<figure><img src="image_23.png" /></figure>

<table><thead><tr><th>Reference</th><th>(Nestel et al., 2012) 4</th><th>(Nestel et al., 2012) 5</th><th>(Sofi et al., 2010) 2</th><th>(Wang et al., 2011) 2</th><th>(van Bussel et al., 2011)</th><th>(Meyer et al., 2011) 5</th></tr></thead><tbody><tr><td>Subject category</td><td>MET</td><td>MET</td><td>HEALTH</td><td>HEALTH</td><td>HEALTH</td><td>HEALTH</td></tr><tr><td>Target indication</td><td>Systemic inflammation</td><td>Systemic inflammation</td><td>Atherosclerosis</td><td>Obesity and cardiovascular disease</td><td>Endothelial dysfunction and low grade inflammation</td><td>Coronary heart disease</td></tr><tr><td>Target population</td><td>Overweight or obese subjects</td><td>Overweight or obese subjects</td><td>Healthy adults</td><td>Normal-weight and overweight adolescents</td><td>Healthy adults</td><td>Overall population</td></tr><tr><td>Fat content</td><td>High-fat</td><td>High-fat</td><td>High-fat</td><td>High-fat</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Fermentation</td><td>Fermented</td><td>Fermented</td><td>Fermented</td><td>Non-fermented</td><td>N.a.</td><td>Non-fermented</td></tr><tr><td>Test product</td><td>Cheese</td><td>Yoghurt</td><td>Pecorino sheep cheese naturally rich in CLA</td><td>Dietary dairy fatty acids</td><td>Dairy products</td><td>Inflammatory risk dietary pattern (IRDP) containing milk</td></tr><tr><td>Control product</td><td>—</td><td>—</td><td>Commercial cow cheese low in CLA</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Test subjects</td><td>13 / 61.6±7.6 y / overweight or obese</td><td>13 / 61.6±7.6 y / overweight or obese</td><td>4 M, 6 F / 30-65 y / healthy</td><td>112 M, 80 F / 15.2±1.2 y / normal weight</td><td>140 M, 161 F / 42.5±0.6 y / healthy</td><td>981 M / 45-64 y / healthy</td></tr><tr><td>Control subjects</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Diet</td><td>110 g cheddar cheese / postprandial challenge study</td><td>600 mL yoghurt / postprandial challenge study</td><td>Cheese / 200 g per week / 10 weeks</td><td>FFQ / measurement of dairy fatty acids</td><td>510±334 g dairy/d (dietary history method 6y before biomarker determination) / measurement of serum biomarkers</td><td>Diet assessment (FFQ)</td></tr><tr><td>Controlled dairy test</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Randomization</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Cross-sectional</td><td>Cross-sectional</td><td>Cross-sectional</td></tr><tr><td>Study results</td><td>³Cheese (3h vs 0h): MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-1β, TNF-α, CRP →</td><td>³Yoghurt (3h vs 0h): MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-1β, TNF-α, CRP →</td><td>²Control cheese (w10 vs w0): IL-6, IL-8, TNF-α, IL-10, IL-12 →</td><td>⁵Dairy fatty acids: corr→ with CRP, TNF-α (adjusted for confounders)</td><td>⁵Dairy: corr→ with von Willebrand factor, E-selectin, VCAM-1, ICAM-1, CRP, SAA, IL-6, IL-8, TNF-α (corrected for confounders)</td><td>⁷Pattern including milk corr → with IL-6, CRP, IL-18 not adjusted for confounders</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Dose-response</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Bioavailability data</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Biological plausibility</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Investigated - odd-numbered dairy fatty acids accumulate in epididymal fat rather than being β-oxidized in liver in obese but not normal-weight</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Investigated - dairy fatty acids (15-0, Not discussed 17-0)</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Clinical evidence</td><td>N.a.</td><td>N.a.</td><td>No</td><td>Yes - higher levels of dairy fatty acids associated with lower markers of oxidative stress</td><td>No</td><td>Yes - inflammatory dietary pattern significantly associated with all-cause mortality; milk did not contribute to the effect</td></tr><tr><td>Financing of research</td><td>Private</td><td>Private</td><td>Public</td><td>Public</td><td>Private and public</td><td>Public</td></tr><tr><td>Grading criteria</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td></tr><tr><td>IS</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr></tbody></table>

(Continued on next page)
<figure><img src="image_24.png" /></figure>

<table><thead><tr><th>Reference</th><th>(Nestel et al., 2012) 4</th><th>(Nestel et al., 2012) 5</th><th>(Sofi et al., 2010) 2</th><th>(Wang et al., 2011) 2</th><th>(van Bussel et al., 2011)</th><th>(Meyer et al., 2011) 5</th></tr></thead><tbody><tr><td>Subject category</td><td>MET</td><td>MET</td><td>HEALTH</td><td>HEALTH</td><td>HEALTH</td><td>HEALTH</td></tr><tr><td>Target indication</td><td>Systemic inflammation</td><td>Systemic inflammation</td><td>Atherosclerosis</td><td>Obesity and cardiovascular disease</td><td>Endothelial dysfunction and low grade inflammation</td><td>Coronary heart disease</td></tr><tr><td>Target population</td><td>Overweight or obese subjects</td><td>Overweight or obese subjects</td><td>Healthy adults</td><td>Normal-weight and overweight adolescents</td><td>Healthy adults</td><td>Overall population</td></tr><tr><td>Fat content</td><td>High-fat</td><td>High-fat</td><td>High-fat</td><td>High-fat</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Fermentation</td><td>Fermented</td><td>Fermented</td><td>Fermented</td><td>Non-fermented</td><td>N.a.</td><td>Non-fermented</td></tr><tr><td>Test product</td><td>Cheese</td><td>Yoghurt</td><td>Pecorino sheep cheese naturally rich in CLA</td><td>Dietary dairy fatty acids</td><td>Dairy products</td><td>Inflammatory risk dietary pattern (IRDP) containing milk</td></tr><tr><td>Control product</td><td>—</td><td>—</td><td>Commercial cow cheese low in CLA</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Test subjects</td><td>13 / 61.6±7.6 y / overweight or obese</td><td>13 / 61.6±7.6 y / overweight or obese</td><td>4 M, 6 F / 30-65 y / healthy</td><td>112 M, 80 F / 15.2±1.2 y / normal weight</td><td>140 M, 161 F / 42.5±0.6 y / healthy</td><td>981 M / 45-64 y / healthy</td></tr><tr><td>Control subjects</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Diet</td><td>110 g cheddar cheese / postprandial challenge study</td><td>600 mL yoghurt / postprandial challenge study</td><td>Cheese / 200 g per week / 10 weeks</td><td>FFQ / measurement of dairy fatty acids</td><td>510±334 g dairy/d (dietary history method 6y before biomarker determination) / measurement of serum biomarkers</td><td>Diet assessment (FFQ)</td></tr><tr><td>Controlled dairy test</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Randomization</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Cross-sectional</td><td>Cross-sectional</td><td>Cross-sectional</td></tr><tr><td>Study results</td><td>³Cheese (3h vs 0h): MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-6, IL-1β, TNF-α, CRP →</td><td>³Yoghurt (3h vs 0h): MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-1β, TNF-α, CRP →</td><td>²Control cheese (w10 vs w0): IL-6, IL-8, TNF-α, IL-10, IL-12 →</td><td>⁵Dairy fatty acids: corr→ with CRP, TNF-α (adjusted for confounders)</td><td>⁵Dairy: corr→ with von Willebrand factor, E-selectin, VCAM-1, ICAM-1, CRP, SAA, IL-6, IL-8, TNF-α (corrected for confounders)</td><td>⁷Pattern including milk corr → with IL-6, CRP, IL-18 not adjusted for confounders</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Dose-response</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Bioavailability data</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Biological plausibility</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Investigated - odd-numbered dairy fatty acids accumulate in epididymal fat rather than being β-oxidized in liver in obese but not normal-weight</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Investigated - dairy fatty acids (15-0, Not discussed 17-0)</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Clinical evidence</td><td>N.a.</td><td>N.a.</td><td>No</td><td>Yes - higher levels of dairy fatty acids associated with lower markers of oxidative stress</td><td>No</td><td>Yes - inflammatory dietary pattern significantly associated with all-cause mortality; milk did not contribute to the effect</td></tr><tr><td>Financing of research</td><td>Private</td><td>Private</td><td>Public</td><td>Public</td><td>Private and public</td><td>Public</td></tr><tr><td>Grading criteria</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td></tr><tr><td>IS</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr></tbody></table>

(Continued on next page)
<figure><img src="image_24.png" /><figcaption>Table 5. (Continued)</figcaption></figure>

<table><thead><tr><th>Reference</th><th>(Jimenez-Flores et al., 2012)</th><th>(Rosti et al., 2011)</th><th>(Dalbeth et al., 2012)</th><th>(Pal & Ellis, 2011)</th><th>(Wennersberg et al., 2009)</th><th>(Topuz et al., 2008)</th></tr></thead><tbody><tr><td>Subject category</td><td>HEALTH</td><td>GIT</td><td>OTHER</td><td>MET</td><td>MET</td><td>GIT</td></tr><tr><td>Target indication</td><td>Endurance exercise</td><td>Food allergy (inflammatory bowel disease)</td><td>Gout</td><td>Cardiovascular disease risk factors syndrome (MS)</td><td>More than 2 factors metabolic syndrome (MS)</td><td>Mucositis induced by chemotherapy</td></tr><tr><td>Target population</td><td>Young active persons</td><td>Infants not being breast-fed</td><td>Subjects with recurrent gout flares</td><td>Overweight and obese postmenopausal women</td><td>Overweight and MS subjects with low dairy intake</td><td>Subjects undergoing standard-dose chemotherapy</td></tr><tr><td>Fat content</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Fermentation</td><td>Non-fermented</td><td>Non-fermented</td><td>Non-fermented</td><td>Non-fermented</td><td>N.a.</td><td>Fermented</td></tr><tr><td>Test product</td><td>Milk bar</td><td>Milk protein formula</td><td>Skim milk powder (SMP)</td><td>Breakfast including whey protein isolate or sodium caseinate</td><td>High dairy consumption</td><td>Kefir</td></tr><tr><td>Control product</td><td>Commercial carbohydrate supplement</td><td>Mother milk</td><td>Lactose powder</td><td>Breakfast including glucose</td><td>Low dairy consumption</td><td>0.9% NaCl</td></tr><tr><td>Test subjects</td><td>33 M, 2 F / 20.7±0.4 y / healthy</td><td>12 M, 14 F / 87±9 d / formula-fed</td><td>37 M, 3 F / 57±16 y / gout</td><td>20 F / 57±1 y / overweight and obese</td><td>52-56 out of a total of 37 M (51.2±8.1 y) and 76 F (56.7± 7.4 y) / obese and 2 MS symptoms</td><td>12 M, 5 F / 19-75 y / colorectal cancer</td></tr><tr><td>Control subjects</td><td>—</td><td>14 M, 25 F / 82.6±7.9 d / breast-fed</td><td>36 M, 4 F / 56±12 y / gout</td><td>—</td><td>52-57 out of a total of 37 M and 76 F / obese and 2 MS symptoms</td><td>12 M, 8 F / 34-72 y / colorectal cancer</td></tr><tr><td>Diet</td><td>Carbohydrate (250 kcal) or milk bar (290 kcal) plus intensive exercise / one bar at the end of each day of exercise / 3 days</td><td>N.a.</td><td>250 mL/d / 3 months</td><td>Single ingestion of whey, casein or glucose breakfast</td><td>Dairy products / 3 to 5 portions/ d / 6 months</td><td>Dairy products / 3 to 5 portions/ Kefir or NaCl 0.9% / 2 × 250 mL per day / 5 days and 6 chemotherapy cycles</td></tr><tr><td>Controlled dairy test</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Randomization</td><td>Randomized</td><td>Non-randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Cross-sectional</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td></tr><tr><td>Study results</td><td><sup>1</sup>Milk bar vs commercial carbohydrate: CRP →</td><td><sup>1</sup>Formula-fed vs breast-fed: fecal calprotectin →</td><td><sup>1</sup>SMP vs lactose: CRP →</td><td><sup>1</sup>Whey breakfast vs control breakfast (6h postprandial, AUC): TNF-α, CRP, IL-6 →</td><td><sup>1</sup>High vs low dairy: CRP, IL-6, TNF-α, C3, C4, VCAM-1, E-selectin, PAI-1, vWf, 8-isopGF2α →</td><td><sup>1</sup>Kefir vs control: mucositis grading, TNF-α, IL-1β, IL-6 →</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Discussed</td></tr><tr><td>Dose-response</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Bioavailability data</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Biological plausibility</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Discussed - Whey protein contains ACE-inhibitory peptides</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Clinical evidence</td><td>No - no significant effect on metabolic parameters</td><td>N.a.</td><td>Yes - frequency of gout flares reduced</td><td>No - no effect on blood pressure</td><td>Yes - decreased HOMA index, waist circumference and abdominal diameter, metabolic parameters unchanged</td><td>N.a.</td></tr><tr><td>Financing of research</td><td>Public</td><td>Public</td><td>Private and public</td><td>Private and public</td><td>Public</td><td>Not presented</td></tr><tr><td>Grading criteria</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td></tr><tr><td>IS</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr></tbody></table>
<figure><img src="image_25.png" /><figcaption>Table 5. (Continued)</figcaption></figure>

<table><thead><tr><th>Reference</th><th>(Jimenez-Flores et al., 2012)</th><th>(Rosti et al., 2011)</th><th>(Dalbeth et al., 2012)</th><th>(Pal & Ellis, 2011)</th><th>(Wennersberg et al., 2009)</th><th>(Topuz et al., 2008)</th></tr></thead><tbody><tr><td>Subject category</td><td>HEALTH</td><td>GIT</td><td>OTHER</td><td>MET</td><td>MET</td><td>GIT</td></tr><tr><td>Target indication</td><td>Endurance exercise</td><td>Food allergy (inflammatory bowel disease)</td><td>Gout</td><td>Cardiovascular disease risk factors syndrome (MS)</td><td>More than 2 factors metabolic syndrome (MS)</td><td>Mucositis induced by chemotherapy</td></tr><tr><td>Target population</td><td>Young active persons</td><td>Infants not being breast-fed</td><td>Subjects with recurrent gout flares</td><td>Overweight and obese postmenopausal women</td><td>Overweight and MS subjects with low dairy intake</td><td>Subjects undergoing standard-dose chemotherapy</td></tr><tr><td>Fat content</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Fermentation</td><td>Non-fermented</td><td>Non-fermented</td><td>Non-fermented</td><td>Non-fermented</td><td>N.a.</td><td>Fermented</td></tr><tr><td>Test product</td><td>Milk bar</td><td>Milk protein formula</td><td>Skim milk powder (SMP)</td><td>Breakfast including whey protein isolate or sodium caseinate</td><td>High dairy consumption</td><td>Kefir</td></tr><tr><td>Control product</td><td>Commercial carbohydrate supplement</td><td>Mother milk</td><td>Lactose powder</td><td>Breakfast including glucose</td><td>Low dairy consumption</td><td>0.9% NaCl</td></tr><tr><td>Test subjects</td><td>33 M, 2 F / 20.7±0.4 y / healthy</td><td>12 M, 14 F / 87±9 d / formula-fed</td><td>37 M, 3 F / 57±16 y / gout</td><td>20 F / 57±1 y / overweight and obese</td><td>52-56 out of a total of 37 M (51.2±8.1 y) and 76 F (56.7± 7.4 y) / obese and 2 MS symptoms</td><td>12 M, 5 F / 19-75 y / colorectal cancer</td></tr><tr><td>Control subjects</td><td>—</td><td>14 M, 25 F / 82.6±7.9 d / breast-fed</td><td>36 M, 4 F / 56±12 y / gout</td><td>—</td><td>52-57 out of a total of 37 M and 76 F / obese and 2 MS symptoms</td><td>12 M, 8 F / 34-72 y / colorectal cancer</td></tr><tr><td>Diet</td><td>Carbohydrate (250 kcal) or milk bar (290 kcal) plus intensive exercise / one bar at the end of each day of exercise / 3 days</td><td>N.a.</td><td>250 mL/d / 3 months</td><td>Single ingestion of whey, casein or glucose breakfast</td><td>Dairy products / 3 to 5 portions/ d / 6 months</td><td>Dairy products / 3 to 5 portions/ Kefir or NaCl 0.9% / 2 × 250 mL per day / 5 days and 6 chemotherapy cycles</td></tr><tr><td>Controlled dairy test</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Randomization</td><td>Randomized</td><td>Non-randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Cross-sectional</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td></tr><tr><td>Study results</td><td>¹Milk bar vs commercial carbohydrate: CRP →</td><td>¹Formula-fed vs breast-fed: fecal calprotectin →</td><td>¹SMP vs lactose: CRP →</td><td>¹Whey breakfast vs control breakfast (6h postprandial, AUC): TNF-α, CRP, IL-6 →</td><td>¹High vs low dairy: CRP, IL-6, TNF-α, C3, C4, VCAM-1, E-selectin, PAI-1, vWf, 8-isopGF2α →</td><td>¹Kefir vs control: mucositis grading, TNF-α, IL-1β, IL-6 →</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Discussed</td></tr><tr><td>Dose-response</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Bioavailability data</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Biological plausibility</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Discussed - Whey protein contains ACE-inhibitory peptides</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Clinical evidence</td><td>No - no significant effect on metabolic parameters</td><td>N.a.</td><td>Yes - frequency of gout flares reduced</td><td>No - no effect on blood pressure</td><td>Yes - decreased HOMA index, waist circumference and abdominal diameter, metabolic parameters unchanged</td><td>N.a.</td></tr><tr><td>Financing of research</td><td>Public</td><td>Public</td><td>Private and public</td><td>Private and public</td><td>Public</td><td>Not presented</td></tr><tr><td>Grading criteria</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td></tr><tr><td>IS</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr></tbody></table>
<figure><img src="image_25.png" /></figure>

<table><thead><tr><th>Reference</th><th>(Arvola et al., 2006)</th><th>(Wojcik et al., 2001)</th><th>(Nestel et al., 2012) 6</th><th>(Nestel et al., 2012) 7</th><th>(Asemi et al., 2013)</th><th>(Strisciuglio et al., 2013)</th></tr></thead><tbody><tr><td>Subject category</td><td>HYPER</td><td>HEALTH</td><td>MET</td><td>MET</td><td>MET</td><td>GIT</td></tr><tr><td>Target indication</td><td>Rectal bleeding in infants with and without milk allergy</td><td>Post-exercice recovery</td><td>Systemic inflammation</td><td>Systemic inflammation</td><td>Pregnancy with gestational diabetes mellitus (GDM)</td><td>Ulcerative colitis</td></tr><tr><td>Target population</td><td>Infants with rectal bleeding</td><td>General population</td><td>Overweight or obese subjects</td><td>Overweight or obese subjects</td><td>Pregnant women with GDM</td><td>Children with ulcerative colitis</td></tr><tr><td>Fat content</td><td>N.a.</td><td>Low-fat</td><td>High-fat</td><td>High-fat</td><td>Low-fat</td><td>N.a.</td></tr><tr><td>Fermentation</td><td>N.a.</td><td>Non-fermented</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Test product</td><td>Milk elimination diet</td><td>Milk-based carbohydrate-protein beverage</td><td>High-fat dairy meals including cheddar cheese, butter, cream, or yoghurt</td><td>High-fat fermented dairy (cheese, yoghurt)</td><td>DASH diet (including low-fat dairy)</td><td>Milk protein elimination diet</td></tr><tr><td>Control product</td><td>Normal diet</td><td>Aspartame-flavored placebo</td><td>Low-fat milk</td><td>High-fat unfermented dairy (butter, cream, ice cream)</td><td>DASH but less fruits and vegetables and more fat</td><td>Free Diet</td></tr><tr><td>Test subjects</td><td>19-4-24 weeks / rectal bleeding</td><td>8 M / 23.5±0.7 y / healthy untrained</td><td>13 / 61.6±7.6 y / overweight or obese</td><td>12 / 59±8.2 y / overweight or obese</td><td>32 F / 18-40 y / pregnant with GDM</td><td>14 M, 15 F / 4.6-17y / newly diagnosed ulcerative colitis</td></tr><tr><td>Control subjects</td><td>21 / 4-24 weeks / rectal bleeding</td><td>9 M (placebo) / 23.5±0.7 y / healthy untrained</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Diet</td><td>Milk elimination or normal diet / 1 month</td><td>Beverage immediately and 2h after exercise</td><td>110 g cheddar or 115 mL cream or 50 g butter or 600 mL yoghurt or 400 mL reduced fat milk / postprandial challenge study</td><td>2 weeks run-in / dairy (fermented or not fermented) / 4 weeks / 2 weeks washout / dairy (fermented or not fermented) / 4 weeks</td><td>DASH / 4 weeks</td><td>Milk elimination or free diet / 1 year</td></tr><tr><td>Controlled dairy test</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Randomization</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td></tr><tr><td>Study results</td><td>Milk elimination diet vs normal diet: tissue inflammation (identified by rectal bleeding and bloody stools) →</td><td>Milk-based beverage vs placebo: TNF-α, IL-1β, IL-6 →</td><td>Postprandial response between each of the high-fat and the low-fat dairy groups: MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-1β, TNF-α, CRP →</td><td>Fermented vs unfermented dairy (4w): MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-1β, TNF-α, CRP →</td><td>DASH diet containing dairy: corr→ with CPR</td><td>Milk protein elimination diet vs free diet: Histological Matt score, CRP, calprotectin →</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>N.a.</td><td>Discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Dose-response Bioavailability data</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Biological plausibility</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Discussed - inflammation processes in developing GIT</td><td>Discussed - modulation of protein synthesis and catabolism</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Discussed - gut inflammation or inadequate caloric intake</td></tr><tr><td>Clinical evidence</td><td>No</td><td>Discussed - protein and carbohydrates</td><td>Not discussed</td><td>Not discussed</td><td>Discussed - arginine (not related to dairy), magnesium and calcium</td><td>Discussed - milk protein antigens</td></tr><tr><td>Financing of research</td><td>Public</td><td>No - no improvement of muscle glycogen replacement or muscle function</td><td>N.a.</td><td>N.a.</td><td>Yes - DASH reduced fasting plasma glucose, serum insulin, and HOMA-IR score; increased antioxidant capacity and glutathione levels</td><td>No - milk protein elimination vs free diet: remission rate (PUCAI) →</td></tr><tr><td>Grading criteria IS</td><td>None</td><td>Public</td><td>Private</td><td>Private</td><td>Public</td><td>Not presented</td></tr><tr><td></td><td>0</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td></tr></tbody></table>

(Continued on next page)
<figure><img src="image_26.png" /></figure>

<table><thead><tr><th>Reference</th><th>(Arvola et al., 2006)</th><th>(Wojcik et al., 2001)</th><th>(Nestel et al., 2012) 6</th><th>(Nestel et al., 2012) 7</th><th>(Asemi et al., 2013)</th><th>(Strisciuglio et al., 2013)</th></tr></thead><tbody><tr><td>Subject category</td><td>HYPER</td><td>HEALTH</td><td>MET</td><td>MET</td><td>MET</td><td>GIT</td></tr><tr><td>Target indication</td><td>Rectal bleeding in infants with and without milk allergy</td><td>Post-exercice recovery</td><td>Systemic inflammation</td><td>Systemic inflammation</td><td>Pregnancy with gestational diabetes mellitus (GDM)</td><td>Ulcerative colitis</td></tr><tr><td>Target population</td><td>Infants with rectal bleeding</td><td>General population</td><td>Overweight or obese subjects</td><td>Overweight or obese subjects</td><td>Pregnant women with GDM</td><td>Children with ulcerative colitis</td></tr><tr><td>Fat content</td><td>N.a.</td><td>Low-fat</td><td>High-fat</td><td>High-fat</td><td>Low-fat</td><td>N.a.</td></tr><tr><td>Fermentation</td><td>N.a.</td><td>Non-fermented</td><td>N.a.</td><td>N.a.</td><td>N.a.</td><td>N.a.</td></tr><tr><td>Test product</td><td>Milk elimination diet</td><td>Milk-based carbohydrate-protein beverage</td><td>High-fat dairy meals including cheddar cheese, butter, cream, or yoghurt</td><td>High-fat fermented dairy (cheese, yoghurt)</td><td>DASH diet (including low-fat dairy)</td><td>Milk protein elimination diet</td></tr><tr><td>Control product</td><td>Normal diet</td><td>Aspartame-flavored placebo</td><td>Low-fat milk</td><td>High-fat unfermented dairy (butter, cream, ice cream)</td><td>DASH but less fruits and vegetables and more fat</td><td>Free Diet</td></tr><tr><td>Test subjects</td><td>19-4-24 weeks / rectal bleeding</td><td>8 M / 23.5±0.7 y / healthy untrained</td><td>13 / 61.6±7.6 y / overweight or obese</td><td>12 / 59±8.2 y / overweight or obese</td><td>32 F / 18-40 y / pregnant with GDM</td><td>14 M, 15 F / 4.6-17y / newly diagnosed ulcerative colitis</td></tr><tr><td>Control subjects</td><td>21 / 4-24 weeks / rectal bleeding</td><td>9 M (placebo) / 23.5±0.7 y / healthy untrained</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Diet</td><td>Milk elimination or normal diet / 1 month</td><td>Beverage immediately and 2h after exercise</td><td>110 g cheddar or 115 mL cream or 50 g butter or 600 mL yoghurt or 400 mL reduced fat milk / postprandial challenge study</td><td>2 weeks run-in / dairy (fermented or not fermented) / 4 weeks / 2 weeks washout / dairy (fermented or not fermented) / 4 weeks</td><td>DASH / 4 weeks</td><td>Milk elimination or free diet / 1 year</td></tr><tr><td>Controlled dairy test</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Randomization</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td><td>Randomized</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td></tr><tr><td>Study results</td><td>Milk elimination diet vs normal diet: tissue inflammation (identified by rectal bleeding and bloody stools) →</td><td>Milk-based beverage vs placebo: TNF-α, IL-1β, IL-6 →</td><td>Postprandial response between each of the high-fat and the low-fat dairy groups: MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-1β, TNF-α, CRP →</td><td>Fermented vs unfermented dairy (4w): MCP-1, MIP-1α, ICAM-1, VCAM-1, IL-6, IL-1β, TNF-α, CRP →</td><td>DASH diet containing dairy: corr→ with CPR</td><td>Milk protein elimination diet vs free diet: Histological Matt score, CRP, calprotectin →</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>N.a.</td><td>Discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Dose-response Bioavailability data</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Biological plausibility</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Discussed - inflammation processes in developing GIT</td><td>Discussed - modulation of protein synthesis and catabolism</td><td>Not discussed</td><td>Not discussed</td><td>Not discussed</td><td>Discussed - gut inflammation or inadequate caloric intake</td></tr><tr><td>Clinical evidence</td><td>No</td><td>Discussed - protein and carbohydrates</td><td>Not discussed</td><td>Not discussed</td><td>Discussed - arginine (not related to dairy), magnesium and calcium</td><td>Discussed - milk protein antigens</td></tr><tr><td>Financing of research</td><td>Public</td><td>No - no improvement of muscle glycogen replacement or muscle function</td><td>N.a.</td><td>N.a.</td><td>Yes - DASH reduced fasting plasma glucose, serum insulin, and HOMA-IR score; increased antioxidant capacity and glutathione levels</td><td>No - milk protein elimination vs free diet: remission rate (PUCAI) →</td></tr><tr><td>Grading criteria IS</td><td>None</td><td>Public</td><td>Private</td><td>Private</td><td>Public</td><td>Not presented</td></tr><tr><td></td><td>0</td><td>None</td><td>None</td><td>None</td><td>None</td><td>None</td></tr></tbody></table>

(Continued on next page)
<figure><img src="image_26.png" /><figcaption>Table 5. (Continued)</figcaption></figure>

<table><thead><tr><th>Reference</th><th>(Iwasa et al., 2013)</th><th>(Jones et al., 2013) 2</th><th>(Pintus et al., 2013) 2</th></tr></thead><tbody><tr><td>Subject category</td><td>HEALTH</td><td>MET</td><td>MET</td></tr><tr><td>Target indication</td><td>Glucose metabolism and muscle damage after exercise</td><td>Metabolic syndrome (MS)</td><td>Hypercholesterolemia</td></tr><tr><td>Target population</td><td>Athletes</td><td>Overweight and obese MS subjects</td><td>Mildly hypercholesterolaemic subjects</td></tr><tr><td>Fat content</td><td>Low-fat</td><td>Low-fat</td><td>High-fat</td></tr><tr><td>Fermentation</td><td>Fermented</td><td>N.a.</td><td>Fermented</td></tr><tr><td>Test product</td><td>Milk fermented with Lactobacillus helveticus</td><td>High dairy high calcium diet plus caloric restriction</td><td>Sheep cheese naturally enriched with CLA</td></tr><tr><td>Control product</td><td>Unfermented milk</td><td>Low dairy low calcium diet plus caloric restriction</td><td>Sheep cheese with pill containing 1 g of a palm oil-soybean oil mix</td></tr><tr><td>Test subjects</td><td>18 M / 21.6±0.8 y / healthy</td><td>7 M, 13F / 52.1±1.5 y / obese MS</td><td>19 M, 23 F / 30-60 y / mild hypercholesterolaemia</td></tr><tr><td>Control subjects</td><td>200 mL of each beverage / 3x before and after exercise</td><td>7 M, 11F / 50.1±2.7 y / obese MS 3-4 servings dairy (low-fat milk or yoghurt)/d and 350 mg/d Ca supplement or 1 serving yoghurt/d / 12 weeks</td><td>Naturally enriched sheep cheese or control cheese / 90 g/d / 3 weeks / between 3 weeks washout</td></tr><tr><td>Controlled dairy test</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Randomization</td><td>Randomized</td><td>Randomized</td><td>Randomized</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td></tr><tr><td>Study results</td><td>¹Fermented vs non-fermented milk: TNF-α, CRP →</td><td>¹High vs low dairy (w12): IL6, TNF-α, MCP-1, IL-1β →</td><td>²Sheep cheese (w3 vs w0): IL-6 (n = 16), CRP (n = 16), leptin (n = 16), adiponectin (n = 16), anandamide →</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>N.a.</td><td>No</td><td>Not discussed</td></tr><tr><td>Dose-response</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Bioavailability data</td><td>Not discussed</td><td>No</td><td>Not discussed</td></tr><tr><td>Biological plausibility</td><td>Discussed - activated antioxidants contribute to suppression of muscle damage and glucose impairment</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Discussed - peptides</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Clinical evidence</td><td>Yes - Muscle soreness and reduction of antioxidant capacity suppressed by fermented milk, blood glucose unchanged</td><td>No - no higher weight loss</td><td>No - sheep cheese decreased total cholesterol and LDL-cholesterol</td></tr><tr><td>Financing of research</td><td>Public</td><td>Public</td><td>Public</td></tr><tr><td>Grading criteria</td><td>None</td><td>None</td><td>None</td></tr><tr><td>IS</td><td>0</td><td>0</td><td>0</td></tr></tbody></table>
<figure><img src="image_27.png" /><figcaption>Table 5. (Continued)</figcaption></figure>

<table><thead><tr><th>Reference</th><th>(Iwasa et al., 2013)</th><th>(Jones et al., 2013) 2</th><th>(Pintus et al., 2013) 2</th></tr></thead><tbody><tr><td>Subject category</td><td>HEALTH</td><td>MET</td><td>MET</td></tr><tr><td>Target indication</td><td>Glucose metabolism and muscle damage after exercise</td><td>Metabolic syndrome (MS)</td><td>Hypercholesterolemia</td></tr><tr><td>Target population</td><td>Athletes</td><td>Overweight and obese MS subjects</td><td>Mildly hypercholesterolaemic subjects</td></tr><tr><td>Fat content</td><td>Low-fat</td><td>Low-fat</td><td>High-fat</td></tr><tr><td>Fermentation</td><td>Fermented</td><td>N.a.</td><td>Fermented</td></tr><tr><td>Test product</td><td>Milk fermented with Lactobacillus helveticus</td><td>High dairy high calcium diet plus caloric restriction</td><td>Sheep cheese naturally enriched with CLA</td></tr><tr><td>Control product</td><td>Unfermented milk</td><td>Low dairy low calcium diet plus caloric restriction</td><td>Sheep cheese with pill containing 1 g of a palm oil-soybean oil mix</td></tr><tr><td>Test subjects</td><td>18 M / 21.6±0.8 y / healthy</td><td>7 M, 13F / 52.1±1.5 y / obese MS</td><td>19 M, 23 F / 30-60 y / mild hypercholesterolaemia</td></tr><tr><td>Control subjects</td><td>200 mL of each beverage / 3x before and after exercise</td><td>7 M, 11F / 50.1±2.7 y / obese MS 3-4 servings dairy (low-fat milk or yoghurt)/d and 350 mg/d Ca supplement or 1 serving yoghurt/d / 12 weeks</td><td>Naturally enriched sheep cheese or control cheese / 90 g/d / 3 weeks / between 3 weeks washout</td></tr><tr><td>Controlled dairy test</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Randomization</td><td>Randomized</td><td>Randomized</td><td>Randomized</td></tr><tr><td>Time factor</td><td>Longitudinal</td><td>Longitudinal</td><td>Longitudinal</td></tr><tr><td>Study results</td><td>¹Fermented vs non-fermented milk: TNF-α, CRP →</td><td>¹High vs low dairy (w12): IL6, TNF-α, MCP-1, IL-1β →</td><td>²Sheep cheese (w3 vs w0): IL-6 (n = 16), CRP (n = 16), leptin (n = 16), adiponectin (n = 16), anandamide →</td></tr><tr><td>Net change in inflammatory marker</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Sustainability of effect over time</td><td>N.a.</td><td>No</td><td>Not discussed</td></tr><tr><td>Dose-response</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Bioavailability data</td><td>Not discussed</td><td>No</td><td>Not discussed</td></tr><tr><td>Biological plausibility</td><td>Discussed - activated antioxidants contribute to suppression of muscle damage and glucose impairment</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Bioactive components</td><td>Discussed - peptides</td><td>Not discussed</td><td>Not discussed</td></tr><tr><td>Clinical evidence</td><td>Yes - Muscle soreness and reduction of antioxidant capacity suppressed by fermented milk, blood glucose unchanged</td><td>No - no higher weight loss</td><td>No - sheep cheese decreased total cholesterol and LDL-cholesterol</td></tr><tr><td>Financing of research</td><td>Public</td><td>Public</td><td>Public</td></tr><tr><td>Grading criteria</td><td>None</td><td>None</td><td>None</td></tr><tr><td>IS</td><td>0</td><td>0</td><td>0</td></tr></tbody></table>
<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /><figcaption>**Figure 2.** Distribution of the inflammatory markers measured in the 52 human studies. The x-axis presents the inflammatory markers. The y-axis presents the number of study results reporting a specific analytical result with the corresponding inflammatory marker. The color code indicates the direction of change of the inflammatory marker; significant anti-inflammatory change (black bars), no significant change (grey bar), significant pro-inflammatory change (white bars). The inflammatory markers are ranked in descending order with regard to their frequency of reporting in all 52 studies reviewed.</figcaption></figure>
<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /><figcaption>**Figure 2.** Distribution of the inflammatory markers measured in the 52 human studies. The x-axis presents the inflammatory markers. The y-axis presents the number of study results reporting a specific analytical result with the corresponding inflammatory marker. The color code indicates the direction of change of the inflammatory marker; significant anti-inflammatory change (black bars), no significant change (grey bar), significant pro-inflammatory change (white bars). The inflammatory markers are ranked in descending order with regard to their frequency of reporting in all 52 studies reviewed.</figcaption></figure>
<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /><figcaption>**Figure 3.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" for the entire data set composed of 78 study results. (A) Number of study results labeled as "anti-inflammatory", "no effect", "pro-inflammatory" based on the initial grading defined in Table 2. (B) Distribution of the Inflammatory Score. The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

and high-fat dairy products. The IS indicated an anti-inflammatory activity of high-fat dairy products despite the fact that nine studies were identified in which these products were associated with a pro-inflammatory activity. The pro-inflammatory activity identified with high-fat dairy products in these studies was mainly attributed to the presence of saturated fat. Fat consumption, in particular saturated fat (Steinberg, 2005) and trans-fatty acids (Micha and Mozaffarian, 2009), has been associated with inflammatory processes in humans. However, recent opinions in nutrition research advocate that the adverse health effects formerly associated with saturated fats, were most likely due to other factors (Lawrence, 2013). The positive IS, calculated for the high-fat products, is thus in line with this reevaluation of the impact of fat consumption on human health. Additionally, as both low-fat and high-fat products were associated with a positive IS, the molecules with a potential anti-inflammatory activity in milk may cover a broad range of nutrients, including polyunsaturated fatty acids (German and Dillard, 2006), proteins (Chatterton et al., 2013), and glycans (Newburg, 2013).

The IS of the product category "fermented dairy products" indicates a beneficial anti-inflammatory contribution, possibly resulting from the bacteria present in dairy products or their metabolic activity. The anti-inflammatory activity of strains of lactic acid bacteria and bifidobacteria has indeed been reported (Lomax & Calder, 2009; Tsai et al., 2012). The recent awareness of the role of the gut microbiota in the modulation of the immune system (Hakansson and Molin, 2011), further raises interest in the integration of bacteria with anti-inflammatory properties into dairy products (Dunne et al., 2001). Moreover, products deriving from the fermentation of milk with bacteria,

in particular bioactive peptides (Ceapa et al., 2013) and glycans (Newburg, 2013), which both interact with gut microbes or immune cells, may contribute to an anti-inflammatory activity of dairy products.

## Research gaps

Our review also aimed at identifying research gaps preventing a comprehensive understanding of inflammatory processes in food and nutrition sciences. In particular, we have identified the following gaps:

No consensus is available yet which clearly defines clinically relevant inflammatory markers. For illustration in Europe, the EFSA was required, following a consultation of stakeholders, to give guidance on potential markers of inflammation. In its response, the EFSA stated that "for function claims referring to reduction of inflammation, a change in markers of inflammation such as various interleukins does not indicate a beneficial physiological effect per se, but should be accompanied by a beneficial physiological or clinical outcome" (EFSA Panel on Dietetic Products, 2011). This position is an important challenge to the food and nutrition research community, given the difficulties associated with the identification of validated clinical markers of disease reduction by dietary interventions. In that context, the importance of validating sets of molecules present in the circulation as biomarkers of low-grade inflammation has been emphasized (Calder et al., 2013). At the same time, the predictive value tentatively attributed by the authors of this review to these sets of inflammatory markers, illustrates the gap with the position of regulatory authorities. The present review further highlights this gap: human studies complementing the inflammatory markers
<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /><figcaption>**Figure 3.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" for the entire data set composed of 78 study results. (A) Number of study results labeled as "anti-inflammatory", "no effect", "pro-inflammatory" based on the initial grading defined in Table 2. (B) Distribution of the Inflammatory Score. The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

and high-fat dairy products. The IS indicated an anti-inflammatory activity of high-fat dairy products despite the fact that nine studies were identified in which these products were associated with a pro-inflammatory activity. The pro-inflammatory activity identified with high-fat dairy products in these studies was mainly attributed to the presence of saturated fat. Fat consumption, in particular saturated fat (Steinberg, 2005) and trans-fatty acids (Micha and Mozaffarian, 2009), has been associated with inflammatory processes in humans. However, recent opinions in nutrition research advocate that the adverse health effects formerly associated with saturated fats, were most likely due to other factors (Lawrence, 2013). The positive IS, calculated for the high-fat products, is thus in line with this reevaluation of the impact of fat consumption on human health. Additionally, as both low-fat and high-fat products were associated with a positive IS, the molecules with a potential anti-inflammatory activity in milk may cover a broad range of nutrients, including polyunsaturated fatty acids (German and Dillard, 2006), proteins (Chatterton et al., 2013), and glycans (Newburg, 2013).

The IS of the product category "fermented dairy products" indicates a beneficial anti-inflammatory contribution, possibly resulting from the bacteria present in dairy products or their metabolic activity. The anti-inflammatory activity of strains of lactic acid bacteria and bifidobacteria has indeed been reported (Lomax & Calder, 2009; Tsai et al., 2012). The recent awareness of the role of the gut microbiota in the modulation of the immune system (Hakansson and Molin, 2011), further raises interest in the integration of bacteria with anti-inflammatory properties into dairy products (Dunne et al., 2001). Moreover, products deriving from the fermentation of milk with bacteria,

in particular bioactive peptides (Ceapa et al., 2013) and glycans (Newburg, 2013), which both interact with gut microbes or immune cells, may contribute to an anti-inflammatory activity of dairy products.

## Research gaps

Our review also aimed at identifying research gaps preventing a comprehensive understanding of inflammatory processes in food and nutrition sciences. In particular, we have identified the following gaps:

No consensus is available yet which clearly defines clinically relevant inflammatory markers. For illustration in Europe, the EFSA was required, following a consultation of stakeholders, to give guidance on potential markers of inflammation. In its response, the EFSA stated that "for function claims referring to reduction of inflammation, a change in markers of inflammation such as various interleukins does not indicate a beneficial physiological effect per se, but should be accompanied by a beneficial physiological or clinical outcome" (EFSA Panel on Dietetic Products, 2011). This position is an important challenge to the food and nutrition research community, given the difficulties associated with the identification of validated clinical markers of disease reduction by dietary interventions. In that context, the importance of validating sets of molecules present in the circulation as biomarkers of low-grade inflammation has been emphasized (Calder et al., 2013). At the same time, the predictive value tentatively attributed by the authors of this review to these sets of inflammatory markers, illustrates the gap with the position of regulatory authorities. The present review further highlights this gap: human studies complementing the inflammatory markers
<figure><img src="image_31.png" /><figcaption>**Table 6.** Inflammatory Score for the impact of dairy products on humans.</figcaption></figure>

<table><thead><tr><th></th><th></th><th>N</th><th>Q1<sup>1</sup></th><th>Median</th><th>Q3<sup>1</sup></th><th>Mean</th><th>p<sup>2</sup></th><th>p<sup>3</sup></th></tr></thead><tbody><tr><td rowspan="2">All data</td><td rowspan="2">ALL study results</td><td>78</td><td>0</td><td>0</td><td>6</td><td>1.4</td><td>0.009</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="5">Subject category</td><td>HEALTH</td><td>37</td><td>-3.2</td><td>0</td><td>6</td><td>1.7</td><td>0.017</td><td rowspan="5">0.083</td></tr><tr><td>MET</td><td>24</td><td>0</td><td>4.5</td><td>7.5</td><td>3.9</td><td>0.001</td></tr><tr><td>GIT</td><td>8</td><td>-5.5</td><td>-2.5</td><td>0</td><td>-3.1</td><td>0.066</td></tr><tr><td>HYPER</td><td>6</td><td>-6</td><td>-6</td><td>-6</td><td>-5.5</td><td>0.034</td></tr><tr><td>OTHER</td><td>3</td><td>0</td><td>0</td><td>6.75</td><td>3.0</td><td>0.317</td></tr><tr><td rowspan="4">Product category</td><td>High-fat</td><td>35</td><td>-2.25</td><td>0</td><td>6</td><td>1.7</td><td>0.017</td><td rowspan="2">0.084</td></tr><tr><td>Low-fat</td><td>20</td><td>0</td><td>4.5</td><td>7.5</td><td>4.2</td><td>0.001</td></tr><tr><td>Non-fermented</td><td>33</td><td>0</td><td>0</td><td>6</td><td>1.8</td><td>0.108</td><td rowspan="2">0.845</td></tr><tr><td>Fermented</td><td>16</td><td>0</td><td>0</td><td>7</td><td>2.4</td><td>0.037</td></tr></tbody></table>

<figure><img src="image_32.png" /><figcaption>**Figure 4.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" among the subject categories. Subject categories: HEALTH, healthy subjects; MET, subject with metabolic disorders including obesity; GIT, subjects with gastrointestinal disorders; HYPER, subjects with hypersensitivity, including allergy, to milk products. The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

with convincingly addressing clinical outcomes, as described by the descriptor "Clinical evidence" in Tables 3–5, are unsurprisingly scarce.

Validation issues are raised by new analytical technologies that now allow researchers to quantitate large sets of inflammatory markers in a single measurement (Liu et al., 2005; Breen et al., 2011; Thompson et al., 2012). Although these analytical issues were not discussed in the set of human trials reviewed, particular care should be taken in the future to better characterize the performance of these tests.

Regulatory authorities clearly highlight the importance of characterizing the food products investigated in human trials in their guidance for the authorization of health claims (EFSA Panel on Dietetic Products Nutrition and Allergies, 2011; FDA Office of Nutrition Labeling and Dietary Supplements, 2009). However, the studies reported in this review give little emphasis on the characterization of the dairy products investigated, as

<figure><img src="image_33.png" /><figcaption>**Figure 5.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" among the dairy product categories "high-fat" and "low-fat". The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

<figure><img src="image_34.png" /><figcaption>**Figure 6.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" among the dairy product categories "fermented" and "non-fermented". The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

<footnote n="1">¹Abbreviations: Q1, first quartile; Q3: third quartile.</footnote>

<footnote n="2">²Wilcoxon Signed-Rank test (two-sided).</footnote>

<footnote n="3">³Kruskal-Wallis test.</footnote>
<figure><img src="image_32.png" /><figcaption>**Table 6.** Inflammatory Score for the impact of dairy products on humans.</figcaption></figure>

<table><thead><tr><th></th><th></th><th>N</th><th>Q1<sup>1</sup></th><th>Median</th><th>Q3<sup>1</sup></th><th>Mean</th><th>p<sup>2</sup></th><th>p<sup>3</sup></th></tr></thead><tbody><tr><td rowspan="2">All data</td><td rowspan="2">ALL study results</td><td>78</td><td>0</td><td>0</td><td>6</td><td>1.4</td><td>0.009</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="5">Subject category</td><td>HEALTH</td><td>37</td><td>-3.2</td><td>0</td><td>6</td><td>1.7</td><td>0.017</td><td rowspan="5">0.083</td></tr><tr><td>MET</td><td>24</td><td>0</td><td>4.5</td><td>7.5</td><td>3.9</td><td>0.001</td></tr><tr><td>GIT</td><td>8</td><td>-5.5</td><td>-2.5</td><td>0</td><td>-3.1</td><td>0.066</td></tr><tr><td>HYPER</td><td>6</td><td>-6</td><td>-6</td><td>-6</td><td>-5.5</td><td>0.034</td></tr><tr><td>OTHER</td><td>3</td><td>0</td><td>0</td><td>6.75</td><td>3.0</td><td>0.317</td></tr><tr><td rowspan="4">Product category</td><td>High-fat</td><td>35</td><td>-2.25</td><td>0</td><td>6</td><td>1.7</td><td>0.017</td><td rowspan="2">0.084</td></tr><tr><td>Low-fat</td><td>20</td><td>0</td><td>4.5</td><td>7.5</td><td>4.2</td><td>0.001</td></tr><tr><td>Non-fermented</td><td>33</td><td>0</td><td>0</td><td>6</td><td>1.8</td><td>0.108</td><td rowspan="2">0.845</td></tr><tr><td>Fermented</td><td>16</td><td>0</td><td>0</td><td>7</td><td>2.4</td><td>0.037</td></tr></tbody></table>

<figure><img src="image_33.png" /><figcaption>**Figure 4.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" among the subject categories. Subject categories: HEALTH, healthy subjects; MET, subject with metabolic disorders including obesity; GIT, subjects with gastrointestinal disorders; HYPER, subjects with hypersensitivity, including allergy, to milk products. The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

with convincingly addressing clinical outcomes, as described by the descriptor "Clinical evidence" in Tables 3–5, are unsurprisingly scarce.

Validation issues are raised by new analytical technologies that now allow researchers to quantitate large sets of inflammatory markers in a single measurement (Liu et al., 2005; Breen et al., 2011; Thompson et al., 2012). Although these analytical issues were not discussed in the set of human trials reviewed, particular care should be taken in the future to better characterize the performance of these tests.

Regulatory authorities clearly highlight the importance of characterizing the food products investigated in human trials in their guidance for the authorization of health claims (EFSA Panel on Dietetic Products Nutrition and Allergies, 2011; FDA Office of Nutrition Labeling and Dietary Supplements, 2009). However, the studies reported in this review give little emphasis on the characterization of the dairy products investigated, as

<figure><img src="image_34.png" /><figcaption>**Figure 5.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" among the dairy product categories "high-fat" and "low-fat". The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

<figure><img src="image_35.png" /><figcaption>**Figure 6.** Distribution of the study results labeled as "anti-inflammatory", "no effect", and "pro-inflammatory" among the dairy product categories "fermented" and "non-fermented". The color code indicates the direction of change of the inflammatory marker, i.e., significant anti-inflammatory change (black bars), no significant change (grey bars), and significant pro-inflammatory change (white bars).</figcaption></figure>

<footnote n="1">¹Abbreviations: Q1, first quartile; Q3: third quartile.</footnote>

<footnote n="2">²Wilcoxon Signed-Rank test (two-sided).</footnote>

<footnote n="3">³Kruskal-Wallis test.</footnote>
<figure><img src="image_35.png" /></figure>

illustrated by a range of uncharacterized descriptors in Tables 3–5 (e.g., identification of bioactive nutrients, bioavailability data, dose-response effects, sustainability of the effect of the food product over time). In particular, integrating the variable ‘dose’ into study designs could allow researchers to draw a causal relationship between the food investigated and the physiological response measured in humans (Schwander et al., 2014). Also, although dozens of nutrients with immunomodulatory activity have been proposed in the literature (Ballard and Morrow, 2013), the bioactive nutrients potentially modulating inflammation in the reviewed studies, remain largely unknown even considering animal studies. The major reason for this gap is clearly inherent to the complex molecular composition of food. In light of the importance of the food matrix on the properties of bioactive nutrients, we endorse that food and nutrition research should shift its focus from the characterization of the nutritional and immunomodulatory properties of isolated nutrients to the characterization of foods, meals, and even dietary patterns.

The scientific basis for claims on bioactive food and nutrients established by national regulatory authorities is not harmonized, thereby hindering internationally harmonized market access (Aggett et al., 2012). To date, a very high number of requested health claims (more than 80%) have been rejected by the EFSA's NDA Panel, who underlined the need to identify the molecule(s) responsible of the claimed effect, and their mechanisms of action. The mechanisms of action of bioactives are usually studied in vitro, whereas in vivo studies are very often focused on demonstrating an effect on specific endpoints, without considering the underlying mechanisms. Evidence of the anti-inflammatory effectiveness of dairy components could be retrieved from in vitro studies, but they were not considered in this review for a specific reason, i.e., bioactive components are just one part of food, embedded in a very complex matrix. Cell supplementation in in vitro studies, as well as intervention studies administering bioactives as pure compounds assume that there are no confounding effects related to the food matrix. The food matrix, as well as food processing (Bordoni et al., 2011) can, indeed modify the digestibility and bioavailability of bioactive compounds, thus introducing a fundamental bias when translating in vitro data to humans. The ideal in vitro study should thus digest food in a static or dynamic model of digestion, have the digested nutrients transported through an intestinal cellular layer mimicking the gastrointestinal barrier, ideally with a model integrating the gut microbiota, and finally measure the ability of the absorbed nutrients to modulate inflammation. Such integrated in vitro models have not yet been successfully developed, although first steps in that direction have already been taken (Vergeres et al., 2012). Meanwhile, the COST action FA1005 ‘Improving health properties of food by sharing our knowledge on the digestive process’ (INFOGEST) has published an harmonized protocol of in vitro digestion (Minekus et al., 2014). To perform in vitro digestion prior to in vitro studies will help to bypass the enormous, and unscientific, gap in our knowledge related to the assumption, without any demonstration, that the in vivo effects of foods are related to the mechanisms of action observed in vitro supplementing cells with pure molecules. In vitro studies supplementing cells with digested food can mimic in a closer way the in vivo effects and

underlying mechanism of actions of food bioactives, thus evidencing the cause-effect relationship as requested by the body authorities.

## Strengths and limitations of the IS

The literature focusing on the impact of dairy products on inflammatory processes in humans revealed a very heterogeneous methodological landscape. The IS was therefore defined in order to take these limitations into account as follows:

Inflammation is a complex phenomenon that cannot be described by a single biomarker (Calder et al., 2013). Indeed, more than fifty inflammatory markers were reported in the pool of the 52 human studies reviewed. The data consisted of cellular markers of inflammation and measures of tissue infiltration, but the majority of studies concentrated on a few soluble circulatory cytokines. Furthermore, the number of markers measured in each study varied from one to more than ten. These points all raised the issue of the weighting of each study result in this heterogeneous environment. For the sake of simplicity, and to avoid over-interpreting the data, we decided to (i) rate each of the inflammatory markers listed in Table 1 at the same level and (ii) to increase the IS by one unit in cases in which changes in the concentration of more than one inflammatory markers were pointing in the same direction (see point 5 in Table 2). Note, however, that the IS was not upgraded by additional grades for studies in which more than two inflammatory markers were concordantly changed as this would have given too much weight to this criterion compared to the ten other criteria presented in Table 2.

As milk is amenable to a wide range of technological transformations and important in human diets, a large spectrum of dairy products was investigated in the 52 reviewed studies. As each of these products may differently modulate inflammation, we addressed this issue by defining a limited range of product categories in which the data could be stratified and analyzed (low-fat vs. high fat; fermented vs. non-fermented).

The health status of the subjects enrolled in the 52 studies was quite diverse, reflecting the generic importance of inflammatory processes in modulating human health and disease. The clinical indications targeted by these studies were consequently heterogeneous and we therefore classified the study results according to a limited, but clinically meaningful, set of subject categories (HEALTH, MET, GIT, HYPER).

Given the relative paucity of high-quality studies on the topic of dairy and inflammation, we chose an inclusive strategy which means that we considered all available publications on dairy and systemic inflammation, including randomized controlled trials, cross-over design trials and longitudinal cohort studies. This approach enabled us to analyze data from studies per se not considered in systemic reviews and we could thus provide a wide overview of studies dealing with dairy and inflammation. The downside of this strategy is that some studies of low quality, small sample size and short duration, were included in this review.

The last issue that became evident during the reviewing process, is the usage of dairy products as controls in human studies actually aiming at investigating the ability of other food products to modulate inflammatory processes. This phenomenon was particularly the case for clinical studies using the milk matrix to supplement the test meals with bioactive
<figure><img src="image_36.png" /></figure>

illustrated by a range of uncharacterized descriptors in Tables 3–5 (e.g., identification of bioactive nutrients, bioavailability data, dose-response effects, sustainability of the effect of the food product over time). In particular, integrating the variable ‘dose’ into study designs could allow researchers to draw a causal relationship between the food investigated and the physiological response measured in humans (Schwander et al., 2014). Also, although dozens of nutrients with immunomodulatory activity have been proposed in the literature (Ballard and Morrow, 2013), the bioactive nutrients potentially modulating inflammation in the reviewed studies, remain largely unknown even considering animal studies. The major reason for this gap is clearly inherent to the complex molecular composition of food. In light of the importance of the food matrix on the properties of bioactive nutrients, we endorse that food and nutrition research should shift its focus from the characterization of the nutritional and immunomodulatory properties of isolated nutrients to the characterization of foods, meals, and even dietary patterns.

The scientific basis for claims on bioactive food and nutrients established by national regulatory authorities is not harmonized, thereby hindering internationally harmonized market access (Aggett et al., 2012). To date, a very high number of requested health claims (more than 80%) have been rejected by the EFSA's NDA Panel, who underlined the need to identify the molecule(s) responsible of the claimed effect, and their mechanisms of action. The mechanisms of action of bioactives are usually studied in vitro, whereas in vivo studies are very often focused on demonstrating an effect on specific endpoints, without considering the underlying mechanisms. Evidence of the anti-inflammatory effectiveness of dairy components could be retrieved from in vitro studies, but they were not considered in this review for a specific reason, i.e., bioactive components are just one part of food, embedded in a very complex matrix. Cell supplementation in in vitro studies, as well as intervention studies administering bioactives as pure compounds assume that there are no confounding effects related to the food matrix. The food matrix, as well as food processing (Bordoni et al., 2011) can, indeed modify the digestibility and bioavailability of bioactive compounds, thus introducing a fundamental bias when translating in vitro data to humans. The ideal in vitro study should thus digest food in a static or dynamic model of digestion, have the digested nutrients transported through an intestinal cellular layer mimicking the gastrointestinal barrier, ideally with a model integrating the gut microbiota, and finally measure the ability of the absorbed nutrients to modulate inflammation. Such integrated in vitro models have not yet been successfully developed, although first steps in that direction have already been taken (Vergeres et al., 2012). Meanwhile, the COST action FA1005 ‘Improving health properties of food by sharing our knowledge on the digestive process’ (INFOGEST) has published an harmonized protocol of in vitro digestion (Minekus et al., 2014). To perform in vitro digestion prior to in vitro studies will help to bypass the enormous, and unscientific, gap in our knowledge related to the assumption, without any demonstration, that the in vivo effects of foods are related to the mechanisms of action observed in vitro supplementing cells with pure molecules. In vitro studies supplementing cells with digested food can mimic in a closer way the in vivo effects and

underlying mechanism of actions of food bioactives, thus evidencing the cause-effect relationship as requested by the body authorities.

## Strengths and limitations of the IS

The literature focusing on the impact of dairy products on inflammatory processes in humans revealed a very heterogeneous methodological landscape. The IS was therefore defined in order to take these limitations into account as follows:

Inflammation is a complex phenomenon that cannot be described by a single biomarker (Calder et al., 2013). Indeed, more than fifty inflammatory markers were reported in the pool of the 52 human studies reviewed. The data consisted of cellular markers of inflammation and measures of tissue infiltration, but the majority of studies concentrated on a few soluble circulatory cytokines. Furthermore, the number of markers measured in each study varied from one to more than ten. These points all raised the issue of the weighting of each study result in this heterogeneous environment. For the sake of simplicity, and to avoid over-interpreting the data, we decided to (i) rate each of the inflammatory markers listed in Table 1 at the same level and (ii) to increase the IS by one unit in cases in which changes in the concentration of more than one inflammatory markers were pointing in the same direction (see point 5 in Table 2). Note, however, that the IS was not upgraded by additional grades for studies in which more than two inflammatory markers were concordantly changed as this would have given too much weight to this criterion compared to the ten other criteria presented in Table 2.

As milk is amenable to a wide range of technological transformations and important in human diets, a large spectrum of dairy products was investigated in the 52 reviewed studies. As each of these products may differently modulate inflammation, we addressed this issue by defining a limited range of product categories in which the data could be stratified and analyzed (low-fat vs. high fat; fermented vs. non-fermented).

The health status of the subjects enrolled in the 52 studies was quite diverse, reflecting the generic importance of inflammatory processes in modulating human health and disease. The clinical indications targeted by these studies were consequently heterogeneous and we therefore classified the study results according to a limited, but clinically meaningful, set of subject categories (HEALTH, MET, GIT, HYPER).

Given the relative paucity of high-quality studies on the topic of dairy and inflammation, we chose an inclusive strategy which means that we considered all available publications on dairy and systemic inflammation, including randomized controlled trials, cross-over design trials and longitudinal cohort studies. This approach enabled us to analyze data from studies per se not considered in systemic reviews and we could thus provide a wide overview of studies dealing with dairy and inflammation. The downside of this strategy is that some studies of low quality, small sample size and short duration, were included in this review.

The last issue that became evident during the reviewing process, is the usage of dairy products as controls in human studies actually aiming at investigating the ability of other food products to modulate inflammatory processes. This phenomenon was particularly the case for clinical studies using the milk matrix to supplement the test meals with bioactive
<figure><img src="image_36.png" /></figure>

components. Given the potential bioactivity of dairy products, we decided to also evaluate their properties even when used as control products, although this might pose the risk of misleading information when comparing data against baseline within randomized groups (Bland and Altman, 2011).

## Conclusions

We have established the IS as a new tool to conduct a quantitative evaluation of human studies investigating the impact of dairy products on inflammation. Taken together, our review suggests that dairy products, in particular fermented products, have anti-inflammatory properties in humans not suffering from allergy to milk, in particular in subjects with metabolic disorders. As the clinical relevance of inflammatory markers is currently debated among researchers and regulatory authorities, the translation of these findings into dietary guidelines remains to be clarified.

## Acknowledgments

We thank Ueli Bütikofer and Diklah Geva for support on the statistical analyses. We also thank Capucine Musard for a preliminary analysis of the literature on the topic of this review.

## Funding

The authors of this review are members of the FA COST Action FA1005 "Improving health properties of food by sharing our knowledge on the digestive process" (INFOGEST) that financed the travel costs for the meetings of the MindTheGap project team. This work was, furthermore financed by the institutions employing the authors of this report. The work of PP and CNS was supported by Fundação para a Ciência e Tecnologia (PEst-OE/ EQB/LA0004/2011 and IF/01097/2013).

## References

* Aggett, P. J., Hathcock, J., Jukes, D., Richardson, D. P., Calder, P. C., Bischoff-Ferrari, H., Nicklas, T., Muhlebach, S., Kwon, O., Lewis, J., Lugard, M. J. and Prock, P. (2012). Nutrition issues in Codex: health claims, nutrient reference values and WTO agreements: a conference report. *Eur. J. Nutr.* **51**(Suppl 1):S1–S7.

* Arvola, T., Ruuska, T., Keranen, J., Hyoty, H., Salminen, S. and Isolauri, E. (2006). Rectal bleeding in infancy: clinical, allergological, and microbiological examination. *Pediatrics* **117**:e760–e768.

* Asemi, Z., Samimi, M., Tabassi, Z., Sabihi, S. S. and Esmaillzadeh, A. (2013). A randomized controlled clinical trial investigating the effect of DASH diet on insulin resistance, inflammation, and oxidative stress in gestational diabetes. *Nutrition* **29**:619–624.

* Augustin, M. A. and Udabage, P. (2007). Influence of processing on functionality of milk and dairy proteins. *Adv. Food Nutr. Res.* **53**:1–38.

* Ballard, O. and Morrow, A. L. (2013). Human milk composition: nutrients and bioactive factors. *Pediatr. Clin. North Am.* **60**:49–74.

* Beavers, K. M., Serra, M. C., Beavers, D. P., Cooke, M. B. and Willoughby, D. S. (2009). Soymilk supplementation does not alter plasma markers of inflammation and oxidative stress in postmenopausal women. *Nutr Res* **29**:616–622.

* Bland, J. M. and Altman, D. G. (2011). Comparisons against baseline within randomised groups are often used and can be highly misleading. *Trials* **12**:264.

* Bordini, A., Picone, G., Babini, E., Vignali, M., Danesi, F., Valli, V., Di, N. M., Laghi, L. and Capozzi, F. (2011). NMR comparison of in vitro digestion of Parmigiano Reggiano cheese aged 15 and 30 months. *Magn. Reson. Chem.* **49**(Suppl 1):S61–S70.

* Breen, E. C., Reynolds, S. M., Cox, C., Jacobson, L. P., Magpantay, L., Mulder, C. B., Dibben, O., Margolick, J. B., Bream, J. H., Sambrano, E., Martinez-Maza, O., Sinclair, E., Borrow, P., Landay, A. L., Rinaldo, C. R. and Norris, P. J. (2011). Multisite comparison of high-sensitivity multiplex cytokine assays. *Clin. Vaccine Immunol.* **18**:1229–1242.

* Calder, P. C., Ahluwalia, N., Albers, R., Bosco, N., Bourdet-Sicard, R., Haller, D., Holgate, S. T., Jonsson, L. S., Latulippe, M. E., Marcos, A., Moreines, J., M'Rini, C., Muller, M., Pawelec, G., van Neerven, R. J., Watzl, B. and Zhao, J. (2013). A consideration of biomarkers to be used for evaluation of inflammation in human nutritional studies. *Br. J. Nutr.* **109**(Suppl 1):S1–34.

* Calder, P. C., Ahluwalia, N., Brouns, F., Buetler, T., Clement, K., Cunningham, K., Esposito, K., Jonsson, L. S., Kolb, H., Lansink, M., Marcos, A., Margioris, A., Matusheski, N., Nordmann, H., O'Brien, J., Pugliese, G., Rizkalla, S., Schalkwijk, C., Tuomilehto, J., Warnberg, J., Watzl, B. and Winklhofer-Roob, B. M. (2011). Dietary factors and low-grade inflammation in relation to overweight and obesity. *Br. J. Nutr.* **106**(Suppl 3):S5–78.

* Candore, G., Caruso, C., Jirillo, E., Magrone, T. and Vasto, S. (2010). Low grade inflammation as a common pathogenetic denominator in age-related diseases: novel drug targets for anti-ageing strategies and successful ageing achievement. *Curr. Pharm. Des.* **16**:584–596.

* Ceapa, C., Wopereis, H., Rezaiki, L., Kleerebezem, M., Knol, J. and Oozeer, R. (2013). Influence of fermented milk products, prebiotics and probiotics on microbiota composition and health. *Best Pract. Res. Clin. Gastroenterol.* **27**:139–155.

* Chatterton, D. E., Nguyen, D. N., Bering, S. B. and Sangild, P. T. (2013). Anti-inflammatory mechanisms of bioactive milk proteins in the intestine of newborns. *Int. J. Biochem. Cell Biol.* **45**:1730–1747.

* Dalbeth, N., Ames, R., Gamble, G. D., Horne, A., Wong, S., Kuhn-Sherlock, B., MacGibbon, A., McQueen, F. M., Reid, I. R. and Palamano, K. (2012). Effects of skim milk powder enriched with glycomacropeptide and G600 milk fat extract on frequency of gout flares: a proof-of-concept randomised controlled trial. *Ann Rheum. Dis.* **71**:929–934.

* Dawczynski, C., Massey, K. A., Ness, C., Kiehntopf, M., Stepanow, S., Platzer, M., Grun, M., Nicolaou, A. and Jahreis, G. (2013). Randomized placebo-controlled intervention with n-3 LC-PUFA-supplemented yoghurt: effects on circulating eicosanoids and cardiovascular risk factors. *Clin. Nutr.* **32**:686–696.

* Dawczynski, C., Schubert, R., Hein, G., Muller, A., Eidner, T., Vogelsang, H., Basu, S. and Jahreis, G. (2009). Long-term moderate intervention with n-3 long-chain PUFA-supplemented dairy products: effects on pathophysiological biomarkers in patients with rheumatoid arthritis. *Br. J Nutr* **101**:1517–1526.

* De Aguilar-Nascimento, J. E., Prado Silveira, B. R. and Dock-Nascimento, D. B. (2011). Early enteral nutrition with whey protein or casein in elderly patients with acute ischemic stroke: a double-blind randomized trial. *Nutrition* **27**:440–444.

* Deopurkar, R., Ghanim, H., Friedman, J., Abuaysheh, S., Sia, C. L., Mohanty, P., Viswanathan, P., Chaudhuri, A. and Dandona, P. (2010). Differential effects of cream, glucose, and orange juice on inflammation, endotoxin, and the expression of Toll-like receptor-4 and suppressor of cytokine signaling-3. *Diabetes Care* **33**:991–997.

* Dunne, C., O'Mahony, L., Murphy, L., Thornton, G., Morrissey, D., O'Halloran, S., Feeney, M., Flynn, S., Fitzgerald, G., Daly, C., Kiely, B., O'sullivan, G. C., Shanahan, F. and Collins, J. K. (2001). In vitro selection criteria for probiotic bacteria of human origin: correlation with in vivo findings. *Am. J. Clin. Nutr.* **73**:386S–392S.

* EFSA Panel on Dietetic Products Nutrition and Allergies. (2011). Scientific and technical guidance for the preparation and presentation of an application for authorisation of a health claim (revision 1). 9 edn, p. 2170.

* EFSA Panel on Dietetic Products, N. a. A. (2011). Guidance on the scientific requirements for health claims related to gut and immune function. *EFSA J.*. **9**:1984.

* Esmaillzadeh, A., Kimiagar, M., Mehrabi, Y., Azadbakht, L., Hu, F. B. and Willett, W. C. (2007). Dietary patterns and markers of systemic inflammation among Iranian women. *J. Nutr.* **137**:992–998.

* FAO. (2013a). Food outlook - Biannual report on global food markets.

* FAO. (2013b). Milk and dairy products in human nutrition.

* FDA Office of Nutrition Labeling and Dietary Supplements. (2009). Guidance for Industry: Evidence-Based Review System for the Scientific Evaluation of Health Claims.
components. Given the potential bioactivity of dairy products, we decided to also evaluate their properties even when used as control products, although this might pose the risk of misleading information when comparing data against baseline within randomized groups (Bland and Altman, 2011).

## Conclusions

We have established the IS as a new tool to conduct a quantitative evaluation of human studies investigating the impact of dairy products on inflammation. Taken together, our review suggests that dairy products, in particular fermented products, have anti-inflammatory properties in humans not suffering from allergy to milk, in particular in subjects with metabolic disorders. As the clinical relevance of inflammatory markers is currently debated among researchers and regulatory authorities, the translation of these findings into dietary guidelines remains to be clarified.

## Acknowledgments

We thank Ueli Bütikofer and Diklah Geva for support on the statistical analyses. We also thank Capucine Musard for a preliminary analysis of the literature on the topic of this review.

## Funding

The authors of this review are members of the FA COST Action FA1005 "Improving health properties of food by sharing our knowledge on the digestive process" (INFOGEST) that financed the travel costs for the meetings of the MindTheGap project team. This work was, furthermore financed by the institutions employing the authors of this report. The work of PP and CNS was supported by Fundação para a Ciência e Tecnologia (PEst-OE/ EQB/LA0004/2011 and IF/01097/2013).

## References

Aggett, P. J., Hathcock, J., Jukes, D., Richardson, D. P., Calder, P. C., Bischoff-Ferrari, H., Nicklas, T., Muhlebach, S., Kwon, O., Lewis, J., Lugard, M. J. and Prock, P. (2012). Nutrition issues in Codex: health claims, nutrient reference values and WTO agreements: a conference report. *Eur. J. Nutr.* **51**(Suppl 1):S1–S7.

Arvola, T., Ruuska, T., Keranen, J., Hyoty, H., Salminen, S. and Isolauri, E. (2006). Rectal bleeding in infancy: clinical, allergological, and microbiological examination. *Pediatrics* **117**:e760–e768.

Asemi, Z., Samimi, M., Tabassi, Z., Sabihi, S. S. and Esmaillzadeh, A. (2013). A randomized controlled clinical trial investigating the effect of DASH diet on insulin resistance, inflammation, and oxidative stress in gestational diabetes. *Nutrition* **29**:619–624.

Augustin, M. A. and Udabage, P. (2007). Influence of processing on functionality of milk and dairy proteins. *Adv. Food Nutr. Res.* **53**:1–38.

Ballard, O. and Morrow, A. L. (2013). Human milk composition: nutrients and bioactive factors. *Pediatr. Clin. North Am.* **60**:49–74.

Beavers, K. M., Serra, M. C., Beavers, D. P., Cooke, M. B. and Willoughby, D. S. (2009). Soymilk supplementation does not alter plasma markers of inflammation and oxidative stress in postmenopausal women. *Nutr Res* **29**:616–622.

Bland, J. M. and Altman, D. G. (2011). Comparisons against baseline within randomised groups are often used and can be highly misleading. *Trials* **12**:264.

Bordoni, A., Picone, G., Babini, E., Vignali, M., Danesi, F., Valli, V., Di, N. M., Laghi, L. and Capozzi, F. (2011). NMR comparison of in vitro digestion of Parmigiano Reggiano cheese aged 15 and 30 months. *Magn. Reson. Chem.* **49**(Suppl 1):S61–S70.

Breen, E. C., Reynolds, S. M., Cox, C., Jacobson, L. P., Magpantay, L., Mulder, C. B., Dibben, O., Margolick, J. B., Bream, J. H., Sambrano, E., Martinez-Maza, O., Sinclair, E., Borrow, P., Landay, A. L., Rinaldo, C. R. and Norris, P. J. (2011). Multisite comparison of high-sensitivity multiplex cytokine assays. *Clin. Vaccine Immunol.* **18**:1229–1242.

Calder, P. C., Ahluwalia, N., Albers, R., Bosco, N., Bourdet-Sicard, R., Haller, D., Holgate, S. T., Jonsson, L. S., Latulippe, M. E., Marcos, A., Moreines, J., M'Rini, C., Muller, M., Pawelec, G., van Neerven, R. J., Watzl, B. and Zhao, J. (2013). A consideration of biomarkers to be used for evaluation of inflammation in human nutritional studies. *Br. J. Nutr.* **109**(Suppl 1):S1–34.

Calder, P. C., Ahluwalia, N., Brouns, F., Buetler, T., Clement, K., Cunningham, K., Esposito, K., Jonsson, L. S., Kolb, H., Lansink, M., Marcos, A., Margioris, A., Matusheski, N., Nordmann, H., O'Brien, J., Pugliese, G., Rizkalla, S., Schalkwijk, C., Tuomilehto, J., Warnberg, J., Watzl, B. and Winklhofer-Roob, B. M. (2011). Dietary factors and low-grade inflammation in relation to overweight and obesity. *Br. J. Nutr.* **106**(Suppl 3):S5–78.

Candore, G., Caruso, C., Jirillo, E., Magrone, T. and Vasto, S. (2010). Low grade inflammation as a common pathogenetic denominator in age-related diseases: novel drug targets for anti-ageing strategies and successful ageing achievement. *Curr. Pharm. Des.* **16**:584–596.

Ceapa, C., Wopereis, H., Rezaiki, L., Kleerebezem, M., Knol, J. and Oozeer, R. (2013). Influence of fermented milk products, prebiotics and probiotics on microbiota composition and health. *Best Pract. Res. Clin. Gastroenterol.* **27**:139–155.

Chatterton, D. E., Nguyen, D. N., Bering, S. B. and Sangild, P. T. (2013). Anti-inflammatory mechanisms of bioactive milk proteins in the intestine of newborns. *Int. J. Biochem. Cell Biol.* **45**:1730–1747.

Dalbeth, N., Ames, R., Gamble, G. D., Horne, A., Wong, S., Kuhn-Sherlock, B., MacGibbon, A., McQueen, F. M., Reid, I. R. and Palamano, K. (2012). Effects of skim milk powder enriched with glycomacropeptide and G600 milk fat extract on frequency of gout flares: a proof-of-concept randomised controlled trial. *Ann Rheum Dis.* **71**:929–934.

Dawczynski, C., Massey, K. A., Ness, C., Kiehntopf, M., Stepanow, S., Platzer, M., Grun, M., Nicolaou, A. and Jahreis, G. (2013). Randomized placebo-controlled intervention with n-3 LC-PUFA-supplemented yoghurt: effects on circulating eicosanoids and cardiovascular risk factors. *Clin. Nutr.* **32**:686–696.

Dawczynski, C., Schubert, R., Hein, G., Muller, A., Eidner, T., Vogelsang, H., Basu, S. and Jahreis, G. (2009). Long-term moderate intervention with n-3 long-chain PUFA-supplemented dairy products: effects on pathophysiological biomarkers in patients with rheumatoid arthritis. *Br. J Nutr* **101**:1517–1526.

De Aguilar-Nascimento, J. E., Prado Silveira, B. R. and Dock-Nascimento, D. B. (2011). Early enteral nutrition with whey protein or casein in elderly patients with acute ischemic stroke: a double-blind randomized trial. *Nutrition* **27**:440–444.

Deopurkar, R., Ghanim, H., Friedman, J., Abuaysheh, S., Sia, C. L., Mohanty, P., Viswanathan, P., Chaudhuri, A. and Dandona, P. (2010). Differential effects of cream, glucose, and orange juice on inflammation, endotoxin, and the expression of Toll-like receptor-4 and suppressor of cytokine signaling-3. *Diabetes Care* **33**:991–997.

Dunne, C., O'Mahony, L., Murphy, L., Thornton, G., Morrissey, D., O'Halloran, S., Feeney, M., Flynn, S., Fitzgerald, G., Daly, C., Kiely, B., O'sullivan, G. C., Shanahan, F. and Collins, J. K. (2001). In vitro selection criteria for probiotic bacteria of human origin: correlation with in vivo findings. *Am. J. Clin. Nutr.* **73**:386S–392S.

EFSA Panel on Dietetic Products Nutrition and Allergies. (2011). Scientific and technical guidance for the preparation and presentation of an application for authorisation of a health claim (revision 1). 9 edn, p. 2170.

EFSA Panel on Dietetic Products, N. a. A. (2011). Guidance on the scientific requirements for health claims related to gut and immune function. *EFSA J. Food* **9**:1984.

Esmaillzadeh, A., Kimiagar, M., Mehrabi, Y., Azadbakht, L., Hu, F. B. and Willett, W. C. (2007). Dietary patterns and markers of systemic inflammation among Iranian women. *J. Nutr.* **137**:992–998.

FAO. (2013a). Food outlook - Biannual report on global food markets.

FAO. (2013b). Milk and dairy products in human nutrition.

FDA Office of Nutrition Labeling and Dietary Supplements. (2009). Guidance for Industry: Evidence-Based Review System for the Scientific Evaluation of Health Claims.
<figure><img src="image_37.png" /></figure>

German, J. B. and Dillard, C. J. (2006). Composition, structure and absorption of milk lipids: a source of energy, fat-soluble nutrients and bioactive molecules. *Crit. Rev. Food Sci. Nutr.* **46**:57–92.

Global Business Intelligence Research. (2011). Anti-Inflammatory Therapeutics Market to 2017 - Respiratory Diseases and Arthritis Continue to Dominate.

Gonsalves, N., Yang, G. Y., Doerfler, B., Ritz, S., Ditto, A. M. and Hirano, I. (2012). Elimination diet effectively treats eosinophilic esophagitis in adults; food reintroduction identifies causative factors. *Gastroenterology* **142**:1451–1459.

Guri, A. J. and Bassaganya-Riera, J. (2011). Systemic effects of white adipose tissue dysregulation and obesity-related inflammation. *Obesity* (*Silver Spring*) **19**:689–700.

Hakansson, A. and Molin, G. (2011). Gut microbiota and inflammation. *Nutrients* **3**:637–682.

Haug, A., Hostmark, A. T. and Harstad, O. M. (2007). Bovine milk in human nutrition—a review. *Lipids Health Dis.* **6**:25.

Henderson, C. J., Abonia, J. P., King, E. C., Putnam, P. E., Collins, M. H., Franciosi, J. P. and Rothenberg, M. E. (2012). Comparative dietary therapy effectiveness in remission of pediatric eosinophilic esophagitis. *J Allergy Clin Immunol* **129**:1570–1578.

Hernandez-Aguilera, A., Rull, A., Rodriguez-Gallego, E., Riera-Borrull, M., Luciano-Mateo, F., Camps, J., Menendez, J. A. and Joven, J. (2013). Mitochondrial dysfunction: a basic mechanism in inflammation-related non-communicable diseases and therapeutic opportunities. *Mediators Inflamm.* **2013**:135698.

Hirai, S., Takahashi, N., Goto, T., Lin, S., Uemura, T., Yu, R. and Kawada, T. (2010). Functional food targeting the regulation of obesity-induced inflammatory responses and pathologies. *Mediators Inflamm.* **2010**:367838.

Hlebowicz, J., Persson, M., Gullberg, B., Sonestedt, E., Wallstrom, P., Drake, I., Nilsson, J., Hedblad, B. and Wirfalt, E. (2011). Food patterns, inflammation markers and incidence of cardiovascular disease: the Malmo Diet and Cancer study. *J Intern Med* **270**:365–376.

Holmer-Jensen, J., Karhu, T., Mortensen, L. S., Pedersen, S. B., Herzig, K. H. and Hermansen, K. (2011). Differential effects of dietary protein sources on postprandial low-grade inflammation after a single high fat meal in obese non-diabetic subjects. *Nutr J* **10**:115.

Hotamisligil, G. S. (2006). Inflammation and metabolic disorders. *Nature* **444**:860–867.

Hunter, D. C., Brown, R., Green, T., Thomson, C., Skeaff, M., Williams, S., Todd, J. M., Lister, C. E., McGhie, T., Zhang, J., Martin, H., Rippon, P., Stanley, R. and Skinner, M. A. (2012). Changes in markers of inflammation, antioxidant capacity and oxidative stress in smokers following consumption of milk, and milk supplemented with fruit and vegetable extracts and vitamin C. *Int J Food Sci Nutr* **63**:90–102.

Hunter, D. J. and Reddy, K. S. (2013). Noncommunicable diseases. *N. Engl. J. Med.* **369**:1336–1343.

Iacono, G., Cavataio, F., Montalto, G., Florena, A., Tumminello, M., Soresi, M., Notarbartolo, A. and Carroccio, A. (1998). Intolerance of cow's milk and chronic constipation in children. *N Engl J Med* **339**:1100–1104.

Iwasa, M., Aoi, W., Mune, K., Yamauchi, H., Furuta, K., Sasaki, S., Takeda, K., Harada, K., Wada, S., Nakamura, Y., Sato, K. and Higashi, A. (2013). Fermented milk improves glucose metabolism in exercise-induced muscle damage in young healthy men. *Nutr. J.* **12**:83.

Jimenez-Flores, R., Heick, J., Davis, S. C., Hall, K. G. and Schaffner, A. (2012). A comparison of the effects of a high carbohydrate vs. a higher protein milk supplement following simulated mountain skirmishes. *Mil. Med* **177**:723–731.

Jones, K. W., Eller, L. K., Parnell, J. A., Doyle-Baker, P. K., Edwards, A. L. and Reimer, R. A. (2013). Effect of a dairy- and calcium-rich diet on weight loss and appetite during energy restriction in overweight and obese adults: a randomized trial. *Eur. J. Clin. Nutr.* **67**:371–376.

Jyonouchi, H., Sun, S. and Itokazu, N. (2002). Innate immunity associated with inflammatory responses and cytokine production against common dietary proteins in patients with autism spectrum disorder. *Neuropsychobiology* **46**:76–84.

Kagalwalla, A. F., Shah, A., Li, B. U., Sentongo, T. A., Ritz, S., Manuel-Rubio, M., Jacques, K., Wang, D., Melin-Aldana, H. and Nelson, S. P. (2011). Identification of specific foods responsible for inflammation in

children with eosinophilic esophagitis successfully treated with empiric elimination diet. *J Pediatr. Gastroenterol Nutr* **53**:145–149.

Kagalwalla, A. F., Amsden, K., Shah, A., Ritz, S., Manuel-Rubio, M., Dunne, K., Nelson, S. P., Wershil, B. K. and Melin-Aldana, H. (2012). Cow's milk elimination: a novel dietary approach to treat eosinophilic esophagitis. *J. Pediatr. Gastroenterol. Nutr.* **55**:711–716.

Kau, A. L., Ahern, P. P., Griffin, N. W., Goodman, A. L. and Gordon, J. I. (2011). Human nutrition, the gut microbiome and the immune system. *Nature* **474**:327–336.

Klop, B., Proctor, S. D., Mamo, J. C., Botham, K. M. and Castro, C. M. (2012). Understanding postprandial inflammation and its relationship to lifestyle behaviour and metabolic diseases. *Int. J. Vasc. Med.* **2012**:947417.

Kristjansson, G., Venge, P. and Hallgren, R. (2007). Mucosal reactivity to cow's milk protein in coeliac disease. *Clin Exp. Immunol* **147**:449–455.

Labonte, M. E., Couture, P., Richard, C., Desroches, S. and Lamarche, B. (2014). Impact of dairy products on biomarkers of inflammation: a systematic review of randomized controlled nutritional intervention studies in overweight and obese adults. *Am. J. Clin. Nutr.* **97**:706–717.

Lawrence, G. D. (2013). Dietary fats and health: dietary recommendations in the context of scientific evidence. *Adv. Nutr.* **4**:294–302.

Lee, Y. M., Skurk, T., Hennig, M. and Hauner, H. (2007). Effect of a milk drink supplemented with whey peptides on blood pressure in patients with mild hypertension. *Eur J Nutr* **46**:21–27.

Lepage, P. and Van de Perre, P. (2012). The immune system of breast milk: antimicrobial and anti-inflammatory properties. *Adv. Exp. Med. Biol.* **743**:121–137.

Liu, M. Y., Xydakis, A. M., Hoogeveen, R. C., Jones, P. H., Smith, E. O., Nelson, K. W. and Ballantyne, C. M. (2005). Multiplexed analysis of biomarkers related to obesity and the metabolic syndrome in human plasma, using the Luminex-100 system. *Clin. Chem.* **51**:1102–1109.

Lomax, A. R. and Calder, P. C. (2009). Probiotics, immune function, infection and inflammation: a review of the evidence from studies conducted in humans. *Curr. Pharm. Des.* **15**:1428–1518.

Melnik, B. C. (2009). Milk—the promoter of chronic Western diseases. *Med. Hypotheses.* **72**:631–639.

Meyer, A. L., Elmadfa, I., Herbacek, I. and Micksche, M. (2007). Probiotic, as well as conventional yogurt, can enhance the stimulated production of proinflammatory cytokines. *J Hum Nutr Diet* **20**:590–598.

Meyer, J., Doring, A., Herder, C., Roden, M., Koenig, W. and Thorand, B. (2011). Dietary patterns, subclinical inflammation, incident coronary heart disease and mortality in middle-aged men from the MONICA/KORA Augsburg cohort study. *Eur J Clin Nutr* **65**:800–807.

Micha, R. and Mozaffarian, D. (2009). Trans fatty acids: effects on metabolic syndrome, heart disease and diabetes. *Nat. Rev. Endocrinol.* **5**:335–344.

Minekus, M., Alminger, M., Alvito, P., Ballance, S., Bohn, T., Bourlieu, C., Carrière, F., Boutrou, R., Corredig, M., Dupont, D., Dufour, C., Egger, L., Golding, M., Karakaya, S., Birkhus, B., Le Feunteun, S., Lesmes, U., Maczierzanka, A., MacKie, A., Marze, S., McClements, D. J., Ménard, O., Recio, I., Santos, C. N., Singh, R. P., Vegarud, G. E., Wickham, M. S. J., Weitschies, W. and Brodkorb, A. (2014). A standardized static in vitro digestion method suitable for food - an international consensus. *Food. Funct. Jun*;5(6):1113–1124.

Moher, D., Liberati, A., Tetzlaff, J. and Altman, D. G. (2009). Reprint-preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. *Phys. Ther.* **89**:873–880.

Monagas, M., Khan, N., Andres-Lacueva, C., Casas, R., Urpi-Sarda, M., Llorach, R., Lamuela-Raventos, R. M. and Estruch, R. (2009). Effect of cocoa powder on the modulation of inflammatory biomarkers in patients at high risk of cardiovascular disease. *Am J Clin Nutr* **90**:1144–1150.

Nestel, P. J., Pally, S., MaCintosh, G. L., Greeve, M. A., Middleton, S., Jowett, J. and Meikle, P. J. (2012). Circulating inflammatory and atherogenic biomarkers are not increased following single meals of dairy foods. *Eur J Clin Nutr* **66**:25–31.

Nettleton, J. A., Steffen, L. M., Mayer-Davis, E. J., Jenny, N. S., Jiang, R., Herrington, D. M. and Jacobs, JR D. R. (2006). Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA). *Am J Clin Nutr* **83**:1369–1379.
<figure><img src="image_37.png" /></figure>

German, J. B. and Dillard, C. J. (2006). Composition, structure and absorption of milk lipids: a source of energy, fat-soluble nutrients and bioactive molecules. *Crit. Rev. Food Sci. Nutr.* **46**:57–92.

Global Business Intelligence Research. (2011). Anti-Inflammatory Therapeutics Market to 2017 - Respiratory Diseases and Arthritis Continue to Dominate.

Gonsalves, N., Yang, G. Y., Doerfler, B., Ritz, S., Ditto, A. M. and Hirano, I. (2012). Elimination diet effectively treats eosinophilic esophagitis in adults; food reintroduction identifies causative factors. *Gastroenterology* **142**:1451–1459.

Guri, A. J. and Bassaganya-Riera, J. (2011). Systemic effects of white adipose tissue dysregulation and obesity-related inflammation. *Obesity* (*Silver Spring*) **19**:689–700.

Hakansson, A. and Molin, G. (2011). Gut microbiota and inflammation. *Nutrients* **3**:637–682.

Haug, A., Hostmark, A. T. and Harstad, O. M. (2007). Bovine milk in human nutrition—a review. *Lipids Health Dis.* **6**:25.

Henderson, C. J., Abonia, J. P., King, E. C., Putnam, P. E., Collins, M. H., Franciosi, J. P. and Rothenberg, M. E. (2012). Comparative dietary therapy effectiveness in remission of pediatric eosinophilic esophagitis. *J Allergy Clin Immunol* **129**:1570–1578.

Hernandez-Aguilera, A., Rull, A., Rodriguez-Gallego, E., Riera-Borrull, M., Luciano-Mateo, F., Camps, J., Menendez, J. A. and Joven, J. (2013). Mitochondrial dysfunction: a basic mechanism in inflammation-related non-communicable diseases and therapeutic opportunities. *Mediators Inflamm.* **2013**:135698.

Hirai, S., Takahashi, N., Goto, T., Lin, S., Uemura, T., Yu, R. and Kawada, T. (2010). Functional food targeting the regulation of obesity-induced inflammatory responses and pathologies. *Mediators Inflamm.* **2010**:367838.

Hlebowicz, J., Persson, M., Gullberg, B., Sonestedt, E., Wallstrom, P., Drake, I., Nilsson, J., Hedblad, B. and Wirfalt, E. (2011). Food patterns, inflammation markers and incidence of cardiovascular disease: the Malmo Diet and Cancer study. *J Intern Med* **270**:365–376.

Holmer-Jensen, J., Karhu, T., Mortensen, L. S., Pedersen, S. B., Herzig, K. H. and Hermansen, K. (2011). Differential effects of dietary protein sources on postprandial low-grade inflammation after a single high fat meal in obese non-diabetic subjects. *Nutr J* **10**:115.

Hotamisligil, G. S. (2006). Inflammation and metabolic disorders. *Nature* **444**:860–867.

Hunter, D. C., Brown, R., Green, T., Thomson, C., Skeaff, M., Williams, S., Todd, J. M., Lister, C. E., McGhie, T., Zhang, J., Martin, H., Rippon, P., Stanley, R. and Skinner, M. A. (2012). Changes in markers of inflammation, antioxidant capacity and oxidative stress in smokers following consumption of milk, and milk supplemented with fruit and vegetable extracts and vitamin C. *Int J Food Sci Nutr* **63**:90–102.

Hunter, D. J. and Reddy, K. S. (2013). Noncommunicable diseases. *N. Engl. J. Med.* **369**:1336–1343.

Iacono, G., Cavataio, F., Montalto, G., Florena, A., Tumminello, M., Soresi, M., Notarbartolo, A. and Carroccio, A. (1998). Intolerance of cow's milk and chronic constipation in children. *N Engl J Med* **339**:1100–1104.

Iwasa, M., Aoi, W., Mune, K., Yamauchi, H., Furuta, K., Sasaki, S., Takeda, K., Harada, K., Wada, S., Nakamura, Y., Sato, K. and Higashi, A. (2013). Fermented milk improves glucose metabolism in exercised-induced muscle damage in young healthy men. *Nutr. J.* **12**:83.

Jimenez-Flores, R., Heick, J., Davis, S. C., Hall, K. G. and Schaffner, A. (2012). A comparison of the effects of a high carbohydrate vs. a higher protein milk supplement following simulated mountain skirmishes. *Mil. Med* **177**:723–731.

Jones, K. W., Eller, L. K., Parnell, J. A., Doyle-Baker, P. K., Edwards, A. L. and Reimer, R. A. (2013). Effect of a dairy- and calcium-rich diet on weight loss and appetite during energy restriction in overweight and obese adults: a randomized trial. *Eur. J. Clin. Nutr.* **67**:371–376.

Jyonouchi, H., Sun, S. and Itokazu, N. (2002). Innate immunity associated with inflammatory responses and cytokine production against common dietary proteins in patients with autism spectrum disorder. *Neuropsychobiology* **46**:76–84.

Kagalwalla, A. F., Shah, A., Li, B. U., Sentongo, T. A., Ritz, S., Manuel-Rubio, M., Jacques, K., Wang, D., Melin-Aldana, H. and Nelson, S. P. (2011). Identification of specific foods responsible for inflammation in

children with eosinophilic esophagitis successfully treated with empiric elimination diet. *J Pediatr. Gastroenterol Nutr* **53**:145–149.

Kagalwalla, A. F., Amsden, K., Shah, A., Ritz, S., Manuel-Rubio, M., Dunne, K., Nelson, S. P., Wershil, B. K. and Melin-Aldana, H. (2012). Cow's milk elimination: a novel dietary approach to treat eosinophilic esophagitis. *J. Pediatr. Gastroenterol. Nutr.* **55**:711–716.

Kau, A. L., Ahern, P. P., Griffin, N. W., Goodman, A. L. and Gordon, J. I. (2011). Human nutrition, the gut microbiome and the immune system. *Nature* **474**:327–336.

Klop, B., Proctor, S. D., Mamo, J. C., Botham, K. M. and Castro, C. M. (2012). Understanding postprandial inflammation and its relationship to lifestyle behaviour and metabolic diseases. *Int. J. Vasc. Med.* **2012**:947417.

Kristjansson, G., Venge, P. and Hallgren, R. (2007). Mucosal reactivity to cow's milk protein in coeliac disease. *Clin Exp. Immunol* **147**:449–455.

Labonte, M. E., Couture, P., Richard, C., Desroches, S. and Lamarche, B. (2014). Impact of dairy products on biomarkers of inflammation: a systematic review of randomized controlled nutritional intervention studies in overweight and obese adults. *Am. J. Clin. Nutr.* **97**:706–717.

Lawrence, G. D. (2013). Dietary fats and health: dietary recommendations in the context of scientific evidence. *Adv. Nutr.* **4**:294–302.

Lee, Y. M., Skurk, T., Hennig, M. and Hauner, H. (2007). Effect of a milk drink supplemented with whey peptides on blood pressure in patients with mild hypertension. *Eur J Nutr* **46**:21–27.

Lepage, P. and Van de Perre, P. (2012). The immune system of breast milk: antimicrobial and anti-inflammatory properties. *Adv. Exp. Med. Biol.* **743**:121–137.

Liu, M. Y., Xydakis, A. M., Hoogeveen, R. C., Jones, P. H., Smith, E. O., Nelson, K. W. and Ballantyne, C. M. (2005). Multiplexed analysis of biomarkers related to obesity and the metabolic syndrome in human plasma, using the Luminex-100 system. *Clin. Chem.* **51**:1102–1109.

Lomax, A. R. and Calder, P. C. (2009). Probiotics, immune function, infection and inflammation: a review of the evidence from studies conducted in humans. *Curr. Pharm. Des.* **15**:1428–1518.

Melnik, B. C. (2009). Milk—the promoter of chronic Western diseases. *Med. Hypotheses.* **72**:631–639.

Meyer, A. L., Elmadfa, I., Herbacek, I. and Micksche, M. (2007). Probiotic, as well as conventional yogurt, can enhance the stimulated production of proinflammatory cytokines. *J Hum Nutr Diet* **20**:590–598.

Meyer, J., Doring, A., Herder, C., Roden, M., Koenig, W. and Thorand, B. (2011). Dietary patterns, subclinical inflammation, incident coronary heart disease and mortality in middle-aged men from the MONICA/KORA Augsburg cohort study. *Eur J Clin Nutr* **65**:800–807.

Micha, R. and Mozaffarian, D. (2009). Trans fatty acids: effects on metabolic syndrome, heart disease and diabetes. *Nat. Rev. Endocrinol.* **5**:335–344.

Minekus, M., Alminger, M., Alvito, P., Ballance, S., Bohn, T., Bourlieu, C., Carrière, F., Boutrou, R., Corredig, M., Dupont, D., Dufour, C., Egger, L., Golding, M., Karakaya, S., Birkhus, B., Le Feunteun, S., Lesmes, U., Maczierzanka, A., MacKie, A., Marze, S., McClements, D. J., Ménard, O., Recio, I., Santos, C. N., Singh, R. P., Vegarud, G. E., Wickham, M. S. J., Weitschies, W. and Brodkorb, A. (2014). A standardized static in vitro digestion method suitable for food - an international consensus. *Food. Funct. Jun*;5(6):1113–1124.

Moher, D., Liberati, A., Tetzlaff, J. and Altman, D. G. (2009). Reprint-preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. *Phys. Ther.* **89**:873–880.

Monagas, M., Khan, N., Andres-Lacueva, C., Casas, R., Urpi-Sarda, M., Llorach, R., Lamuela-Raventos, R. M. and Estruch, R. (2009). Effect of cocoa powder on the modulation of inflammatory biomarkers in patients at high risk of cardiovascular disease. *Am J Clin Nutr* **90**:1144–1150.

Nestel, P. J., Pally, S., MaCintosh, G. L., Greeve, M. A., Middleton, S., Jowett, J. and Meikle, P. J. (2012). Circulating inflammatory and atherogenic biomarkers are not increased following single meals of dairy foods. *Eur J Clin Nutr* **66**:25–31.

Nettleton, J. A., Steffen, L. M., Mayer-Davis, E. J., Jenny, N. S., Jiang, R., Herrington, D. M. and Jacobs, JR D. R. (2006). Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA). *Am J Clin Nutr* **83**:1369–1379.
Newburg, D. S. (2013). Glycobiology of human milk. *Biochemistry (Mosc)* **78**:771–785.

Oftedal, O. T. (2012). The evolution of milk secretion and its ancient origins. *Animal* **6**:355–368.

Pal, S. and Ellis, V. (2011). Acute effects of whey protein isolate on blood pressure, vascular function and inflammatory markers in overweight postmenopausal women. *Br.J Nutr* **105**:1512–1519.

Panagiotakos, D. B., Pitsavos, C. H., Zampelas, A. D., Chrysohoou, C. A. and Stefanadis, C. I. (2010). Dairy products consumption is associated with decreased levels of inflammatory markers related to cardiovascular disease in apparently healthy adults: the ATTICA study. *J Am Coll Nutr* **29**:357–364.

Panagiotakos, D. B., Pitsavos, C. H., Zampelas, A. D., Chrysohoou, C. A. and Stefanadis, C. I. (2010). Dairy products consumption is associated with decreased levels of inflammatory markers related to cardiovascular disease in apparently healthy adults: the ATTICA study. *J. Am. Coll. Nutr*. **29**:357–364.

Pintus, S., Murru, E., Carta, G., Cordeddu, L., Batetta, B., Accossu, S., Pistis, D., Uda, S., Elena, G. M., Mele, M., Secchiari, P., Almerighi, G., Pintus, P. and Banni, S. (2013). Sheep cheese naturally enriched in alpha-linolenic, conjugated linoleic and vaccenic acids improves the lipid profile and reduces anandamide in the plasma of hypercholesterolaemic subjects. *Br. J. Nutr.* **109**:1453–1462.

Raff, M., Tholstrup, T., Basu, S., Nonboe, P., Sorensen, M. T. and Straarup, E. M. (2008). A diet rich in conjugated linoleic acid and butter increases lipid peroxidation but does not affect atherosclerotic, inflammatory, or diabetic risk markers in healthy young men. *J Nutr* **138**:509–514.

Rebholz, C. M., Reynolds, K., Wofford, M. R., Chen, J., Kelly, T. N., Mei, H., Whelton, P. K. and He, J. (2013). Effect of soybean protein on novel cardiovascular disease risk factors: A randomized controlled trial. *Eur. J. Clin. Nutr.* **67**:58–63.

Romeo, J., Warnberg, J., Garcia-Marmol, E., Rodriguez-Rodriguez, M., Diaz, L. E., Gomez-Martinez, S., Cueto, B., Lopez-Huertaz, E., Cepero, M., Boza, J. J., Fonolla, J. and Marcos, A. (2011). Daily consumption of milk enriched with fish oil, oleic acid, minerals and vitamins reduces cell adhesion molecules in healthy children. *Nutr Metab Cardiovasc. Dis* **21**:113–120.

Rosti, L., Braga, M., Fulcieri, C., Sammarco, G., Manenti, B. and Costa, E. (2011). Formula milk feeding does not increase the release of the inflammatory marker calprotectin, compared to human milk. *Pediatr. Med Chir* **33**:178–181.

Savilahti, E. and Westerholm-Ormio, M. (2004). Gut inflammation and extraintestinal manifestation of food allergy. *J. Pediatr. Gastroenterol. Nutr.* **39**(Suppl 3):S742–S743.

Schwander, F., Kopf-Bolanz, K. A., Buri, C., Portmann, R., Egger, L., Chollet, M., mcTernan, P. G., Piya, M. K., Gijs, M. A. M., Vionnet, N., Pralong, F., Laederach, K. and Vergères, G. (2014). A dose-response strategy reveals differences between normal weight and obese men in their metabolic and inflammatory responses to a high-fat meal. *J. Nutr. Oct*;**144**(10):1517–1523.

Sofi, F., Buccioni, A., Cesari, F., Gori, A. M., Minieri, S., Mannini, L., Casini, A., Gensini, G. F., Aabbate, R. and Anatongiovanni, M. (2010). Effects of a dairy product (pecorino cheese) naturally rich in cis-9, trans-11 conjugated linoleic acid on lipid, inflammatory and haemoscrolleological variables: a dietary intervention study. *Nutr Metab Cardiovasc. Dis* **20**:117–124.

Spegel, J. M., Andrews, T., Brown-Whitehorn, T. F., Beausoleil, J. L. and Liacouras, C. A. (2005). Treatment of eosinophilic esophagitis with specific food elimination diet directed by a combination of skin prick and patch tests. *Ann Allergy Asthma Immunol* **95**:336–343.

Stancliffe, R. A., Thorpe, T. and Zemel, M. B. (2011). Dairy attenuates oxidative and inflammatory stress in metabolic syndrome. *Am J Clin Nutr* **94**:422–430.

Steinberg, D. (2005). Thematic review series: the pathogenesis of atherosclerosis. An interpretive history of the cholesterol controversy: part II:

the early evidence linking hypercholesterolemia to coronary disease in humans. *J. Lipid. Res.* **46**:179–190.

Strisciuglio, C., Giannetti, E., Martinelli, M., Sciorio, E., Staiano, A. and Miele, E. (2013). Does cow's milk protein elimination diet have a role on induction and maintenance of remission in children with ulcerative colitis? *Acta Paediatr.* **102**:e273–e278.

Sugawara, K., Takahashi, H., Kashiwagura, T., Yamada, K., Yanagida, S., Homma, M., Dairiki, K., Sasaki, H., Kawagoshi, A., Satake, M. and Shioya, T. (2012). Effect of anti-inflammatory supplementation with whey peptide and exercise therapy in patients with COPD. *Respir.Med* **106**:1526–1534.

Thompson, D. K., Huffman, K. M., Kraus, W. E. and Kraus, V. B. (2012). Critical appraisal of four IL-6 immunoassays. *PLoS One* **7**:e30659.

Topuz, E., Derin, D., Can, G., Kurklu, E., Cinar, S., Aykan, F., Cevikbas, A., Disci, R., Durna, Z., Sakar, B., Saglam, S., Tanyeri, H., Deniz, G., Gurer, U., Tas, F., Guney, N. and Aydiner, A. (2008). Effect of oral administration of kefir on serum proinflammatory cytokines on 5-FU induced oral mucositis in patients with colorectal cancer. *Invest New Drugs* **26**:567–572.

Tsai, Y. T., Cheng, P. C. and Pan, T. M. (2012). The immunomodulatory effects of lactic acid bacteria for improving immune functions and benefits. *Appl. Microbiol. Biotechnol.* **96**:853–862.

Ulsemer, P., Toutounian, K., Kressel, G., Schmidt, J., Karesten, U., Hahn, A. and Goletz, S. (2012). Safety and tolerance of Bacteroides xylanisolvens DSM 23964 in healthy adults. *Benef Microbes* **3**:99–111.

Unknown. (1994). Dietary and other risk factors of ulcerative colitis. A case-control study in Japan. Epidemiology Group of the Research Committee of Inflammatory Bowel Disease in Japan. *J Clin Gastroenterol* **19**:166–171.

Van Bussel, B. C., Henry, R. M., Schalkwijk, C. G., Ferreira, I., Feskens, E. J., Streppel, M. T., Smulders, Y. M., Twisk, J. W. and Stehouwer, C. D. (2011). Fish consumption in healthy adults is associated with decreased circulating biomarkers of endothelial dysfunction and inflammation during a 6-year follow-up. *J Nutr* **141**:1719–1725.

Van Meijl, L. E. and Mensink, R. P. (2010). Effects of low-fat dairy consumption on markers of low-grade systemic inflammation and endothelial function in overweight and obese subjects: an intervention study. *Br.J Nutr* **104**:1523–1527.

Vazquez-Agell, M., Urpi-Sarda, M., Sacanella, E., Camino-Lopez, S., Chiva-Blanch, G., Llorente-Cortes, V., Tobias, E., Roura, E., Andres-Lacueva, C., Lamuela-Raventos, R. M., Badimon, L. and Estruch, R. (2013). Cocoa consumption reduces NF-kappaB activation in peripheral blood mononuclear cells in humans. *Nutr.Metab Cardiovasc.Dis.* **23**:257–263.

Vergeres, G., Bogicevic, B., Buri, C., Carrara, S., Chollet, M., Corbino-Giunta, L., Egger, L., Gille, D., Kopf-Bolanz, K., Laederach, K., Portmann, R., Ramadan, Q., Ramsden, J., Schwander, F., Silacci, P., Walther, B. and Gijs, M. (2012). The NutriChip project-translating technology into nutritional knowledge. *Br. J. Nutr.* **108**:762–768.

Wang, H., Steffen, L. M., Vessby, B., Basu, S., Steinberger, J., Moran, A., Jacobs, D. R., JR., Hong, C. P. and Sinaiko, A. R. (2011). Obesity modifies the relations between serum markers of dairy fats and inflammation and oxidative stress among adolescents. *Obesity (Silver Spring)* **19**:2404–2410.

Wennersberg, M. H., Smedmann, A., Turpeinen, A. M., Retterstol, K., Tengblad, S., Lipre, E., Aro, A., Mutanen, P., Seljeflot, I., Basu, S., Pedersen, J. I., Mutanen, M. and Vessby, B. (2009). Dairy products and metabolic effects in overweight men and women: results from a 6-mo intervention study. *Am J Clin Nutr* **90**:960–968.

Wojcik, J. R., Walber-Rankin, J., Smith, L. L. and Gwazdauskas, F. C. (2001). Comparison of carbohydrate and milk-based beverages on muscle damage and glycogen following exercise. *Int J Sport Nutr Exerc. Metab* **11**:406–419.

Zemel, M. B. and Sun, X. (2008). Dietary calcium and dairy products modulate oxidative and inflammatory stress in mice and humans. *J Nutr* **138**:1047–1052.

Zemel, M. B., Sun, X., Sobhani, T. and Wilson, B. (2010). Effects of dairy compared with soy on oxidative and inflammatory stress in overweight and obese subjects. *Am J Clin Nutr* **91**:16–22.
<figure><img src="image_38.png" /></figure>

Newburg, D. S. (2013). Glycobiology of human milk. *Biochemistry (Mosc)* **78**:771–785.

Oftedal, O. T. (2012). The evolution of milk secretion and its ancient origins. *Animal* **6**:355–368.

Pal, S. and Ellis, V. (2011). Acute effects of whey protein isolate on blood pressure, vascular function and inflammatory markers in overweight postmenopausal women. *Br.J Nutr* **105**:1512–1519.

Panagiotakos, D. B., Pitsavos, C. H., Zampelas, A. D., Chrysohoou, C. A. and Stefanadis, C. I. (2010). Dairy products consumption is associated with decreased levels of inflammatory markers related to cardiovascular disease in apparently healthy adults: the ATTICA study. *J Am Coll Nutr* **29**:357–364.

Panagiotakos, D. B., Pitsavos, C. H., Zampelas, A. D., Chrysohoou, C. A. and Stefanadis, C. I. (2010). Dairy products consumption is associated with decreased levels of inflammatory markers related to cardiovascular disease in apparently healthy adults: the ATTICA study. *J. Am. Coll. Nutr*. **29**:357–364.

Pintus, S., Murru, E., Carta, G., Cordeddu, L., Batetta, B., Accossu, S., Pistis, D., Uda, S., Elena, G. M., Mele, M., Secchiari, P., Almerighi, G., Pintus, P. and Banni, S. (2013). Sheep cheese naturally enriched in alpha-linolenic, conjugated linoleic and vaccenic acids improves the lipid profile and reduces anandamide in the plasma of hypercholesterolaemic subjects. *Br. J. Nutr.* **109**:1453–1462.

Raff, M., Tholstrup, T., Basu, S., Nonboe, P., Sorensen, M. T. and Straarup, E. M. (2008). A diet rich in conjugated linoleic acid and butter increases lipid peroxidation but does not affect atherosclerotic, inflammatory, or diabetic risk markers in healthy young men. *J Nutr* **138**:509–514.

Rebholz, C. M., Reynolds, K., Wofford, M. R., Chen, J., Kelly, T. N., Mei, H., Whelton, P. K. and He, J. (2013). Effect of soybean protein on novel cardiovascular disease risk factors: A randomized controlled trial. *Eur. J. Clin. Nutr.* **67**:58–63.

Romeo, J., Warnberg, J., Garcia-Marmol, E., Rodriguez-Rodriguez, M., Diaz, L. E., Gomez-Martinez, S., Cueto, B., Lopez-Huertaz, E., Cepero, M., Boza, J. J., Fonolla, J. and Marcos, A. (2011). Daily consumption of milk enriched with fish oil, oleic acid, minerals and vitamins reduces cell adhesion molecules in healthy children. *Nutr Metab Cardiovasc. Dis* **21**:113–120.

Rosti, L., Braga, M., Fulcieri, C., Sammarco, G., Manenti, B. and Costa, E. (2011). Formula milk feeding does not increase the release of the inflammatory marker calprotectin, compared to human milk. *Pediatr. Med Chir* **33**:178–181.

Savilahti, E. and Westerholm-Ormio, M. (2004). Gut inflammation and extraintestinal manifestation of food allergy. *J. Pediatr. Gastroenterol. Nutr.* **39**(Suppl 3):S742–S743.

Schwander, F., Kopf-Bolanz, K. A., Buri, C., Portmann, R., Egger, L., Chollet, M., mcTernan, P. G., Piya, M. K., Gijs, M. A. M., Vionnet, N., Pra-long, F., Laederach, K. and Vergères, G. (2014). A dose-response strategy reveals differences between normal weight and obese men in their metabolic and inflammatory responses to a high-fat meal. *J. Nutr. Oct*;**144**(10):1517–1523.

Sofi, F., Buccioni, A., Cesari, F., Gori, A. M., Minieri, S., Mannini, L., Casini, A., Gensini, G. F., Aabbate, R. and Anatongiovanni, M. (2010). Effects of a dairy product (pecorino cheese) naturally rich in cis-9, trans-11 conjugated linoleic acid on lipid, inflammatory and haemo-rheological variables: a dietary intervention study. *Nutr Metab Cardiovasc. Dis* **20**:117–124.

Spegel, J. M., Andrews, T., Brown-Whitehorn, T. F., Beausoleil, J. L. and Liacouras, C. A. (2005). Treatment of eosinophilic esophagitis with specific food elimination diet directed by a combination of skin prick and patch tests. *Ann Allergy Asthma Immunol* **95**:336–343.

Stancliffe, R. A., Thorpe, T. and Zemel, M. B. (2011). Dairy attenuates oxidative and inflammatory stress in metabolic syndrome. *Am J Clin Nutr* **94**:422–430.

Steinberg, D. (2005). Thematic review series: the pathogenesis of atherosclerosis. An interpretive history of the cholesterol controversy: part II: the early evidence linking hypercholesterolemia to coronary disease in humans. *J. Lipid. Res.* **46**:179–190.

Strisciuglio, C., Giannetti, E., Martinelli, M., Sciorio, E., Staiano, A. and Miele, E. (2013). Does cow's milk protein elimination diet have a role on induction and maintenance of remission in children with ulcerative colitis? *Acta Paediatr.* **102**:e273–e278.

Sugawara, K., Takahashi, H., Kashiwagura, T., Yamada, K., Yanagida, S., Homma, M., Dairiki, K., Sasaki, H., Kawagoshi, A., Satake, M. and Shioya, T. (2012). Effect of anti-inflammatory supplementation with whey peptide and exercise therapy in patients with COPD. *Respir.Med* **106**:1526–1534.

Thompson, D. K., Huffman, K. M., Kraus, W. E. and Kraus, V. B. (2012). Critical appraisal of four IL-6 immunoassays. *PLoS One* **7**:e30659.

Topuz, E., Derin, D., Can, G., Kurklu, E., Cinar, S., Aykan, F., Cevikbas, A., Disci, R., Durna, Z., Sakar, B., Saglam, S., Tanyeri, H., Deniz, G., Gurer, U., Tas, F., Guney, N. and Aydiner, A. (2008). Effect of oral administration of kefir on serum proinflammatory cytokines on 5-FU induced oral mucositis in patients with colorectal cancer. *Invest New Drugs* **26**:567–572.

Tsai, Y. T., Cheng, P. C. and Pan, T. M. (2012). The immunomodulatory effects of lactic acid bacteria for improving immune functions and benefits. *Appl. Microbiol. Biotechnol.* **96**:853–862.

Ulsemer, P., Toutounian, K., Kressel, G., Schmidt, J., Karesten, U., Hahn, A. and Goletz, S. (2012). Safety and tolerance of Bacteroides xylanisolvens DSM 23964 in healthy adults. *Benef Microbes* **3**:99–111.

Unknown. (1994). Dietary and other risk factors of ulcerative colitis. A case-control study in Japan. Epidemiology Group of the Research Committee of Inflammatory Bowel Disease in Japan. *J Clin Gastroenterol* **19**:166–171.

Van Bussel, B. C., Henry, R. M., Schalkwijk, C. G., Ferreira, I., Feskens, E. J., Streppel, M. T., Smulders, Y. M., Twisk, J. W. and Stehouwer, C. D. (2011). Fish consumption in healthy adults is associated with decreased circulating biomarkers of endothelial dysfunction and inflammation during a 6-year follow-up. *J Nutr* **141**:1719–1725.

Van Meijl, L. E. and Mensink, R. P. (2010). Effects of low-fat dairy consumption on markers of low-grade systemic inflammation and endothelial function in overweight and obese subjects: an intervention study. *Br.J Nutr* **104**:1523–1527.

Vazquez-Agell, M., Urpi-Sarda, M., Sacanella, E., Camino-Lopez, S., Chiva-Blanch, G., Llorente-Cortes, V., Tobias, E., Roura, E., Andres-Lacueva, C., Lamuela-Raventos, R. M., Badimon, L. and Estruch, R. (2013). Cocoa consumption reduces NF-kappaB activation in peripheral blood mononuclear cells in humans. *Nutr.Metab Cardiovasc.Dis.* **23**:257–263.

Vergeres, G., Bogicevic, B., Buri, C., Carrara, S., Chollet, M., Corbino-Giunta, L., Egger, L., Gille, D., Kopf-Bolanz, K., Laederach, K., Portmann, R., Ramadan, Q., Ramsden, J., Schwander, F., Silacci, P., Walther, B. and Gijs, M. (2012). The NutriChip project–translating technology into nutritional knowledge. *Br. J. Nutr.* **108**:762–768.

Wang, H., Steffen, L. M., Vessby, B., Basu, S., Steinberger, J., Moran, A., Jacobs, D. R., JR., Hong, C. P. and Sinaiko, A. R. (2011). Obesity modifies the relations between serum markers of dairy fats and inflammation and oxidative stress among adolescents. *Obesity (Silver Spring)* **19**:2404–2410.

Wennersberg, M. H., Smedmann, A., Turpeinen, A. M., Retterstol, K., Tengblad, S., Lipre, E., Aro, A., Mutanen, P., Seljeflot, I., Basu, S., Pedersen, J. I., Mutanen, M. and Vessby, B. (2009). Dairy products and metabolic effects in overweight men and women: results from a 6-mo intervention study. *Am J Clin Nutr* **90**:960–968.

Wojcik, J. R., Walber-Rankin, J., Smith, L. L. and Gwazdauskas, F. C. (2001). Comparison of carbohydrate and milk-based beverages on muscle damage and glycogen following exercise. *Int J Sport Nutr Exerc. Metab* **11**:406–419.

Zemel, M. B. and Sun, X. (2008). Dietary calcium and dairy products modulate oxidative and inflammatory stress in mice and humans. *J Nutr* **138**:1047–1052.

Zemel, M. B., Sun, X., Sobhani, T. and Wilson, B. (2010). Effects of dairy compared with soy on oxidative and inflammatory stress in overweight and obese subjects. *Am J Clin Nutr* **91**:16–22.