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© 2004 The American Society for Nutritional Sciences J. Nutr. 134:2717-2721, October 2004

Nutritional Methodology

An In Vitro Digestion/Caco-2 Cell Culture System Accurately Predicts the Effects of Ascorbic Acid and Polyphenolic Compounds on Iron Bioavailability in Humans1

Shumei Yun, Jean-Pierre Habicht, Dennis D. Miller* and Raymond P. Glahn{dagger},2

Division of Nutritional Sciences, Savage Hall, Cornell University, Ithaca, NY14853; * Department of Food Science, Cornell University, Ithaca, NY 14853; and {dagger} U.S. Plant, Soil and Nutrition Laboratory, U.S. Department of Agriculture/ARS, Cornell University, Tower Road, Ithaca, NY 14853

2To whom correspondence should be addressed. E-mail: rpg3{at}cornell.edu.


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
We developed a rapid in vitro digestion/Caco-2 cell culture model for assessing relative bioavailabilities of iron in foods and meals. The objective of the present study was to determine how closely our Caco-2 model reflects the human response. Meals described in published reports of studies on effects of varying levels of ascorbic acid (AA) and tannic acid (TA) on iron absorption by human subjects were carefully replicated. Iron absorption ratios (iron absorption from meals containing AA or TA divided by iron absorption from identical meals without these enhancers or inhibitors) were determined using the Caco-2 model. Ferritin formation by the Caco-2 cells was used as an indicator of iron absorption. Response patterns of effects of AA and TA on absorption ratios (AR) calculated from Caco-2 and human data were very similar: AA increased ARs in a dose-response manner and TAs decreased AR. The natural logs of the ARs determined in Caco-2 and human studies were correlated: R = 0.935 (P = 0.012) and 0.927 (P = 0.007) for AA and TA, respectively. When results from meals with AA and TA were pooled, a linear relation between the natural logs of ARs from Caco-2 and human studies was observed (R = 0.968, P < 0.001). We conclude that our Caco-2 model accurately predicts the human response to AA and TA in the meals we tested. If future work reproduces the precision and accuracy shown in this paper for predicting iron bioavailability to humans, then the implications for saving time and resources in iron bioavailability measurements are considerable.

KEY WORDS: • iron bioavailability • Caco-2 • ascorbic acid • tannic acid

Iron deficiency is the most widespread and prevalent nutritional deficiency in the world (1). Many factors contribute to iron deficiency but low bioavailability of dietary iron is a major cause (2).

Studies of dietary iron bioavailability in humans are extremely expensive; thus, there is considerable need for valid animal and in vitro models. Animal models such as rats offer a useful alternative, but their response may differ from that of humans (3). Alternatively, in vitro methods provide an attractive, rapid, and low cost option for initial screening of iron bioavailability. The most effective and peer-accepted models are those that combine simulated gastrointestinal digestion with culture of human intestinal epithelial cells. Most are based on simulated gastrointestinal digestion followed by quantitation of "available" iron. Many employ cultured Caco-2 cells as a surrogate for enterocytes of the small intestine (4–6). Most commonly, radiolabeled iron can be used to measure iron uptake by the cells (7).

We applied a model in which in vitro gastric and intestinal digestion is combined with cultured Caco-2 cells to simulate digestion and absorption in the human intestine (8). A unique feature of our model is that formation of ferritin by Caco-2 cells exposed to digested food serves as an indicator of bioavailable iron. An increase in cell ferritin is unequivocal evidence that iron has entered the cell because cells produce ferritin in response to increases in intracellular iron. In contrast, an increase in the apparent cellular content of a radioiron tracer could represent surface-bound iron as well as intracellular iron. Moreover, the exchange of an added radioactive tracer with intrinsic iron in a food may be incomplete because it may depend on the form of the iron in the food. Commercial kits for measuring ferritin concentration with high sensitivity and specificity are widely available and easy to use. Therefore, using ferritin as the indicator of bioavailable iron has advantages over methods that rely on radioisotopes.

Recent studies involving human subjects provide additional support for the validity of using cell ferritin as an index of bioavailability. For example, Hunt and Roughhead (9,10) reported a strong correlation between ferritin concentrations in feces collected from human subjects and iron bioavailability. Presumably, fecal ferritin concentrations reflect enterocyte ferritin levels formed in response to uptake of bioavailable dietary iron, and it is this step that the above-mentioned model was designed to reproduce (8). This Caco-2-cell model system was qualitatively validated under a multitude of conditions. For example, studies using the model showed that heme iron uptake is higher than nonheme iron uptake (4); the iron in human milk is more available than iron in bovine milk (5); the availability of iron from FeSO4 is higher than from a polysaccharide-Fe complex (11); and ascorbic acid (AA)3 and meat enhance uptake, whereas phytic acid, tannic acid (TA), and zinc inhibit (12). Qualitatively similar effects were all shown in humans. As a result, this model has found applications in the development of infant foods (13,14); in agriculture for screening plant cultivars for bioavailable iron (15); in the pharmaceutical industry for developing improved iron supplements (11); and in fundamental studies designed to investigate factors in digests of animal tissue that promote iron uptake [Glahn et al. (16)].

All of the above uses require that estimates from in vitro models be accurate predictors of iron bioavailability to humans. Au and Reddy (7) observed that bioavailability estimates from their Caco-2 model correlated well with results from human studies but this relation was less evident at lower levels of bioavailability in their study, and their data did not extend to the even lower levels of bioavailability seen with iron absorption inhibitors. It is therefore important to show that Caco-2 cell ferritin formation is quantitatively related to concentrations of bioavailable iron in human foods and diets. Therefore, the objective of the present study was to replicate meals fed in human trails and determine how closely our Caco-2 cell model reflects the human response over a wide range of bioavailability.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 LITERATURE CITED
 
    Chemicals, enzymes, and hormones. Unless otherwise stated, all chemicals, enzymes, and hormones were purchased from Sigma Chemical. The source of FeCl3 was a 1.04 g Fe/L solution in 1% HCl (Sigma #1–9011). Dextrimaltose was purchased from American Maize Product.

    Expt. 1. Cook and Monsen’s study (17) of the effects of 0, 25, 50, 100, 250, and 500 mg AA on iron absorption, by human subjects, from a semisynthetic (SS) meal (18) was replicated in the first experiment. Cook and Monsen measured iron absorption from each meal with and without AA by 12–13 human subjects at each level of AA. Meals were extrinsically labeled with radioiron, and iron absorption was estimated from radioactivity in a blood sample taken 2 wk after ingestion of a single radiolabeled meal. Absorption ratios (levels of AA relative to no AA) were calculated from the data for each individual. Geometric means of these individual absorption ratios (AR) were calculated for each level of AA and are presented in Table 1. We also presented in Table 1, the logarithm of the geometric means of the ARs, which is identical to the mean of the individuals’ Ln AR because the geometric mean is the antilog of the mean of the logged data. From the data presented in their article, we also calculated the SD of Ln AR (Table 1). This logarithmic approach was used by Monson and Cook because the logarithmic transformation rendered the data more Gaussian. It also has the advantage of transforming the AR from a multiplicative to an additive function.


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  		TABLE 1 Effects of ascorbic acid (AA) addition to a semisynthetic meal on Caco-2 cell ferritin formation and absorption ratios (ARs)

 
We prepared semisynthetic (SS) meals with varying AA content as described by Monsen and Cook (17,18) as follows: egg albumen, 18.4 g; dextrimaltose, 33.4 g; corn oil, 17.4 g; CaHPO4 · 2H2O, 0.38 g; and K2HPO4 · 3H2O, 0.87 g were mixed with 100 mL water and homogenized in a blender (Waring Products). The AA contents were adjusted to levels corresponding to 0, 25, 50, 100, 250, 500 mg in the original meals with an AA stock solution (7.35 g/L), which was prepared immediately before use. The iron content was adjusted to a level that corresponded to 4.1 mg in the original meal described by Monsen and Cook (17) using a FeCl3 stock solution (1.04 g Fe/L FeCl3). A 2-g portion of the SS meal was used for each in vitro digestion. Relative iron bioavailability in each meal was estimated using an in vitro digestion/Caco-2 cell model system (see below). Six independent replicates of each meal were analyzed.

    Expt. 2. The study of Brune et al. (19) on the effect of TA on iron absorption by human subjects was replicated in the second experiment. The basal meal used in the Brune study consisted of a wheat roll baked from unfortified wheat flour of 60% extraction. The amount of TA added to the basal meal was 0, 5, 10, 25, 50, 100, or 200 mg. Iron absorption from each meal with and without TA was measured in each of 9–10 human subjects at each level of TA. Brune et al. (19) calculated absorption ratios (levels of iron absorption with TA relative to no TA) for each individual. The arithmetic mean of the ARs from their paper is reproduced in Table 2. From these data and the SD reported, we calculated the CV (SD/mean) and applied a logarithmic transformation to the mean AR and its CV to approximate the mean Ln (AR) and its SD in Table 2 column 6. A good approximation of the SD of Ln AR is obtained from Ln (1+ CV).


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  		TABLE 2 Effects of tannic acid (TA) addition to wheat rolls on Caco-2 cell ferritin formation and absorption ratios (AR)

 
In the present study, wheat rolls baked from a low extraction (60%) flour were prepared. The iron content of the wheat rolls was measured. The TA contents of the wheat rolls were adjusted to levels corresponding to 0, 5, 10, 25, 50, 100, or 200 mg in the original meal. The iron content in the wheat roll was adjusted with FeSO4 to a level that corresponded to the 3.8 mg in the original meals used by Brune et al. (19). A 1-g aliquot of the wheat roll was used for in vitro digestion to which melted margarine (250 mg) was added to replicate the meals fed in the human experiment. Six independent replicates were analyzed for each level of TA.

In vitro methodology

    Cell culture. Caco-2 cells were obtained from American Type Culture Collection at passage 17, and used in experiments at passage 25–33. Cells were seeded at a density of 50,000 cells/cm2 in collagen-treated 6-well plates (Costar). The cells were grown in DMEM (GIBCO) with 10% (v:v) fetal calf serum (GIBCO), 25 mmol/L HEPES and 1% antibiotic antimycotic solution (GIBCO). The cells were maintained at 37°C in an incubator with 5% CO2 and 95% air atmosphere at constant humidity. The medium was changed every 2 d. The cells were used in the iron uptake experiments at 13 d postseeding.

    In vitro digestion. The in vitro digestion protocol was performed as described previously (8). With this method, Caco-2 cells grown on the bottom of 6-well plates were exposed to food digests placed in the upper chamber of each culture well. The "upper chamber" was created by attaching a dialysis membrane (15,000 Da molecular weight cutoff) to an insert ring. Iron from samples placed in the upper chamber dialyzes through the membrane and becomes accessible for uptake by the Caco-2 cells. The dialysis membrane is necessary to protect the cells from the digestive enzymes, similar to the protection provided by the mucus layer in the human intestine. Ferritin formation by the Caco-2 cells, a marker for cell Fe uptake, was used as the indicator of Fe bioavailability.

    Measurement of ferritin and total iron. All glassware used in the sample preparation and analyses was acid-washed. Caco-2 cell protein was measured on samples that had been solubilized in 0.5 mol/L NaOH, using a semimicro adaptation of the Bio-Rad DC protein assay kit (Bio-Rad Laboratories). A one stage, a 2-site immunoradiometric assay was used to measure Caco-2 cell ferritin content (FER-Iron II ferritin Assay, RAMCO Laboratories). A 10-µL sample of the sonicated Caco-2 cell monolayer, harvested in 2 mL of water, was used for each ferritin measurement. Analyses of the iron content of the experimental solutions, food samples, and digests were conducted using an inductively coupled plasma emission spectrometer (ICAP model 61E Trance Analyzer, Thermo Jarrell Ash). The ferritin was expressed per unit of cell protein (ng ferritin/mg cell protein).

    Statistical analysis. For both experiments, the geometric means of the ferritin values are presented in Tables 1, and 2. The arithmetic SDs are also presented for comparison with literature values. The ARs were calculated as the ratio of the ferritin content of a well containing digests of a meal with AA or TA relative to a well without the AA or TA in the same plate. In both tables, we present the mean and SD of the natural log of the absorption ratio [Ln(AR)] at each dose of AA or TA. The antilog of the mean of Ln(AR) is the geometric mean of the ARs.

The similarity in pattern between the Caco-2 cell and the human AR results was examined separately for AA and TA. All other calculations were performed with the Ln(AR) values in the Caco-2 cell (C) and the human (H) experiments. We calculated the Pearson correlation coefficients for the AA and TA studies separately and together.

We calculated the mean of the 11 H/C ratios to estimate a conversion factor (K) after ascertaining whether the data from 2 two experiments could be pooled, and whether K could be estimated by the ratio. K was used to estimate the Ln Human AR(H) from the Ln Caco 2-cell results (C), such that H = KC.


   RESULTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 LITERATURE CITED
 
    Expt. 1. As AA content increased, the ferritin levels in Caco-2 cells increased (Table 1). The response pattern of absorption ratios in Caco-2 cells was very similar to that in humans (Fig. 1). The logarithms of the absorption ratios (meals with AA/meals without AA) in Caco-2 cells were correlated with values from human studies (R = 0.934; P = 0.012).



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  		FIGURE 1 Iron absorption ratios (AR) calculated from Caco-2 and human data (17) for semisynthetic meals containing varying levels of AA. Values represent the geometric mean of iron absorption at a given level of AA divided by the geometric mean of iron absorption without AA. Iron absorption in the Caco-2 cell model was indexed by ferritin formation. The natural log of the Caco-2 cell values and that of human studies were correlated (R = 0.934, P = 0.012).

 
    Expt. 2. Caco-2 cell ferritin formation decreased in response to increasing amounts of TA in wheat rolls (Table 2). The Caco-2 cell model responded to TA addition of up to 100 mg/meal in a pattern similar to that in humans (Table 2; Fig. 2). The logarithms of the absorption ratios (meals with TA/meals without TA) in Caco-2 cells and in human studies were correlated (R = 0.927; P = 0.007).



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  		FIGURE 2 Iron absorption ratios (AR) from Caco-2 cell and human studies (19) on the effects of TA on iron absorption. Values represent the geometric mean of iron absorption at a given level of TA divided by the geometric mean of iron absorption without TA. The natural log of the Caco-2 cell values and that of human studies were correlated (R = 0.927, P = 0.007).

 
    Measurement precision in Caco-2 and human experiments. A comparison of the SDs of the mean Ln(AR) in Tables 1, and 2 shows that the Caco-2 cell precision for each of the 6 replicates across the 2 experiments was comparable to the precision of that obtained for each individual studied in the human study.

    Predicting human bioavailability from Caco-2 cell results. When the results from the 2 Caco-2 experiments and the corresponding 2 human studies were pooled together, a linear relation (R = 0.986; P < 0.001) was observed between the natural log transformed ARs in the Caco-2 cell model and the ARs from the human trials (Fig. 3). This regression showed no difference in slope between the AA and TA studies and it had an intercept of –0.027 ± 0.085 (P > 0.75), which is not different from the zero expected (the natural logarithm of 1 represented in Fig. 3). Therefore, the conversion factor to estimate human iron availability from Caco-2 cell results was calculated from the ratio of the human (H) to the Caco-2 cell (C) results combining both studies. The mean of the ratios of the logarithms (H/C) of the ARs (i.e., the conversion factor K) is 0.6401 (with a SD of ± 0.1137) so that the conversion equation is: H = 0.6401 x C, where C comes from Tables 1, and 2. For example, the estimate of H at the TA dose of 100 mg is: 0.6401 x –3.37 = –2.16. The actual figure for H (Table 2) is –2.12.



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  		FIGURE 3 The log-log relation between absorption ratios (AR) from human (16,18) and the parallel Caco-2 cell studies of this study. Caco-2 cell values represent the mean Ln(AR), calculated from 6 replicates in the Caco 2 cell model. Human values represent the mean Ln(AR), calculated from data for 12–13 subjects in a human study [Table 1, Cook and Monson (17)]. The Caco-2 and human values shown in this figure, and their respective SD, are also listed in Tables 1and 2. Values were correlated (R = 0.986, P < 0.001).

 

   DISCUSSION
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
LITERATURE CITED
 
Although the in vitro digestion/Caco-2 cell culture model has been used in many studies (4,5,11,13–15), the present study is the first to directly compare results from the model with results from human studies over a broad range of iron bioavailability for a known promoter (AA) and inhibitor (TA). This comparison showed that the Caco-2 model responded quantitatively to AA and TA with the same pattern as in human studies, even though the food matrices in the AA and the TA studies were different. Thus, the results indicate that the in vitro digestion/Caco-2 cell model may be used to estimate human iron bioavailability from complex meals, provided that the results can be compared as absorption ratios. These results may represent a significant advancement in the field because previous studies in this area were designed to demonstrate only qualitative similarities to human trials. Additional studies using different food matrices and different iron absorption enhancers and inhibitors are now warranted to define the quantitative potential of this system over a broad range of meal conditions.

Au and Reddy (7) also plotted the results of a Caco-2 cell model against results from a human trial and found a linear association in the arithmetic scale, which we did not find. When we plotted their values in the logarithmic scale, their slope was 0.565, lower (P < 05) than the 1.484 we found. Their methods differ from ours in many ways. For example, they utilized radioactive iron to measure cell Fe uptake, whereas we utilized ferritin formation. From the methods section of their paper, it appears that they added the radioactive Fe to the sample digest ~30 min after the start of the intestinal digestion phase of the in vitro digestion period. Thus, there may not have been full equilibration of the radiolabeled iron with the nonradiolabeled Fe in the meal because it was not subject to the complete digestion conditions and food interactions as the nonradiolabeled iron. This is a concern that is common to all studies in which the food is extrinsically radiolabeled, and may explain why Au And Reddy did not observe an effect of AA. Another major contrast between the present study and that of Au and Reddy is that our study represents a concentration-response study of well-documented promoter and inhibitor compounds, whereas Au and Reddy focused on single concentrations of various protein sources and known promoter and inhibitor foods. Thus, it is not surprising that the slope of the correlations differed between our study and that of Au and Reddy. In our opinion, it is likely that different laboratories with the exact same method will find some difference in slopes. Overall, it is encouraging that both methods correlated well with human studies. However, if a particular in vitro model is to gain widespread use, it is important that some standardized meals with varying levels of enhancers or inhibitors be developed and agreed upon so that adjustments can be made to correct for differences between methods or laboratories before data are used to predict human iron absorption.

Further work on the statistics is warranted if the conversion constant K (i.e., conversion of Caco-2 data to prediction for humans) is shown across many studies to be true for iron absorption inhibitors and enhancers. For instance, it would be helpful to know the precision of using the Caco 2 cell model to estimate human iron availability using this conversion factor. This value compared with the precision of using the direct estimate from the human model would permit calculations of the relative costs of the 2 methods. The SD presented in this paper are similar for the 2 methods (see Tables 1, and 2). This suggests the potential for great cost savings from using the Caco 2-cell model even though the conversion operation introduces some imprecision into the estimate of the human iron availability from the Caco 2-cell model.

A common question often received by the authors of this paper concerns the cost of this in vitro model. In the Glahn laboratory, costs for comparing 8 experimental samples (including controls) are estimated at $4000, with a minimal turnaround time for results of ~1 wk. This estimate includes materials and labor, but not facility overhead costs. Also, the support personnel in this laboratory are highly trained and well-practiced in the application of these techniques. Similar studies in animals are likely to cost many times this amount and questions about the validity of extrapolating from animals to humans are often raised (3). Similar studies in humans would take considerably longer and entail much higher costs.

A fourth approach to estimating bioavailable iron in foods and diets is calculation using an algorithm (2,20). These algorithms are based on data from human studies on effects of enhancers and inhibitors on heme and nonheme iron absorption. Their accuracy in predicting bioavailable iron depends on the quality of the data used to develop them and the accuracy and availability of food composition data for iron, enhancers, and inhibitors. For example, limited knowledge of the content of the phytate, tannins, and iron of certain foods can affect the accuracy of the prediction. Furthermore, the practical problem of degradation of iron uptake enhancers (e.g., AA) and inhibitors due to storage, cooking, and food preparation methods is also difficult to account for in an algorithm, and must be overcome by expansion of composition data sets to include these effects.

An advantage of an in vitro digestion/Caco-2 cell approach is that bioavailability can be determined even when composition data are inaccurate or unavailable. The in vitro model can also be used to study interactions between Fe and enhancers or inhibitors, such as the effect of polyphenolics (21), or to identify factors present in human milk that promote Fe availability (22). The model has also been used to compare Fe bioavailability in genotypes of various staple food crops, thus enabling plant breeders to select for enhanced Fe bioavailability traits (15,23). Such comparisons are cost prohibitive to perform in vivo, and could not be done via algorithms due to the lack of appropriate compositional data, and the likely presence of unknown factors influencing Fe bioavailability [e.g., specific subclasses of polyphenolics (23)]. Also, conducting complete compositional analysis of Fe uptake enhancers and inhibitors would take as much time and resources as simply running the in vitro trials (Glahn et al., personal observations). It is far more practical and cost effective to first rank the genotypes for iron bioavailability, then compare the composition of those that show promise relative to others with lesser Fe bioavailability. If the above experimental exercises are to be worthwhile, then validation studies such as that described in this paper are essential.

In conclusion, the in vitro model described in this paper represents a useful tool for examining factors that affect Fe bioavailability. Although it was encouraging to see such a strong correlation between this model and human trials, amore direct comparison of this model to human studies should be pursued to explore its potential for quantitative predictions of Fe bioavailability over a wide range of foods and meal preparations.


   ACKNOWLEDGMENTS
 
The authors are grateful for the fine technical assistance provided by Gary Wortley and Yongpei Chang. We also appreciate the assistance of Manju Reddy in providing key information regarding the comparison of the in vitro models.


   FOOTNOTES
 
1 Funded by USDA-ARS and the Division of Nutritional Sciences, Cornell University. Proprietary or brand names are provided for the convenience of the reader. The USDA neither guarantees nor warrants the standard of the product, and the use of the name by the USDA implies no approval of the product to the exclusion of others that may also be suitable. Back

3 Abbreviations used: AA, ascorbic acid; AR, absorption ratio; SS, semisynthetic; TA, tannic acid. Back

Manuscript received 8 March 2004. Initial review completed 29 March 2004. Revision accepted 1 July 2004.


   LITERATURE CITED
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 

1. WHO/UNICEF/UNU (2001) Iron Deficiency Anaemia. Assessment, Prevention and Control. A Guide for Progamme Managers (WHO/NHD/01.3) 2001 World Health Organization Geneva, Switzerland.

2. Hallberg, L. & Hulthen, L. (2000) Prediction of dietary iron absorption: an algorithm for calculating absorption and bioavailability of dietary iron. Am. J. Clin. Nutr. 71:1147-1160.[Abstract/Free Full Text]

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5. Glahn, R. P., Lai, C., Hsu, J., Thompson, J. F. & Van Campen, D. R. (1998) Decreased citrate improves iron availability from infant formula: Application of an in vitro digestion/Caco-2 cell culture model. J. Nutr. 128:257-264.[Abstract/Free Full Text]

6. Pinto, M., Robine-Leon, S., Appay, M.-D., Kedinger, M., Triadou, N., Dussaulx, E., LaCroix, B., Simon-Assmann, P., Haffen, K., Fogh, J. & Zweibaum, A. (1983) Enterocyte-like differentiation and polarization of the human colon carcinoma cell line Caco-2 in culture. Biol. Cell 47:323-330.

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8. Glahn, R. P., Lee, O. A., Yeung, A., Goldman, M. I. & Miller, D. D. (1998) Caco-2 cell ferritin formation predicts nonradiolabeled food iron availability in an in vitro digestion/Caco-2 cell culture model. J. Nutr. 128:1555-1561.[Abstract/Free Full Text]

9. Hunt, J. R. & Roughhead, Z. K. (1999) Nonheme-iron absorption, fecal ferritin excretion, and blood indexes of iron status in women consuming controlled lactoovovegetarian diets for 8 wk. Am. J. Clin. Nutr. 69:944-952.[Abstract/Free Full Text]

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11. Glahn, R. P., Rassier, M., Goldman, M. I., Lee, O. A. & Cha, J. (2000) A comparison of iron availability from commercial iron preparations using an in vitro digestion/Caco-2 cell culture model. J. Nutr. Biochem. 11:62-68.[Medline]

12. Glahn, R. P., Wortley, G. M., South, P. K. & Miller, D. D. (2002) Inhibition of iron uptake by phytic acid, tannic acid, and ZnCl2: studies using an in vitro digestion/Caco-2 cell model. J. Agric. Food Chem. 50:390-395.[Medline]

13. Etcheverry, P., Wallingford, J. C., Miller, D. D. & Glahn, R. P. (2002) Simultaneous determination of (45)calcium and (65)zinc uptake by caco-2 cells. J. Agric. Food Chem. 50:6287-6294.[Medline]

14. Glahn, R. P., Lee, O. A. & Miller, D. D. (1999) In vitro digestion/Caco-2 cell culture model to determine optimal ascorbic acid to Fe ratio in rice cereal. J. Food Sci. 64:925-928.

15. Oikeh, S. O., Menkir, A., Maziya-Dixon, B., Welch, R. & Glahn, R. P. (2003) Assessment of concentrations of iron and zinc and bioavailable iron in grains of early-maturing tropical maize varieties. J. Agric. Food Chem. 51:3688-3694.[Medline]

16. Huh, E. C., Hotchkiss, A., Brouillette, J. & Glahn, R. P. (2004) Carbohydrate fractions from cooked fish promote iron uptake by Caco-2 cells. J. Nutr. 134:1681-1689.[Abstract/Free Full Text]

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19. Brune, M., Rossander, L. & Hallberg, L. (1989) Iron absorption and phenolic compounds: importance of different phenolic structures. Eur. J. Clin. Nutr. 43:547-558.[Medline]

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21. Yeung, C. K., Glahn, R. P., Wu, X., Liu, R. H. & Miller, D. D. (2002) In vitro iron bioavailability and antioxidant activity of raisins. J. Food Sci. 68:701-705.

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23. Glahn, R. P., Cheng, Z., Welch, R. M. & Gregorio, G. B. (2002) A comparison of iron bioavailability from 15 rice genotypes: studies using an in vitro digestion/Caco-2 cell culture model. J. Agric. Food Chem. 50:3586-3591.[Medline]




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O. Kenny, Y. O'Callaghan, and N.M. O'Brien
Effects of Ingredient Incorporation into Sausage Meat on the Micellarisation and uptake of {alpha}-tocopherol by Caco-2 Human Intestinal Cells
Food Science and Technology International, February 1, 2008; 14(1): 79 - 86.
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 Am. J. Clin. Nutr.Home page
J. M Beiseigel, J. R Hunt, R. P Glahn, R. M Welch, A. Menkir, and B. B Maziya-Dixon
Iron bioavailability from maize and beans: a comparison of human measurements with Caco-2 cell and algorithm predictions
Am. J. Clinical Nutrition, August 1, 2007; 86(2): 388 - 396.
[Abstract] [Full Text] [PDF]

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 J. Nutr.Home page
S. S. g. Bonsmann, T. Walczyk, S. Renggli, and R. F Hurrell
Nonheme Iron Absorption in Young Women Is Not Influenced by Purified Sulfated and Unsulfated Glycosaminoglycans
J. Nutr., May 1, 2007; 137(5): 1161 - 1164.
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