Long-Term Releasing Kinetics of Chromium from Leather

The release of chromium from leather inevitably results in potential risks and this study is conducted to investigate the long-term releasing behavior. The leaching tests proceed using water at solid to liquid ratio of 1:20 and rotational speed 60 r/min for 240 hours to simulate the release of chrome leather under natural conditions. The experimental data successfully fit with the Pseudo-second-order equation, Elovich equation, and Weber-Morris model, indicating the long-term leaching behavior of chromium in heterogeneous leather is controlled by liquid-solid film, while the interparticle and intraparticle diffusion also play important roles. The leachable chromium accounts for 2.8-4.5% total chromium in leather and increases with temperature. The Three-compartment model depicts the releasing process as rapid, slow, and very slow stages, and temperature mainly affected the very slow stage. The amount of released chromium in rapid and slow stages slightly increases with temperature, which could be used to assess the hazard of chrome leather.

Advancement of pharmacokinetic models of iohexol in patients aged 70 years or older with impaired kidney function

Plasma clearance of iohexol is a pivotal metric to quantify glomerular filtration rate (GFR), but the optimal timing and frequency of plasma sampling remain to be assessed. In this study, we evaluated the impact of a Bayesian estimation procedure on iohexol clearance estimates, and we identified an optimal sampling strategy based on data in individuals aged 70+. Assuming a varying number of random effects, we re-estimated previously developed population pharmacokinetic two- and three-compartment models in a model development group comprising 546 patients with iohexol concentration data up to 300 min post injection. Model performance and optimal sampling times were assessed in an evaluation group comprising 104 patients with reduced GFR and concentration data up to 1440 min post injection. Two- and three-compartment models with random effects for all parameters overestimated clearance values (bias 5.07 and 4.40 mL/min, respectively) and underpredicted 24-h concentrations (bias − 14.5 and − 12.0 µg/ml, respectively). Clearance estimates improved distinctly when limiting random effects of the three-compartment model to clearance and central volume of distribution. Two blood samples, one early and one 300 min post injection, were sufficient to estimate iohexol clearance. A simplified three-compartment model is optimal to estimate iohexol clearance in elderly patients with reduced GFR.

Estimation of the Loading Dose for Target-Controlled Infusion of Dexmedetomidine. Reply to Eleveld et al. Comment on “Morse et al. A Universal Pharmacokinetic Model for Dexmedetomidine in Children and Adults. J. Clin. Med. 2020, 9, 3480”

The parameters for a three-compartment model described by Morse and colleagues [...]

The role of endoplasmic reticulum in in vivo cancer FDG kinetics

A recent result obtained by means of an in vitro experiment with cancer cultured cells has configured the endoplasmic reticulum as the preferential site for the accumulation of 2-deoxy-2-[18F]fluoro-D-glucose (FDG). Such a result is coherent with cell biochemistry and is made more significant by the fact that the reticular accumulation rate of FDG is dependent upon extracellular glucose availability. The objective of the present paper is to confirm in vivo the result obtained in vitro concerning the crucial role played by the endoplasmic reticulum in FDG cancer metabolism. This study utilizes data acquired by means of a Positron Emission Tomography scanner for small animals in the case of CT26 models of cancer tissues. The recorded concentration images are interpreted within the framework of a three-compartment model for FDG kinetics, which explicitly assumes that the endoplasmic reticulum is the dephosphorylation site for FDG in cancer cells. The numerical reduction of the compartmental model is performed by means of a regularized Gauss-Newton algorithm for numerical optimization. This analysis shows that the proposed three-compartment model equals the performance of a standard Sokoloff’s two-compartment system in fitting the data. However, it provides estimates of some of the parameters, such as the phosphorylation rate of FDG, more consistent with prior biochemical information. These results are made more solid from a computational viewpoint by proving the identifiability and by performing a sensitivity analysis of the proposed compartment model.

Vertebral fractures and luxations in dogs and cats part 2: treatment and surgery options

Assessing the presence of vertebral column instability is essential in animals with vertebral fractures or luxations. Spinal instability is most commonly assessed using a three-compartment model and unstable vertebral fractures and luxations require surgical stabilisation. In cases of compression of the spinal cord (by haematoma, traumatic intervertebral disc extrusion or bone fragment), decompression surgery is necessary. Prompt surgery prevents additional spinal cord damage, but the overall condition of the patient, including any concurrent injuries, needs to be continually kept in mind. The vertebral column can be stabilised using multiple techniques, such as screws, pins, polymethylmetacrylate and plating techniques, as well as external stabilisation and spinal stapling. Complications of spinal surgeries include haemorrhage, infection, neurological deterioration, particularly in cases of spinal stabilisations, implant loosening and failure.

Increasing age is independently associated with higher free water in non-active MS brain - A multi-compartment analysis using FAST-T2

PurposeTo explore the relationship between the cerebral cortical perivascular space (PVS) and aging in non-active MS subjects by using the multi-echo T2 relaxometry based cerebrospinal fluid fraction (CSFF) map.MethodsMulti-echo spiral T2 data from 111 subjects with non-active multiple sclerosis (MS) were retrospectively investigated by fitting the T2 data into a three-compartment model, the three water compartments including myelin water, intra-extracellular water, and cerebrospinal fluid. Segmentation of T1w image was performed to get the region of interest (ROI) in cerebral cortical regions. The white matter lesion segmentation was conducted using a convolutional neural network (CNN) based segmentation tool. The CSFF in the ROIs were correlated with age by controlling the gender, white matter hyperintensity lesion burden, and MS disease duration. Multiple linear models were created for the analysis of aging effect on the CSFF.ResultsThe ROI analysis shows that the CSFF in the cerebral cortical regions (temporal, occipital, parietal, front, hippo, and mtl) are significantly linear increasing with age (p<0.01). The intra-extracellular water fraction (IEWF) in the ROIs are significantly linear decreasing (p<0.01).ConclusionThe multi-echo T2 based three-compartment model can be used to quantify the CSFF. The linear increase of CSF water contents in the cerebral cortical regions indicates increased perivascular space load in cortex with aging. The quantification of CSFF may provide a way to understand the glymphatic clearance function in aging and neurodegenerations.HighlightsMR T2 relaxometry is a valid method to quantify the cerebrospinal fluid fraction (CSFF) in cerebral cortical regionsThe CSFF in the cerebral cortical regions are positively correlated with age by controlling the white matter lesion load in non-active MS subjects.Quantification of cerebral CSFF may reflect the perivascular space load in cortex and better interpret the disease progression in neurodegenerative disease, such as MS.

End-tidal to Arterial Gradients and Alveolar Deadspace for Anesthetic Agents

Background According to the “three-compartment” model of ventilation-perfusion () inequality, increased scatter in the lung under general anesthesia is reflected in increased alveolar deadspace fraction (Vda/Va) customarily measured using end-tidal to arterial (a-a) partial pressure gradients for carbon dioxide. a-a gradients for anesthetic agents such as isoflurane are also significant but have been shown to be inconsistent with those for carbon dioxide under the three-compartment theory. The authors hypothesized that three-compartment Vda/Va calculated using partial pressures of four inhalational agents (Vda/Vag) is different from that calculated using carbon dioxide (Vda/Vaco2) measurements, but similar to predictions from multicompartment models of physiologically realistic “log-normal” distributions. Methods In an observational study, inspired, end-tidal, arterial, and mixed venous partial pressures of halothane, isoflurane, sevoflurane, or desflurane were measured simultaneously with carbon dioxide in 52 cardiac surgery patients at two centers. Vda/Va was calculated from three-compartment model theory and compared for all gases. Ideal alveolar (Pag) and end-capillary partial pressure (Pc’g) of each agent, theoretically identical, were also calculated from end-tidal and arterial partial pressures adjusted for deadspace and venous admixture. Results Calculated Vda/Vag was larger (mean ± SD) for halothane (0.47 ± 0.08), isoflurane (0.55 ± 0.09), sevoflurane (0.61 ± 0.10), and desflurane (0.65 ± 0.07) than Vda/Vaco2 (0.23 ± 0.07 overall), increasing with lower blood solubility (slope [Cis], –0.096 [–0.133 to –0.059], P &lt; 0.001). There was a significant difference between calculated ideal Pag and Pc’g median [interquartile range], Pag 5.1 [3.7, 8.9] versus Pc’g 4.0[2.5, 6.2], P = 0.011, for all agents combined. The slope of the relationship to solubility was predicted by the log-normal lung model, but with a lower magnitude relative to calculated Vda/Vag. Conclusions Alveolar deadspace for anesthetic agents is much larger than for carbon dioxide and related to blood solubility. Unlike the three-compartment model, multicompartment scatter models explain this from physiologically realistic gas uptake distributions, but suggest a residual factor other than solubility, potentially diffusion limitation, contributes to deadspace. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New