Human Kinetic Data Research Articles

Estimation of Lower Extremity Joint Moments and 3D Ground Reaction Forces Using IMU Sensors in Multiple Walking Conditions: A Deep Learning Approach.

Human kinetics, specifically joint moments and ground reaction forces (GRFs) can provide important clinical information and can be used to control assistive devices. Traditionally, collection of kinetics is mostly limited to the lab environment because it relies on data that are measured from a motion capture system and floor-embedded force plates to calculate the dynamics via musculoskeletal models. This spatially limited method makes it extremely challenging to measure kinetics outside the laboratory in a variety of walking conditions due to the expensive device setup and large space required. Recently, employing machine learning with IMU sensors are suggested as an alternative method for biomechanical analyses. Although these methods enable estimating human kinetic data outside the laboratory by linking IMU sensor data with kinetics dataset, they are limited to show inaccurate kinetic estimates even in highly repeatable single walking conditions due to the employment of generic deep learning algorithms. Thus, this paper proposes a novel deep learning model, Kinetics-FM-DLR-Ensemble-Net for single limb prediction of hip, knee, and ankle joint moments and 3 dimensional Ground Reaction Forces (GRFs) using three IMU sensors on the thigh, shank, and foot under several representatives walking conditions in daily living, such as treadmill, level-ground, stair, and ramp. This is the first study that implements both joint moments and GRFs in multiple walking conditions using IMU sensors via deep learning. Our deep learning model is versatile and accurate for identifying human kinetics across diverse subjects and walking conditions and our model outperforms state-of-the-art deep learning model for kinetics estimation by a large margin.

Evidence of Direct Hepatic Secretion of Low density Lipoprotein (LDL) in Mice

<h3>Lead Author's Financial Disclosures</h3> Nothing to disclose. <h3>Study Funding</h3> National Lipid Association Junior Faculty Research Award 2020, NIH P01HL151328 and HL45095 (IJG). <h3>Background/Synopsis</h3> LDL is the major atherogenic lipoprotein causing atherosclerosis, leading to cardiovascular disease (CVD), the primary cause of morbidity and mortality in the United States. Lipoprotein lipase (LpL) is the rate limiting enzyme hydrolyzing triglyceride rich lipoproteins in the circulation. Current understanding is that LpL mediated hydrolysis of very low density lipoprotein (VLDL) generates cholesterol rich LDL particles in the circulation. However, evidence from in vitro studies as well as some human kinetic data suggest that the liver might directly secrete LDL into the circulation. <h3>Objective/Purpose</h3> In this study, we determine whether combined deficiency of lipoprotein lipase and hepatic LDL receptor (LDLR) would lead to decreased circulating LDL cholesterol (LDL-C) levels. <h3>Methods</h3> We used a mouse model of tamoxifen inducible global LpL deficiency (iLpl-/-). To knock down hepatic genes like LDLR and hepatic lipase (HL) we utilized anti sense oligonucleotides (ASOs). <h3>Results</h3> As expected, iLpl-/- mice display reduced plasma LDL-C levels compared to control mice (5 mg/dl vs 30 mg/dl). To determine whether LDL-C would increase with knock down of hepatic LDLRs, we used LDLR ASO in control and iLpl-/- mice. As anticipated, LDL-C levels increased in control mice to 150 mg/dl. Remarkably, plasma LDL-C also increased in iLpl-/- mice to levels similar to that of control mice. We then fed the mice a high cholesterol western diet for two weeks; this increased LDL-C levels equally in both mice to 300 mg/dl. When we overexpressed PCSK9 to inhibit LDLR in iLpl-/- mice, we again observed increases in LDL-C similar to control mice with PCSK9 overexpression. Further, to test if HL, another extracellular triglyceride lipase, is converting VLDL to LDL in iLpl-/- mice, we knocked down HL in control and iLpl-/- mice. HL knockdown did not alter LDL-C levels in control or iLpl-/- mice. <h3>Conclusions</h3> These data suggest the presence of direct LDL secretion from liver. We are investigating why this is apparent only with concomitant loss of LpL and LDLRs. We postulate that LDLRs have an additional gate-keeping function to halt secretion of newly synthesized LDL particles from the liver in addition to their well-established role in clearance of plasma LDL. When LDLRs are limiting or in patients with combined hyperlipidemia, direct LDL production may constitute a major source of circulating LDL. If so, this could uncover a novel approach to treat familial hypercholesterolemia.

Human variability in influx and efflux transporters in relation to uncertainty factors for chemical risk assessment

Transporters are divided into the ABC and SLC super-families, mediating the cellular efflux and influx of various xenobiotic and endogenous substrates. Here, an extensive literature search was performed to identify in vivo probe substrates for P-gp, BCRP and OAT1/3. For other transporters (e.g. OCT, OATP), no in vivo probe substrates could be identified from the available literature. Human kinetic data (Cmax, clearance, AUC) were extracted from 142 publications and Bayesian meta-analyses were performed using a hierarchical model to derive variability distributions and related uncertainty factors (UFs). For P-gp, human variability indicated that the kinetic default UF (3.16) would cover over 97.5% of healthy individuals, when considering the median value, while the upper confidence interval is exceeded. For BCRP and OAT1/3 human variability indicated that the default kinetic UF would not be exceeded while considering the upper confidence interval. Although limited kinetic data on transporter polymorphisms were available, inter-phenotypic variability for probe substrates was reported, which may indicate that the current default kinetic UF may be insufficient to cover such polymorphisms. Overall, it is recommended to investigate human genetic polymorphisms across geographical ancestry since they provide more robust surrogate measures of genetic differences compared to geographical ancestry alone. This analysis is based on pharmaceutical probe substrates which are often eliminated relatively fast from the human body. The transport of environmental contaminants and food-relevant chemicals should be investigated to broaden the chemical space of this analysis and assess the likelihood of potential interactions with transporters at environmental concentrations.

Aggregate exposure of the adult French population to pyrethroids

The French Nutrition and Health Survey (ENNS) reported higher biomarker levels of exposure to pyrethroids than those observed in North American and German biomonitoring studies. The authors therefore investigated aggregate exposure to permethrin as an initial case study because this compound is one of the most widely-used pyrethroid insecticides. We assessed several contamination sources—such as indoor and outdoor air, settled dust and diet—and several pathways, including oral, inhalation and dermal routes. We used permethrin exposure level estimations (computed from ENNS data) and a PBPK model calibrated with human kinetic data (from 6 individuals) to simulate an internal dose of cis- and trans-3-(2,2 dichlorovinyl)-2,2-dimethyl-(1-cyclopropane) carboxylic acid (cis- or trans-DCCA) in a population of 219 individuals. The urinary concentrations of cis- and trans -DCCA predicted by the PBPK model according to three permethrin exposure scenarios (“lower”, “intermediate”, and “upper”), were compared to the urinary levels measured in the ENNS study. The ENNS levels were between the levels simulated according to permethrin exposure scenarios “lower” and “intermediate”. The “upper” scenario led to an overestimation of the predicted urinary concentration levels of cis - and trans -DCCA compared to those measured in the ENNS study. The most realistic scenario was the “lower” one (permethrin concentration of left-censored data considered as 0). Using PBPK modeling, we estimated the contribution of each pathway and source to the internal dose. The main route of permethrin exposure was oral (98%), diet being the major source (87%) followed by dust (11%) then the dermal route (1.5%) and finally inhalation (0.5%).

Non-animal approaches for toxicokinetics in risk evaluations of food chemicals.

The objective of the present work was to review the availability and predictive value of non-animal toxicokinetic approaches and to evaluate their current use in European risk evaluations of food contaminants, additives and food contact materials, as well as pesticides and medicines. Results revealed little use of quantitative animal or human kinetic data in risk evaluations of food chemicals, compared with pesticides and medicines. Risk evaluations of medicines provided sufficient in vivo kinetic data from different species to evaluate the predictive value of animal kinetic data for humans. These data showed a relatively poor correlation between the in vivo bioavailability in rats and dogs versus that in humans. In contrast, in vitro (human) kinetic data have been demonstrated to provide adequate predictions of the fate of compounds in humans, using appropriate in vitro-in vivo scalers and by integration of in vitro kinetic data with in silico kinetic modelling. Even though in vitro kinetic data were found to be occasionally included within risk evaluations of food chemicals, particularly results from Caco-2 absorption experiments and in vitro data on gut-microbial conversions, only minor use of in vitro methods for metabolism and quantitative in vitro-in vivo extrapolation methods was identified. Yet, such quantitative predictions are essential in the development of alternatives to animal testing as well as to increase human relevance of toxicological risk evaluations. Future research should aim at further improving and validating quantitative alternative methods for kinetics, thereby increasing regulatory acceptance of non-animal kinetic data.

New specific and sensitive biomonitoring methods for chemicals of emerging health relevance.

In this publication the challenges to cope for the aim to obtain innovative biomonitoring methods in our laboratory are visualized for di(2-propylheptyl)phthalate, 2-mercaptobenzothiazole, 3,5-di-tert-butyl-4-hydroxytoluene, 4-nonylphenol, 4-tert-octylphenol, 3-(4-methylbenzylidene)camphor, 4,4'-methylene diphenyl diisocyanate, and Hexabromocyclododecane. For these substances new specific markers were explored based on animal or human kinetic data with urine being the preferred matrix compared to blood. The determination of these markers was complex in all cases, because the sample preparation as well as the detection by high performance liquid chromatography, capillary gas chromatography coupled to tandem mass spectrometers or high resolution mass spectrometry should enable the lowest possible detection limit by use of minimal biological sample volumes. To get a first hint of a possible background level, the analytical methods were applied to urine samples of about 40 persons for each chemical. For Di(2-propylheptyl)phthalate and 2-Mercaptobenzothiazole first results are presented from population biomonitoring.

Development of a human physiologically based pharmacokinetic (PBPK) model for dermal permeability for lindane.

Lindane is a neurotoxicant used for the treatment of lice and scabies present on human skin. Due to its pharmaceutical application, an extensive pharmacokinetic database exists in humans. Mathematical diffusion models allow for calculation of lindane skin permeability coefficients using human kinetic data obtained from in vitro and in vivo experimentation as well as a default compound-specific calculation based on physicochemical characteristics used in the absence of kinetic data. A dermal model was developed to describe lindane diffusion into the skin, where the skin compartment consisted of homogeneous dermal tissue. This study utilized Fick's law of diffusion along with chemical binding to protein and lipids to determine appropriate dermal absorption parameters which were then incorporated into a physiologically based pharmacokinetic (PBPK) model to describe in vivo kinetics. The estimation of permeability coefficients using chemical binding in combination with in vivo data demonstrates the advantages of combining physiochemical properties with a PBPK model to predict dermal absorption.

Bayesian Analysis of a Physiologically Based Pharmacokinetic Model for Perchloroethylene in Humans

Perchloroethylene (PCE) is a widely distributed pollutant in the environment, and is the primary chemical used in dry cleaning. PCE-induced liver cancer was observed in mice, and central nervous system (CNS) effects were reported in dry-cleaning workers. To support reconstruction of human PCE exposures, including the potential for CNS effects, an existing physiologically based pharmacokinetic (PBPK) model for PCE in the human (Covington et al., 2007) was modified by adding a brain compartment. A Bayesian approach, using Markov chain Monte Carlo (MCMC) analysis, was employed to re-estimate the parameters in the modified model by combining information from prior distributions for the model parameters and experimental data. Experimental data were obtained from five different human pharmacokinetic studies of PCE inhalation exposures ranging from 150 ppm to as low as 0.495 ppm. The data include alveolar or exhaled breath concentrations of PCE, blood concentrations of PCE and trichloroacetic acid (TCA), and urinary excretion of TCA. The PBPK model was used to predict target tissue dosimetry of PCE and its key metabolite, TCA, during and after the inhalation exposures. Posterior analysis was performed to see whether convergence criteria for each parameter were satisfied and whether the model with posterior distributions may be used to make accurate predictions of human kinetic data. With posteriors, the trend of percent of PCE metabolized in the liver at low concentrations was predicted under different exposure conditions. The 95th percentile for the fraction PCE metabolized at a concentration of 1 ppb was estimated to be 1.89%.

Uptake and Disposition of Inhaled Methanol Vapor in Humans

Methanol is a widely used solvent and a potential fuel for motor vehicles. Human kinetic data of methanol are sparse. As a basis for biological exposure monitoring and risk assessment, we studied the inhalation toxicokinetics of methanol vapor in four female and four male human volunteers during light physical exercise (50 W) in an exposure chamber. The relative uptake of methanol was about 50% (range 47-53%). Methanol in blood increased from a background level of about 20 to 116 and 244 microM after 2 h exposure at 0, 100 ppm (131 mg/m3) and 200 ppm (262 mg/m3), respectively. Saliva showed substantially higher levels than blood immediately after exposure. This difference disappeared in a few minutes; thereafter the concentrations and time courses in blood, urine, and saliva were similar, with half times of 1.4, 1.7, and 1.3 h, respectively. The postexposure decrease of methanol in exhaled air was faster, with a half time of 0.8 h. The methanol concentrations were approximately twice as high in all four types of biological samples at 200 compared to 100 ppm. No increase in urinary formic acid was seen in exposed subjects. Our study indicates non-saturated, dose-proportional kinetics of methanol up to 200 ppm for 2 h. No gender differences were detected. Similar, parallel patterns were seen with regard to the methanol time courses in blood, urine, and saliva, whereas the concentration in exhaled air decreased markedly faster. Thus, apart from blood and urine, saliva also seems suitable for biomonitoring of methanol exposure.

Determination of Biological Reference Values for Chlorpyrifos Metabolites in Human Urine Using a Toxicokinetic Approach

Urinary biomarkers of chlorpyrifos (CPF) exposure are often measured in field studies, although biological reference values (BRVs) are not yet available to assess health risks. This study aimed at proposing BRVs for CPF metabolites in workers' urine based on a toxicokinetic approach. As a first step, a toxicokinetic model was developed, using published human kinetic data, to link the absorbed dose of CPF under a variety of exposure routes and temporal scenarios to the urinary excretion of its major metabolites, 3,5,6-trichloro-2-pyridinol (3,5,6-TCP) and alkyl phosphates (AP). The model was then used to propose BRVs for CPF metabolites in urine below which workers should not experience adverse health effects. This was achieved by linking (1) a literature-reported, repeated CPF no-observed-effect level (NOEL) daily exposure dose for the inhibition of red-blood-cell acetylcholinesterase activity to a corresponding absorbed daily dose, and (2) this absorbed daily dose to the urinary excretion of CPF metabolites. Model simulations under a variety of exposure scenarios showed that the safest BRVs are obtained from a dermal exposure scenario with the slowest absorption rate compatible with available literature data rather than from respiratory or oral exposure scenarios. Also, model simulations showed that, for a given total absorbed dose, absorption over 8 hours results in smaller 3,5,6-TCP and AP urinary excretion rates than those obtained from the same dose absorbed over shorter durations. From these considerations, BRVs were derived by simulating an 8-hour dermal CPF exposure such that the total absorbed daily dose corresponds to the absorbed NOEL. The reference values are proposed in the form of total amounts of 3,5,6-TCP and AP metabolites excreted in urine over chosen time periods (24 and 48 hours).

Estimation of interindividual variation in oxidative metabolism of dichloromethane in human volunteers

A modified version of the original physiologically based pharmacokinetic (PBPK) model by Andersen et al. (1987) has been developed and used in conjunction with previously published human kinetic data for dichloromethane (DCM) metabolism and to assess interindividual variability in the rate of oxidative metabolism. Time-course data for 13 volunteers (10 males, 3 females) exposed to one or more concentrations of DCM (50 ppm, 100 ppm, 150 ppm, or 200 ppm) for 7.5 h were used to optimize the maximal rate of hepatic metabolism ( V maxC) through the cytochrome P450 pathway for each individual. DCM breath and blood concentrations were used, along with carboxyhemoglobin concentrations in blood and carbon monoxide (CO) concentrations in exhaled breath, to estimate the model parameters. Significant improvements in model fit were achieved when extrahepatic oxidative metabolism of DCM was added to the model structure. The 13 individual V maxC values ranged from 7.1 to 23.6 mg/h/kg 0.7 and appeared to be bimodally distributed. The distribution was not sex related and may be related to differential CYP2E1 induction. A comparison of the observed variation in V maxC values to other estimates of variability in the rate of oxidative metabolism and human CYP2E1 activity suggest a relatively narrow range in human hepatic activity toward DCM.

A Toxicokinetic Model for Predicting the Tissue Distribution and Elimination of Organic and Inorganic Mercury Following Exposure to Methyl Mercury in Animals and Humans. II. Application and Validation of the Model in Humans

The objective of this study was to develop a biologically based dynamical model describing the disposition kinetics of methyl mercury and its inorganic mercury metabolites in humans following different methyl mercury exposure scenarios. The model conceptual and functional representation was similar to that used for rats but relevant data on humans served to determine the critical parameters of the kinetic behavior. It was found that the metabolic rate of methyl mercury was on average 3 to 3.5 times slower in humans than in rats. Also, excretion rates of organic mercury from the whole body into feces and hair were 100 and 40 times smaller in humans, respectively, and urinary excretion of organic mercury in humans was found to be negligible. The human transfer rate of inorganic mercury from blood to hair was found to be 5 times lower than that of rats. On the other hand, retention of inorganic mercury in the kidney appeared more important in humans than in rats: the transfer rate of inorganic mercury from blood to kidney was 19 times higher than in rats and that from kidney to blood 19 times smaller. The excretion rate of inorganic mercury from the kidney to urine in humans was found to be twice that of rats. With these model parameters, simulations accurately predicted human kinetic data available in the published literature for different exposure scenarios. The model relates quantitatively mercury species in biological matrices (blood, hair, and urine) to theabsorbed dose and tissue burden at any point in time. Thus, accessible measurements on these matrices allow inferences of past, present, and future burdens. This couldprove to be a useful tool in assessing the health risks associated with various circumstances of methyl mercury exposure.

Rat to Human Extrapolation of HCFC-123 Kinetics Deduced from Halothane Kinetics: A Corollary Approach to Physiologically Based Pharmacokinetic Modeling

The goal of this study was to develop a human physiologically based pharmacokinetic (PBPK) model for the chemical HCFC-123 (2,2-dichloro-1,1,1-trifluoroethane) and its major metabolite, trifluoroacetic acid (TFA). No human kinetic data for HCFC-123 are available, thus a corollary approach was developed. HCFC-123 is a structural analog of the common anesthetic agent halothane (2-bromo-2-chloro-1,1,1-trifluoroethane) and follows a common pathway of oxidative biotransformation, resulting in the formation of the same metabolite, TFA. In this study, halothane models for rats and humans were developed and validated. Then the corollary approach was used to develop a human HCFC-123 model from a rat HCFC-123 model. This strategy was implemented by using a previously validated PBPK model for HCFC-123/TFA in the Fischer 344 rat as a template model for halothane in rats. Model predictions were then compared to, and were in good agreement with, measured values for the concentration of halothane in rat blood and fat tissue. A human PBPK model for halothane was developed. The identical model structure (with the exception of the description for the fat compartment) that was used to describe halothane and TFA in the rat was used for describing halothane and TFA in the human. Human physiological parameters for tissue volumes and flows were taken from the literature, and human tissue partition coefficients for halothane were measured in the laboratory. Based on reported similarity in metabolism of halothane by humans and rats, metabolic constants for halothane in the rat were used in the human model, and specific parameters describing the kinetics of TFA were estimated by optimization. The model was validated against human exposure data for halothane from six published studies (expired breath concentrations of halothane and serum/urine data for TFA). A similar approach was then used to derive a human HCFC-123 model for humans from the HCFC-123 rat model. The corollary approach described here illustrates the innovative use of template model structures to aid in the development and validation of models for structural analogs with similar metabolism and activity in biologic systems. Furthermore, given that the PBPK model adequately describes the kinetics of halothane in rats and humans and of HCFC-123 in rats, use of the human PBPK model is proposed for deriving dose–response estimates of human health risks in the absence of human kinetic data.

Sulbactam: Secondary mechanisms of action

Light and scanning electron microscopy showed that 0.25, 0.5 and 1 times the minimum inhibitory concentrations (MICs) of sulbactam (SULB) caused filament formation in different species of Enterobacteriaceae, while 2 and 4 times the MICs caused spheroplast formation and subsequent lysis. By using a competitive assay with 125I-penicillin X, SULB showed a primary affinity for the PBP 1a and PBP3 of Escherichia coli, as well as for the PBP1a of Proteus mirabilis. The bactericidal interaction of human polymorphonuclear leukocytes (PMN) and SULB against E. coli K-1 resistant to the bactericidal activity of human serum was studied in vitro; however, SULB concentrations showed variations in the medium according to human kinetic data. Under these conditions, bacterial growth occurred in Hanks balanced salt solution containing SULB, PMN, or SULB-PMN in combination. In addition, bactericidal activity was observed in serum, with a killing rate of 90% for PMN or SULB, and 95% for SULB-PMN in combination. The postantibiotic enhancement of PMN bactericidal function was assessed against E. coli K1 pretreated with 0.5 the MIC of SULB (32 μg/ml) for 0.5 hr. The 90% bacterial killing rate of PMN occurred by 1.5 hr for pretreated bacteria and by 2.5 hr for untreated bacteria. Furthermore, the luminol-enhanced chemiluminescence (CL) assay using an E. coli stimulus showed that SULB does not modify PMN activity.