Ultrasound-induced transport across lipid bilayers: Influence of phase behavior

Colloids and Surfaces A: Physicochem. Eng. Aspects 390 (2011) 40–47

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Ultrasound-induced transport across lipid bilayers: Influence of phase behavior Eleanor F. Small a , Michael C. Willy a , Peter A. Lewin b , Steven P. Wrenn a,∗ a b

Department of Chemical and Biological Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, United States School of Biomedical Engineering, Science and Health Systems, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, United States

a r t i c l e

i n f o

Article history: Received 8 June 2011 Received in revised form 5 August 2011 Accepted 26 August 2011 Available online 22 September 2011 Keywords: Ultrasound Liposome Lipid phase behavior Controlled drug release Lipid raft

a b s t r a c t This paper examines the role of lipid membrane phase behavior on the kinetics and mechanism of ultrasound-induced transport. We present a quantitative study of low frequency ultrasound (LFUS)induced release of calcein from the aqueous core of large unilamellar vesicles (LUVs) comprising a wide range of lipid compositions. The LUVs comprise of the lipids 1,2-dioleoyl-phosphocholine (DOPC), 1,2-dipalmitoyl-phosphocholine (DPPC), and cholesterol, as these species constitute a proven model membrane system for which the phase behavior is well described. Samples from different regions in the composition space were exposed to 20 kHz, continuous wave ultrasound and steady-state fluorescence spectroscopy was used to quantify leakage. Results are presented in the form of a “release map”; that is, leakage results are superimposed onto a phase diagram. Additionally, release kinetics are fit with simple mathematical models that account for diffusion and bilayer destruction. As membrane phase changes toward liquid-ordered, the membrane becomes increasingly resistant to destruction such that the rate of diffusion decreases. Two mechanisms of release are evident in ld samples, diffusion and destruction. lO samples on the other hand, do not exhibit vesicle destruction and fit well to diffusion-only model. The phase of the membrane, rather than the cholesterol mole fraction per se, has a stronger influence on membrane permeability and destruction potential. Specifically the variation in permeability among different phases, but whose cholesterol mole fraction is identical, is roughly twice the variation in permeability observed as cholesterol mole fraction is varied within the a given phase. The difference in membrane thickness between ld and lO phases does not account for the observed difference in permeability; thus influence of phase behavior is not trivial. The correlation of permeability with phase behavior might prove useful in designing and developing therapies based on ultrasound and membrane interactions. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Therapeutic ultrasound is a growing field. Building on its classical use for lithotripsy [1], ultrasound is now used in applications such as DNA and protein delivery into the cell [2–4], drug delivery into the blood stream [5], transdermal delivery [6,7], and highintensity focused ultrasound (HIFU) [1]. Many ultrasound-based therapies require sonoporation, which is the process by which an otherwise impermeable membrane is made permeable in the presence of a sound field [8,9]. Despite its widespread use, the physical mechanism(s) of ultrasound-induced transport is not fully understood. In particular, it is not known whether ultrasound driven transport results from inertial cavitation [3,8,10,11], stable cavitation [12–14], or both. Regardless, ultrasound- induced transport necessarily involves interactions with the cell membrane, and this points to the possibility, if not probability, that membrane physical

∗ Corresponding author. Tel.: +1 215 895 6694; fax: +1 215 895 5837. E-mail address: [email protected] (S.P. Wrenn). 0927-7757/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.colsurfa.2011.08.048

properties play a role. Given the existence of lipid rafts [15–19], which change membrane physical properties [20–23], this paper examines the hypothesis that ultrasound-induced transport correlates with membrane phase behavior. Both rates and extents of ultrasound-induced leakage are measured for a wide range of lipid membrane compositions, and results are analyzed with multiple transport models. This work is motivated by research involving ultrasound contrast agents, or microbubbles, which has shown a strong correlation between microbubble shell chemistry and acoustic response [24–28]. We anticipate that ultrasound-induced transport, both amount and rate, will similarly be influenced by membrane composition. In particular, different membrane phases are expected to exhibit different ultrasound-induced transport kinetics. Previous work on cells and lipid vesicles at low frequency (20–100 KHz) focused on membrane curvature [29], lipid packing geometry [30], and addition of surfactants [29,31–33], but few studies have examined the specific role of membrane phase behavior. Pong et al. [29] investigated the effect of membrane curvature and found that membranes with higher curvature were more resistant to low frequency ultrasound (LFUS)-induced leakage. This result was

E.F. Small et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 390 (2011) 40–47

readily explained by an increase in the Laplace pressure associated with increased vesicle curvature. Moreover, the relative length scales (vesicle diameter in comparison with ultrasound wavelength) involved in that work precluded a direct shearing of the vesicle bilayer due to an ultrasound-induced pressure gradient [29]. Evjen et al. [30] compared the serum-induced leakage and LFUS-induced leakage of distearoylphosphatidylethanolamine (DSPE), which has a non-bilayer forming inverted cone geometry, to distearoylphosphatidylcholine (DSPC), which has bilayer favorable cylindrical geometry. Whereas DSPE increased LFUS leakage, the smaller head group also destabilized the lipid vesicles in serumexcept when high cholesterol mole fractions were present [30]. The addition of surfactants such as a PEGylated lipid increases LFUS-induced release [29,31,32]. Pong et al. [29] found that release increased with increasing the PEG2000-DPPE concentration up to 5 mol%. There was negligible difference between 5 mol% and 8 mol%, the latter value being the saturation concentration of PEGDPPE in the lipid bilayer. Lin and Thomas [31,32] investigated the effect of PEG chain length on LFUS-induced release and found no difference between the influence of PEG2000 and PEG350 below the saturation limit. Huang and MacDonald [33] studied the effect of adding a short-chained lipid, diheptanoylphosphatidylcholine (DHPC), known for disrupting bilayers due to its micelle-forming tendencies. The addition of only 4 mol% DHPC liposomes increased LFUS sensitivity 3.5 fold. These studies produced qualitative observations concerning the relationship between cholesterol in the membrane and liposome leakage. This study seeks to build on earlier observations by quantifying the relationship between membrane composition and ultrasound-induced transport across lipid membranes by correlating results with membrane phase behavior. Lipid phase behavior depends strongly on lipid type and composition. Incorporating cholesterol into a phosphatidylcholine (PC) membrane with saturated or monounsaturated lipids causes the membrane to pack more cohesively, stiffening and lengthening the lipid acyl chains and thereby reducing the area per molecule [20,34,35]. This so-called condensation effect increases membrane rigidity, shear stress resistance, and toughness [20,21,34,35], giving rise to what is referred to as the liquid-ordered, or lO , phase. The lO phase differs from the condensed, solid-ordered (so ), and liquiddisordered, ld , phases in that the lipids retain the lateral mobility of the ld phase but exhibit the mechanical properties of the so phase [20,34,36,37]. Moreover, lO domains are widely believed to account for the existence of protein-containing lipid rafts in cell membranes [38–40]. The question of relevance here is how phase behavior might influence interactions of a membrane with an ultrasound wave. It is well known that sound travels faster in bulk solids than in bulk liquids [1]; key to this work, the bulk phenomenon extends to two dimensions. Consequently, sound travels faster through solidordered liposomes[41] than through liquid-disordered liposomes [42]. When ultrasound is applied the response and susceptibility to stressed of the two phases is markedly different [20,21,34]. Gong et al. [20] investigated the effect of cholesterol mole fraction on thermodynamic stability of DPPC/Cholesterol monolayers. Increasing cholesterol from 0.2 to 0.6 mole fraction more than doubled the decrease in excess Gibbs free energy. Needham and Nunn [34] measured elastic compressibility modulus and failure energy (toughness) of lipid bilayers using giant unilamellar vesicles (GUVs) in various phases. Membranes in the lO phase exhibited 4 times the elastic compressibility and two times the toughness of membranes in the ld phase [34]. Liu et al. [21] subjected EggPC/Cholesterol vesicles (bilayers) to 50 s−1 shear at 298 K and 310 K to investigate the effect of cholesterol and temperature on membrane shear stress resistance. The threshold of shear stress needed to destroy the PC bilayer increased with increasing cholesterol at both temperatures. Moreover, the shear stress thresholds at 298 K were more than

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double those at 310 K, further suggesting a role of membrane phase behavior [21]. Here we report a study that systematically evaluates the relationship between low-frequency ultrasound (LFUS) and lipid phase behavior. We present results in the form of a “release map”, in which measured leakage results are superimposed onto a phase diagram. Additionally, results are fit with simple mathematical models describing diffusion and bilayer destruction. It is shown that leakage depends strongly on composition and that the mechanism of release depends on the type and amount of phases present. Such results might prove useful in designing and developing therapies involving ultrasound and membrane interactions.

2. Materials and methods 2.1. Materials of 1,2-dioleoyl-phosphocholine (DOPC), Samples 1-palmitoyl-2-oleoyl-phosphatidylcholine (POPC), and 1,2dipalmitoyl-phosphocholine (DPPC) were provided by Lipoid, LLC (Newark, NJ). Cholesterol (Chol), sodium chloride (NaCl), Calcein, Triton X-100, Sephadex G-50, Sephadex G-75, and ethylenediaminetetra-acetic acid (EDTA anhydrous) were purchased from Sigma-Aldrich (St. Louis, MO). TrisBase (Tris) and chloroform were purchased from Fisher Scientific, Inc. (Fair Lawn, NJ). Extrusion drain disks and poly carbon filters were purchased from Nuclepore, Whatman Inc. (Clifton, NJ). Nitrogen (N2 ) was obtained from Airgas (Allentown, PA). All products were used without further purification.

2.2. Vesicle preparation Samples for the “release map” were determined by finding the intersections of constant DPPC (every 5%) lines and constant molar ratio lines (DOPC/DPPC: 90-10, 85-15, 80-20 . . .55-45, 50-50, 4555. . .25-75), for a total of seventy-four points. Kinetic studies were performed on twenty-seven points chosen as follows; nine compositions along the tie-lines published by Veatch et al. [43] (shown as the solid lines in Fig. 2). One point at each intersection of the tie-line (published by [43]) and phase boundary (published by [44]). Composition trajectory lines (dashed lines in Fig. 2) were extended from the published tie-lines beyond the two-phase boundary and used to select twelve samples of single phase. For each trajectory line two points were purely liquid-disordered, and two points purely liquid-ordered, for a total of nine points per tie-line/composition trajectory line. Data from some of the kinetic studies were added to the “release map” if the points were clearly distinct from compositions already evaluated. Large unilamellar vesicles (LUVs) were created by extrusion of multilamellar vesicles (MLVs) to maintain consistency with research reviewed above and with previous work by this lab. Multilamellar vesicles were created using the Rapid Solvent Exchange (RSE) method [45], to avoid undesired cholesterol crystallization at the higher cholesterol samples. Briefly, stock solutions of the lipids were placed in 25 mL, flat bottomed, shell vials (Fisher Scientific, Inc.). 3 mL of 60 ◦ C Calcein Buffer (150 mM NaCl, 10 mM Tris, 1 mM EDTA, 70 mM Calcein, pH 7.4) was added and the mixture was vortexed under a vacuum of 635 mmHg for 60 s. Additional buffer was added to make a final lipid concentration of 1 mM. MLVs were then extruded seven times through double stacked poly carbon filters with a pore size of 0.2 ␮m to create LUVs nominally 200 nm in diameter. Extruded samples were subject to size exclusion chromatography in 50 cm columns packed with either Sephadex G-50 or G-75, and eluted with room temperature

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Ultrasound Buffer (150 mM NaCl, 10 mM Tris, 1 mM EDTA, pH 7.4) to separate the vesicles from un-encapsulated calcein. 2.3. DLS and release fluorescence assays Column eluate was collected in 4 mL sections and analyzed using a Brookhaven 90 Plus, Dynamic Light Scattering (DLS) apparatus. Those sections with a light scattering intensity of 100 kcps or higher were mixed and divided into three, 3 mL samples. For each composition the three samples were divided; one aliquot was selected as a control, in which fluorescence was measured periodically but no sonication was applied. The other aliquots, referred to as “test samples”, were then exposed to ultrasound and rest cycles as described below. Analysis of re-aliquoted samples obtained effective diameter and polydispersity statistics. All release assays were performed using a Misonix XL2020 probe tip sonicator (Misonix Inc., Farmingdale, NY) operating at 20 kHz using a 419 tip. Sonicator was calibrated using the Misonix tuning protocol and set to 10% output power (electrical) at a setting of 3. The 20 kHz sonicator was selected because cavitation is inversely proportional to frequency, so the likelihood of inertial cavitation governing the release was optimized. Ultrasound field parameters, including peak-to-peak pressure amplitudes and spatial-peak, temporal-peak intensity were measured using a Reson TC4038 hydrophone (Reson Inc., US, Goleta, CA) with a sensitivity of −228.2 dB re 1 V/␮Pa at 20 kHz. At this frequency the wavelength is about 75 mm in water-like medium, and therefore the tip can be considered to behave as a point source. Accordingly, to protect the relatively fragile and expensive hydrophone the acoustic pressure amplitude measurements were performed at 10, 9, and 8 cm radial distances from the probe’s tip. Next, the measurement data were used to estimate the pressure amplitude at 1 cm (the distance at which release assays were performed). This amplitude was calculated to be equal to approximately 1027 ± 134 kPa, which corresponds to a spatial-peak, temporal-peak intensity of approximately 35.5 W/cm2 . Fluorescence studies used a well-established assay of relief of self-quenching of calcein. Co-encapsulation of another species is not required for calcein quenching, and none were used here. “Release map” data were gathered by exposing the test sample to 180 consecutive seconds of continuous wave, 20 kHz ultrasound. Samples were placed in an ice water bath to maintain their temperature at 22 ± 2 ◦ C. A steady-state fluorescence spectrometer (Photon Technology International, Ontario, Canada, model Q5/W-601) measured fluorescence after each ultrasound exposure. Fluorescent kinetic release studies were performed by exposing the test sample to 30 s of continuous wave, 20 kHz ultrasound using the Misonix XL2020 under the same conditions as above. Fluorescence measurements were obtained on these test samples during a 3 min rest period between ultrasonic exposures. This procedure was repeated until total ultrasonic exposure reached 360 s, resulting in a total experimental time of 42 min. Time values were chosen based upon previous work by this lab [29], as it allowed for the maximum number of compositions to be sampled while giving enough data to analyze the kinetics of release. In all cases samples reached at least 80% release. Fraction of release was determined via: (It − It=0 )/(Imax − It=0 ) where It represents the intensity of the current run, It=0 is the intensity prior to any ultrasonic exposure (t = 0), and Imax is the intensity after adding 10 ␮l of TritonX-100 (final concentration of 5.7 E−3 M), which destroys all the membranes releasing all encapsulated dye [29,31,46,47]. Samples were excited at 488 nm and peak emission was found to be 521 ± 3 nm. Negative controls were run to determine potential interactions between Triton X-100 and calcein (data not shown). Results showed negligible effect of Triton X-100 (at 5.7 E−3 M) on calcein fluorescence (range of 1.0 E−5 M to 1.5 E−1 M).

Data for destruction studies were collected by preparing vesicles as described above using Ultrasound Buffer (no calcein), which was then passed through columns to achieve similar dilution levels as calcein samples. Samples were then subject to initial DLS measurements followed by kinetic study-style sonication. After every 120 s of LFUS exposure (four rounds on 30 s sonication, 3 min rest) samples were re-read on the DLS and recorded. The procedure was continued until 360 s of LFUS exposure was reached and final DLS measurements were made. “Destruction” in this case meaning catastrophic damage to the bilayer causing it to lose vesicle formation. Exposed ends of the bilayer debris are thermodynamically unfavorable thus in the absence of external influence the lipids will form large aggregates. 2.4. Modeling Model parameters P, permeability (cm2 /s) and ˇ, rate of destruction, (both described in detail in Section 4.0) were fit using the built-in least squares fit function “Lsqcurvefit.” Ordinary differential equations were solved using the “ODE 45 solver” routine in MatLAB R2010a (The MathWorks, Inc. Natick, MA). 3. Experimental results and discussion A primary goal of this study is to quantify the role that lipid phase behavior plays in membrane susceptibility to LFUS-induced release and to ascertain the mechanism(s) of release. A ternary system of DOPC, DPPC, and cholesterol, which has well documented phase behavior that comprises a relatively large liquid-liquid coexistence region, was used for this purpose [16–19,43,44]. Samples were prepared and particle size determined as described in Sections 2.2 and 2.3. In all lipid compositions the average diameter was 190 ± 10 nm. Test samples were exposed to 3 min of continuous 20 kHz ultrasound, and the final fraction of release was recorded as described in Section 2.3. The 3 min exposure time was chosen based on preliminary studies as that time which minimizes the duration of the experiment while still capturing all the relevant leakage. Fig. 1 depicts the resulting “release map” with respect to the sample composition. The two-phase region at 25 ◦ C (redrawn from [44]) has been overlaid on the map to clarify the boundaries of phase coexistence. A clear pattern of decreasing release with increasing cholesterol is apparent from the gradual change of data shades from white (76% release) to black (31% release). While the release map in Fig. 1 shows a large difference among phases (liquid-ordered samples exhibit much less leakage than liquid-disordered samples) it does not reveal whether leakage correlates with phase behavior per se or merely with the cholesterol compositions. Discerning a relation between phase behavior and ultrasound requires analysis of the kinetics of release along tie-lines which are drawn based on the work of Veatch et al. [43]. Accordingly kinetic profiles for calcein release were obtained for each composition indicated in Fig. 2 and results are shown as the open squares in Fig. 3. In all lipid compositions the average diameter was 186 ± 18 nm. The test samples were repeatedly exposed to LFUS in 30 s bursts with 3 min rest cycles, release was recorded and fraction-of-release was calculated as stated in Section 2.3. Release kinetics reveal a strong correlation with membrane phase behavior-consistent with the phase map-and gives insight to the different leakage mechanisms; the latter is explored in Section 4.0. Release profiles in all samples resembled a first order process, with a rapid initial rise, reaching at least 80% of maximum release after 180 s of LFUS exposure, and then leveling off. This agreed with release profiles obtained by [29,30] and [48]. In general, samples with more cholesterol exhibited a slower release: for example, an average fraction of release at 180 s of 0.65 ± 0.05 was observed in lO

E.F. Small et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 390 (2011) 40–47

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Fig. 1. “Release map” of DOPC/DPPC/Cholesterol system. Color bar indicates fraction of release after 180 s of continuous wave 20 kHz ultrasound. Each data point is the average of three samples; error bars not shown. Fluorescence was measured at ex. 488 nm, em. peak 521 ± 3 nm. Fraction of release was based on 100% = intensity after 10 ␮l of Triton X-100, undiluted, added to destroy all vesicles. Two phase region redrawn from Buboltz et al. [44].

samples versus 0.76 ± 0.06 in ld samples. More specifically, lO samples exhibited an average initial slope in fraction-of-release versus time of 0.61 ± 0.05% per second, half the value observed in ld samples (1.4 ± 0.4% per second). Thus both extent and kinetics of release are highly sensitive to membrane phase behavior. 4. Modeling membrane phase behavior-dependent LFUS-induced drug release 4.1. Diffusion only model Another key goal of this study was to develop a predictive model that accurately describes release in terms of membrane phase parameters and potentially sheds light on the release mechanisms.

This is because existing ultrasound-induced liposome release models do not account for membrane phase behavior. In the absence of ultrasound, transport across a membrane is effectively zero for large water-soluble molecules, such as calcein, on a time scale of 500 min (i.e. the experimental time scale herein). In the presence of ultrasound release occurs over a time scale of minutes, signifying membrane permeability [1,8,29]. Although previous work by this lab [29], and supporting experimental and simulation evidence by others [1,8,32,48,49], suggests that release is achieved via diffusion through transient pores formed in the membrane, the existence of transient pores remains an open question. Our model is thus not dependent on pore formation. Rather, membrane permeability is quantified by a permeability, P, which is the product of diffusivity and partition coefficient and would account for-but does not require-any putative pore formation. For this model, an encapsulated model drug (calcein dye) is released solely via diffusion through the membrane. Both aqueous compartments (internal and external to the liposome) are well mixed. The system is schematically depicted in Fig. 4. The equation of continuity in a (spherical) liposomal bilayer, with no convective terms, gives a well known, time-dependent diffusion model for calcein transport through the membrane of lipid vesicles: ∂C D ∂ = 2 ∂t r ∂r



r

2 ∂C



(1)

∂r

Initial and boundary conditions are: C(RI , 0) = CO

Fig. 2. DOPC/DPPC/Cholesterol system used in kinetic study. Open circles indicate sample compositions studied and modeled in this paper. Tie-lines shown in solid black are referred to in the text as “L” the lower line, “M” the middle, and “U” the upper line. Composition trajectory lines shown in dashed black are extensions of tie-lines beyond the two phase region. Tie-lines redrawn from Veatch et al. [43], two phase region redrawn from Buboltz et al. [44].

C(RI , t) = KCI

C(RO , t) = KCE

where C is the concentration of calcein in the membrane. CI , CE , RI , and RO are radii as defined in Fig. 4, where the subscript I denotes “internal to liposome” and the subscript E denotes “external to the liposome.” CO is the initial concentration of dye in the liposome, K is the partition coefficient, and RO is the outer vesicle radius. A lumped parameter model defines the time dependent concentration in each compartment (internal “I” and external “E”). dCI = dt



−4DK 1/RI − 1/Ro



(CI − CE ) VI

(2)

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E.F. Small et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 390 (2011) 40–47

Fig. 3. LFUS release profiles of calcein, inset from Fig. 2. 䊉 denotes actual samples. Y axis is fraction of release (NE (t)/NO ), X axis is sonication time (s). Note that left column (panels A, D, G) correspond to the lower tie-line/composition trajectory line. The center column (panels B, E, H) correspond to the middle tie-line/composition trajectory line, and the right column (panels C, F, I) correspond to the upper tie-line/composition trajectory line. The top row (panels A–C) are all ld , the middle row (panels D–F) are 2˚ and fit of solution to Eqs. (2) and (3), and time derivative of (6), diffusion the bottom (panels G–I) are lO .  Experimental data, - - - - fit of Eq. (5), 1st order diffusion model. plus destruction model.

dCE = dt



4DK 1/RI − 1/Ro



(CI − CE ) VO

(3)

where D is diffusivity, V is volume with subscripts having the same meaning as above. As stated above, membrane permeability during LFUS exposure might be the result of transient pore formation, which would decrease the surface area for transport to just a fraction of the vesicle surface area [29,50]. Such a phenomenon, if it were to happen, is accounted for in the model by the parameter, K, partition coefficient. The known solution for Eq. (1) is obtained by subtracting the integrated forms Eqs. (2) and (3):

 CI (t) − CE (t) = CO exp



−DK4 1/RI − 1/RO



1

1 + VI VE



·t

(4)

Measurements from steady state fluorescence spectroscopy are interpreted in terms of fraction of release (NE /NO ) as a function of time, where N is the moles of calcein with subscripts having the same meaning as above. Thus, Eq. (4) is recast in moles instead of concentration. A material balance NO = NE (t) + NI (t) eliminates NI (t). Furthermore, VE is eliminated since VO = VI + VE . As VO is the sample volume and VI is the total volume encapsulated by all vesicles, VO »VI (3 mL versus 6 ␮l) such that VO − VI ≈ VO . Finally, combining DK into a single term P (permeability, with units of cm2 /s) gives a model for diffusion:



NE (t) = 1 − exp NO



−P4

VI 1/RI − 1/RO



 ·t

(5)

Dashed lines in Fig. 3 show best fits of Eq. (5) to selected samples. From each tie-line, one two-phase (2˚) sample (Fig. 3D–F) is shown. From each composition trajectory line one ld sample (Fig. 3A–C), and one lO sample (Fig. 3G–I) are shown. Comparison of the best fit with experimental data (open squares) reveals that a diffusion-only model does not properly describe release in samples containing ld phase. In single phase ld and 2˚ samples the model under-predicts release at early times and over-predicts at late times. Conversely, the diffusion only model provides a reasonable fit in the lO samples. 4.2. Evidence of destruction

Fig. 4. Schematic of diffusion through a lipid bilayer in the radial direction. RI and RO are inner and outer membrane radius, and K is membrane partition coefficient, membrane thickness, h, is 3.6 nm [56,57].

Building on previous work by [5,48] DLS measurements were made on select ld , lO and 2˚ samples to test for ultrasound-induced

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destruction to the initial diffusion model for the liquid-disordered and two phase samples is accounted for in a time-dependent change in VI : VI (t) = V1vesicle M(t)

(6)

M(t) = MO (1 − ω) + ωe−ˇt

(7)

where V1vesicle is the volume of a single vesicle and MO is the initial number of vesicles contained in the sample. Both depend upon the membrane composition since cholesterol does not contribute to vesicle surface area [52]. ω is the fraction of sample in the ld phase as calculated via the reverse lever rule from published phase boundaries [44] and tie-lines [43]. Remarkably, because it is not fit but is pre-determined by phase behavior, ω is tantamount to a weighting factor that quantifies how much destruction occurs. That is, when ω is zero no destruction occurs, and destruction grows in proportion to the amount of ld phase. It is important to note that the dimensions of individual vesicles remain constant, and the decrease in VI (t) is solely due to reduction in the number of vesicles in the sample. Accounting for destruction by simultaneously solving Eqs. (2) and (3), and the time derivative (6), given experimental initial conditions (refer to Section 4.1), and normalizing CE (t) over its theoretical maximum allowed P and ˇ to be fit to the experimental fraction of release profiles. Results of such fits are shown in Fig. 3, where the solid line is the solution to Eqs. (2) and (3), and the time derivative of (6). Fig. 5. Normalized average count rate (A) and effective diameter (B) from dynamic light scattering as a function of LFUS time (s). Open markers indicate liquid dis); solid markers indicate liquid ordered ordered samples (L1, M1, U1, U4 samples (L9, M5 , M9, U9䊉).

destruction as described in Section 2.4. During the 360 s of ultrasound exposure the light scattering intensity of ld samples was nearly halved (Fig. 5A). Less decrease was seen in 2˚ samples, and negligible change was observed in lO samples. Given that light scattering intensity is proportional to the sixth power of diameter and directly proportional to the number of scatterers [51], decrease in intensity indicates small or fewer liposomes, or both. Accordingly, size was also measured (Fig. 5B). Effective diameter of ld samples actually increased, while lO samples remained largely unaffected. This increase in size, concomitant with a decrease in scattering intensity, suggests the formation of fewer but larger structures. We interpret these results to mean that vesicles in the liquid-disordered samples are destroyed by ultrasound (halving of scattering intensity) and that resulting lipid debris produced the large aggregates owing to the hydrophobic effect. Enden and Schroeder [50] used turbidity to track destruction as a function of ultrasonic exposure time and then fit that data to develop a model for vesicle destruction. Working with multiple lipid compositions prevents the use turbidity as a measure of destruction, because absorbance will inherently change with the changing mole fraction of phosphatidylcholine in the sample. Light scattering intensity is dependent on both the number and diameter of scatters, thus it cannot be used directly of a measure of vesicle concentration [51]. The DLS data shown in Fig. 5 emphasize the membrane chemistry dependence of vesicle destruction, and indicate that destruction might correlate with phase behavior. To test this possibility a destruction term was added to the diffusion model and the dependence of destruction on composition was quantified as described below. 4.3. Addition of destruction to the diffusion model We treat destruction of liquid-disordered vesicles as a first order process with rate constant, ˇ (1/s). Thus the addition of

4.4. Diffusion plus destruction model In the case of liquid-disordered samples (Fig. 3A–C) addition of the destruction term improved the fit considerably, increasing R2 values from as low as 0.793 to as high as 0.985. Substantial improvement in the fits of the 2˚ samples is also seen (Fig. 3D–F), and in both cases the systematic error of the model is effectively eliminated. In the case of liquid-ordered samples, no difference between the two models is observed (Fig. 3G–I), as is expected given that ω is zero for lO samples in the diffusion/destruction model. Values returned for P and ˇ are listed in Table 1, along with coefficient of determination (R2 ) for each fit. The fraction of destruction (%d) listed in Table 1 was calculated for each sample by a simple rearrangement of Eq. (7); subtracting the fraction of vesicles at time 360 from 1 (%d = 1− M(360)/MO ). Comparison of the R2 values between the two models further exemplifies the improvement of fits when destruction is added to the diffusion model. Focusing on the diffusion/destruction model, there is a clear decrease in permeability as the sample becomes more liquidordered. Consequently the mole fraction of cholesterol increases. However, if the decrease in permeability were simply correlated with increased cholesterol, the permeabilities of a given cholesterol mole fraction should be similar. This is not the case. Samples C2 and T1 both have 10% cholesterol, yet their permeabilities vary by 6.6 × 10−3 cm2 /s. Further examples are B5 and T3 at 16% cholesterol – 6.0 × 10−3 , C5 and T4 at 20% cholesterol – 2.3 × 10−3 , B9 and T7 at 32% cholesterol – 5.38 × 10−3 . Analyzing permeability variations along phase behavior splits gives a variation of 2.2 × 10−2 cm2 /s over a range of 14% cholesterol for liquiddisordered samples (B, C, and T points 1 and 2). The liquid-ordered samples (B, C, T points 8 and 9) exhibit only 3.3 × 10−3 cm2 /s over a range of 9% cholesterol. While the variation in ld samples is only slightly more than twice the variation within a single cholesterol mole fraction, the variation in lO samples is smaller than the majority of single cholesterol variations. This evidence suggests that permeability correlates more strongly with phase behavior than cholesterol mole fraction, and that cholesterol composition has a stronger influence in the ld phase than in the lO phase.

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Table 1 Permeability (P in cm2 /s), rate of destruction (ˇ in 1/s), fraction of vesicles destroyed (%d), and coefficient of determination (R2 ) for 1st order diffusion model (Eq. (5)) and diffusion plus destruction model (solution to Eqs. (2) and (3), and time derivative of (6). %d = 1− M(360)/MO (rearrangement of Eq. (7)). Tie line

Sample

1◦ Diffusion

Diffusion and destruction

Pa

R2

Pa

ˇb

%dc

R2

L

1 ld 2 ld 3 Boundary 4 2˚ 5 2˚ 6 2˚ 7 Boundary 8 lO 9 lO

2.70E − 02 1.59E − 02 1.75E − 02 1.78E − 02 1.79E − 02 2.01E − 02 1.17E − 02 1.03E − 02 7.92E − 03

0.939 0.956 0.945 0.910 0.964 0.970 0.980 0.982 0.990

3.34E − 02 1.93E − 02 2.15E − 02 2.37E − 02 2.12E − 02 2.33E − 02 1.17E − 02 1.03E − 02 7.92E − 03

2.08E − 03 2.38E − 03 2.18E − 03 3.75E − 03 3.40E − 03 7.96E − 03 0.00E + 00 0.00E + 00 0.00E + 00

0.53 0.58 0.54 0.59 0.39 0.23 0.00 0.00 0.00

0.989 0.994 0.995 0.990 0.996 0.996 0.980 0.982 0.990

M

1 ld 2 ld 3 Boundary 4 2˚ 5 2˚ 6 2˚ 7 Boundary 8 lO 9 lO

2.63E − 02 2.11E − 02 2.04E − 02 2.03E − 02 1.81E − 02 2.10E − 02 1.74E − 02 8.92E − 03 8.29E − 03

0.793 0.878 0.905 0.922 0.968 0.979 0.967 0.958 0.968

4.12E − 02 2.93E − 02 2.72E − 02 2.59E − 02 2.12E − 02 2.10E − 02 1.74E − 02 8.92E − 03 8.29E − 03

4.40E − 03 3.24E − 03 2.83E − 03 3.34E − 03 3.42E − 03 7.96E − 13 0.00E + 00 0.00E + 00 0.00E + 00

0.79 0.69 0.64 0.53 0.36 0.00 0.00 0.00 0.00

0.985 0.990 0.992 0.989 0.995 0.979 0.967 0.958 0.968

U

1 ld 2 ld 3 Boundary 4 2˚ 5 2˚ 6 2˚ 7 Boundary 8 lO 9 lO

1.88E − 02 1.69E − 02 1.25E − 02 1.44E − 02 9.01E − 03 1.20E − 02 1.33E − 02 1.09E − 02 7.64E − 03

0.948 0.959 0.955 0.919 0.862 0.978 0.973 0.959 0.971

2.27E − 02 2.00E − 02 1.52E − 02 1.89E − 02 1.39E − 02 1.40E − 02 1.33E − 02 1.09E − 02 7.64E − 03

2.01E − 03 1.79E − 03 2.43E − 03 4.16E − 03 2.18E − 02 1.62E − 01 0.00E + 00 0.00E + 00 0.00E + 00

0.51 0.48 0.58 0.57 0.44 0.09 0.00 0.00 0.00

0.991 0.988 0.993 0.991 0.993 0.993 0.973 0.959 0.971

a b c

P in cm2 /s. ˇ in 1/s. Fraction of vesicles destroyed. %d = 1 − M(360)/MO (Eq. (7)).

The rate of destruction (ˇ) remains generally stable in the purely ld domain. In the 2˚ region the rate of destruction steadily increases, but its contribution to overall leakage decreases as the sample becomes more liquid-ordered. An important exception is found at point T6, where the model forces ˇ to nearly zero. In this instance the model finds the best fit by attempting to treat this sample as purely lO . Using ˇ and ω to calculate the fraction of leakage due to destruction, a trend of decreased destruction with increasing liquid-ordered phase is seen (Table 1, column 7, “%d”). For completeness, all P and ˇ results are given in Table 1. In Ref. [50], using 0.51:0.05:0.44 HSPC:PEG2000-DSPE:Chol, the fraction of drug release due to vesicle destruction is shown to be around 20%. Our diffusion/destruction model revealed that samples with 20% of leakage due to destruction only contain around 20% cholesterol. This disagreement between our study and [50] serves to emphasize work by [29,32]; addition of PEGylated lipids has a much stronger effect in increasing release than cholesterol has in reducing release. 4.5. Contribution of membrane thickness to phase behavior influence Diffusion across a membrane also depends on membrane thickness. This raises the question as to what extent the P values obtained herein tem from changes in the membrane associated with the cholesterol-induced condensation effect (reviewed in Section 1.0). Gandhavadi et al., Pandit et al., and Rinia et al. reported an increase in membrane thickness of about 9 A˚ (25% increase) from liquid-disordered to liquid-ordered [53–55]. Given that the models presented in Sections 4.1 and 4.3 use a single membrane thickness of 3.6 nm [56,57] for all sample compositions one might expect lO ·P values to be just 80% (i.e. 1/1.25) of the ld ·P values if membrane thickness is the sole factor accounting for differences in release.

However, P values for lO samples in composition trajectory line L averaged 34.5% of the ld values (calculated from P values in Table 1). In composition trajectory lines M and U, lO permeabilities averaged 24.4% and 43.4%, respectively, of ld values. Thus, the contribution of membrane thickness to the overall influence of phase behavior on permeability is minor. 5. Summary The relationship between membrane composition and ultrasound-induced transport across lipid membranes is systematically studied and quantified. A mathematical model is presented that accounts for phase behavior. The model offers description of the mechanisms at work in LFUS-induced release in agreement with a previous model present by [50]. It also provides insight into the influence of lipid phase behavior over membrane response to ultrasound. As membrane phase changes toward liquid-ordered, it becomes resistant to destruction and the rate of diffusion decreases. Phase behavior has a stronger influence on membrane permeability and destruction potential than cholesterol mole fraction. The variation in permeabilities within a single phase, spread over range of 9% cholesterol, is roughly half of the difference between premeabilities of two phases that share the same cholesterol mole faction. However, cholesterol is not without influence as it partially determines phase behavior. Cholesterol has a stronger influence in the ld domain, i.e., a 50% larger range in cholesterol mole fraction produces 6.7 fold increase in permeability variance when compared to the lO domain. The increase in membrane thickness between ld and lO phases cannot account for the observed decrease in permeability, thus influence of phase behavior on permeability is more complex than simple membrane thickness.

E.F. Small et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 390 (2011) 40–47

Acknowledgments The authors would like to thank Chris Bawiec for measurement of ultrasound field parameters, Dr. Andrzej Nowicki for valuable discussions on ultrasound dynamics and cavitation, and Dr. Yossef Elabd for discussions on diffusion. The authors would also like to thank the anonymous reviewer whose comprehensive and constructive comments were instrumental in refining this manuscript to its final form. This work was supported in part by the National Science Foundation (CTS-0346638 and DGE-0947936).

References [1] A. Schroeder, J. Kost, Y. Barenholz, Ultrasound, liposomes, and drug delivery: principles for using ultrasound to control the release of drugs from liposomes, Chem. Phys. Lipids 162 (2009) 1–16. [2] T.P. McCreery, R.H. Sweitzer, E.C. Unger, DNA delivery to cells in culture using ultrasound, Methods Mol. Biol. 245 (2004) 287–292. [3] R.K. Schlicher, H. Radhakrishna, T.P. Tolentino, R.P. Apkarian, V. Zarnitsyn, M.R. Prausnitz, Mechanism of intracellular delivery by acoustic cavitation, Ultrasound Med. Biol. 32 (2006) 915–924. [4] R. Suzuki, T. Takizawa, Y. Negishi, N. Utoguchi, K. Maruyama, Effective gene delivery with novel liposomal bubbles and ultrasonic destruction technology, Int. J. Pharm. 354 (2008) 49–55. [5] A. Schroeder, R. Honen, K. Turjeman, A. Gabizon, J. Kost, Y. Barenholz, Ultrasound triggered release of cisplatin from liposomes in murine tumors, J. Controlled Release 137 (2009) 63–68. [6] S. Mitragotri, D. Blankschtein, R. Langer, Transdermal drug delivery using lowfrequency sonophoresis, Pharm. Res. 13 (1996) 411–420. [7] S. Mitragotri, J. Kost, Low-frequency sonophoresis: a review, Adv. Drug Delivery Rev. 56 (2004) 589–601. [8] D.L. Miller, S.V. Pislaru, J.E. Greenleaf, Sonoporation: mechanical DNA delivery by ultrasonic cavitation, Somat. Cell Mol. Genet. 27 (2002) 115–134. [9] W.L. Nyborg, Biological effects of ultrasound: development of safety guidelines. Part II: general review, Ultrasound Med. Biol. 27 (2001) 301–333. [10] D.M. Hallow, A.D. Mahajan, T.E. McCutchen, M.R. Prausnitz, Measurement and correlation of acoustic cavitation with cellular bioeffects, Ultrasound Med. Biol. 32 (2006) 1111–1122. [11] P. Prentice, A. Cuschieri, K. Dholakia, M. Prausnitz, P. Campbell, Membrane disruption by optically controlled microbubble cavitation, Nat. Phys. 1 (2005) 107–110. [12] P. Marmottant, S. Hilgenfeldt, Controlled vesicle deformation and lysis by single oscillating bubbles, Nature 423 (2003) 153–156. [13] A. van Wamel, K. Kooiman, M. Harteveld, M. Emmer, F.J. ten Cate, M. Versluis, N. de Jong, Vibrating microbubbles poking individual cells: drug transfer into cells via sonoporation, J. Controlled Release 112 (2006) 149–155. [14] J. Wu, J.P. Ross, J.F. Chiu, Reparable sonoporation generated by microstreaming, J. Acoust. Soc. Am. 111 (2002) 1460–1464. [15] S.A. Akimov, P.I. Kuzmin, J. Zimmerberg, F.S. Cohen, Y.A. Chizmadzhev, An elastic theory for line tension at a boundary separating two lipid monolayer regions of different thickness, J. Electroanal. Chem. 564 (2004) 13–18. [16] P.F. Almeida, Thermodynamics of lipid interactions in complex bilayers, Biochim. Biophys. Acta 1788 (2009) 72–85. [17] S.L. Veatch, S.L. Keller, Organization in lipid membranes containing cholesterol, Phys. Rev. Lett. 89 (2002) 268101. [18] S.L. Veatch, S.L. Keller, Separation of liquid phases in giant vesicles of ternary mixtures of phospholipids and cholesterol, Biophys. J. 85 (2003) 3074–3083. [19] S.L. Veatch, S.L. Keller, Seeing spots: complex phase behavior in simple membranes, Biochim. Biophys. Acta 1746 (2005) 172–185. [20] K. Gong, S.-S. Feng, M.L. Go, P.H. Soew, Effects of pH on the stability and compressibility of DPPC/cholesterol monolayers at the air-water interface, Colloids Surf. A: Physicochem. Eng. Aspects 207 (2002) 113–125. [21] D.-Z. Liu, W.-Y. Chen, L.-M. Tasi, S.-P. Yang, Microcalorimetric and shear studies on the effects of cholesterol on the physical stability of lipid vesicles, Colloids Surf. A: Physicochem. Eng. Aspects 172 (2000) 57–67. [22] W. Rawicz, K.C. Olbrich, T. McIntosh, D. Needham, E. Evans, Effect of chain length and unsaturation on elasticity of lipid bilayers, Biophys. J. 79 (2000) 328–339. [23] W. Rawicz, B.A. Smith, T.J. McIntosh, S.A. Simon, E. Evans, Elasticity, strength, and water permeability of bilayers that contain raft microdomain-forming lipids, Biophys. J. 94 (2008) 4725–4736. [24] K.W. Ferrara, M.A. Borden, H. Zhang, Lipid-shelled vehicles: engineering for ultrasound molecular imaging and drug delivery, Acc. Chem. Res. 42 (2009) 881–892. [25] M.A. Borden, D.E. Kruse, C.F. Caskey, S. Zhao, P.A. Dayton, K.W. Ferrara, Influence of lipid shell physicochemical properties on ultrasound-induced microbubble destruction, IEEE Trans. Ultrason. Ferroelectr. Freq. Control 52 (2005) 1992–2002. [26] M.A. Borden, G. Pu, G.J. Runner, M.L. Longo, Surface phase behavior and microstructure of lipid/PEG-emulsifier monolayer-coated microbubbles, Colloids Surf. B: Biointerfaces 35 (2004) 209–223.

47

[27] S.P. Wrenn, M. Mleczko, G. Schmitz, Phospholipid-stabilized microbubbles: influence of shell chemistry on cavitation threshold and binding to giant unilamellar vesicles, Appl. Acoust. 70 (2009) 1313–1322. [28] S. Dicker, M. Mleczko, G. Schmitz, S.P. Wrenn, Determination of microbubble cavitation threshold pressure as function of shell chemistry, Eng. Technol. 2 (2010) 55–64 (Bubble Science). [29] M. Pong, S. Umchid, A.J. Guarino, P.A. Lewin, J. Litniewski, A. Nowicki, S.P. Wrenn, In vitro ultrasound-mediated leakage from phospholipid vesicles, Ultrasonics 45 (2006) 133–145. [30] T.J. Evjen, E.A. Nilssen, S. Rögnvaldsson, M. Brandl, S.L. Fossheim, Distearoylphosphatidylethanolamine-based liposomes for ultrasoundmediated drug delivery, Eur. J. Pharm. Biopharm. 75 (2010) 327–333. [31] H.Y. Lin, J.L. Thomas, Factors affecting responsivity of unilamellar liposomes to 20 kHz ultrasound, Langmuir 20 (2004) 6100–6106. [32] H.Y. Lin, J.L. Thomas, PEG-Lipids and oligo(ethylene glycol) surfactants enhance the ultrasonic permeabilizability of liposomes, Langmuir 19 (2003) 1098–1105. [33] S.L. Huang, R.C. MacDonald, Acoustically active liposomes for drug encapsulation and ultrasound-triggered release, Biochim. Biophys. Acta 1665 (2004) 134–141. [34] D. Needham, R.S. Nunn, Elastic deformation and failure of lipid bilayer membranes containing cholesterol, Biophys. J. 58 (1990) 997–1009. [35] J.M. Smaby, V.S. Kulkarni, M. Momsen, R.E. Brown, The interfacial elastic packing interactions of galactosylceramides, sphingomyelins, and phosphatidylcholines, Biophys. J. 70 (1996) 868–877. [36] D.A. Brown, E. London, Structure of detergent-resistant membrane domains: does phase separation occur in biological membranes? Biochem. Biophys. Res. Commun. 240 (1997) 1–7. [37] E. London, D.A. Brown, Insolubility of lipids in triton X-100: physical origin and relationship to sphingolipid/cholesterol membrane domains (rafts), Biochim. Biophys. Acta 1508 (2000) 182–195. [38] A. de Gassart, C. Geminard, B. Fevrier, G. Raposo, M. Vidal, Lipid raft-associated protein sorting in exosomes, Blood 102 (2003) 4336–4344. [39] K. Fiedler, T. Kobayashi, T.V. Kurzchalia, K. Simons, Glycosphingolipid-enriched, detergent-insoluble complexes in protein sorting in epithelial cells, Biochemistry 32 (1993) 6365–6373. [40] K. Simons, E. Ikonen, Functional rafts in cell membranes, Nature 387 (1997) 569–572. [41] E. Khazanov, A. Priev, J.P. Shillemans, Y. Barenholz, Physicochemical and biological characterization of ceramide-containing liposomes: paving the way to ceramide therapeutic application, Langmuir 24 (2008) 6965–6980. [42] O. Tirosh, Y. Barenholz, J. Katzhendler, A. Priev, Hydration of polyethylene glycol-grafted liposomes, Biophys. J. 74 (1998) 1371–1379. [43] S.L. Veatch, O. Soubias, S.L. Keller, K. Gawrisch, Critical fluctuations in domain-forming lipid mixtures, Proc. Natl. Acad. Sci. U.S.A. 104 (2007) 17650–17655. [44] J.T. Buboltz, C. Bwalya, K. Williams, M. Schutzer, High-resolution mapping of phase behavior in a ternary lipid mixture: do lipid-raft phase boundaries depend on the sample preparation procedure? Langmuir 23 (2007) 11968–11971. [45] J.T. Buboltz, G.W. Feigenson, A novel strategy for the preparation of liposomes: rapid solvent exchange, Biochim. Biophys. Acta 1417 (1999) 232–245. [46] M. Hara, Y. Yamano, Y. Sakai, E. Kodama, T. Hoshino, M. Ito, J. Miyake, Stabilization of liposomal membranes by carotenoids: zeaxanthin, zeaxanthin glucoside and thermozeaxanthin, Mater. Sci. Eng. C 28 (2008) 274–279. [47] J.A. Kopechek, T.M. Abruzzo, B. Wang, S.M. Chrzanowski, D.A. Smith, P.H. Kee, S. Huang, J.H. Collier, D.D. McPherson, C.K. Holland, Ultrasound-mediated release of hydrophilic and lipophilic agents from echogenic liposomes, J. Ultrasound Med. 27 (2008) 1597–1606. [48] A. Schroeder, Y. Avnir, S. Weisman, Y. Najajreh, A. Gabizon, Y. Talmon, J. Kost, Y. Barenholz, Controlling liposomal drug release with low frequency ultrasound: mechanism and feasibility, Langmuir 23 (2007) 4019–4025. [49] B. Krasovitski, V. Frenkel, S. Shoham, E. Kimmel, Intramembrane cavitation as a unifying mechanism for ultrasound-induced bioeffects, Proc. Natl. Acad. Sci. U.S.A. 108 (2011) 3258–3263. [50] G. Enden, A. Schroeder, A mathematical model of drug release from liposomes by low frequency ultrasound, Ann. Biomed. Eng. 37 (2009) 2640–2645. [51] C.S. Johnson, D.A. Gabriel, Laser Light Scattering, Dover Publications, 1995. [52] J. Huang, G.W. Feigenson, A microscopic interaction model of maximum solubility of cholesterol in lipid bilayers, Biophys. J. 76 (1999) 2142–2157. [53] M. Gandhavadi, D. Allende, A. Vidal, S.A. Simon, T.J. McIntosh, Structure, composition, and peptide binding properties of detergent soluble bilayers and detergent resistant rafts, Biophys. J. 82 (2002) 1469–1482. [54] S.A. Pandit, S. Vasudevan, S.W. Chiu, R. Jay Mashl, E. Jakobsson, H.L. Scott, Sphingomyelin-cholesterol domains in phospholipid membranes: atomistic simulation, Biophys. J. 87 (2004) 1092–1100. [55] H.A. Rinia, M.M. Snel, J.P. van der Eerden, B. de Kruijff, Visualizing detergent resistant domains in model membranes with atomic force microscopy, FEBS Lett. 501 (2001) 92–96. [56] A.C. Brown, K.B. Towles, S.P. Wrenn, Measuring raft size as a function of membrane composition in PC-based systems: Part 1 – binary systems, Langmuir 23 (2007) 11180–11187. [57] Z.V. Leonenko, E. Finot, H. Ma, T.E.S. Dahms, D.T. Cramb, Investigation of temperature-induced phase transitions in DOPC and DPPC phospholipid bilayers using temperature-controlled scanning force microscopy, Biophys. J. 86 (2004) 3783–3793.