Project description:This model is supplementary material of publication "Physiologically based metformin pharmacokinetics model of mice and scale-up to humans for the estimation of concentrations in various tissues" by Darta Maija Zake, Linda Zaharenko, JanisKurlovics, Vitalijs Komasilovs, Egils Stalidzans and Janis Klovins. This is a whole-body model representing the pharmacokinetics of metformin in the human body. The model is in the form of Ordinary differential equations and describes metformin concentration in 21 compartments. The model consists of 21 compartments (“compartments” in COPASI model) describing various tissues or tissue sub-compartments and body fluids of metformin action (venous and arterial plasma, red blood cells, intestine, kidney, heart, fat, muscle, brain, lungs, stomach, liver, portal vein, remainder, urine and feces). Body weight and the weight of all compartments is expressed as a volume in mL and for the calculations it is assumed that 1mL = 1g. The volumes of most compartments are calculated as a fraction of the body weight/volume, and the fractions are determined from literature data, the volumes of the stomach lumen and intestine lumen are fixed and do not change depending on the body weight. Similarly, the volume of external urine and feces is set to 1L, but those are “volumeless” compartments as they are only necessary for the calculation of metformin amount, not concentration. The model consists of 21 species (“species” in COPASI model) that correspond to the metformin concentrations in the 21 compartments. The initial concentrations for all the species are 0 nmol/mL as metformin is not produced in the body and can only be detected after dose administration. The model consists of 35 reactions – they describe the transport processes of metformin in the body. The reactions include local parameters that are involved only in that particular reaction and global parameters – parameters that are used in multiple reactions or are calculated depending on another parameter e.g. scale-up coefficients. The model consists of 62 global quantities – parameters involved in multiple reactions or necessary for another parameter calculation: 1.Parameters describing peroral metformin dose (Metformin Dose in Lumen in mg). 2.Parameter describing human physiology – body weight (in mL), cardiac output, blood flow to different compartments described as Q”compartment_name” (for example Qliver describes blood flow to the liver compartment). Qgfr refers to the glomerular filtration rate. 3.Parameters involved in the scale-up of the model •Tissue:plasma partition coefficients (Ktp) that were estimated in the mice model. •Kidney coefficient that is used for the scale-up of metformin elimination and is involved in the calculation of the rate parameters in the reactions “13.4. KidneyPlasma -> KidneyTissue” and “13.5. KidneyTissue -> KidneyTubular”. This parameter was determined using parameter estimation. •Intestine coefficient that is involved in the calculation of the intestinal reaction rates of the reactions (03.2. IntestineLumen -> Enterocytes (PMAT OCT3), 03.3. Enterocytes -> IntestineVascular (OCT1), 03.4. IntestineLumen -> IntestineVascular (Saturable), 03.6. IntestineLumen -> Enterocytes (Diffusion) , 03.7. IntestineLumen -> IntestineVascular (Diffusion)). The parmaeters for these reactions are taken from Proctor publication and the intectine coefficient is used for the scale-up from the cell-culture to the human intestine. 4.Parameters involved in the calculation of metformin amount in mg, these parameters are named mg”Compartment_name” (for example mgLiver describes the metformin amount in mg in the liver tissues). The time points of dose release are defined as “events” in COPASI and can be changed as necessary. The current model has 14 events and is set for a multiple-dose regimen for 7-day long twice-daily metformin administration. Time course simulations can be accessed through the section “Time Course” in this section the time duration and intervals can be changed. When time-course simulations are run three plots are created – Metformin amount in the 21 compartments, metformin concentrations in the compartments and reaction fluxes of all the reactions (see “Output Specifications” -> “Plots” to activate or deactivate plots). The time-course also includes multiple "Sliders" that allow to easily change 3 parameters - "Body Weight", "Cardiac Output", "Metformin Dose in Lumen in mg".

Project description:This model is supplementary material of publication "Physiologically based metformin pharmacokinetics model of mice and scale-up to humans for the estimation of concentrations in various tissues" by Darta Maija Zake, Linda Zaharenko, Janis Kurlovics, Vitalijs Komasilovs, Janis Klovins and Egils Stalidzans. The model is pre-set for simulation of a single peroral dose. This is a whole-body model representing the pharmacokinetics of metformin in the mouse body. The model is in the form of ordinary differential equations and describes metformin concentration in 20 compartments. The model consists of 20 compartments (“Compartments” in COPASI model) describing various tissues or tissue sub-compartments and body fluids of metformin action (venous and arterial plasma, intestine, kidney, heart, fat, muscle, brain, lungs, stomach, liver, portal vein, remainder urine and feces). Body weight and the weight of all compartments is expressed as a volume in mL and for the calculations it is assumed that 1mL = 1g. The volumes of most compartments are calculated as a fraction of the body weight/volume, and the fractions are determined from literature data, the volumes of the stomach lumen and intestine lumen are fixed and do not change depending on the body weight. Similarly, the volume of external urine and feces is set to 1mL, but those are “volumeless” compartments as they are only necessary for the calculation of metformin amount, not concentration. The model consists of 20 species (“Species” in COPASI model) that correspond to the metformin concentrations in the 20 compartments. The initial concentrations for all the species are 0 nmol/mL as metformin is not produced in the body and can only be detected after dose administration. The model consists of 33 reactions – they describe the transport processes of metformin in the body. The reactions include local parameters that are involved only in that particular reaction and global parameters – parameters that are used in multiple reactions or are calculated depending on another parameter e.g. scale-up coefficients. The model consists of 52 global quantities – parameters involved in multiple reactions or necessary for another parameter calculation: 1.Parameters describing metformin dose – either in peroral (Metformin Dose in Lumen in mg) or intravenous (Metformin Dose in Plasma in mg). 2.Parameter describing mice physiology – body weight (in mL), cardiac output, blood flow to different compartments described as Q”compartment_name” (for example Qliver describes blood flow to the liver compartment). Qgfr refers to the glomerular filtration rate. 3.Tissue:plasma partition coefficients (Ktp) that are necessary for the scale-up to humans. 4.Parameters involved in the calculation of metformin amount in mg, these parameters are named mg”Compartment_name” (for example mgLiver describes the metformin amount in mg in the liver tissues). The time points of dose release are defined as “events” in COPASI and can be changed as necessary. Time course simulations can be accessed through the section “Time Course” in this section the time duration and intervals can be changed. When time-course simulations are run three plots are created – Metformin amount in the 20 compartments, metformin concentrations in the compartments and reaction fluxes of all the reactions (see “Output Specifications” -> “Plots” to activate or deactivate plots).

Project description:This model is supplementary material of publication "Physiologically based metformin pharmacokinetics model of mice and scale-up to humans for the estimation of concentrations in various tissues" by Darta Maija Zake, Linda Zaharenko, JanisKurlovics, Vitalijs Komasilovs, Egils Stalidzans and Janis Klovins. This is a whole-body model representing the pharmacokinetics of metformin in the mouse body. The model is in the form of ordinary differential equations and describes metformin concentration in 20 compartments. The model consists of 20 compartments (“Compartments” in COPASI model) describing various tissues or tissue sub-compartments and body fluids of metformin action (venous and arterial plasma, intestine, kidney, heart, fat, muscle, brain, lungs, stomach, liver, portal vein, remainder urine and feces). Body weight and the weight of all compartments is expressed as a volume in mL and for the calculations it is assumed that 1mL = 1g. The volumes of most compartments are calculated as a fraction of the body weight/volume, and the fractions are determined from literature data, the volumes of the stomach lumen and intestine lumen are fixed and do not change depending on the body weight. Similarly, the volume of external urine and feces is set to 1mL, but those are “volumeless” compartments as they are only necessary for the calculation of metformin amount, not concentration. The model consists of 20 species (“Species” in COPASI model) that correspond to the metformin concentrations in the 20 compartments. The initial concentrations for all the species are 0 nmol/mL as metformin is not produced in the body and can only be detected after dose administration. The model consists of 33 reactions – they describe the transport processes of metformin in the body. The reactions include local parameters that are involved only in that particular reaction and global parameters – parameters that are used in multiple reactions or are calculated depending on another parameter e.g. scale-up coefficients. The model consists of 52 global quantities – parameters involved in multiple reactions or necessary for another parameter calculation: 1.Parameters describing metformin dose – either in peroral (Metformin Dose in Lumen in mg) or intravenous (Metformin Dose in Plasma in mg). 2.Parameter describing mice physiology – body weight (in mL), cardiac output, blood flow to different compartments described as Q”compartment_name” (for example Qliver describes blood flow to the liver compartment). Qgfr refers to the glomerular filtration rate. 3.Tissue:plasma partition coefficients (Ktp) that are necessary for the scale-up to humans. 4.Parameters involved in the calculation of metformin amount in mg, these parameters are named mg”Compartment_name” (for example mgLiver describes the metformin amount in mg in the liver tissues). The time points of dose release are defined as “events” in COPASI and can be changed as necessary. Time course simulations can be accessed through the section “Time Course” in this section the time duration and intervals can be changed. When time-course simulations are run three plots are created – Metformin amount in the 20 compartments, metformin concentrations in the compartments and reaction fluxes of all the reactions (see “Output Specifications” -> “Plots” to activate or deactivate plots). Also plotting the species result after 0.5 hours will reproduce the literature results.

Project description:Purpose: Photoperiod is known to cause physiological changes in seasonal mammals, including body weight, physical activity, and reproductive status. Because cats are seasonal breeders, we recently tested the effects of day length on resting metabolic rate, voluntary physical activity, and food intake. In that study, resting metabolic rate, physical activity, and food intake to maintain body weight were greater in cats exposed to long days vs. short days. Because photoperiod has also been demonstrated to affect adipose tissue gene expression in several species, including dairy cows, sheep, and Siberian hamsters, the objective of this study was to determine the effects of day length on the adipose transcriptome profile of cats as assessed by RNA-seq. Methods: Ten healthy adult neutered male domestic shorthair cats were used in a randomized crossover design study. During two 12-wk periods, cats were exposed to either short days (8 hr light:16 hr dark) or long days (16 hr light:8 hr dark). Cats were fed a commercial diet to maintain baseline body weight. Subcutaneous adipose biopsies were collected at wk 12 of each period for RNA isolation and Illumina sequencing. Results: A total of 578 million sequences (28.9 million/sample) were generated by Illumina sequencing. Using a raw p value of P<0.005, 170 mRNA transcripts were differentially expressed between short day- and long day-housed cats. Of the 170 transcripts highlighted, 25 annotated transcripts were up-regulated, while 116 annotated transcripts were down-regulated by long days. Another 29 un-annotated transcripts (name and function not known) were also different between groups. In general, adipose tissue of long day-housed cats had greater expression of genes involved with cholesterol trafficking, fatty acid synthesis and immune function, and lower expression of genes involved with cell cycle and growth, cell development and structure, and protein processing, when compared to short day-housed cats. Subcutaneous adipose tissue mRNA profiles of healthy adult neutered male cats exposed to short days (8 hr light: 16 hr dark) or long days (16 hr light: 8 hr dark) using Illumina sequencing.

Project description:Purpose: Photoperiod is known to cause physiological changes in seasonal mammals, including body weight, physical activity, and reproductive status. Because cats are seasonal breeders, we recently tested the effects of day length on resting metabolic rate, voluntary physical activity, and food intake. In that study, resting metabolic rate, physical activity, and food intake to maintain body weight were greater in cats exposed to long days vs. short days. Because photoperiod has also been demonstrated to affect adipose tissue gene expression in several species, including dairy cows, sheep, and Siberian hamsters, the objective of this study was to determine the effects of day length on the adipose transcriptome profile of cats as assessed by RNA-seq. Methods: Ten healthy adult neutered male domestic shorthair cats were used in a randomized crossover design study. During two 12-wk periods, cats were exposed to either short days (8 hr light:16 hr dark) or long days (16 hr light:8 hr dark). Cats were fed a commercial diet to maintain baseline body weight. Subcutaneous adipose biopsies were collected at wk 12 of each period for RNA isolation and Illumina sequencing. Results: A total of 578 million sequences (28.9 million/sample) were generated by Illumina sequencing. Using a raw p value of P<0.005, 170 mRNA transcripts were differentially expressed between short day- and long day-housed cats. Of the 170 transcripts highlighted, 25 annotated transcripts were up-regulated, while 116 annotated transcripts were down-regulated by long days. Another 29 un-annotated transcripts (name and function not known) were also different between groups. In general, adipose tissue of long day-housed cats had greater expression of genes involved with cholesterol trafficking, fatty acid synthesis and immune function, and lower expression of genes involved with cell cycle and growth, cell development and structure, and protein processing, when compared to short day-housed cats.

Project description:Measuring global gene expression using cDNA or oligonucleotide microarrays is an effective approach to understanding the complex mechanisms of the effects of radiation. However, few studies have been carried out that investigate gene expression in vivo after prolonged exposure to low-dose-rate radiation. In this study, C57BL/6J mice were continuously irradiated with ?-rays for 485 days at dose-rates of 0.032 – 13 ?Gy/min. Gene expression profiles in the kidney and testis from irradiated and unirradiated mice were analyzed, and differentially expressed genes were identified. A combination of pathway analysis and hierarchical clustering of differentially expressed genes revealed that expression of genes involved in mitochondrial oxidative phosphorylation was elevated in the kidney after irradiation at the dose-rates of 0.65 ?Gy/min and 13 ?Gy/min. Expression of cell cycle-associated genes was not profoundly modulated in the kidney, in contrast to the response to acute irradiation, suggesting a threshold in the dose-rate for modulation of the expression of cell cycle-related genes in vivo following exposure to radiation. We demonstrated that changes to the gene expression profile in the testis were largely different from those in the kidney. The Gene Ontology categories “DNA metabolism”, “response to DNA damage” and “DNA replication” overlapped significantly with the clusters of genes whose expression decreased with an increase in the dose-rate to the testis. These observations provide a fundamental insight into the organ-specific responses to low-dose-rate radiation. Key Words: kidney, low-dose-rate, radiation, microarray, mitochondrial oxidative phosphorylation, testis 3 biological replicates for each experimental group were analysed. GSE14290_Kidney_raw_data.csv contains the raw data for GSM357146, GSM357425, GSM357426, GSM357452 to GSM357460. GSE14290_Testis_raw_data.csv contains the raw data for GSM357471 to GSM357482. In these files, the sample identifiers are included in the column headers.

Project description:For the purpose of establishing a mice model for sever COVID-19 , mice were infected intranasally with SARS-CoV-2 two days after pulmonary application of low-dose ricin. The goal of this study is to perform a comparative transcriptomic analysis by exploring the alterations in gene expression in lungs of mice exposed to low-dose ricin and SARS-CoV-2 (samples OR009-OR012) compared to lungs of mice infected solely with SARS-CoV-2 (48 hr after infection, samples OR021-OR024) or mice exposed to low-dose ricin (96 hr post exposure,samples OR005-OR008)) or mice exposed to lethal dose of ricin (48 hr post exposure, samples OR013-OR016). Methods: Total RNA was extracted from lungs of ricin intoxicated mice (intranasally exposure to 1.7 µg/kg or 10 µg/kg ricin ) or of SARS-CoV-2 infected mice (intranasal administration of 5 x 106 PFU), using the RNeasy mini kit (Qiagen). RNA-seq libraries were constructed and sequencing of 100bp paired-end was performed on the Illumina NovaSeq 6000 system. Sequencing yielded about 22M reads per sample that were mapped to the mouse genome. RNA ratios were clustered using partitioning clustering. We next carried out Ingenuity Pathway Analysis (IPA). Results: Principal component analysis revealed distinct transcriptional signatures between lungs mice exposed to low-dose ricin and infected with SARS-CoV-2 compared to lungs of mice infected solely with SARS-CoV-2 or mice exposed to low-dose ricin (96 hr post exposure) or mice exposed to lethal dose of ricin (48 hr post exposure). Differentially Expressed Genes (DEGs) were defined as such when having false discovery rate (FDR) value (p-adjusted) of ≤ 0.01 and a fold change (FC) of ≥ 1.5 or ≤ 0.66. Analysis of Low-dose-ricin-treated mice transcripts resulted in the detection of 6684 DEGs, 55% upregulated and 45% downregulated. Similarly, in Low-dose-ricin-treated mice infected with SARS-CoV-2, we found a total of 6044 differentially expressed genes, 52% induced and 48% repressed. Considerably fewer (797, 67% upregulated and 33% downregulated) differentially expressed genes were identified in lungs of mice infected only with SARS-CoV-2.

Dataset Information

Sluka2016 - Acetaminophen PBPK

Publications

A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

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