13C Metabolic Flux Analysis Service - Creative Proteomics Metabolomics

Q: What is the difference between 13C metabolic flux analysis and static metabolomics?

Static metabolomics measures metabolite concentrations (pool sizes) at a single time point, which cannot determine whether an increase in a metabolite is due to accelerated synthesis or blocked consumption. 13C‑MFA uses stable carbon isotope tracers and mathematical modeling to quantify the in vivo reaction rates (fluxes) and directional carbon routing through pathways.

Q: How do I choose the best 13C tracer for my biological question?

Tracer selection depends on the target pathway branch point. [1,2‑13C2]glucose is ideal for quantifying the split ratio between glycolysis and the oxidative pentose phosphate pathway; [U‑13C6]glucose measures glycolytic rate, PDH vs. PC entry, and overall TCA carbon contribution; and [U‑13C5]glutamine resolves oxidative vs. reductive TCA cycle flux.

Q: What is the difference between isotopic steady‑state MFA and dynamic (INST‑MFA)?

Isotopic steady‑state MFA requires cells to be cultured until isotopic labeling in intermediate pools reaches equilibrium (constant MIDs over time), which is standard for fast‑growing microbial and mammalian cell cultures. Isotopically nonstationary MFA (INST‑MFA) measures time‑resolved labeling trajectories (seconds to minutes) and is required for slow‑growing cells, photosynthetic organisms, or systems with large nutrient storage pools.

Q: Why is natural isotope abundance correction necessary in 13C‑MFA?

Naturally occurring heavy isotopes (1.1% 13C, 0.37% 15N, 0.2% 18O, 29Si/30Si from derivatization reagents) introduce artificial mass shifts in measured mass spectra. We use validated deconvolution algorithms (IsoCor, AccuCor) to subtract natural abundance contributions, ensuring that model fitting is based strictly on tracer‑derived labeling.

Q: How do you ensure statistical confidence in estimated metabolic fluxes?

We perform Chi‑square (χ²) goodness‑of‑fit testing to assess whether the stoichiometric model adequately fits the experimental data. Furthermore, we compute non‑linear 95% confidence intervals using Profile Likelihood methods, which test parameter identifiability and reveal whether specific fluxes are tightly constrained by the measurements.

Q: Why is rapid sub‑second quenching critical for sample preparation?

Intracellular metabolites in central pathways have rapid turnover times (often milliseconds to seconds). Standard room‑temperature washes or trypsinization cause immediate metabolic shifts and label scrambling. Our sub‑zero (-80 °C) organic solvent quenching instantly arrests enzymatic activity, capturing the true in vivo metabolic state.

Q: What sample types can be analyzed with your 13C‑MFA platform?

Our platform accommodates adherent mammalian cells, suspension cultures, primary cells, microbial fermentations (bacteria, yeast, fungi), plant tissues, and isolated perfused organs. Custom sampling and extraction protocols are optimized for each matrix.

13C Metabolic Flux Analysis — Resolving In Vivo Reaction Rates

Static metabolite profiling reveals pool sizes but cannot determine whether an altered concentration reflects increased pathway synthesis, reduced consumption, or redirected branch-point flux. 13C metabolic flux analysis (13C-MFA) solves this fundamental limitation by tracking the transfer of stable carbon-13 isotopes through intracellular biochemical networks to calculate the actual in vivo reaction rates (fluxes) of enzymatic steps.

As part of our comprehensive metabolic flux analysis service, targeted 13C-MFA delivers quantitative insights into carbon skeleton distribution. It enables you to:

(i) Differentiate mitochondrial carbon entry via pyruvate dehydrogenase (PDH) versus pyruvate carboxylase (PC) anaplerosis

(ii) Quantify the exact split ratio between glycolysis and the oxidative pentose phosphate pathway (PPP)

(iii) Resolve forward oxidative TCA cycling versus IDH-mediated reductive carboxylation for lipid synthesis

(iv) Map carbon overflow and nutrient partitioning under genetic knockouts, environmental perturbations, or therapeutic interventions.

What Analytical Challenges Do We Solve in 13C Fluxomics?

Accurate flux calculation requires precise isotopic measurements, rigorous correction routines, and identifiable network models. Creative Proteomics resolves key industry bottlenecks through an integrated workflow that is:

Isotopically Resolved: High-resolution Orbitrap mass spectrometry (>140,000 FWHM) resolves 13C isotopologues from overlapping 15N, 2H, and 18O isobaric species, ensuring pure mass isotopologue distributions (MIDs).
Quantitatively Constrained: Extracellular exchange rates (glucose, lactate, glutamine, amino acids) are measured concurrently via targeted metabolomics panels to provide absolute boundary conditions for stoichiometric fitting.
Statistically Validated: Elementary Metabolic Unit (EMU) algorithms combined with non-linear parameter estimation calculate 95% profile likelihood confidence intervals, establishing parameter identifiability and eliminating ill-conditioned models.
Artifact-Free: Fast sub-zero solvent quenching arrests enzymatic turnover in sub-seconds, preserving true in vivo labeling states.

Targeted 13C Tracer Selection Strategies: Resolving Specific Metabolic Nodes

Creative Proteomics provides custom stable-isotope tracer configurations tailored to specific biological questions and metabolic branch points across mammalian, microbial, and plant systems.

1. Standard Central Carbon Tracing Panels

Tracer Configuration	Target Pathway Resolution & Readout
[1,2-¹³C₂]Glucose	Resolves the split ratio between glycolysis (generating M+2 lactate/pyruvate) and the oxidative pentose phosphate pathway (releasing ¹³CO₂ to yield M+1 lactate/pyruvate) within our pentose phosphate pathway metabolic flux analysis framework.
[U-¹³C₆]Glucose	Measures glycolytic rate, pyruvate entry into TCA via PDH (M+2 citrate) vs. PC (M+3 malate, M+3/M+5 citrate), and downstream anaplerotic networks in our glycolytic pathway metabolic flux analysis service.
[U-¹³C₅]Glutamine	Differentiates forward oxidative TCA cycle flux (M+4 succinate, fumarate, malate) from reverse reductive carboxylation (M+5 citrate, M+3 malate) supporting lipid biosynthesis in our TCA cycle pathway metabolic flux analysis.

2. Advanced Tracing & Co-Substrate Panels

Tracer Configuration	Target Pathway Resolution & Readout
[1-¹³C]Glucose & [6-¹³C]Glucose	Independent parallel labeling experiments quantifying non-oxidative PPP reversibility and transketolase/transaldolase exchange kinetics.
[U-¹³C₃]Lactate & [U-¹³C₃]Pyruvate	Quantifies exogenous lactate/pyruvate uptake, oxidation, and gluconeogenic flux in liver and cancer tissue models within our central carbon metabolic flux analysis module.
[U-¹³C₁₆]Palmitate & [1,2-¹³C₂]Acetate	Measures beta-oxidation rate, acetyl-CoA pool dilution, and de novo lipogenesis in our fatty acid metabolic flux analysis.
[U-¹³C₃]Serine & [U-¹³C₂]Glycine	Tracks one-carbon unit generation, folate cycle flux, and purine precursor synthesis in our one-carbon metabolic flux analysis.

3. Customization & Add-ons

Category	Options
Custom Tracer Synthesis	Deuterium (2H), nitrogen-15 (15N), or dual-labeled isotopes (13C/15N) tailored to client metabolic models
Dynamic / INST-MFA	Short-time-scale labeling for systems not in isotopic steady state via dynamic and INST metabolic flux analysis
Extracellular Rate Panels	Quantitative measurement of medium consumption and secretion rates for absolute flux anchoring
Complex Matrices	Optimized protocols for 3D spheroids, tissue slices, co-cultures, plant organs, and fermentation broths

Why Choose Our 13C Metabolic Flux Analysis Service?

High-Resolution Mass Spectrometry Platform
Ultra-high-resolution Orbitrap MS (>140,000 FWHM) eliminates spectral interference between 13C and other heavy isotopes (15N, 2H), providing highly accurate mass isotopologue distributions without chemical derivatization bias.
Statistically Constrained EMU Network Modeling
We implement Elementary Metabolic Unit (EMU) algorithms in INCA and 13CFLUX2, evaluating parameter identifiability, Chi-square (χ²) goodness-of-fit, and rigorous 95% profile likelihood confidence intervals.
Matrix-Specific Cryogenic Quenching Protocols
Standardized rapid sub-zero organic solvent quenching (-80 °C) arrests cellular enzymatic activity in sub-seconds, preventing post-harvest metabolic changes.
Parallel & Multi-Tracer Experimental Capability
We design parallel labeling schemes (e.g. [1,2-13C2]glucose + [U-13C5]glutamine) fitted simultaneously within a unified stoichiometric model to resolve complex, overlapping metabolic networks.

Instrumentation & Method Parameters for 13C Isotopologue Profiling

Analytical Platform

High-Resolution LC-Orbitrap MS (Primary Platform)

Mass Spectrometer: Thermo Scientific Orbitrap Exploris 240 / 480 & Q-Exactive HF-X

Ionization Mode: Electrospray Ionization (ESI), Positive & Negative Polarity Switching

LC System: Vanquish Horizon UHPLC System

Chromatography: HILIC (SeQuant ZIC-pHILIC) & Reversed-Phase Ion-Pairing

Target Intermediates: Intact phosphorylated hexoses (G6P, F6P), trioses (DHAP, 3PG, PEP), organic acids (citrate, alpha-KG, succinate, malate), amino acids, and nucleotides

Method Performance

Parameter	Typical Specification
Mass Resolving Power	Up to 240,000 FWHM at m/z 200
Mass Accuracy	< 1.5 ppm internal calibration
MID Analytical Precision	CV ≤ 1.0% across replicate injections
Linear Dynamic Range	3.5–4 orders of magnitude
Injection Volume	Typically 2–5 μL
Polarity Switching	Fast positive/negative cycle

GC-MS & High-Field NMR (Orthogonal Platforms)

GC-MS provides robust fragment-level positional constraints for derivatized amino acids and organic acids, while our NMR-based metabolic flux analysis platform provides non-destructive positional isotopomer quantification.

GC-MS System: Agilent 7890B GC coupled with 5977B MSD, EI mode (70 eV)
GC Derivatization: MOX-TBDMS and TMS derivatization for organic acids and amino acids
NMR Platform: Bruker Avance III HD 600 MHz Spectrometer equipped with cryoprobe

Quality Control & Data Validation

Instrument Performance QC: Monitored retention time reproducibility (CV < 0.5%) and peak symmetry
Natural Abundance Correction: Mathematical deconvolution of natural isotope contributions (13C, 18O, 15N, 29Si, 30Si) using IsoCor / AccuCor algorithms
Mass Balance Verification: Measured substrate uptake and product excretion rates applied as hard stoichiometric constraints

Thermo Scientific Orbitrap Exploris High-Resolution LC-MS

Thermo Scientific Orbitrap Exploris (Figure from Thermo Fisher)

SCIEX Triple Quad™ 6500+ (Figure from Sciex)

Agilent 7890B / 5977B GC-MS (Figure from Agilent)

Bruker Avance III HD 600 MHz NMR Spectrometer

Bruker Avance III HD 600 MHz NMR (Figure from Bruker)

13C Metabolic Flux Analysis Workflow — A Step-by-Step Guide

Study Feasibility & Network Formulation

We review your research objectives, culture conditions, and candidate pathways, constructing a stoichiometric model with mapped carbon atom transitions.

13C Tracer Incubation & Sub-Second Quenching

Cells or microorganisms are cultured with validated 13C tracers. Enzymatic activity is arrested in sub-seconds using pre-cooled (-80 °C) organic solvent mixtures.

High-Resolution Mass Spectrometry Acquisition

Extracts are analyzed via LC-Orbitrap MS or GC-MS to determine 13C mass isotopologue distributions (MIDs). Culture media are analyzed for extracellular exchange rates.

Natural Abundance Correction & QC Audit

Raw isotopologue signals are corrected for natural 13C background, derivatization atoms, and instrument isotopic overlap using validated deconvolution algorithms.

EMU Computational Flux Modeling & Validation

Corrected MIDs and boundary rates are fitted into EMU network models. Flux rates are calculated with Chi-square (χ²) goodness-of-fit testing and 95% profile likelihood confidence intervals.

How to Prepare and Submit Samples for 13C-MFA

Sample Type	Amount Required	Preparation & Quenching Instructions	Storage & Shipping
Adherent Mammalian Cells	1–10 × 10⁶ cells (e.g. 60/100 mm dish)	Aspirate medium (<3 s), rapid wash with ice-cold saline, add pre-cooled (-80 °C) 80:20 MeOH:H2O, scrape on dry ice. Avoid trypsinization. Retain parallel plate for cell count in mammalian cell metabolic flux analysis.	Store at −80 °C; ship on dry ice
Suspension Cells	2–10 × 10⁶ cells	Rapid cold centrifugation (4 °C, <2 min) or direct sub-zero buffered quenching (-40 °C). Avoid prolonged room-temperature washes.	Store at −80 °C; ship on dry ice
Microbial Broth / Fermentation	2–10 mg dry cell weight (OD-adjusted)	Fast vacuum filtration (<2 s) with immediate liquid nitrogen filter immersion, or cold methanol quenching for microbial metabolic flux analysis. Retain supernatant for exchange rate analysis.	Store at −80 °C; ship on dry ice
Conditioned Media (Supernatant)	≥ 200 μL	Collect from matched labeling time points, centrifuge (10,000 × g, 5 min) to remove debris, aliquot supernatant for extracellular rate quantification.	Store at −80 °C; ship on dry ice
Plant Tissues (Leaves / Roots)	20–100 mg wet weight	Instant freeze-clamping in liquid nitrogen, cryo-pulverization under liquid nitrogen conditions without thawing for plant metabolic flux analysis.	Store at −80 °C; ship on dry ice

Notes

Always retain parallel uncultured medium blanks and conditioned media to quantify extracellular consumption and secretion rates
Do not use enzymatic detachment (trypsin) for adherent cultures; perform direct in-plate cold solvent quenching
Maintain continuous cold chain (−80 °C or dry ice) during sample storage and transport
Contact our technical team prior to collecting specialized or low-biomass matrices

Deliverables: What You Receive from 13C Metabolic Flux Analysis

Natural-Abundance-Corrected MID Matrix: Fractional isotopic abundances (M+0 to M+n) for all target metabolites (.csv / Excel).
Extracellular Consumption & Secretion Rates: Measured absolute boundary rates (mmol/gDW/h or nmol/10⁶ cells/h).
Reaction Network & EMU Model Files: Complete stoichiometric equations, carbon atom transition matrices, and executable project files (.xml / INCA / 13CFLUX2).
Fitted Metabolic Flux Values & Confidence Intervals: Estimated net (v_net) and exchange (v_xch) fluxes with 95% profile likelihood confidence intervals.
Statistical Diagnostics & Residuals: Chi-square (χ²) goodness-of-fit statistics, sum of squared residuals (SSR), and measured vs. simulated correlation plots.
Publication-Ready Pathway Flux Maps: High-resolution vector graphics (PDF/SVG) illustrating intracellular carbon distribution with flux-scaled arrow widths, supported by comprehensive fluxomics data analysis.

$13C Mass Isotopologue Distribution Bar Plot showing fractional isotopic labeling across glycolytic and TCA cycle intermediates$

Representative 13C mass isotopologue distribution (MID) bar plot displaying natural-abundance-corrected fractional labeling (M+0 to M+6) across central carbon intermediates.

Quantitative Metabolic Flux Map of Central Carbon Metabolism

Quantitative central carbon metabolic flux map illustrating glycolysis, pentose phosphate pathway, and TCA cycle fluxes with arrow widths scaled to absolute fluxes.

Profile likelihood confidence interval analysis demonstrating nonlinear 95% statistical boundaries and parameter identifiability for key branch-point fluxes.

Statistical Goodness-of-Fit and Chi-Square Residual Diagnostics Plot

Statistical goodness-of-fit diagnostic plot showing measured versus simulated MID correlation and weighted residual distribution with chi-square cutoff threshold.

Applications of 13C Metabolic Flux Analysis

Our 13C metabolic flux analysis service supports researchers across academic, biotechnology, and biopharma programs:

Cancer Metabolism & Drug Target Validation

Quantify Warburg effect glycolysis, glutamine addiction, and reductive carboxylation under small-molecule metabolic enzyme inhibitor treatments

Metabolic Engineering & Industrial Bioprocess

Identify pathway bottlenecks, optimize carbon yield, and eliminate byproduct secretion in engineered microbial and mammalian cell factories

Immunometabolism & T-Cell Reprogramming

Track nutrient allocation shifts across glycolysis, oxidative phosphorylation, and one-carbon metabolism during immune cell activation

Diabetes, NAFLD & Hepatic Lipid Overload

Measure in vivo hepatic glucose production, mitochondrial pyruvate cycling, and de novo lipogenic flux in metabolic syndrome models

Plant & Photosynthetic Systems

Determine carbon partitioning between starch synthesis, secondary metabolism, and nitrogen assimilation during abiotic stress

Stable Isotope 13C-Glutamine Tracing Resolves Anaplerotic Flux and TCA Cycle Rewiring in Proliferating Tissues

Journal: Biology of Reproduction

Published: 2022

DOI: https://doi.org/10.1093/biolre/ioac097

Background

During peri-implantation development, rapid elongation of the conceptus requires extensive metabolic coordination between glycolysis and the tricarboxylic acid (TCA) cycle. While proliferating cells predominantly utilize aerobic glycolysis for biomass synthesis, maintaining mitochondrial TCA cycle flux is critical for energy generation. To elucidate how conceptus tissues metabolically adapt to changes in nutrient availability, researchers investigated the capacity of trophectoderm cells to utilize glutamine via glutaminolysis as an alternative anaplerotic carbon source.

Challenge:

Determine whether proliferating trophectoderm cells can decouple glycolysis from the TCA cycle by utilizing glutamine-derived carbons to maintain mitochondrial anaplerotic flux when glucose is restricted.

Findings (from the published study)

Active Glutaminolysis Induction: Expression of glutaminase (GLS) and aminotransferases (PSAT1, GOT2, GPT2) was upregulated in elongating conceptus trophectoderm, establishing active glutamine conversion into glutamate and α-ketoglutarate.
TCA Anaplerosis Maintenance: Stable isotope tracing with [U-13C5]glutamine confirmed substantial 13C label incorporation into downstream TCA intermediates (succinate, fumarate, malate, citrate), proving that glutaminolysis maintains anaplerotic flux to sustain mitochondrial function.
Glucose-Deprivation Compensation: When glucose was omitted from the medium, glutamine oxidation to 14CO2 and 13C incorporation into aspartate increased significantly, demonstrating metabolic flexibility to support nucleotide precursor synthesis.
Pathway Rewiring: The study established that proliferating tissues actively decouple glycolysis from the TCA cycle, utilizing glutamine catabolism to maintain mitochondrial anaplerosis and provide precursors for cell migration and growth.

Figure 7. Mass isotopologue distributions and 13C-enrichment of central carbon and TCA cycle intermediates from [U-13C5]glutamine tracing

Figure 7. Isotopic enrichment of central carbon and TCA cycle intermediates from glutamine tracing Figure 8. Schematic model of spatial-temporal glutaminolysis pathway flux and carbon transition network

Figure 8. Schematic model of glutaminolysis pathway flux and carbon transitions

Process Insight

The study highlights how 13C stable isotope tracing combined with high-resolution mass spectrometry resolves pathway-level metabolic flexibility, demonstrating that amino acid catabolism acts as an essential anaplerotic buffer when primary nutrient availability changes.

Where Our 13C Metabolic Flux Analysis Service Fits

Creative Proteomics performed the stable isotope tracing mass spectrometry workflow for this study, delivering complete analytical and data processing support:

Tracer Experimental Design: Optimizing isotopic precursor concentrations, incubation timelines, and medium blank controls.
High-Resolution LC-MS Analysis: Accurate mass acquisition and peak deconvolution on high-resolution mass spectrometry platforms.
Natural Abundance Isotope Correction: Automated matrix correction and mass isotopologue reporting ready for stoichiometric flux modeling.

Reference

Seo H, Kramer AC, McLendon BA, et al. Elongating porcine conceptuses can utilize glutaminolysis as an anaplerotic pathway to maintain the TCA cycle. Biology of Reproduction. 2022;107(4):948-959.

What is the difference between 13C metabolic flux analysis and static metabolomics?

Static metabolomics measures metabolite concentrations (pool sizes) at a single time point, which cannot determine whether an increase in a metabolite is due to accelerated synthesis or blocked consumption. 13C-MFA uses stable carbon isotope tracers and mathematical modeling to quantify the in vivo reaction rates (fluxes) and directional carbon routing through pathways.

How do I choose the best 13C tracer for my biological question?

Tracer selection depends on the target pathway branch point. [1,2-13C2]glucose is ideal for quantifying the split ratio between glycolysis and the oxidative pentose phosphate pathway; [U-13C6]glucose measures glycolytic rate, PDH vs. PC entry, and overall TCA carbon contribution; and [U-13C5]glutamine resolves oxidative vs. reductive TCA cycle flux.

What is the difference between isotopic steady-state MFA and dynamic (INST-MFA)?

Isotopic steady-state MFA requires cells to be cultured until isotopic labeling in intermediate pools reaches equilibrium (constant MIDs over time), which is standard for fast-growing microbial and mammalian cell cultures. Isotopically nonstationary MFA (INST-MFA) measures time-resolved labeling trajectories (seconds to minutes) and is required for slow-growing cells, photosynthetic organisms, or systems with large nutrient storage pools.

Why is natural isotope abundance correction necessary in 13C-MFA?

Naturally occurring heavy isotopes (1.1% 13C, 0.37% 15N, 0.2% 18O, 29Si/30Si from derivatization reagents) introduce artificial mass shifts in measured mass spectra. We use validated deconvolution algorithms (IsoCor, AccuCor) to subtract natural abundance contributions, ensuring that model fitting is based strictly on tracer-derived labeling.

How do you ensure statistical confidence in estimated metabolic fluxes?

We perform Chi-square (χ²) goodness-of-fit testing to assess whether the stoichiometric model adequately fits the experimental data. Furthermore, we compute non-linear 95% confidence intervals using Profile Likelihood methods, which test parameter identifiability and reveal whether specific fluxes are tightly constrained by the measurements.

Why is rapid sub-second quenching critical for sample preparation?

Intracellular metabolites in central pathways have rapid turnover times (often milliseconds to seconds). Standard room-temperature washes or trypsinization cause immediate metabolic shifts and label scrambling. Our sub-zero (-80 °C) organic solvent quenching instantly arrests enzymatic activity, capturing the true in vivo metabolic state.

What sample types can be analyzed with your 13C-MFA platform?

Our platform accommodates adherent mammalian cells, suspension cultures, primary cells, microbial fermentations (bacteria, yeast, fungi), plant tissues, and isolated perfused organs. Custom sampling and extraction protocols are optimized for each matrix.

Impaired ketogenesis ties metabolism to T cell dysfunction in COVID-19

Karagiannis, F., Peukert, K., Surace, L., Michla, M., Nikolka, F., Fox, M., ... & Kurts, C.

Journal: Nature

Year: 2022

DOI: https://doi.org/10.1038/s41586-022-05128-8

Elongating porcine conceptuses can utilize glutaminolysis as an anaplerotic pathway to maintain the TCA cycle

Seo, H., Kramer, A. C., McLendon, B. A., Fang, X., Satterfield, M. C., Wu, G., ... & Johnson, G. A.

Journal: Biology of Reproduction

Year: 2022

DOI: https://doi.org/10.1093/biolre/ioac097

Hierarchical glycolytic pathways control the carbohydrate utilization regulator in human gut Bacteroides

Kabonick, S. G., Verma, K., Modesto, J. L., Pearce, V. H., Winokur, K. M., Groisman, E. A., & Townsend, G. E.

Journal: Nature Communications

Year: 2025

DOI: https://doi.org/10.1038/s41467-025-59704-3

Macrophage-Associated Lipin-1 Promotes beta-Oxidation in Response to Proresolving Stimuli

Schilke, R. M., Blackburn, C. M. R., Rao, S., Krzywanski, D. M., Finck, B. N., & Woolard, M. D.

Journal: ImmunoHorizons

Year: 2020

DOI: https://doi.org/10.4049/immunohorizons.2000047

The mitochondrial Pyruvate Carrier 1 is needed for the synthesis of 1-deoxysphingolipids in spheroids of the preputial gland

Panknin, I., Rieder, D., Mair, R., Sailer, S., Gotic, M., Meissner, C., ... & Keller, M. A.

Journal: eLife

Year: 2021

DOI: https://doi.org/10.7554/eLife.67500

The role of carnitine palmitoyl transferase 2 in the progression of salt-sensitive hypertension

Dissanayake, L. V., Smith, B. A., Zietara, A., Levchenko, V., Lowe, M., Kravtsova, O., ... & Staruschenko, A.

Journal: American Journal of Physiology-Cell Physiology