsequently deposited onto the cathode as Ni0. While complete Ni-EDTA removal and Ni recovery are achieved within 2 h, the overall TOC removal by EAOP is limited, with only 50% TOC removal achieved after 2 h of treatment. The low affinity of small molecular weight EDTA degradation products (such as formic acid, glycine, oxamic acid, and acetic acid) for the anode surface limits oxidation of these compounds and overall TOC removal by the anodic oxidation process. We have developed a mathematical kinetic model that satisfactorily describes Ni-EDTA removal, Ni recovery, and TOC removal over a range of Ni and EDTA concentrations and provides a good description of the oxidation of various EDTA degradation intermediates. The mathematical model developed here, when coupled with the hydrodynamics of the electrochemical cell using a computational fluid dynamics tool, can assist in both cell design and the selection of operating parameters such that the performance of the EAOP process for Ni-EDTA degradation and TOC removal is optimized.

CENTRAL COMPOSITE FACE-CENTERED DESIGN-BASED OPTIMISATION, DEVELOPMENT AND CHARACTERISATION OF FAVIPIRAVIR-LOADED PLGA NANOPARTICLES

Objective: The objective of this study is to fabricate favipiravir-loaded PLGA nanoparticulate systems that can increase the solubility along with the sustained release of favipiravir. Methods: The favipiravir-loaded Poly (D, L-lactic-co-glycolide) (PLGA) nanoparticulate systems were prepared by the nanoprecipitation method. A 3-factor, 2-level central composite face-centered design was employed to study the effect of formulation variables having a concentration of PLGA, polyvinyl alcohol (PVA) and stirring rate as critical formulation attributes and particle size, drug entrapment efficiency, and percentage cumulative drug release as critical quality attributes on prepared favipiravir nanoparticles. Drug interaction studies were performed by FTIR and DSC. Surface morphology was analysed by scanning electron microscopy (FEI Quanta 250 FEG, USA). Particle size, zeta potential, and polydispersity index were analysed by the nanoparticle analyser SZ-100 (HORIBA Scientific nanopartica, Japan). In vitro drug release studies were performed using a UV-Visible spectrophotometer at λmax 234 nm. In vitro drug release data obtained was fitted into various mathematical kinetic models. Results: The numerical optimization process predicted the level of PLGA concentration as 69.96 mg, PVA concentration as 4.99%, and stirring rate as 799 rpm for the optimised formulation. The low percentage of relative error for the optimised formulation confirms the validation of the model. The optimised formulation had a 77.65% entrapment efficiency with a particle size of 109.7 nm and the percent cumulative drug release showed 86.46% drug release over 720 min. The drug release was found to follow first-order release kinetics with anomalous non-Fickian diffusion kinetics. Conclusion: Hence, such an attempt at fabrication of favipiravir-loaded PLGA nanoparticulate systems may be useful for sustained release of drug over 720 min.

Characteristics of latex coatings for steel protection against corrosion

This paper examines the kinetics of corrosion for steel St3 samples covered with a latex coating 69B–2k, manufactured by Kapitel LLC (Irkutsk), by analysing gravimetric tests performed using steel samples. A 3 wt % solution of sodium chloride was used as an electrolyte. The accuracy of the obtained results was confirmed by carrying out at least two parallel experiments. Prior to coating, the metal surface of samples was carefully prepared as per GOST R 9.907-2007. Film coatings were applied onto the metal surface by threefold dipping of samples in liquid latex followed by drying within 24 hours. The quality of the coating prior to and following the experiments was assessed visually and by microphotography. Gravimetric studies were carried out under temperature control (25 ± 0.2°C) in the working area. At the same time, changes in the sample mass were recorded over a controlled time interval (from 1 to 24 hours). The results of weighing samples obtained prior to and following the experiments were analysed using a kinetic flowchart, in which the type of reaction is defined in stages in a natural sequence. Kinetic analysis of the gravimetric results confirmed the absence of characteristic signs associated with chemical interactions on the surface of steel St3 coated with latex 69B-2k. Out of the known mathematical models of phenomenological kinetics, it is admissible to use a first-order equation to describe the course of a simple reaction during heterogeneous interaction, where the penetration of reagents through a latex film comprises a limiting stage. The kinetic analysis showed that it is necessary to study the properties of latex films; a strategy for further corrosion studies was determined.

Structural, kinetic, and thermodynamic aspects of insulin aggregation.

Given the significance of protein aggregation in proteinopathies and the development of therapeutic protein pharmaceuticals, revamped interest in assessing and modelling the aggregation kinetics has been observed. Quantitative analysis of aggregation includes data of gradual monomeric depletion followed by the formation of subvisible particles. Kinetic and thermodynamic studies are essential to gain key insights into the aggregation process. Despite being the medical marvel in the world of diabetes, insulin suffers from the challenge of aggregation. Physicochemical stresses are experienced by insulin during industrial formulation, storage, delivery, and transport, considerably impacting product quality, efficacy, and effectiveness. The present review briefly describes the pathways, mathematical kinetic models, and thermodynamics of protein misfolding and aggregation. With a specific focus on insulin, further discussions include the structural heterogeneity and modifications of the intermediates incurred during insulin fibrillation. Finally, different model equations to fit the kinetic data of insulin fibrillation are discussed. We believe that this review will shed light on the conditions that induce structural changes in insulin during the lag phase of fibrillation and will motivate scientists to devise strategies to block the initialization of the aggregation cascade. Subsequent abrogation of insulin fibrillation during bioprocessing will ensure stable and globally accessible insulin for efficient management of diabetes.

Functionalized nanohybrids with rod shape for improved chemo-phototherapeutic effect against cancer by sequentially generating singlet oxygen and carbon dioxide bubbles.

The application of hybrid nanocarriers is expected to play an active role in improving treatment of chemotherapy and phototherapy. Herein, a nanohybrid with a core of mesoporous silica nanorods and shell of folate-functionalized zeolite imidazole framework (ZIF-8/FA) was synthesized via polydopamine (PDA)-mediated integration. A chemotherapeutic drug (DOX), bubble generator (NH4HCO3, ABC), and photosensitive agent (ICG) were simultaneously loaded into the delivery system to construct smart ZIF-8/FA-coated mesoporous silica nanorods (IDa-PRMSs@ZF). We found that ICG endowed the designed delivery system with a moderate photothermal conversion efficiency of 26.06% and the capacity to release 1O2. The produced hyperthermia caused ABC to decompose and further generate carbon dioxide bubbles, thereby facilitating DOX release, sequentially. Importantly, the underlying mechanism was also investigated using mathematical kinetic modeling. The tumor inhibition rate of IDa-PRMSs@ZF under NIR irradiation reached 83.8%. This study provides a promising strategy based on rod-shaped nanohybrids for effective combination antitumor therapy.

Plasma SARS-CoV-2 RNA elimination and RAGE kinetics distinguish COVID-19 severity.

Identifying biomarkers causing differential SARS-CoV-2 infection kinetics associated with severe COVID-19 is fundamental for effective diagnostics and therapeutic planning. In this work, we applied mathematical modelling to investigate the relationships between patient characteristics, plasma SARS-CoV-2 RNA dynamics and COVID-19 severity. Using a straightforward mathematical model of within-host viral kinetics, we estimated key model parameters from serial plasma viral RNA (vRNA) samples from 256 hospitalised COVID-19+ patients. Our model predicted that clearance rates distinguish key differences in plasma vRNA kinetics and severe COVID-19. Moreover, our analyses revealed a strong correlation between plasma vRNA kinetics and plasma receptor for advanced glycation end products (RAGE) concentrations (a plasma biomarker of lung damage), collected in parallel to plasma vRNA from patients in our cohort, suggesting that RAGE can substitute for viral plasma shedding dynamics to prospectively classify seriously ill patients. Overall, our study identifies factors of COVID-19 severity, supports interventions to accelerate viral clearance and underlines the importance of mathematical modelling to better understand COVID-19.

Математическое моделирование макрокинетики термолиза сложных углеводородных систем

Stochastic mathematical models of thermolysis kinetics of complex oil-like hydrocarbon systems using mathematical statistics and the theory of random processes are considered. Mathematical modeling shows that the thermolysis process is collective,non-ergodic and non-stationary. The criteria for which hydrocarbon systems obey the kinetic laws of the first order and Abraham are established. Using the example of thermolysis of high-viscosity Alshacha oil, it is shown that the kinetics of the release of gaseous products of thermolysis are better described by models of stationary kinetics, and the models of the release of residues and distillates by models of non-stationary kinetics. The established regularities can be used in modeling thermal and thermocanalytic processes of petrochemistry and oil refining.

EVALUATION OF THE EFFECT OF PETROLEUM HYDROCARBONS ON THE OXYGEN REGIME OF A SHALLOW WATER

The paper covers the influence of petroleum hydrocarbons on the oxygen regime of a shallow water, as well as on zooplankton populations sensitive to lack of oxygen and oil pollution even at their low concentrations. A mathematical model of biological kinetics is constructed taking into account the number of abiotic and biotic factors that directly affect the water ecosystem: the movement of the water environment, microturbulent diffusion, temperature regime, illumination, wind stresses, salinity, concentration of oxygen dissolved in water. The model is implemented in a software focused on a high-performance computer system. Nonlinear dependences in the rate of growth of zooplankton concentrations are introduced, taking into account the influence of oil pollution. This makes it possible to determine their dynamics in conditions of insufficient oxygen supply with spatial and temporal variability of temperature and illumination. The problem discretization is based on the difference scheme that takes into account the partial occupancy of the computational cells. This made it possible to increase the simulation accuracy of hydrobiological processes and phenomena

MATHEMATICAL MODELING AND ECOLOGICAL DESIGN OF THE MARINE SYSTEMS TAKING INTO ACCOUNT MULTI-SCALE TURBULENCE USING REMOTE SENSING DATA

The paper considers a mathematical model of biological kinetics and geochemical cycles based on a system of convection-diffusion equations with nonlinear coefficients, supplemented by a spatially inhomogeneous three-dimensional mathematical model of wave hydrodynamics of a shallow reservoir, with a refined coefficient of turbulent vertical exchange. The task of monitoring the water surface in order to detect phytoplankton spots involves the creation and verification of effective methods for clustering these objects on the surface of reservoirs, in particular, restoring their boundaries based on remote sensing data. The article uses multispectral satellite images as sounding data. Based on the obtained images of plankton populations, the initial conditions for mathematical models of biogeochemical cycles can be determined, on the basis of which prognostic calculations are performed.

Mathematical Modeling of the Inhibition Kinetics of Malachite Green Decolorization by Staphylococcus aureus

Basic Green 4 or Malachite Green (MG) is an important dye that found great usage in controlling fish pathogens. The use of MG has been banned but developing, and third-world countries still found applications for this dye. Bioremediation of dyes using microorganisms is on the rise. The ability to accurately predict the rate of bioremediation relies upon the gathering of the accurate rate of decolourisation, which is often inhibited at high concentrations of the toxicant. Various secondary models such as Monod, Haldane, Teissier, Aiba, Yano and Koga, Hans-Levenspiel, Webb and the Luong models were utilized to fit the specific decolourisation rate, and most of them show visually acceptable fitting except Monod and Teissier. The best model based on statistical analysis was Hans-Levenspiel with the highest value for the adjusted coefficient of determination and the lowest values for RMSE, AICc, HQC and BIC and the closest value to 1.0 for accuracy and bias factors. The Hans-Levenspiel model was found to conform to normality tests and is adequate to be used to fit the experimental data. The normality tests carried out using tests such as the Kolmogorov-Smirnov, Wilks-Shapiro and the D'Agostino-Pearson omnibus K2 test shows that the model pass the normality tests with p &gt;0.05 for all normality tests carried out. The experimental data obtained indicates that Malachite Green is toxic and slows down the rate of decolourisation at higher concentrations. The maximum MG specific biodegradation rate (qmax), half-saturation concentration (KS), maximum allowable MG concentration (Sm), and the shape factors (n and m) were 0.136 h-1, 0.56 mg/L, 2691 mg/L, -33.31 and 35.12, respectively. The parameters obtained from this exercise can be utilized to model the bioremediation of MG in the future.

Input function and modeling for determining bone metabolic flux using [18 F] sodium fluoride PET imaging: A step-by-step guide.

Studies of skeletal metabolism using measurements of bone metabolic flux (Ki ) obtained with [18 F] sodium fluoride ([18 F]NaF) positron emission tomography (PET) scans have been used in clinical research for the last 30 years. The technique has proven useful as an imaging biomarker in trials of novel drug treatments for osteoporosis and investigating other metabolic bone diseases, including chronic kidney disease mineral and bone disorder. It has also been shown to be valuable in metastatic bone disease in breast cancer patients and may have potential in other cancer types, such as prostate cancer, to assess early bone fracture risk. However, these studies have usually required a 60-min dynamic PET scan and measurement of the arterial input function (AIF), making them difficult to translate into the clinic for diagnostic purposes. We have previously proposed a simplified method that estimates the Ki value at an imaging site from a short (4-min) static scan and venous blood samples. A key advantage of this method is that, by acquiring a series of static scans, values of Ki can be quickly measured at multiple sites using a single injection of the tracer. To date, the widespread use of [18 F]NaF PET has been limited by the need to measure the AIF required for the mathematical modeling of tracer kinetics to derive Ki and other kinetic parameters. In this report, we review different methods of measuring the AIF, including direct arterial sampling, the use of a semi-population input function (SP-AIF), and image-derived input function, the latter two requiring only two or three venous blood samples obtained between 30 and 60min after injection. We provide an SP-AIF model and a spreadsheet for calculating Ki values using the static scan method that others can use to study bone metabolism in metabolic and metastatic bone diseases without requiring invasive arterial blood sampling. The method shortens scan times, simplifies procedures, and reduces the cost of multicenter trials without losing accuracy or precision.

Kinetic Mathematical Modeling of Oxidative Phosphorylation in Cardiomyocyte Mitochondria.

Oxidative phosphorylation (OXPHOS) is an oxygen-dependent process that consumes catabolized nutrients to produce adenosine triphosphate (ATP) to drive energy-dependent biological processes such as excitation-contraction coupling in cardiomyocytes. In addition to in vivo and in vitro experiments, in silico models are valuable for investigating the underlying mechanisms of OXPHOS and predicting its consequences in both physiological and pathological conditions. Here, we compare several prominent kinetic models of OXPHOS in cardiomyocytes. We examine how their mathematical expressions were derived, how their parameters were obtained, the conditions of their experimental counterparts, and the predictions they generated. We aim to explore the general landscape of energy production mechanisms in cardiomyocytes for future in silico models.

Electrochemical Reduction of Nitrate with Simultaneous Ammonia Recovery Using a Flow Cathode Reactor.

The presence of excessive concentrations of nitrate in industrial wastewaters, agricultural runoff, and some groundwaters constitutes a serious issue for both environmental and human health. As a result, there is considerable interest in the possibility of converting nitrate to the valuable product ammonia by electrochemical means. In this work, we demonstrate the efficacy of a novel flow cathode system coupled with ammonia stripping for effective nitrate removal and ammonia generation and recovery. A copper-loaded activated carbon slurry (Cu@AC), made by a simple, low-cost wet impregnation method, is used as the flow cathode in this novel electrochemical reactor. Use of a 3 wt % Cu@AC suspension at an applied current density of 20 mA cm-2 resulted in almost complete nitrate removal, with 97% of the nitrate reduced to ammonia and 70% of the ammonia recovered in the acid-receiving chamber. A mathematical kinetic model was developed that satisfactorily describes the kinetics and mechanism of the overall nitrate electroreduction process. Minimal loss of Cu to solution and maintenance of nitrate removal performance over extended use of Cu@AC flow electrode augers well for long-term use of this technology. Overall, this study sheds light on an efficient, low-cost water treatment technology for simultaneous nitrate removal and ammonia generation and recovery.