Tailoring Emulsions for Controlled Lipid Release: Establishing in vitro

Apr 30, 2018 - In brief, gastric mucin was added so that the SGF reflects the negative surface charge (expressed by the zeta-potential ζ) of natural ...
0 downloads 3 Views 7MB Size
Subscriber access provided by Kaohsiung Medical University

Biological and Medical Applications of Materials and Interfaces

Tailoring Emulsions for Controlled Lipid Release: Establishing in vitro – in vivo Correlation for Digestion of Lipids Nathalie Scheuble, Joschka Schaffner, Manuel Schumacher, Erich Josef Windhab, Dian Liu, Helen Parker, Andreas Steingoetter, and Peter Fischer ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.8b02637 • Publication Date (Web): 30 Apr 2018 Downloaded from http://pubs.acs.org on May 5, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

Tailoring Emulsions for Controlled Lipid Release: Establishing in vitro – in vivo Correlation for Digestion of Lipids Nathalie Scheuble,† Joschka Schaffner,† Manuel Schumacher,† Erich J. Windhab,† Dian Liu,‡ Helen Parker,¶ Andreas Steingoetter,‡ and Peter Fischer∗,† †Institute of Food Nutrition and Health, ETH Zurich, 8092 Zurich, Switzerland ‡Institute for Biomedical Engineering, University Zurich and ETH Zurich, 8092 Zurich, Switzerland ¶Division of Gastroenterology and Hepatology, University Hospital Zurich, 8091 Zurich, Switzerland (present address: Institute of Health and Society, Newcastle University, Newcastle upon Tyne, United Kingdom) E-mail: [email protected]

Abstract The use of oil-in-water emulsions for controlled lipid release is of interest to the pharmaceutical industry in the development of poorly water soluble drugs and also has gained major interest in the treatment of obesity. In this study, we focus on the relevant in vitro parameters reflecting gastric and intestinal digestion steps to reach a reliable in vitro – in vivo correlation for lipid delivery systems. We found that (i) gastric lipolysis determines early lipid release and sensing. This was mainly influenced by the emulsion stabilization mechanism. (ii) Gastric mucin influences the structure of chargestabilized emulsion systems in the stomach leading to destabilization or gel formation,

1

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

which is supported by in vivo magnetic resonance imaging in healthy volunteers. (iii) The precursor structures of these emulsion modulate intestinal lipolysis kinetics in vitro, which is reflected in plasma triglyceride and cholecystokinin concentrations in vivo.

Keywords: lipid digestion, gastric digestion, intestine digestion, interfacial design, human studies, in vitro - in vivo correlation

1

Introduction

Oral lipid delivery systems such as oil-in-water emulsions can be used to increase the bioavailability of poorly water-soluble drugs and functional food ingredients. 1 These substances are embedded within a lipid system and as such can be released in a controlled manner through lipid digestion. Furthermore, lipid emulsion systems have attracted interest as possible strategy to counteract obesity. Tailored emulsion systems have the ability to intensify the sensing of fat and delay gastric emptying. Hence, the sensation of fullness is prolonged, which ultimately reduces further intake of energy-rich food such as lipids. 2–5 The performance of lipid delivery and emulsion systems are commonly investigated by in-vitro models of human digestion. 6–10 The key performance indicator of any such in-vitro model is its ability to predict in vivo processes and behavior, i.e. its underlying in vitro – in vivo correlation. Therefore, validation studies which compare the observed outcomes from in vitro and in vivo studies are required. However, very few in vitro systems were initially validated with in vivo data and many of these models have been subsequently criticized due to a lack of correlation with in vivo data. 11,12 In this perspective, the pH-stat technique is the most common and rapid technique to determine lipase activity and lipolysis kinetics. 13–15 This technique is usually applied isolated for either intestinal lipid digestion or for gastric lipid digestion. One potential reason for the lack of correlation is that most models omit gastric lipid digestion and/or its impact on the subsequent intestinal lipase activity and lipolysis kinetics. 16–19 The aim of this study is to develop and validate an in vitro model, which incorporates 2

ACS Paragon Plus Environment

Page 2 of 35

Page 3 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

the effects of emulsion structural change, gastric mucin, and gastric lipase within the gastric environment. Lipid release patterns of emulsions are tailored by means of stimuli-responsive biopolymers. Stimuli-responsive biopolymers such as whey protein isolate (WPI), methylcellulose (MC), and nanocrystalline cellulose (NCC) change their mechanical and emulsion stabilization properties at specific physicochemical conditions present in the human gastric environment. WPI has an isoelectric point around pH 5, is sensitive to changes in ionic strength and pH, 20 and enzymatically degradable during gastric digestion, which leads to displacement from the interfaces of lipid emulsion droplets. MC is commercially available and sensitive to changes in temperature, which leads to thermogelation in both bulk as well as at interfaces. The interfacial thermogelation sets in at about 22◦ C and leads to closed compact interfacial structures, which are ideal for encapsulation. 21,22 On the other hand, NCC is less prone to pH alterations and resist enzymatic degradation but is sensitive to changes in ionic strength. Moreover, NCC possess outstanding purity and elasticity (150 GPa), close to the value of a perfect cellulose crystal. It consists of 100 % sulfated cellulose nanocrystals with a crystal size ranging from 2 - 10 nm width and 80 - 150 nm length. 23,24 Therefore, these biopolymer based emulsions undergo different structural changes when mixed with gastric juice within the stomach. This restructuring ultimately leads to differences in fat gastric emptying, bile secretion, and gastrointestinal hormone response, which modulates lipid sensing, release, and uptake. The in vitro - in vivo correlation of this concept is validated by imaging the emulsion structures formed inside the stomach of healthy adults during gastric digestion using Magnetic Resonance Imaging (MRI) and simultaneous measurements of plasma cholecystokinin and triglycerides concentration.

3

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

2

Results

2.1 2.1.1

in vitro model incorporating gastric digestion Emulsion stabilization influences in vitro gastric lipolysis

A key design feature of this in vitro model of lipid digestion was the addition of gastric lipase. Gastric lipases have been shown to contribute up to 25 % of lipid digestion. 25 However, gastric lipase activity is frequently not included within in vitro models, because gastric lipases are commercially not available. The lack of inclusion of gastric lipase in an in vitro model may result in a lack of correlation between the in vitro and in vivo data. This section demonstrates that controlled lipid release begins in the intragastric environment. Lipases hydrolyze lipids at oil-water interfaces. Generally, lipase activity depends on the spatial access to these interfaces and thus on the material, which covers the lipid phase of emulsion droplets. The activity of recombinant dog gastric lipase (rDGL) 26 on oil-in-water emulsions stabilized by WPI, MC, or NCC was measured titrimetrically by the pH-stat technique. The maximum rDGL activity as a function of biopolymer concentration in the aqueous phase of the emulsion is shown in Figure 1. In addition, Figure 1 illustrates the proposed mode of action of rDGL on these biopolymer interfaces. The following behavior for the stimuli-responsive biopolymers is observed: (i) WPI adsorbs to oil-water interfaces forming a viscoelastic interfacial film. 27,28 WPI stabilized emulsions demonstrated the highest activity of rDGL. This level of activity did not change significantly with increased WPI concentration, which indicates that rDGL was able to penetrate and hydrolyze oil independent of layer thickness and droplet coverage of the interfacial WPI layer. (ii) MC adsorbs irreversibly at the oil-water interface forming a viscoelastic adsorption layer, 29 which thermogels at 37◦ C. 22 The activity of rDGL gradually decreased with MC concentration until no rDGL activity could be measured with 4 wt% MC. (iii) No rDGL activity was measured with any emulsion system stabilized with NCC. This property was also evidenced during back-titration to higher pHs as experiments were performed at pH = 4

ACS Paragon Plus Environment

Page 4 of 35

Page 5 of 35

400

max rDGL activity (U/mg)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

WPI

WPI

MC

MC

fatty acids

300 200

rDGL

100 NCC

NCC

0 0.5

1

2

4

Biopolymer concentration (wt%)

+ NaTDC

Figure 1: The effect of emulsion formulation on gastric lipolysis. Maximal recombinant dog gastric lipase (rDGL) activity as a function of biopolymer concentrations (WPI, MC, NCC) in aqueous phase of MCT oil-water emulsions (1 U is equal to 1µmol of free fatty acid released per minute). Measured with the pH-stat technique (5 wt% MCT oil), at pH 5, 37◦ C, 10 µl of a 1 mg/ml solution of rDGL. 2 mM NaTDC was added to the 4 wt% MC and NCC stabilized emulsions to explore the displacement of the biopolymers from the interface and thus make rDGL active again. Since rDGL already displaces WPI from interfaces, it was not added to WPI stabilized emulsions. Lines are to guide the eye. Illustrations of the proposed stabilization mechanism and interaction with rDGL for the three biopolymer interfaces are embedded. Measurements were done at substrate saturated conditions. Therefore, rDGL activity does not dependent on droplet sizes used (0.5 - 10 µm), but mainly on the ability to adsorb to the oil-water interface. 5. At this pH not all free fatty acids are titratable due to the pKA of MCT oil. Adding bile salts (NaTDC) to MC and NCC stabilized emulsions led to measurable activity of rDGL in MC stabilized emulsions only. Since rDGL already displaces WPI from interfaces, it was not added to WPI stabilized emulsions. In summary, rDGL activity was influenced by different interfacial stabilization mechanisms, which originate from WPI, MC, and NCC. These led to highly active rDGL at WPI interfaces, concentration dependent activity of rDGL on MC interfaces, and no activity of rDGL on NCC interfaces. The findings for WPI stabilized emulsions are supported by previous measurements on lipase activity using interfacial techniques such as interfacial rheology, neutron reflectivity, 22,30,31 and in vitro models. 32 There is limited literature regarding concentration de5

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

pendent lipolytic activity for MC stabilized emulsions. Previous work demonstrated that not only thermosensitive substances inhibit lipases with increasing concentration, but as well other substances like gum arabic. 33 MC was partially displaced from the interfaces by NaTDC. A recent study showed a direct interaction between MC and NaTDC that impacted on the thermal gelation of methylcellulose and actively removed MC from the interface. 34 The total inhibition of gastric lipolysis observed for NCC appears to be a unique feature only matched by the strong inhibitory effects observed with Tween 80 surfactant. 35 Similar stabilization behavior have only been observed for highly interfacial active emulsifying agents. 36 Conversely, NCC demonstrated no interfacial activity. 30 Therefore, the stabilization mechanism of NCC emulsion was examined in more detail as described further within in the discussion. Besides gastric lipase, other components contained in the gastric fluid such as mucin also contribute to the structuring of a colloidal system. Therefore, these components should also be incorporated into an optimized in vitro model. 2.1.2

Emulsion structuring is influenced by mucin and gastric mixing

Immediately after ingestion, emulsions mix with gastric fluid. This leads to digestion of lipids through gastric lipases and structural changes in emulsions caused by the physicochemical environment present in the human stomach. Emulsion droplets can destabilize and coalesce or the emulsion can gel through increasing colloidal interactions caused by compounds present in human gastric juice. Such changes in emulsion structures are crucial for intestinal lipolysis kinetics. 9,12,13,37 The simulated gastric fluid (SGF) applied in this in-vitro model was based upon that described by Minekus et al. 38 but adapted in order to include the role of gastric mucin. In brief, gastric mucin was added so that the SGF reflects the negative surface charge (expressed by the zeta-potential ζ) of natural human gastric juice at approximately - 5 mV. 39 Gastric mucin is a high molecular weight glycoprotein consisting of 80 % oligosaccharide chains covalently attached to 20 % polypeptide side-chains. It 6

ACS Paragon Plus Environment

Page 6 of 35

Page 7 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

protects the stomach wall from self digestion by undergoing a pH-dependent sol-gel transition from neutral to acidic pH. 40,41 This gelation originates from the complex structure of gastric mucin, which involves hydrophilic/hydrophobic, hydrogen bond, and electrostatic interactions. Gastric mucin exhibits electrostatic charge buffering properties and therefore can impact on the structure of colloidal systems. 42 Due to its charge neutralizing effect, mucin will decrease and neutralize charges, also at the interface. Therefore, mucin mainly impacts on charged colloidal systems used. In Figure 2a the effect of electrolytes and gastric mucin on the zeta potentials of emulsions stabilized by WPI, MC, and NCC is shown. This highlights that mainly gastric mucin and not the electrolytes present in the gastric environment buffers the charge of WPI and NCC stabilized emulsions. The surface charge reduction by mucin impacts crucially the structure of colloidal systems and, thus, leads to flocculation, droplet coalescence, or complete emulsion destabilization. Therefore, the addition of mucin appears to be strictly necessary to mimic the correct physicochemical conditions present in the gastric environment. Gastric mixing is not a homogeneous process as it depends on the structure and composition of the food and varies with the location in the stomach and digestion time. 43,44 Figure 2b illustrates the mixing of a liquid meal in a human stomach. Hence, emulsion structures were analyzed in vitro by mixing them with different degrees of SGF. In Figure 2c the decrease of electrostatic repulsion with SGF is shown. With 25 % SGF, the WPI emulsion-SGF mixture exhibited a pH of 4.8 and a zeta potential of - 28.5 mV. The isoelectric point of WPI is approximately pH 5 and therefore a zeta potential closer to zero was expected. This low zeta potential originates from negatively charged mucin and added xanthan that aggregates with positively charged amino acids from WPI, which drives the overall zeta potential negative. This aggregation is represented by the strong increase in the complex viscosity as depicted in Figure 2d. It demonstrates that both charged colloidal systems, WPI and NCC stabilized emulsions increased in viscosity and gelled by blending with 25 % SGF (G’  G”, data not shown). The complex viscosity of the uncharged MC 7

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces

WPI MC NCC mucin gastric juice

40 30 20 10

c

0

mixing gradient

rin

g

-10

bu ffe

-20

ge

-30 -40 -50 pH 3

pH 3 salts

20 10 0 -10 -20 -30 -40 -50

pH 3 salts mucin

pH 3 gastric juice mucin

e

2

10

1

10

0

% gastric fluid

25

50

75

SGF (%)

f

2

10

droplet diameter d1,2(µm)

d

b

ch ar

zeta potential ζ (mV)

50

zeta potential ζ (mV)

a

∗ complex viscosity η (Pa s)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 35

WPI

MC

NCC

no structuring

structuring without coalescence

1

10

0

10

50 μm

0

10

-1

10

structuring with coalescence

-2

10

0

25

50

SGF (%)

75

100

-1

10

0

25

50

SGF (%)

75

Figure 2: in vitro emulsion structure formation in gastric environment. (a) Impact of electrolytes and gastric mucin on zeta-potential ζ of human gastric juice, mucin, and WPI, MC, and NCC based emulsions at pH 3. Emulsions were produced with 4 wt% biopolymer in 10 mM PBS buffer. (b) Illustration of the mixing gradient of a liquid meal in a human stomach. Impact of different percentages of SGF on (c) zeta potential ζ, (d) complex viscosity η ∗ at 37◦ C, and (e) droplet size d1,2 of WPI, MC, NCC based emulsions. (f ) Light microscopy images of emulsions after mixing with 50 % SGF. Emulsions compositions: NCC and MC based: 4 % biopolymer in Evian water, 20 wt% rapeseed oil; WPI based: 1 wt % WPI and 0.232 wt% xanthan in 5 mM citric acid PBS buffer pH 7; 20 wt% rapeseed oil. The composition of the SGF is based on Minekus et al. 38 and discussed in detail in the Experimental Section. stabilized emulsions decreased with SGF and were purely viscous. Therefore, when charged colloidal systems are blended with SGF this results in a reduction of electrostatic repulsion and depletion alongside bridging flocculation with mucin. A decrease in droplet repulsion subsequently leads to coalescence or flocculation that increases emulsion viscosity. However, complex viscosity decreases again with higher mixing degrees of SGF. The emulsion structure is dependent upon the charge sensitivity of the system, the concentration of the biopolymer, and hence the degree of SCF mixing. Furthermore, droplet coalescence depends on the steric repulsion of the interfacial layer built by the emulsifying agent. WPI stabilized emulsions

8

ACS Paragon Plus Environment

Page 9 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

destabilized with SGF resulting in an increase in droplet size as shown in Figure 2e and f. Thus, WPI-based emulsions have a tendency to cream during gastric digestion. The droplet size increase was mainly affected by the mixing degree with SGF containing mucin, and was not dominated by the activity of pepsin (data not shown). In comparison, NCC based emulsion droplets did not significantly increase in droplet size after mixing with SGF. The uncharged MC based emulsion was diluted by SGF and thus droplet sizes remained constant. The structuring of emulsions can be visualized and analyzed in humans using gastric MRI. 45 This noninvasive technique enables the observed in vitro findings to be validated in vivo. Thus, enabling the assessment of the in vitro – in vivo correlation of the optimized model. 2.1.3

In vivo validation of gastric emulsion structuring

One healthy subject ingested all three emulsion systems on three different study days separated by one week. The gastric content was repeatedly imaged over 60 min by two different image acquisition methods. Figure 3 shows the standard multislice MR images (grayscale) and the corresponding dedicated fat fraction maps (color coded) of the segmented gastric content of one healthy subject 60 min after emulsion ingestion. 45 The standard MR image data indicated that the NCC stabilized emulsion structured and formed a lump in the middle of the stomach. Over time, this lump was slowly diluted from the stomach wall to the inside of the system (data not shown). This phenomena has been observed previously with highly viscous meals. 46 Conventional MR image data also suggested that the MC emulsion underwent the least amount of structural changes within the gastric environment. The fat fraction maps visualize the distribution of fat/lipid concentrations within the stomach. These image data demonstrated that the WPI stabilized emulsion had a tendency to destabilize and cream within the stomach, resulting in higher lipid concentration in the fundus. The MC stabilized emulsion showed an overall lower lipid concentration, suggesting a continuous dilution of the emulsion system. The NCC stabilized emulsion showed a homogeneous distribution of lipids throughout the stomach. This is most likely due to gel formation whereby mixing with 9

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces

gastric fluid decreases gastric mixing efficiency. All three emulsion systems demonstrated a slight gradient of the lipid concentration from the gastric wall to the internal gastric content. The visualization of the ingested lipid emulsion systems by in vivo MRI supported the in vitro findings. Thus, WPI stabilized emulsions tend to destabilize, MC stabilized emulsions are not affected, and the NCC stabilized emulsions gelled within the gastric environment. WPI

MC

NCC

viscous layers

stomach

emulsion 50

slice

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 35

40 30

creaming

dilution

structuring

20 10 0

% lipid

Figure 3: Intragastric emulsion structure formation in a healthy subject. On the left, the schematic illustrates the MR image slice orientation relative to the stomach shape. The columns separate and visualize the reconstructed and segmented multi-slice image data at 60 min after emulsion ingestion in 3D for the three emulsion systems (WPI, MC, and NCC). The upper panels display the conventional image data (gray scale). The lower panels display the corresponding fat fraction maps used for the calculation of the intragastric lipid concentration. The color bar provides the conversion of the color to the percentage lipid volume. Emulsions compositions: NCC and MC stabilized: 4 % biopolymer in Evian water, 20 wt% rapeseed oil; WPI stabilized: 1 wt % WPI and 0.232 wt% xanthan in 5 mM citric acid PBS buffer pH 7; 20 wt% rapeseed oil.

10

ACS Paragon Plus Environment

Page 11 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

2.2 2.2.1

In vivo lipid digestion correlates with in vitro observations Emulsion structure influences in vitro intestinal lipolysis by pancreatic enzymes

The processed mixture of structured emulsion system and gastric fluid is steadily emptied into the proximal small intestine where intestinal lipolysis and fat sensing takes place. Therefore, emulsions were pre-structured with 50% SGF before adding them to simulated intestinal fluid (SIF). The amount of free fatty acids titrated from this mixture were recorded as a function of time (Figure 4a). Fatty acid release kinetics were distinctly related to the gastric structuring. Triglycerides from unstructured MC emulsions were hydrolyzed quickest followed by those from the intermediate structured WPI emulsion. NCC stabilized emulsions had the slowest fatty acid release kinetics. The gel formed with NCC during digestion protects part of the emulsion from digestion and resulted in regions of original droplets size (1 - 2 µm) present after 2 hours of digestion (Figure 4b). WPI and NCC stabilized emulsions, which were not pre-structured with SGF demonstrated almost identical titration curves (Figure 4c). The emulsion bulk structure produced during gastric digestion is responsible for altering intestinal lipolysis and not the droplet stabilization mechanism. Thus, the rate of intestinal lipolysis can depend upon both coalesced droplet formation and aggregation and lump formation. Aggregation and lump formation decrease the rate of triglyceride hydrolysis by reducing the accessibility of the oil-water interface for lipase adsorption. 2.2.2

Emulsion structure and lipid release patterns influence gastric lipid emptying, plasma triglyceride, plasma CCK, and gallbladder volume

The effect of above described structuring of the emulsion systems on gastric lipid emptying, plasma triglyceride (TAG), plasma cholecystocinin (CCK), and gallbladder volume (GV) was tested in healthy volunteers. These physiological measures were regarded as either direct (TAG) or indirect biomarkers for the sensing and release characteristics of the ingested

11

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces

a

b

100 WPI NCC

Lumps

MC

80 60 12

40

0.1M NaOH (ml)

% FFA released

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 12 of 35

20

pre-structured

0 0

3

6

10

500 µm

nonstructured

Droplets

8 6 4 2 0 0

9

12

5

Time (min)

10

15

Time (min)

15

20

18

c

25

30

21

40 µm

Figure 4: Impact of emulsion structures on intestinal lipolysis. (a) Fatty acid release as a function of time for gastric structured WPI, NCC, or MC stabilized emulsions in SIF measured with the pH-stat technique. Emulsion composition: 4 wt% biopolymer in 10 mM citric acid PBS pH 7, 20 wt% MCT oil. Emulsions were pre-structured with 50 % SGF. (b) Light microscopy images of lumps consisting of droplets present from NCC emulsions after 2 h of digestion. (c) Titration curve of WPI and NCC emulsion systems with no gastric phase. lipids. Gastric lipid emptying was not different between emulsions. Half-times of gastric lipid emptying times were T50,gastric,W P I = 145 (129, 162) min, T50,gastric,M C = 139 (123, 156) min, and T50,gastric,N CC = 133 (111, 148) min for WPI, MC, and NCC stabilized emulsions, respectively. This indicates that lipid delivery to the duodenum was comparable for each emulsion. Figure 5a shows the computed post-prandial delta over baseline (DOB) curves with group median and 95 % credible interval for TAG, CCK, and GV for each emulsion as a function of time. DOB curves were fitted by a power-exponential function to extract the area over baseline AOB, the maximum positive (or negative) amplitude Amax and the time-to-maximum amplitude tmax . 47 Figure 5b visualizes these parameters’ estimates for each measure with a full numerical description in Supporting Information Table S1. In the following, significant differences are expressed as relative differences for each parameter.

12

ACS Paragon Plus Environment

Page 13 of 35

A TAG (mM)

MC

WPI

0.5

NCC

0.4 0.3 0.2

0.0 0.25

CCK (pM )

Group median DOB (95 % HPD CI)

0.1

0..20 0.15 0.10 0.05 0.00 0.0 -0.1

GV (mL)

-0.2 -0.3 -0.4 -0.5 -0.6 0

100

200

300

400

Time (min)

B

0,5

500

600 0

TAG

100

0,3

200

300

400

Time (min)

500

600 0

CCK

100

200

300

400

Time (min)

500

600

GV -0,1

0,4

-0,2 0,2 -0,3

Amax

0,3

-0,4

0,2

0,1 -0,5

0,1

-0,6 0,0

AOB

Group median (95 % HPD CI)

0,0

tmax

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

-0,7

80

80

-50

60

60

-100

40

40

-150

20

20

-200

0

0

-250

400

400

400

300

300

300

200

200

200

100

100

100

0

WPI MC NCC

0

WPI MC NCC

0

WPI MC NCC

Figure 5: Effect of lipid release patterns on gastric lipid emptying, plasma triglyceride, plasma CCK, and gallbladder volume. (a) Group median DOB curves (line) with HPD 95% CI (grey area) of TAG and CCK plasma concentration profiles as well as GV in humans after intake of WPI, MC, or NCC stabilized emulsions. The data is grouped by emulsion type (columns) and measure (rows). (b) Boxplots displaying median and HPD 95% CI of extracted parameter values (Amax , AOB, and tmax ) as a function of emulsion type for the individual measures (TAG, CCK, GV). Units for AOB were mM·min, pM·min, or mL·min for TAG, CCK, or GV, respectively. Units for Amax were mM, pM, or mL for TAG, CCK, or GV, respectively. 13

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

The NCC stabilized emulsion system demonstrated a clear difference to the other emulsions with 80 and 70 % lower Amax values for TAG and CCK, respectively. The minimum value of GV (here tmax ) was reached 80 to 110 % later for the NCC emulsion. This indicates that NCC emulsions were digested less efficiently. The WPI emulsion system showed 45 % lower overall CCK release compared to MC (AOB) and reached the CCK maximum 76 and 113 % earlier than the MC and NCC emulsion system, respectively. Moreover, tmax of plasma TAG was reached 13% earlier for the WPI emulsion. This suggests that WPI stabilized emulsions are digested earlier and triggered less release of CCK than MC emulsion systems. The WPI emulsion system was the only emulsion in which gastric lipase was active as measured in vitro. Full numerical description of the comparison between the differently stabilized lipid emulsions is given in Supporting Information Table S2. These results strongly suggest that fatty acids produced during the gastric phase trigger the early release of CCK and presence of plasma TAG. The lower overall release of CCK in WPI stabilized emulsions compared to MC stabilized emulsions suggest slower lipid digestion due to increased droplet size. In vivo gastric emptying, metabolite and hormone data reflect the exceptional in vitro gelling behavior of NCC, and the in vitro specifics of the WPI stabilized emulsion, i.e. intragastric lipolysis and destabilization.

3

Discussion

This work demonstrates that with an optimized in vitro analysis of lipid delivery systems an improved in vitro – in vivo correlation for lipid release patterns can be established. Oilin-water emulsions stabilized by stimuli-responsive biopolymers such as whey protein isolate (WPI), methylcellulose (MC), and nanocrystalline cellulose (NCC) were used to show how emulsion structures and lipid release patterns can be tailored. We demonstrate that primarily the interfacial properties of the material selection have a direct influence on gastric lipolysis. Gastric lipase was consistently active for WPI, concentration dependent active for MC, and

14

ACS Paragon Plus Environment

Page 14 of 35

Page 15 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

not active for NCC covered interfaces. Emulsion structuring during gastric in vitro digestion depend highly on the charge sensitivity of the emulsion droplets and the bulk phase. The NCC emulsions gelled strongly and remained stable, whereas the WPI emulsions gelled and destabilized, and the MC emulsions simply diluted. This in vitro gastric emulsion structuring could be validated by in vivo MRI experiments and is seen as the main contributor, i.e. the precursor structure formation for intestinal lipolysis. As a consequence, blood sample analysis demonstrated that NCC stabilized emulsions result in significantly lower plasma TAG and CCK values due to the strong gel formation in the gastric phase. WPI stabilized emulsions showed an earlier release of plasma TAG and CCK than both other emulsions highlighting the important role of gastric lipase. The mechanism of emulsion stabilization is not only important for gastric lipolysis, but also determines the stability of the emulsion in the gastric environment. Highly surface active material can compete with gastric lipases and inhibit its activity. 36,48,49 Other materials can sterically hinder its adsorption when the oil droplets are fully covered. One interesting phenomenon observed during this work was the stabilization of emulsions by NCC, which completely inhibited gastric lipolysis. NCC formed highly stable emulsions with droplets sizes around 1 µm, even though no interfacial activity could be measured with any interfacial technique. 30 In Figure 6a the cryo-SEM image shows craters formed by oil droplets stabilized by NCC (aqueous solution) and a perfectly aligned network of NCC, which shows that NCC was located within the aqueous phase. This finding was recently evidenced by small angle neutron scattering and questions the widely-used assumption that particle adsorption to interfaces is required for a Pickering emulsion stabilization. 30,50 In our case, droplet sizes of the negatively charged NCC emulsions (- 60 mV) were slightly decreased by adding ions prior to emulsification. This leads us to the following hypothesis for a possible, new stabilization mechanism: Charged hydrophilic NCC particles are attracted by oppositely charged ions, which accumulate around the negatively charged oil surface as oil-water interfaces. 51 Consequently, positively charged ions concentrate around oil droplets attracting 15

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 35

negatively charged NCC particles. This forms a stable network around the droplet, in which particle-particle interactions dominate as illustrated in Figure 6b. The sensitivity of NCC to ions leads to both a more compact interfacial film and an increase in emulsion viscosity.

a

b

particle-particle interaction

interface

+ ions

oil droplet

500 nm oil droplet crater

NCC

100 nm

NCC

droplet-droplet interaction

Figure 6: Potential mechanism for emulsion stabilization mechanism for nanocrystalline cellulose.(a) Cryo-SEM images of NCC stabilized oil droplets leave a crater after freeze fracturing. Emulsion composition: 4 wt% NCC in 10 mM PBS pH 7 and 20 wt% MCT oil. (b) Illustration of a possible stabilization mechanism of NCC stabilized emulsions. Charged hydrophilic NCC particles accumulate close at the interface due to a counter-ion cloud close to the negatively charged oil-water interface. Upon addition of ions, dropletdroplet and particle-particle interactions increases, whereas the ion cloud might concentrate. The expected structural properties and the lipid release patterns from in vitro measurements were supported by the in vivo analysis. The gastric lipolysis and the gastric emulsion structure formed had a large impact on plasma TAG. Golding et al. (2011) 12 highlighted the impact of gastric emulsion structure on intestinal lipolysis. They stated that only large changes in emulsion droplet surface area can impact on intestinal lipolysis. However, we observed that it is not the effective droplet surface area, but rather gelling determined intestinal lipolysis. With this the available droplet surface area for lipolysis is impaired and diffusion is reduced. The structural properties of the tested lipid systems had minor effect 16

ACS Paragon Plus Environment

Page 17 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

on the gastric emptying rate into the duodenum. However, previous work demonstrated that highly acid unstable emulsions cream within the stomach and the aqueous phase empties faster. This results in overall faster gastric emptying rate with unstable emulsion than stable emulsions. 3,52,53 Experiments for in vitro lipid digestion often neglect (i) gastric lipolysis, (ii) addition of mucin, or (iii) a pre-gastric digestion steps including mixing flow prior to intestinal lipolysis. 7,8,11,38 These are highly important parameters, which must be considered in order for a good in vitro – in vivo correlation to be made. Gastric lipolysis contributes up to 25% for total lipid digestion. 25 This can lead to earlier lipid sensing and fat absorption in the small intestine. This was demonstrated with the WPI emulsion system. WPI was the only emulsion system, where gastric lipase was active and thus FFA released in the stomach. Therefore, plasma TAG and CCK appeared earlier. Here, we clearly show the role of FFA released in the stomach on the CCK production, which has been speculated for a long time but never been demonstrated so far. The I-cells producing CCK are located in the upper part of the duodenum, and thus are activated by FFA released form the stomach. The role of gastric mucin for charged colloidal systems is fundamental, because it shields charges independent of pH. Charge shielding can lead to depletion stabilization/flocculation, droplet coalescence, and/or creaming. Thus mucin contributes to the macroscopic structure formed during gastric digestion. This macroscopic structure evolved during gastric digestion (both in vitro and in vivo) mainly determines the subsequent intestinal lipolysis. This pre-gastric digestion and emulsion bulk structuring step is crucial. The key limitation of the current work is the absence of the validation of gastric lipolysis in vivo. The in vivo measurement of gastric lipolysis requires the application of a gastric tube, which is known to influence gastric secretion, motor function, and thus gastric mixing. Nevertheless, the gastric lipase used in the current in vitro work, rDGL, has 85.7 % amino sequences identity with human gastric lipase and shows a similar 3D structure and enzyme activity. 54–56 Thus, rDGL activity should highly correlate with human lipase activity. One 17

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

limitation of the design of lipid delivery systems by interfacial approaches is that interfacial characteristics are never completely decoupled from emulsion bulk properties. Therefore, emulsion droplet size and bulk viscosity are always limited to certain material characteristics. Within this work we provide a simple method to predict emulsion structure during digestion in the gastric phase and how these structures influence intestinal lipid digestion. Here, gastric and intestinal lipolysis are analyzed separately to avoid superimposing effects and, as a consequence the real impact of gastric lipase might be underestimated.

4

Conclusion

In conclusion, representative prediction and in vitro simulation of lipid digestion in both the gastric and intestine environment can be achieved for stimuli-responsive emulsions. This includes the assessment of the gastric lipolytic activity, determining droplet size and viscosity when the lipid emulsion is mixed with SGF containing mucin and, in a second step, of the intestinal lipolysis of the gastric precursor emulsion. Finally, the relevant in vitro parameters for the gastric and intestinal digestion steps are matched to in vivo parameter to reach a reliable in vitro – in vivo correlation for lipid delivery systems. This approach highlights that gastric structuring determines lipolysis as well as early lipid release and sensing. Further, gastric mucin strongly influences the structure of charge-stabilized emulsion systems leading to destabilization or gel formation. The precursor structures of these emulsion modulate intestinal lipolysis kinetics in vitro, which is reflected in blood values such as plasma triglyceride and cholecystokinin concentrations in vivo as measured in healthy adults.

18

ACS Paragon Plus Environment

Page 18 of 35

Page 19 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

5 5.1

Experimental section Emulsion production

Oil-in-water emulsions were prepared dispersing medium chain triglyceride oils (MCT, Delios V, BASF) or rapeseed oil (Sabo) in an aqueous phase composing of whey protein isolate WPI (BiPro, Davisco), methylcellulose MC (MC A15, Dow Chemicals), or nanocrystalline cellulose NCC (Celluforce). Two oil phases were used to adapt the pKa for the optimal tritration of the enzyme activity. The emulsifiers were dissolved or dispersed prior to emulsification. WPI was mixed at least for 1 h and NCC for 2 h with a magnetic stirrer, whereas MC was dispersed over night at 4◦ C in an agitator to allow full hydration of the molecules. The aqueous phase consisted either of a 10 mM PBS pH 7 in MilliQ, pure MilliQ, 5 or 10 mM citric acid (Hanseler) phosphate buffer solution (PBS, sodium phosphate dibasic dihydrate, Sigma-Aldrich) in Evian water. In some experiments, viscosity of WPI based emulsions were adapted using xanthan (Keltrol, CP Kelco). Xanthan was dissolved at 70◦ C for 30 min before cooling and blending it with WPI emulsions after pre-emulsification. Emulsions were produced using a high pressure homogenizer, the microfluidizer® processor M-110EH30 (Microfluidics Corp., United States). Emulsions were pre-emulsified for 2-5 min using a rotor stator device, before they were passed multiple times (at least 3) through the microfluidizer at 500 bars. All emulsions were pasteurized for 5 min at 75◦ C, except those used for gastric lipase activity measurements.

5.2

Characterization of emulsions

Droplet size Droplet sizes were measured by laser diffraction (LS 13 320, Beckman Coulter, United States). Therefore, emulsions were diluted with distilled water. Imaging Emulsions were primarily imaged by light microscopy (Nikon Diaphot TMD light micro19

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

scope). NCC based emulsions were additionally analyzed by cryo scanning electron microscopy (SEM). SEM was used to analyze the interfacial structure of oil in water emulsions stabilized by NCC (4 wt% NCC in 10 mM PBS pH 7, 20 wt% MCT oil). Emulsions were filled in metal tubes and frozen under high pressure (2100 bar) within milliseconds by using the HPM 100 high-pressure freezing system to prevent the formation of ice-crystals. The samples were then freeze fractured and metal-coated before they were transferred to a precooled (−120◦ C) cryo-SEM (Zeiss Gemini 1530) for imaging. Bulk rheology Bulk rheological measurements were performed on a shear rheometer (Physica MCR 300 rheometer, Anton Paar, Austria). Complex viscosity η ∗ was extracted from oscillatory experiments at fixed frequency and amplitude (37◦ C, 10 s−1 , 1 %, after equilibration). Low viscous media were measured with the double gap geometry and higher viscous media were measured with a coaxial cylinder geometry CC27. Zeta potential Zeta potential ζ of emulsions were measured with a Zetasizer Nano ZS (Malvern Instruments Ltd.) to extract information about droplet charge. Emulsions were diluted with the corresponding pH of the bulk solution. These bulk solutions were either generated by titrating MilliQ water or 10 mM PBS (phosphoric acid, SAFC; sodium phosphate dibasic dihydrate, Sigma-Aldrich) pH 7 with 0.1 M HCl. Fresh human gastric juice was measured undiluted and was provided by the clinical partners.

5.3

in vitro digestion of emulsions

Simulated gastric and intestinal fluids Composition of simulated gastric fluids (SGF) and intestinal fluids (SIF) were based on Minekus et al. 38 In brief, a 1.25x stock solution of SGF was produced with various electrolytes and MilliQ water acidified (1 M HCl) to pH 2 and stored at −20◦ C. 1x SGF contained 6.9 mM KCl (Sigma Aldrich, Switzerland), 0.9 mM KH2 PO4 (Sigma Aldrich, Switzerland), 12.5 20

ACS Paragon Plus Environment

Page 20 of 35

Page 21 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

mM NaHCO3 (VWR International), 11.8 mM NaCl (Sigma Aldrich, Switzerland), 0.4 mM MgCl2 (H2 O)6 (Sigma Aldrich, Switzerland), 0.5 (NH4 )2 CO3 (Sigma Aldrich, Switzerland) electrolytes. To the 1.25x SGF stock solution 0.3 wt% mucin from porcine stomach (Sigma Aldrich, Switzerland) was dissolved and the mix titrated to pH 2, which represents the pH of freshly produced gastric juice. 57 The mix was further diluted with MilliQ pH 2 water. To remove traces of solids present from mucin, the samples were centrifuged at 10000 G for 10 min. Directly before blending with emulsions, 0.22 µ/ml CaCl2 (1mg/ml solution) and 2.3 mg/ml pepsin (Amresco, United states) was added to generate the final SGF. Activity of pepsin was 1747 U/mg and was measured using the procedure proposed by Minekus et al. 38 Different amounts of SGFs were gently blended with emulsions. A stock solution of simulated intestinal fluid (SIF) was produced with several electrolytes (0.63 mg/ml KCl, 0.136 mg/ml KH2 PO4 , 11.3 mg/ml NaHCO3 , 2.8 mg/ml NaCl, 0.04 mg/ml MgCl2 (H2 O)6 , 0.06 mg/ml (NH4 )2 CO3 ). 11 ml of this stock solution was put in the pH-stat device (see below) and heated to 37◦ C. 71 mg bile salt mixture (Sigma Aldrich, Switzerland) and 26 µl CaCl2 (of 0.3 M stock solution) was added to this solution and adjusted to pH 7. Then 2 ml of pancreatic lipase (Lipase from porcine pancreas, Sigma Aldrich, Switzerland) solution was added. The activity of pancreatic lipase was measured as proposed by Minekus et al. 38 and was 118 U/mg, with U equal to 1µmol of free fatty acid released per minute. Therefore final concentrations were set to 17 mg/ml to reach pancreatic lipase activity of 2000 U/ml SIF. The pancreatic lipase solution contained 117 mg/ml of pancreatic lipase dissolved in MilliQ water (15 seconds vortex) and centrifuged (13000 G, 5 min) to remove traces of particles and stored on ice.

pH-stat technique The pH-stat technique was used to determine lipase activity and lipolysis kinetics. 13–15 A T70 titration device (Mettler Toledo, Switzerland) was used to control and adjust the pH in the emulsion by titration of a 0.1 M NaOH (Sigma Aldrich) solution. Gastric lipolysis was 21

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

measured with recombinant dog gastric lipase (rDGL) in emulsions containing MCT oil and different concentrations of either WPI, MC or NCC dissolved in MilliQ water. rDGL had an activity of 183 ± 24 U/mg when using a standard gastric lipase assay (ESI 1). Emulsions were diluted with emulsifier solutions to reach an oil content of 5 wt%. 15 ml emulsion was placed in a glass beaker, which was attached to the titration device and tempered to 37◦ C. The pH was adjusted to pH 5 and the propeller stirrer set to 450 rpm (30 %). For MC and NCC stabilized emulsion, 2 mM NaTDC (Sigma Aldrich, Switzerland) was added to this emulsion. 20 µl rDGL stock solution was injected into the beaker. The stock solution consisted of 1 mg/ml rDGL in 10 mM PBS pH 6 and 150 mM NaCl dissolved in MilliQ water and was stored at −20◦ C. The amount 0.1 M NaOH used to maintain the pH was recorded for 60 min and rapidly back titrated to pH 9 as the experiments were performed at pH = 5. The average conversion factor for the release MCT oil at pH 5 was 10.98 (+/- 3.72). The activity of rDGL was calculated by fitting the fatty acid release function in a linear period at the beginning of the lipolysis. Lipolysis in the intestine was mimicked using the SIF described before. Preheated (37◦ C) emulsions (4 % biopolymer in Evian citric acid PBS buffer pH 7, 20 % MCT oil) were prestructured by blending 1:1 with SGF (without pepsin, as no significant structural changes of the emulsion were observed) and resting for 5 min at 37◦ C. 2 ml of this emulsion-SGF blend was added to the pre-heated (37◦ C) SIF and the fatty acids released were directly titrated at constant pH 7. The compact stirrer was set to 120 rpm (7 %). Maximum amount of fatty acids released from the added MCT oil (0.2 g) accord to 11.7 ml 0.1 M NaOH solution. Back titration experiments to pH 9 showed that the measured values from pH-stat needed to be adjusted by 1.5.

5.4

Study in healthy volunteers

The study was approved by the local ethics committee and was part of a clinical study registered at ClinicalTrials.gov with identifier NCT02865486. This study was a randomized, 22

ACS Paragon Plus Environment

Page 22 of 35

Page 23 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

double-blinded, unbalanced three-way crossover study design. Written informed consent was obtained from healthy subjects prior to the start of the study. At a screening visit, subject eligibility criteria were assessed. Those subjects with current health problems or a history of GI disease or abdominal surgery (excluding appendectomy or hernia repair) were excluded. Subjects must have also provided a negative pregnancy test if applicable, have a BMI between 18 and 25 kg/m2 , be a non-smoker or a non-regular smoker, aged between 18 and 50 years and have no contraindication to MRI. Every subject received three of four different emulsions according to a computer-generated randomization sequence, which was defined by permutated blocks. Emulsions were those described in this work plus an acid stable, small droplet size reference emulsion stablized with Polysorbate 80 and xanthan. 53 All subjects underwent MRI and blood sampling on each study day.

Measurement On each study day, subjects arrived in the morning at the MR center of the University Hospital Zurich after at least 8 h of fasting. All images were acquired in the right decubitus position using a 1.5 Tesla MRI scanner (Achieva, Philips Healthcare) and an abdominal phased array coil (4-channel SENSE body coil, Philips Healthcare). During scan pauses, subjects were allowed to assume a sitting position to ensure that intragastric gas accumulated in the fundus and was excluded from the antrum. 58 200 mL (380 kcal) of each emulsion was ingested within 1 - 2 min in the seated position. Postprandial MRI was performed in nine scan blocks at time points t = 0 (end of ingestion), 20, 40, 60, 90, 120, 150, 180, and 210 min. In each scan block, images were acquired to assess gastric fat and gallbladder content volumes. Venous blood samples were taken in fasting state (baseline) and thereafter at time points t = 0, 10, 20, 35, 50, 80, 110, 140, 170, 200, 250, and 300 min. Blood samples for the analysis of CCK were taken by using an EDTA-containing tubes (Sarstedt, Nämbrecht, Germany) which were prepared with a complete, EDTA-free proteinase inhibitor cocktail (Roche 23

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Diagnostics, Rotkreuz Switzerland) and DPP4-Inhibitor (Merck Millipore, Darmstadt, Germany). The plasma and serum of the samples were isolated by centrifugation (10 min, 10,389 x g), 4◦ C within 60 minutes of collection. Aliquots were stored at −20◦ C for later analysis. Plasma CCK concentration was measured by radioimmunoassay (RIA) using antiserum 92128 as previously detailed. 59 Plasma levels of triglycerides were determined using an enzymatic reaction and measuring the absorbance of the resulting metabolite using a spectrophotometer (Cobas Mira auto analyzer, Hoffman La Roche, Switzerland). Total triglyceride was measured by enzymatic hydrolysis to form glycerol followed by oxidation to give hydrogen peroxide. This was again quantified by formation of a colored product at 505 nm (Diatools AG, Villmergen, Switzerland). Endogenous glycerol was measured by enzymatic phosphorylation to form glycerol-1-phosphate followed by oxidation to give hydrogen peroxide which was quantified by production of a quinoneimine dye, which shows an absorbance maximum at 540 nm (Sigma-Aldrich, Buchs, Switzerland). True triglycerides were calculated by subtraction of endogenous glycerol concentration from total triglyceride concentration. In total 21 subjects were included in the study. Four subjects were withdrawn: one subject was unable to attend, two subjects suffered from nausea and one subject could not be cannulated. 17 subjects (6 men, 11 women; mean ± SD age: 25.6 ± 5.0 years; mean ± SD BMI: 22.2 ± 1.8 kg/m2 ) completed the study. Volume emptying data from two scan blocks and blood data from three samples were missing due to technical errors. Statistical analyses were performed on 378 observations for fitting volume curves and 441 observations for fitting concentration curves.

Volume distribution and emptying All quantitative image processing was performed under a blinded condition. A custom software tool written in MATLAB 2015a (The MathWorks, Natick, MA, USA) was used for segmenting stomach contents from conventional volume images and quantitative fat fraction 24

ACS Paragon Plus Environment

Page 24 of 35

Page 25 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

maps, as well as gallbladder volumes according to previously reported procedures. 53,60 Fat volume (FV) and gallbladder volume (GV) were calculated at each time point and plotted over time to generate volume emptying curves. 45 Postprandial delta over baseline (DOB) curves were calculated from the plasma concentrations of CCK and TAG. The curves of each measure were mathematically described with the power-exponential model according to:

M easure = AOB · k · β(1 − e−kt )β−1 · e−kt

(1)

with the three fitted parameters for the area over baseline AOB, the time-to-maximum/minimum amplitude tmax = logβ/k and the maximum/minimum amplitude Amax = C(tmax ).

Statistical analysis Statistical analyses were carried out with program R, version 3.1.3. 61 Model parameters were extracted from the fitted curves in a hierarchical Bayesian Markov chain Monte Carlo sampling strategy with R package rstan (version 2.8.2). 53 A varying intercepts mixed effects model 62 was used with emulsion as fixed effect and study day and subject as random effects. The effect of the four emulsions on the model parameters were presented as median and 95% highest posterior density CI (HPD 95%CI) in brackets. Half-times of gastric lipid emptying times (T50 ) were derived by setting F V to half its initial volume and solving the equation for the time = T50 numerically.

Acknowledgement The authors thank Celluforce for providing nanocrystalline cellulose, Frederic Carrière for providing recombinant dog gastric lipase, Falk Lucas for performing Cryo SEM, and Pascal Bertsch for critical discussion. This work was supported by the Swiss National Foundation (SNF) (projects No. 406940-145141, No. 200021-137941, and No. 200020-159898). 25

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Supporting Information Available The following files are available free of charge: Table S1 shows the tabulated parameter estimates reflecting the lipid release patterns of Plasma Triglyceride (TAG), Plasma Cholecystocinin (CCK), and Gallbladder Volume (GV). Table S2 shows the tabulated differences in parameter estimates reflecting the differences in lipid emulsion release patterns of Plasma Triglyceride (TAG), Plasma Cholecystocinin (CCK), and Gallbladder Volume (GV). This material is available free of charge via the Internet at http://pubs.acs.org/.

References (1) Porter, C. J. H.; Trevaskis, N. L.; Charman, W. N. Lipids and Lipid-based Formulations: Optimizing the Oral Delivery of Lipophilic Drugs. Nat Rev Drug Discov 2007, 6, 231– 248. (2) Norton, I.; Moore, S.; Fryer, P. Understanding Food Structuring and Breakdown: Engineering Approaches to Obesity. Obes. Rev. 2007, 8, 83–88. (3) Marciani, L.; Faulks, R.; Wickham, M. S. J.; Bush, D.; Pick, B.; Wright, J.; Cox, E. F.; Fillery-Travis, A.; Gowland, P. A.; Spiller, R. C. Effect of Intragastric Acid Stability of Fat Emulsions on Gastric Emptying, Plasma Lipid Profile and Postprandial Satiety. Br. J. Nutr. 2009, 101, 919–928. (4) Dibsdall, L. A.; Wainwright, C. J.; Read, N. W.; Booth, D. A. How Fats and Carbohydrates in Familiar Foods Contribute to Everyday Satiety by their Sensory and Physiological Actions. Nutr. Food Sci. 1996, 96, 37–43. (5) Maljaars, P.; Peters, H.; Mela, D.; Masclee, A. Ileal Brake: A Sensible Food Target for Appetite Control. A Review. Physiol. Behav. 2008, 95, 271 – 281.

26

ACS Paragon Plus Environment

Page 26 of 35

Page 27 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

(6) McClements, D. J.; Li, Y. Review of In Vitro Digestion Models for Rapid Screening of Emulsion-based Systems. Food Funct. 2010, 1, 32–59. (7) Ahmed, K.; Li, Y.; McClements, D. J.; Xiao, H. Nanoemulsion- and Emulsion-based Delivery Systems for Curcumin: Encapsulation and Release Properties. Food Chem. 2012, 132, 799 – 807. (8) Espinal-Ruiz, M.; Parada-Alfonso, F.; Restrepo-Sanchez, L.-P.; Narvaez-Cuenca, C.-E.; McClements, D. J. Impact of Dietary Fibers (Methyl Cellulose, Chitosan, and Pectin) on Digestion of Lipids under Simulated Gastrointestinal Conditions. Food Funct. 2014, 5, 3083–3095. (9) Fernandez, S.; Jannin, V.; Chevrier, S.; Chavant, Y.; Demarne, F.; Carrière, F. In Vitro Digestion of the Self-Emulsifying Lipid Excipient Labrasol® by Gastrointestinal Lipases and Influence of its Colloidal Structure on Lipolysis Rate. Pharm. Res. 2013, 30, 3077–3087. (10) Hur, S. J.; Kim, D. H.; Chun, S. C.; Lee, S. K.; Keum, Y. S. Effects of Biopolymer Encapsulation on Trans Fatty Acid Digestibility in an In Vitro Human Digestion System. Food Funct. 2013, 4, 1827–1834. (11) Hur, S. J.; Decker, E. A.; McClements, D. J. Influence of Initial Emulsifier Type on Microstructural Changes Occurring in Emulsified Lipids during In Vitro Digestion. Food Chemistry 2009, 114, 253 – 262. (12) Golding, M.; Wooster, T. J.; Day, L.; Xu, M.; Lundin, L.; Keogh, J.; Clifton, P. Impact of Gastric Structuring on the Lipolysis of Emulsified Lipids. Soft Matter 2011, 7, 3513– 3523. (13) Gargouri, Y.; Pieroni, G.; Rivière, C.; Lowe, P. A.; Saunière, J.-F.; Sarda, L.; Verger, R. (Importance of Human Gastric Lipase for Intestinal Lipolysis: An in vitro Study. Biochim. Biophys. Acta 1986, 879, 419–423. 27

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(14) Gargouri, Y.; Sarda, L.; Piéroni, G.; Rivière, C.; Lowe, P.; Ferrato, F.; Verger, R. In Enzymes of Lipid Metabolism II ; Freysz, L., Dreyfus, H., Massarelli, R., Gatt, S., Eds.; Springer US: Boston, MA, 1986; Chapter Kinetic Assay of Human Gastric Lipase on Short and Long Chain Triacylglycerol Emulsions, pp 19–22. (15) Armand, M.; Borel, P.; Ythier, P.; Dutot, G.; Melin, C.; Senft, M.; Lafont, H.; Lairon, D. Effects of Droplet Size, Triacylglycerol Composition, and Calcium on the Hydrolysis of Complex Emulsions by Pancreatic Lipase: An In Vitro Study. J. Nutr. Biochem. 1992, 3, 333–341. (16) Helbig, A.; Silletti, E.; Timmerman, E.; Hamer, R. J.; Gruppen, H. In Vitro Study of Intestinal Lipolysis using pH-stat and Gas Chromatography. Food Hydrocolloids 2012, 28, 10–19. (17) Li, Y.; Hu, M.; McClements, D. J. Factors Affecting Lipase Digestibility of Emulsified Lipids using an In Vitro Digestion Model: Proposal for a Standardised pH-stat Method. Food Chem. 2011, 126, 498–505. (18) Marze, S.; Choimet, M. In Vitro Digestion of Emulsions: Mechanistic and Experimental Models. Soft Matter 2012, 8, 10982–10993. (19) Williams, H. D.; Sassene, P.; Kleberg, K.; Bakala-N’Goma, J.-C.; Calderone, M.; Jannin, V.; Igonin, A.; Partheil, A.; Marchaud, D.; Jule, E.; Vertommen, J.; Maio, M.; Blundell, R.; Benameur, H.; Carrière, F.; Müllertz, A.; Porter, C. J. H.; Pouton, C. W., Toward the Establishment of Standardized In Vitro Tests for Lipid-Based Formulations, Part 1: Method Parameterization and Comparison of In Vitro Digestion Profiles Across a Range of Representative Formulations. J. Pharm. Sci. 2012, 101, 3360–3380. (20) Nicolai, T.; Britten, M.; Schmitt, C. β-lactoglobulin and WPI Aggregates: Formation, Structure and Applications. Food Hydrocolloids 2011, 25, 1945–1962.

28

ACS Paragon Plus Environment

Page 28 of 35

Page 29 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

(21) Hirrien, M.; Chevillard, C.; Desbrières, J.; Axelos, M.; Rinaudo, M. Thermogelation of Methylcelluloses: New Evidence for Understanding the Gelation Mechanism. Polymer 1998, 39, 6251–6259. (22) Scheuble, N.; Geue, T.; Kuster, S.; Adamcik, J.; Mezzenga, R.; Windhab, E. J.; Fischer, P. Mechanically Enhanced Liquid Interfaces at Human Body Temperature using Thermosensitive Methylated Nanocrystalline Cellulose. Langmuir 2016, 32, 1396–1404. (23) Peng, B. L.; Dhar, N.; Liu, H. L.; Tam, K. C. Chemistry and Applications of Nanocrystalline Cellulose and its Derivatives: A Nanotechnology Perspective. Can. J. Chem. Eng. 2011, 89, 1191–1206. (24) Miao, C.; Hamad, W. Cellulose Reinforced Polymer Composites and Nanocomposites: A Critical Review. Cellulose 2013, 20, 2221–2262. (25) Lengsfeld, H.; Beaumier-Gallon, G.; Chahinian, H.; De Caro, A.; Verger, R.; Laugier, R.; Carrière, F. Lipases and Phospholipases in Drug Development; Wiley-VCH Verlag GmbH & Co. KGaA, 2005; pp 195–229. (26) Chahinian, H.; Snabe, T.; Attias, C.; Fojan, P.; Petersen,; Carrière, F. How Gastric Lipase an Interfacial Enzyme with a Serhisasp Catalytic Triad acts optimally at Acidic ph. Biochemistry 2006, 45, 993–1001. (27) Patino, J.; Nino, M.; Sanchez, C. Adsorption of Whey Protein Isolate at the Oil-Water Interface as a Function of Processing Conditions: A Rheokinetic Study. J. Agric. Food Chem. 1999, 47, 2241–2248. (28) Nino, M. R. R.; Patino, J. M. R.; Sanchez, C. C.; Fernandez, M. C.; Garcia, J. M. Physicochemical Characteristics of Food Lipids and Proteins at Fluid-Fluid Interfaces. Chem. Eng. Commun. 2003, 190, 15–47.

29

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(29) Arboleya, J.-C.; Wilde, P. J. Competitive Adsorption of Proteins with Methylcellulose and Hydroxypropyl Methylcellulose. Food Hydrocolloids 2005, 19, 485–491. (30) Scheuble, N.; Geue, T.; Windhab, E. J.; Fischer, P. Tailored Interfacial Rheology for Gastric Stable Adsorption Layers. Biomacromolecules 2014, 15, 3139–3145. (31) Scheuble, N.; Lussi, M.; Geue, T.; Carrière, F.; Fischer, P. Blocking Gastric Lipase Adsorption and Displacement Processes with Viscoelastic Biopolymer Adsorption Layers. Biomacromolecules 2016, 17, 3328–3337. (32) Nik, A. M.; Wright, A. J.; Corredig, M. Impact of Interfacial Composition on Emulsion Digestion and Rate of Lipid Hydrolysis Using Different In Vitro Digestion Models. Colloids Surf., B 2011, 83, 321–330. (33) Tiss, A.; Carrière, F.; Verger, R. Effects of Gum Arabic on Lipase Interfacial Binding and Activity. Anal. Biochem. 2001, 294, 36–43. (34) Torcello-Gomez, A.; Fernandez Fraguas, C.; Ridout, M. J.; Woodward, N. C.; Wilde, P. J.; Foster, T. J. Effect of Substituent Pattern and Molecular Weight of Cellulose Ethers on Interactions with Different Bile Salts. Food Funct. 2015, 6, 730–739. (35) Couedelo, L.; Amara, S.; Lecomte, M.; Meugnier, E.; Monteil, J.; Fonseca, L.; Pineau, G.; Cansell, M.; CarriŔre, F.; Michalski, M. C.; Vaysse, C. Impact of Various Emulsifiers on ALA Bioavailability and Chylomicron Synthesis through Changes in Gastrointestinal Lipolysis. Food and Function 2015, 6, 1726–1735. (36) Pafumi, Y.; Lairon, D.; de la Porte, P. L.; Juhel, C.; Storch, J.; Hamosh, M.; Armand, M. Mechanisms of Inhibition of Triacylglycerol Hydrolysis by Human Gastric Lipase. J. Biol. Chem. 2002, 277, 28070–28079. (37) Golding, M.; Wooster, T. J. The Influence of Emulsion Structure and Stability on Lipid Digestion. Curr. Opin. Colloid Interface Sci. 2010, 15, 90–101. 30

ACS Paragon Plus Environment

Page 30 of 35

Page 31 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

(38) Minekus, M.; Alminger, M.; Alvito, P.; Ballance, S.; Bohn, T.; Bourlieu, C.; Carriere, F.; Boutrou, R.; Corredig, M.; Dupont, D.; Dufour, C.; Egger, L.; Golding, M.; Karakaya, S.; Kirkhus, B.; Le Feunteun, S.; Lesmes, U.; Macierzanka, A.; Mackie, A.; Marze, S.; McClements, D. J.; Menard, O.; Recio, I.; Santos, C. N.; Singh, R. P.; Vegarud, G. E.; Wickham, M. S. J.; Weitschies, W.; Brodkorb, A., A Standardised Static In Vitro Digestion Method Suitable for Food - An International Consensus. Food Funct. 2014, 5, 1113–1124. (39) Abodinar, A.; Tømmeraas, K.; Ronander, E.; Smith, A. M.; Morris, G. A. The Physicochemical Characterisation of Pepsin Degraded Pig Gastric Mucin. Int. J. Biol. Macromol. 2016, 87, 281–286. (40) Bansil, R.; Turner, B. S. Mucin Structure, Aggregation, Physiological Functions and Biomedical Applications. Curr. Opin. Colloid Interface Sci. 2006, 11, 164–170. (41) Celli, J. P.; Turner, B. S.; Afdhal, N. H.; Ewoldt, R. H.; McKinley, G. H. Rheology of Gastric Mucin Exhibits a pH-Dependent Sol-Gel Transition. Biomacromolecules 2007, 8, 1580–1586. (42) Bansil, R.; Stanley, H. E.; Lamont, J. T. Mucin Biophysics. Ann. Rev. Physiol. 1995, 57, 635–657. (43) Ferrua, M.; Singh, R. Modeling the Fluid Dynamics in a Human Stomach to Gain Insight of Food Digestion. J. Food Sci. 2010, 75, 151–162. (44) Schulze, K. S. The Imaging and Modelling of the Physical Processes Involved in Digestion and Absorption. Acta Physiol. 2015, 213, 394–405. (45) Liu, D.; Parker, H. L.; Curcic, J.; Schwizer, W.; Fried, M.; Kozerke, S.; Steingoetter, A. The Visualisation and Quantification of Human Gastrointestinal Fat Distribution with MRI: A Randomised Study in Healthy Subjects. Br. J. Nutr. 2016, 115, 903–912.

31

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(46) Marciani, L.; Gowland, P.; Spiller, R.; Manoj, P.; Moore, R.; Young, P.; FilleryTravis, A. Effect of Meal Viscosity and Nutrients on Satiety, Intragastric Dilution, and Emptying Assessed by MRI. Am. J. Physiol.: Gastrointest. Liver Physiol. 2001, 280, G1227–G1233. (47) Steingoetter, A.; Buetikofer, S.; Curcic, J.; Menne, D.; Rehfeld, J. F.; Fried, M.; Schwizer, W.; Wooster, T. J. The Dynamics of Gastric Emptying and Self-Reported Feelings of Satiation are better Predictors than Gastrointestinal Hormones of the Effects of Lipid Emulsion Structure on Fat Digestion in Healthy Adults—A Bayesian Inference Approach. J Nutr. 2017, 147, 706–714. (48) Reis, P.; Miller, R.; Leser, M.; Watzke, H.; Fainerman, V. B.; Holmberg, K. Adsorption of Polar Lipids at the Water-Oil Interface. Langmuir 2008, 24, 5781–5786. (49) Reis, P.; Holmberg, K.; Miller, R.; Krägel, J.; Grigoriev, D. O.; Leser, M. E.; Watzke, H. J. Competition between Lipases and Monoglycerides at Interfaces. Langmuir 2008, 24, 7400–7407. (50) Cherhal, F.; Cousin, F.; Capron, I. Structural Description of the Interface of Pickering Emulsions Stabilized by Cellulose Nanocrystals. Biomacromolecules 2016, 17, 496–502. (51) Wilde, P. J. Interfaces: Their Role in Foam and Emulsion Behaviour. Curr. Opin. Colloid Interface Sci. 2000, 5, 176–181. (52) Marciani, L.; Wickham, M.; Singh, G.; Bush, D.; Pick, B.; Cox, E.; Fillery-Travis, A.; Faulks, R.; Marsden, C.; Gowland, P. A.; Spiller, R. C. Enhancement of Intragastric Acid Stability of a Fat Emulsion Meal delays Gastric Emptying and increases Cholecystokinin Release and Gallbladder Contraction. Am. J. Physiol.: Gastrointest. Liver Physiol. 2007, 292, G1607–G1613. (53) Steingoetter, A.; Radovic, T.; Buetikofer, S.; Curcic, J.; Menne, D.; Fried, M.; Schwizer, W.; Wooster, T. J. Imaging Gastric Structuring of Lipid Emulsions and its 32

ACS Paragon Plus Environment

Page 32 of 35

Page 33 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

Effect on Gastrointestinal Function: A Randomized Trial in Healthy Subjects. Am. J. Clin. Nutr. 2015, 101, 714–724. (54) Roussel, A.; Miled, N.; Berti-Dupuis, L.; Rivière, M.; Spinelli, S.; Berna, P.; Gruber, V.; Verger, R.; Cambillau, C. Crystal Structure of the Open Form of Dog Gastric Lipase in Complex with a Phosphonate Inhibitor. J. Biol. Chem. 2002, 277, 2266–2274. (55) Roussel, A.; Canaan, S.; Egloff, M. P.; Riviere, M.; Dupuis, L.; Verger, R.; Cambillau, C. Crystal Structure of Human Gastric Lipase and Model of Lysosomal acid Lipase, two Lipolytic Enzymes of Medical Interest. J. Biol. Chem. 1999, 274, 16995–17002. (56) Aloulou, A.; Rodriguez, J. A.; Fernandez, S.; van Oosterhout, D.; Puccinelli, D.; Carrière, F. Exploring the Specific Features of Interfacial Enzymology based on Lipase Studies. Biochim. Biophys. Acta, Mol. Cell Biol. Lipids 2006, 1761, 995 – 1013. (57) Steingoetter, A.; Sauter, M.; Curcic, J.; Liu, D.; Menne, D.; Fried, M.; Fox, M.; Schwizer, W. Volume, Distribution and Acidity of Gastric Secretion on and off Proton Pump Inhibitor Treatment: A Randomized Double-blind Controlled Study in Patients with Gastro-esophageal Reflux Disease (GERD) and Healthy Subjects. BMC Gastroenterol. 2015, 15, 1–11. (58) Steingoetter, A.; Fox, M.; Treier, R.; Weishaupt, D.; Marincek, B.; Boesiger, P.; Fried, M.; Schwizer, W. Effects of Posture on the Physiology of Gastric Emptying: A Magnetic Resonance Imaging Study. Scand. J. Gastroenterol. 2006, 41, 1155–1164. (59) Rehfeld, J. F. Accurate Measurement of Cholecystokinin in Plasma. Clin. Chem. 1998, 44, 991–1001. (60) Liu, D.; Parker, H. L.; Curcic, J.; Kozerke, S.; Steingoetter, A. Emulsion Stability Modulates Gastric Secretion and Its Mixing with Emulsified Fat in Healthy Adults in a Randomized Magnetic Resonance Imaging Study. J. Nutr. 2016, 146, 2158–2164.

33

ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(61) Team, R. D. C. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing, 2015. (62) Sorensen, T.; Hohenstein, S.; Vasishth, S. Bayesian Linear Mixed Models using Stan: A Tutorial for Psychologists, Linguists, and Cognitive Scientists. http://arxiv.org/ abs/1506.06201, 2015.

34

ACS Paragon Plus Environment

Page 34 of 35

Page 35 of 35 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

Graphical TOC Entry Interface

NCC

WPI

MC

oil water

Stomach

35

ACS Paragon Plus Environment