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Biomimetics 2018, 3(1), 4; doi:10.3390/biomimetics3010004

Targeting Early Dementia: Using Lipid Cubic Phase Nanocarriers to Cross the Blood–Brain Barrier
Cavitation-Control Technology Inc., Farmington, CT 06032, USA
Current Address: Cav-Con Inc., Bellevue, WA 98007, USA.
Received: 22 January 2018 / Accepted: 6 March 2018 / Published: 7 March 2018


Over the past decades, a frequent co-morbidity of cerebrovascular pathology and Alzheimer’s disease has been observed. Numerous published studies indicate that the preservation of a healthy cerebrovascular endothelium can be an important therapeutic target. By incorporating the appropriate drug(s) into biomimetic (lipid cubic phase) nanocarriers, one obtains a multitasking combination therapeutic, which targets certain cell surface scavenger receptors, mainly class B type I (i.e., SR-BI), and crosses the blood–brain barrier. This targeting allows for various cell types related to Alzheimer’s to be simultaneously searched out for localized drug treatment in vivo.
Alzheimer’s disease; biomimetic nanocarriers; blood–brain barrier; dementia; drug targeting; lipid cubic phase; nanoemulsion; SR-BI; scavenger receptors

1. Introduction

The fundamental involvement of the cerebrovasculature in the pathogenesis of common dementias, widely reported in the biomedical literature, has recently been reviewed (e.g., [1,2]). Small vessel disease is commonly found in patients who have other brain pathologies, such as plaques and tangles associated with neurodegenerative diseases; small vessel disease also increases the risk of Alzheimer’s disease. Accordingly, vascular cognitive impairment and dementia (VCID) is the second leading cause of dementia, behind Alzheimer’s disease, and is a frequent co-morbidity in Alzheimer’s patients [3,4,5,6,7,8,9]. On a worldwide basis, 47 million people had dementia in 2016; of these dementia patients, 60–80% had Alzheimer’s disease [4,10,11].

2. Central Role of Endothelial Dysfunction

It has been reported repeatedly that endothelial modulation and repair is feasible by pharmacological targeting [1,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26] via scavenger receptor class B type I (SR-BI) (cf. [25]). As the detailed review by Mahringer et al. [27] points out, the blood–brain barrier (BBB) is equipped with several endocytic receptors at the luminal surface (i.e., the capillary endothelial membrane), including the SR-BI scavenger receptor. Furthermore, very recently published experimental work (in human-endothelial-cell monolayer cultures as well as in three-dimensional tissue-engineered human vessels) has demonstrated in detail that high-density lipoproteins (HDL), acting via scavenger receptors (specifically SR-BI), block β-amyloid uptake into endothelial cells both in experimental monolayers and probably in the intact human cerebrovascular endothelium [28] (cf. [29,30,31]).
Almer et al. [14] explain in their recent review that the integration of lipoprotein-related or apolipoprotein-targeted nanoparticles, as drug carriers, is an expanding concept in nanomedicine to exploit the intrinsic characteristics of lipoprotein particles as being the natural transporter of lipophilic compounds in human circulation. Discrete lipoprotein assemblies and lipoprotein-based biomimetics offer a versatile nanoparticle platform for constructing drug loaded, reconstituted or artificial lipoprotein particles for specific medical applications. As naturally occurring nanoassemblies, lipoprotein particles are not readily (nor rapidly) cleared by the mononuclear phagocyte system (of the liver and spleen) and remain in circulation for a longer period of time [14]. More recently, Srimanee et al. [12] further explain that receptor-mediated transcytosis (RMT) at the BBB occurs in three steps: (1) receptor-mediated endocytosis at the luminal (capillary endothelial lining/blood) side via ligands (i.e., lipoprotein-related, apolipoprotein-targeted nanoparticles) binding to specific membrane receptors (e.g., SR-BI); (2) transfer of endocytic vesicles through the cytoplasm; (3) and excytosis of the carried (small-molecule or biomolecular) drug at the abluminal (brain/endothelial) side. Currently, several receptors are known to be expressed on the luminal surface of the BBB, which include scavenger receptors (such as SR-BI) [12]. Particularly, SR-BI was found in bovine and porcine brain capillary endothelial cells (BCEC), and also expressed in murine brain. The rodent SR-BI was studied and showed the same structure/behavior as human SR-BI [12,13]. With regard to their own experimental work, Srimanee et al. [12] report that SR-BI are also involved (among several receptor types studied by their group) in the uptake of nanocomplexes into brain endothelial cells, and also mediate the transport of nanocomplexes across their BBB model. Moreover, other published studies have shown that lipophilic compounds bound to HDL (and probably to “HDL-like” nanoparticles as well) have the possibility to be internalized by a “piggy-back”-like mechanism [13]. It was shown that uptake of HDL-associated α-tocopherol by porcine BCEC via SR-BI exceeded the uptake of HDL particles up to 13-fold, suggesting a selective uptake of this compound without the concomitant internalization of the lipoprotein (HDL) particle. Additional work has demonstrated apolipoprotein (apo) A-I expression in porcine brain capillaries [13]. Further research indicated that apoA-I, the major protein component of HDL, was effluxed by porcine BCEC (whereas the aortic endothelium did not efflux any detectable amount of apoA-I). ApoA-I-inducing compounds, such as cholesterol, could upregulate apoA-I in BCEC. These data toegether, suggested that apoA-I is effluxed apparently by the SR-BI receptor in porcine BCEC [13]. Moreover, Fung et al. [32] separately reported that SR-BI mediates the uptake and transcytosis of HDL across brain microvascular endothelial cells (i.e., across the blood–brain barrier). The authors assert that elucidating the mechanisms of HDL transcytosis across the BBB, in particular, may be pathologically significant, as its constituent apoA-I has been demonstrated to confer a protective effect against Alzheimer’s disease. Using a combination of spinning-disc confocal and total internal reflection fluorescence microscopy, these authors examined the internalization and transcytosis of fluorescently labeled HDL by human primary brain microvascular endothelial cell monolayers. Using these approaches, these investigators reported that HDL internalization requires dynamin, but not clathrin heavy chain, and that its internalization and transcytosis are saturable. The authors concluded that these (and other reported) findings indicate that HDL transcytosis across the BBB involves a signaling pathway downstream of SR-BI. These investigators further argue that manipulation of HDL transcytosis across the BBB to increase delivery of plasma apoA-I may, in turn, facilitate increasing the transport of “HDL-like synthetic particles” containing therapeutic drugs across the BBB to treat neurodegenerative disorders such as Alzheimer’s disease [32] (cf. [28,33,34,35,36,37,38,39,40,41,42]).

3. Targeted Drug Treatment for Early Dementia

This targeted drug delivery approach, using an apoA-I-based (SR-BI-mediated) therapeutic agent for treating the more common (late-onset) dementias, receives added impetus from continued findings of cerebrovascular pathology [1,43,44,45,46,47,48,49,50,51,52,53] and an apparent endothelium dysfunction [2,33,34,35,36,37,38,39,40,41,49,54,55,56,57,58,59,60] in both Alzheimer’s disease and its major risk factors [1,2,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72]. By incorporating drug candidates (such as Edaravone, docosahexaenoic acid (DHA), or antibody therapeutics) into the “lipid-coated microbubble/nanoparticle-derived” (LCM/ND) lipid nanoemulsion type (yielding particle sizes mostly <0.1 μm in diameter), known to be a successful drug carrier [73,74], one is likely to obtain a multitasking combination therapeutic capable of targeting cell surface SR-BI. This combination therapeutic would make it possible for various cell types, all potentially implicated in Alzheimer’s disease (cf. [71,72]), to be simultaneously sought out and better reached for localized drug treatment of brain tissue in vivo.
With regard to receptor-mediated membrane transport across the BBB, brain microvascular endothelial cells are believed to control iron uptake and efflux, under the direct guidance of neighboring astrocytes [75,76]. Detailed evidence has been reported recently [75] showing that human brain microvascular endothelial cells, which constitute most of the BBB, receive brain iron status information via paracrine signals from ensheathing astrocytes. Lastly, aging, obesity, and smoking are determinants of brain iron accumulation in human subjects [77] and all have been shown to be associated with the long-term incidence of Alzheimer’s disease [25,50,51,52,54,55,65,78,79,80].
Note that the above-mentioned association of both obesity and diabetes with incidence of Alzheimer’s disease has also renewed the interest in the main facilitative glucose transporter protein in the brain, GLUT-1, and its involvement in and probable contribution to neurodegenerative diseases [81,82,83]. More than two decades ago, it was already recognized that the normal human brain capillary endothelial cells have a high density of GLUT-1, whereas the cerebral microvessels in subjects with Alzheimer’s disease showed a markedly decreased in GLUT-1 density when compared with age-matched controls [84,85]. More recently, Winkler et al. [86] demonstrated that GLUT-1 deficiency in the cerebral endothelium (but not in astrocytes) initiates BBB breakdown in a mouse model of Alzheimer’s disease. These authors observed from their detailed experiments that reduced GLUT-1 expression (at the BBB) worsens Alzheimer’s disease cerebrovascular degeneration, neuropathology, and cognitive function—suggesting that (cerebral endothelial) GLUT-1 may represent a therapeutic target for Alzheimer’s disease vasculo-neuronal dysfunction and degeneration [86]. Furthermore, other investigators [87] (cf. [88]) have recently provided evidence for brain glucose dysregulation as a critical event in Alzheimer’s disease pathogenesis that closely reflects both the severity of the neuropathology and the expression of symptoms in Alzheimer’s disease. Moreover, abnormalities in brain glucose homeostasis may begin several years before the onset of clinical symptoms [87].
In summary, endothelial cells are the main component of the BBB, which is seriously disrupted in various neurological pathologies, including many neurodegenerative disorders [89,90,91]. An early BBB breakdown and/or dysfunction has been documented in Alzheimer’s disease before dementia, neurodegeneration, and/or brain atrophy occur, and investigators have reported that targeting the BBB can influence the course of such neurological disorder [92]. Hence, vascular-targeted therapies become plausible for the prevention and treatment of common dementias [4,36,89,93,94,95]. In respect of vascular tone, vasodilation (mediated by nitric oxide or acetylcholine) is repressed whereas vasoconstriction (mediated by endothelin-1) is enhanced, thus contributing to endothelial dysfunction in Alzheimer’s disease [90,96]. Also, β-amyloid can induce apoptosis and/or necrosis of brain endothelial cells. Presence of β-amyloid, as well as tau protein oligomers, leads to accumulation of inflammatory molecules in microvessels—which further fosters endothelial dysfunction [90,97,98,99]. Other cell types of the neurovascular unit are affected in Alzheimer’s disease as well [90]. For example, deposition and aggregation of β-amyloid within vascular smooth muscle cells leads to inflammation, oxidative stress, impaired vasorelaxation, and disruption of BBB integrity. At the same time, midlife vascular risk factors such as hypertension, cardiovascular disease, diabetes, dyslipidemia, and obesity all increase the relative risk for Alzheimer’s disease [89,100,101,102,103]. These co-morbidities are all characterized by low and/or dysfunctional HDL, which itself is an Alzheimer’s risk factor. Namely (in addition to the widely reported lipid transport), HDL regulates vascular health via modulating vasorelaxation, inflammation, and oxidative stress as well as promoting endothelial cell survival and integrity [36,102,104]. Since SR-BI has already been identified as a major receptor for HDL (with its major constituent apoA-I) as well as for the earlier-described LCM/ND nanoemulsion [1,2], this multitasking lipid nanoemulsion can arguably serve as a targeted, apoA-I-based, (SR-BI-mediated) therapeutic agent for common (late-onset) dementias (cf. [28,33,35,37,38,39,40,41,42]). In this particular targeted delivery approach, the self-assembled HDL-related “lipid nanoemulsion particle” structure itself (after intravenous injection) likely binds to apoA-I in the blood plasma; subsequently, such apoA-I-targeted LCM/ND nanoemulsion particles are recognized by SR-BI receptors on various Alzheimer’s-related cell types [73].

4. Lipid-Coated Microbubble/Nanoparticle-Derived Nanoemulsion Type Contains Lipid Cubic Phase Nanocarriers

The self-assembled LCM/ND lipid nanoemulsion comprises nonionic lipids exclusively (cf. [105,106]) throughout its coated microbubbles and/or related nanoparticles (i.e., related lipid polymorphs) supramolecular structures(s). This biobased lipid composition of LCM/ND nanoemulsions (i.e., glycerides and cholesterol compounds) is similar to lipids contained in several types of plasma lipoproteins; accordingly, when these LCM/ND nanoemulsion particles are injected into the bloodstream, they likely acquire (i.e., bind) plasma apolipoprotein(s)—including notably apoA-I [73]. Hence, the molecular composition of the LCM/ND nanoemulsion particles results in both microbubble/nanoparticle stability and marked targeting toward tumors and certain hyperproliferative disease lesions/sites; this very rapid targeting has been demonstrated to occur by an active uptake process, i.e., endocytosis—which likely involves certain “lipoprotein receptor”-mediated endocytic pathways [2].
The collection of powdered solid lipid surfactants used to produce LCM/ND lipid nanoemulsions, which is described with all structural details of the molecular components in the published patents covering this technology [105,106], can be outlined as follows:
  • “a member selected from the group consisting of glycerol monoesters of saturated carboxylic acids containing from about 10 to about 18 carbon atoms …;
  • a sterol aromatic ester;
  • a member selected from the group consisting of sterols …;
  • a member selected from the group consisting of sterol esters of aliphatic acids containing from one to about 18 carbon atoms; … and
  • a member selected from the group consisting of glycerol, glycerol di-, or triesters of aliphatic acids containing from about 10 to about 18 carbon atoms …”.
“The surfactant mixture of the present invention can be readily prepared by admixing components a through e in a weight ratio a:b:c:d:e of 2–4:0.5–1.5:0.5–1.5:0–1.5:0–1.5, respectively. Preferably … the components of the surfactant mixture of the present invention are combined in a weight ratio a:b:c:d:e of 2–4:1:1:1:1. Since each of the components of the surfactant mixture of the present invention is a dry powder, the resultant admixture is conveniently obtained in a dry powdered form.” In a particularly preferred form (i.e., “Example 1”) of the invention, the “surfactant mixture was prepared in accordance with the present invention by admixing glycerol monolaurate, cholesterol benzoate, cholesterol, cholesterol acetate, and glycerol tripalmitate in a weight ratio of 3:1:1:1:1, respectively, to obtain a dry powdery surfactant mixture” [105,106].
Importantly, monoglyceride is the largest single-lipid fraction (by wt%) of the powdered solid lipid surfactants used to produce the (Filmix®) LCM/ND nanoemulsions [73]. As a group, monoglycerides exhibit different phase behaviors when they are exposed to water [107] (cf. [108,109]). The ability to exist in several different phases is an important property of pure lipids and lipid mixtures; it depends upon temperature, hydration, and lipid class [107]. Although monoglycerides typically have poor water solubility, they have free hydroxyl groups which can hydrogen bond with water, surfactants, cosolvents, etc. As polar lipids, monoglycerides typically: (1) are better solvents for drugs; (2) act as cosurfactants which promote mutual solubility between excipients (i.e., inactive ingredients); (3) enhance water uptake; and (4) promote self-dispersibility of lipid formulations [110]. The above properties of monoglycerides place them in a lipid class known as “insoluble swelling amphiphiles”. These lipid molecules form stable monolayers (at the air/water interface), but also swell in water to form liquid crystalline phases [111]. In their detailed review, Kaasgaard and Drummond [112] explain that these lyotropic (i.e., solvent induced) liquid crystalline phases of monoglycerides include the one-dimensional lamellar phase, which has been widely studied and employed as a model system for biomembranes and drug delivery applications. More recently studied are the structurally more complex two- and three-dimensional ordered (lyotropic) liquid crystalline phases, of which inverse hexagonal and cubic phases are two prominent examples. In agreement with numerous other investigators, Kaasgaard and Drummond also state that all these types of liquid crystalline phases are frequently stable in excess water, which facilitates the preparation of nanoparticle dispersions and makes them suitable candidates for the encapsulation and controlled release of drugs ([112]; cf. [113,114,115,116,117,118,119]).
In the “preferred form” of the LCM/ND nanoemulsion formulations (cf. [105,106]), the monoglyceride content employed consists entirely of the saturated variety. Using only saturated monoglyceride in such nanoemulsion formulations carries an additional benefit. Namely, saturated fatty chains (i.e., saturated acyl groups) are advantageous because they are incapable of undergoing peroxidation reactions, which would lessen the acceptable storage life (cf. [120]) of these (“oil-in-water”) nanoemulsions.
The self-assembly of varied and useful dispersed cubic phases (among other liquid crystalline phases) depends heavily on the acyl chain length of the glycerides (primarily monoglycerides) placed in contact with water [73]. As Yaghmur et al. [119] point out, the significant interest in the formulation and the characterization of these complex and varied, self-assembled, liquid crystalline cubic phases is driven by both fundamental and practical considerations: they offer many advantages compared to conventional dispersed systems (such as simple or double emulsions) because of their confined equilibrium nanostructures with high interfacial area, their low viscosity, and their capabilities to solubilize a wide variety of active molecules. Therefore, there is great interest to utilize theses dispersed cubic phases for the administration of drugs, or for the formulation of new delivery systems [119].
The (lyotropic) cubic liquid crystalline phases may be classified into two distinct classes: bicontinuous cubic phases and micellar or discontinuous (e.g., type Fd3m) cubic phases. Representative illustrations, including suitable micrographs, of these dispersed cubic phases can be found in [107,112,114,121,122,123,124]. As Abraham et al. [125] explain, two alternate structural representations have been utilized to describe the bicontinuous cubic phases, one in terms of rod-like elements and the other in terms of folded surfaces, that is, infinite periodic minimal surfaces (IPMS) (alternatively, the representations in terms of nodal surfaces have been used to describe the dynamic structure of cubic phases). Three different “inverse bicontinuous” cubic lipid phases have been observed experimentally, having the symmetry Pn3m, Ia3d, and Im3m—corresponding to the following IPMS: the diamond type (D-surface), the gyroid type (G-type), and the primitive type (P-surface), respectively [125]. As reviewed by Garg et al. [107], monoglycerides spontaneously form bicontinuous cubic phases upon the addition of water, are relatively insoluble (allowing the formation of colloidal dispersions of cubic phases), and resistant to changes in temperature. Accordingly, lipid nanoparticles comprising interior liquid crystalline structures of curved lipid membranes (i.e., dispersed cubic phases) have been used to solubilize, encapsulate, and deliver medications to disease areas within the body [107].
Besides certain glyceride-based liquid crystalline systems displaying colloidal stability in excess water, the same important attribute has been documented for cholesterol and cholesterol esters—all of which are present in LCM/ND nanoemulsion formulations [73]. For example, cholesterol and its esters change the packing structure of lipids, and in high concentrations they are known to induce the formation of a liquid crystal phase [120]. In addition, Kuntsche and colleagues [126,127] have prepared lipid nanoparticles in the (mesomorphic or) liquid crystalline phase from cholesterol esters with saturated acyl chains. These investigators were motivated by the knowledge that many cholesterol esters are physiologic lipid compounds which can form liquid crystalline phases (thermotropic mesophases) and, hence, they were interested in their potential for the development of liquid crystalline nanoparticles as a carrier system for lipophilic drugs [127]. In accordance with the above observations and considerations, the substantial concentrations of cholesterol esters and cholesterol in the LCM/ND nanoemulsion formulation likely further contribute to the known long-term stability of this nanoemulsion (liquid crystalline) lipid nanoparticles in excess water, thereby providing a persistent carrier matrix upon exposure to liquids such as blood plasma [73].

5. Promising Developments Regarding Supplementary Neurotherapy Using Targeted Sonoporation

A completely separate advantage of such LCM/ND (drug delivery) nanoemulsion(s) stems from the characteristic lipid-coated microbubble subpopulation existing in this nanoemulsion type [1,2,73]. Over the past decade, neuroscientists have been exploring the use of ultrasound in combination with preformed (intravenous) microbubbles to temporarily open the BBB (cf. [128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149]), allowing drugs or the immune system to target brain tumors or Alzheimer’s brain plaque in vivo effectively, repeatedly, and safely [150,151,152,153,154,155,156] in animals up to primates [150,157] and even in humans [157]. It is worth noting that this proposed mechanism of plaque burden reduction, by sonoporation (i.e., “loosening the tight junctions of the cells forming the BBB” via ultrasound irradiation [158,159]), might carry an additional effect. (Microbubble-assisted) sonoporation not only facilitates localized delivery of drugs and/or activated immune cells to target Alzheimer’s brain plaque in vivo [158], but also facilitates (possibly by passive transport) reduction of β-amyloid plaque burden from brain tissue in a mouse model of Alzheimer’s disease [160]. Specifically, this same mechanism might also function to counteract characteristic decreased “brain clearance” of neurotoxic β-amyloid “monomer” [160]—which has been described as a central event in the pathogenesis of Alzheimer’s disease (cf. [1,2,161]).
The actual cellular and biophysical mechanisms of the reversible BBB opening process by sonoporation, when employing focused transcranial ultrasound coupled with injected preformed microbubbles, have been described further in other published studies over the last several years [1,162,163,164,165,166,167,168]. Also, representative illustrations depicting such an opening of the BBB, by postulated loosening of tight junctions (and other mechanisms), can be found in [141,164]. In the foreseeable future, taking full advantage of this ongoing, noninvasive, and targeted use of preformed (LCM/ND nanoemulsion-based) microbubbles to transiently and reversibly increase BBB permeability via sonoporation, while optimizing drug delivery efficiency (through judicious choice of acoustic parameters [152,156]) and minimizing side effects, may assist in advancing transcranial sonoporation to the clinic (cf. [1,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182]).

6. Lipid-Coated Microbubble/Nanoparticle-Derived Nanoemulsion Particles Function as Biomimetic Cubic Phase Nanotransporters

As alluded to in Section 4, the previously documented similarities in lipid composition among HDL (as well as native and modified low-density lipoproteins (LDL)) and LCM/ND nanoemulsion particles can partially simulate or mimic the known heterogeneity (i.e., subpopulations or subspecies) of HDL particles (for a review, see [73]). Moreover, the above-mentioned scavenger receptor (i.e., either SR-BI (rodent) and/or CLA-1 (human) orthologs [29]) has been shown to be a multifunctional receptor able to bind a broad variety of ligands, including HDL, LDL, oxidized low-density lipoproteins (OxLDL), acetylated low-density lipoproteins (AcLDL), very low-density lipoproteins (VLDL), and chylomicron remnants [183,184,185]. The presence of amphipathic helices is a common feature of “exchangeable apolipoproteins”, which are known to be the primary ligands (including notably apoA-I) for SR-BI [183].
One example of a reconstituted (biomimetic) lipoprotein complex utilizing the SR-BI cell surface receptor in the literature concerns manufactured (lipid) emulsions that were designed to mimic chylomicrons in vivo, and therefore were expected to acquire apolipoproteins upon incubation with serum [186]. The experimental data obtained led investigators to conclude that SR-BI is clearly involved in facilitating chylomicron (remnant) metabolism and might function as an initial recognition site for chylomicron remnants [185]. Note that, in this example, the “reconstituted lipoprotein vehicle” was at first constructed solely of lipids, and apolipoprotein(s) (needed for targeting) were acquired only after incubation with serum. This concept of a pure lipid nanocarrier, which can successfully acquire apolipoprotein(s) upon contact with blood plasma, is similarly described elsewhere in the literature. For example, Williams and Scanu [187] reported that phosphoglyceride liposomes, injected intravenously, pick up endogenous apoA-I; in vitro, phosphoglyceride liposomes incubated with plasma acquire apoA-I at the expense of HDL [73] (cf. [188]). Explanatory illustrations depicting the apoA-I chemical structure, the apoA-I conformation on discoidal and spherical HDL particles, and their relative sizes can be found in [189].
To conclude, self-assembled (colloidal mesophase) lipid nanoemulsions (e.g., [190,191,192,193,194,195]), particularly those predominantly containing dispersed cubic phase lipid nanoparticles (e.g., [196,197,198,199,200]), continue to receive growing attention in pharmaceutical and/or biological fields. The main reason behind much of this attention is the fact that nonlamellar lipid nanostructures, such as cubic liquid crystalline phases, have wide potential as delivery systems for numerous drugs, cosmetics, and food applications (e.g., [201,202,203]). Namely, using various lipids and their mixtures to form self-assembled nonlamellar nanostructures, it has continually been reported possible to successfully obtain stable colloidal dispersions of (liquid crystalline) lipid cubic phases with well-defined particle size and morphology (e.g., [202,203]). In particular, within the range of self-assembled phases in model surfactant-like lipid systems, Yaghmur et al. [204] further emphasized that monoglyceride-based lyotropic liquid crystalline phases are relatively unique owing to their rich polymorphism in water and potential application as drug nanocarriers (cf. [205] and Section 4 above). A recurring example of a largely monoglyceride-based drug delivery agent category (cf. Section 4, Section 5 and Section 6) is the multitasking LCM/ND nanoemulsion formulation. In this particular targeted delivery approach, the self-assembled lipid particle structure itself (upon intravenous injection of the LCM/ND nanoemulsion) is apparently successfully utilized as the active targeting ligand—which is directed via (adsorption of) plasma lipoproteins towards the appropriate receptors on the target cell surface. These dispersed liquid crystalline lipid particles, of the LCM/ND nanoemulsion formulation, are colloidally stable nanocarriers which very likely represent liquid-crystalline inverse-topology nanotransporters (nanocarriers), i.e., dispersed lipid cubic phases (cf. [73]).

7. Conclusions

The proposed multitasking combination therapeutic appears likely to display greater efficacy at different stages of Alzheimer’s disease (cf. [72]). Furthermore, the effects on various cell types targeted may be additive, multiplicative, or otherwise synergistic [26]. As a result, this multitasking (drug delivery) therapeutic approach could represent a promising way to treat, delay, or even prevent the disease in the future [1,2]. In particular, LCM/ND (lipid) nanoemulsion particles have a composition (consisting of various glycerides, cholesterol, and cholesterol esters) similar to lipids contained in several plasma lipoproteins (i.e., resembles the lipid content of a “generic” lipoprotein [184,190]). Accordingly, when this specific nanoemulsion type is injected intravenously, its colloidally stable lipid particles apparently acquire apoA-I from the plasma and, subsequently, can be recognized by and bind to certain lipoprotein receptors (predominantly SR-BI) on various Alzheimer’s-related cell types.


This research did not receive any specific grant from funding agencies in the public, commercial, or nonprofit sectors.

Conflicts of Interest

The authors declare no conflict of interest. J.S.D. is employed at Cav-Con Inc.


  1. D’Arrigo, J.S. Alzheimer’s disease, brain injury, and CNS nanotherapy in humans: Sonoporation augmenting drug targeting. Med. Sci. 2017, 5, 29. [Google Scholar]
  2. D’Arrigo, J.S. Nanotherapy for Alzheimer’s disease and vascular dementia: Targeting senile endothelium. Adv. Colloid Interface Sci. 2018, 251, 44–54. [Google Scholar] [CrossRef] [PubMed]
  3. Cooper, L.L.; Mitchell, G.F. Aortic stiffness, cerebrovascular dysfunction, and memory. Pulse 2016, 4, 69–77. [Google Scholar] [CrossRef] [PubMed]
  4. Dichgans, M.; Leys, D. Vascular cognitive impairment. Circ. Res. 2017, 120, 573–591. [Google Scholar] [CrossRef] [PubMed]
  5. Greenberg, S.M. Vascular disease and neurodegeneration: Advancing together. Lancet Neurol. 2017, 16, 333. [Google Scholar]
  6. Kalaria, R.N. Neuropathological diagnosis of vascular cognitive impairment and vascular dementia with implications for Alzheimer’s disease. Acta Neuropathol. 2016, 131, 659–685. [Google Scholar] [CrossRef] [PubMed]
  7. Duncombe, J.; Kitamura, A.; Hase, Y.; Ihara, M.; Kalaria, R.N.; Horsburgh, K. Chronic cerebral hypoperfusion: A key mechanism leading to vascular cognitive impairment and dementia. Closing the translational gap between rodent models and human vascular cognitive impairment and dementia. Clin. Sci. 2017, 131, 2451–2468. [Google Scholar] [CrossRef] [PubMed]
  8. Perrotta, M.; Lembo, G.; Carnevale, D. Hypertension and dementia: Epidemiological and experimental evidence revealing a detrimental relationship. Int. J. Mol. Sci. 2016, 17, 347. [Google Scholar] [CrossRef] [PubMed]
  9. Sudduth, T.L.; Weekman, E.M.; Price, B.R.; Gooch, J.L.; Woolums, A.; Norris, C.M.; Wilcock, D.M. Time-course of glial changes in the hyperhomocysteinemia model of vascular cognitive impairment and dementia (VCID). Neuroscience 2017, 341, 42–51. [Google Scholar] [CrossRef] [PubMed]
  10. Bhat, N.R. Vasculoprotection as a convergent, multi-targeted mechanism of anti-AD therapeutics and interventions. J. Alzheimers Dis. 2015, 46, 581–591. [Google Scholar] [CrossRef] [PubMed]
  11. Alzheimer’s Disease International. World Alzheimer Report 2016; Alzheimer’s Disease International: London, UK, 2016; Available online: (accessed on 20 February 2018).
  12. Srimanee, A.; Regberg, J.; Hallbrink, M.; Vajragupta, O.; Langel, U. Role of scavenger receptors in peptide-based delivery of plasmid DNA across a blood–brain barrier model. Int. J. Pharm. 2016, 500, 128–135. [Google Scholar] [CrossRef] [PubMed]
  13. De Boer, A.G.; van der Sandt, I.C.J.; Gaillard, P.J. The role of drug transporters at the blood–brain barrier. Annu. Rev. Pharmacol. Toxicol. 2003, 43, 629–656. [Google Scholar] [CrossRef] [PubMed]
  14. Almer, G.; Mangge, H.; Zimmer, A.; Prassl, R. Lipoprotein-related and apolipoprotein-mediated delivery systems for drug targeting and imaging. Curr. Med. Chem. 2015, 22, 3631–3651. [Google Scholar] [CrossRef] [PubMed]
  15. Preston, J.E.; Abbott, J.; Begley, D.J. Transcytosis of macromolecules at the blood–brain barrier. Adv. Pharmacol. 2014, 71, 147–163. [Google Scholar] [PubMed]
  16. Di Marco, L.Y.; Venneri, A.; Farkas, E.; Evans, P.C.; Marzo, A.; Frangi, A.F. Vascular dysfunction in the pathogenesis of Alzheimer’s disease—A review of endothelium-mediated mechanisms and ensuing vicious circles. Neurobiol. Dis. 2015, 82, 593–606. [Google Scholar] [CrossRef] [PubMed]
  17. Salmina, A.B.; Inzhutova, A.I.; Malinovskaya, N.A.; Petrova, M.M. Endothelial dysfunction and repair in Alzheimer-type neurodegeneration: Neuronal and glial control. J. Alzheimers Dis. 2010, 22, 17–36. [Google Scholar] [CrossRef] [PubMed]
  18. Tong, X.K.; Hamel, E. Simvastatin restored vascular reactivity, endothelial function and reduced string vessel pathology in a mouse model of cerebrovascular disease. J. Cereb. Blood Flow Metab. 2015, 35, 512–520. [Google Scholar] [CrossRef] [PubMed]
  19. Carradori, D.; Gaudin, A.; Brambilla, D.; Andrieux, K. Application of nanomedicine to the CNS diseases. Int. Rev. Neurobiol. 2016, 130, 73–113. [Google Scholar] [PubMed]
  20. Koster, K.P.; Thomas, R.; Morris, A.W.; Tai, L.M. Epidermal growth factor prevents oligomeric amyloid-β induced angiogenesis deficits in vitro. J. Cereb. Blood Flow Metab. 2016, 36, 1865–1871. [Google Scholar] [CrossRef] [PubMed]
  21. Zenaro, E.; Piacentino, G.; Constantin, G. The blood–brain barrier in Alzheimer’s disease. Neurobiol. Dis. 2016, 107, 41–56. [Google Scholar] [CrossRef] [PubMed]
  22. Qosa, H.; Mohamed, A.; Al Rihani, S.B.; Batarseha, Y.S.; Duong, Q.V.; Keller, J.N.; Kaddoumi, A. High-throughput screening for identification of blood–brain barrier integrity enhancers: A drug repurposing opportunity to rectify vascular amyloid toxicity. J. Alzheimers Dis. 2016, 53, 1499–1516. [Google Scholar] [CrossRef] [PubMed]
  23. Hostenbach, S.; D’haeseleer, M.; Kooijman, R.; De Keyser, J. The pathophysiological role of astrocytic endothelin-1. Prog Neurobiol. 2016, 144, 88–102. [Google Scholar] [CrossRef] [PubMed]
  24. Koizumi, K.; Wang, G.; Park, L. Endothelial dysfunction and amyloid-β-induced neurovascular alterations. Cell. Mol. Neurobiol. 2016, 36, 155–165. [Google Scholar] [CrossRef] [PubMed]
  25. Goldwaser, E.L.; Acharya, N.K.; Sarkar, A.; Godsey, G.; Nagele, R.G. Breakdown of the cerebrovasculature and blood–brain barrier: A mechanistic link between diabetes mellitus and Alzheimer’s disease. J. Alzheimers Dis. 2016, 54, 445–456. [Google Scholar] [CrossRef] [PubMed]
  26. Bredesen, D.E. Reversal of cognitive decline: A novel therapeutic program. Aging (Albany, NY) 2014, 6, 707–717. [Google Scholar] [CrossRef] [PubMed]
  27. Mahringer, A.; Reichel, V.; Ott, M.; MacLean, C.; Reimold, I.; Hollnack-Pusch, E.; Fricker, G. Overcoming the blood brain barrier: The challenge of brain drug targeting. J. Nanoneurosci. 2012, 2, 5–19. [Google Scholar] [CrossRef]
  28. Robert, J.; Button, E.B.; Stukas, S.; Boyce, G.K.; Gibbs, E.; Cowan, C.M.; Gilmour, M.; Cheng, W.H.; Soo, S.K.; Yuen, B.; et al. High-density lipoproteins suppress Aβ-induced PBMC adhesion to human endothelial cells in bioengineered vessels and in monoculture. Mol. Neurodegener. 2017, 12, 60. [Google Scholar] [CrossRef] [PubMed]
  29. Vishnyakova, T.G.; Bocharov, A.V.; Baranova, I.N.; Chen, Z.; Remaley, A.T.; Csako, G.; Eggerman, T.L.; Patterson, A.P. Binding and internalization of lipopolysaccharide by CLA-1, a human orthologue of rodent scavenger receptor B1. J. Biol. Chem. 2003, 278, 22771–22780. [Google Scholar] [CrossRef] [PubMed]
  30. Darlington, D.; Li, S.; Hou, H.; Habib, A.; Tian, J.; Gao, Y.; Ehrhart, J.; Sanberg, P.R.; Sawmiller, D.; Giunta, B.; et al. Human umbilical cord blood-derived monocytes improve cognitive deficits and reduce amyloid-β pathology in PSAPP mice. Cell Transplant. 2015, 24, 2237–2250. [Google Scholar] [CrossRef] [PubMed]
  31. Chang, E.H.; Rigotti, A.; Huerta, P. Age-related influence of the HDL receptor SR-BI on synaptic plasticity and cognition. Neurobiol. Aging 2009, 30, 407–419. [Google Scholar] [CrossRef] [PubMed]
  32. Fung, K.Y.; Wang, C.; Nyegaard, S.; Heit, B.; Fairn, G.D.; Lee, W.L. SR-BI mediated transcytosis of HDL in brain microvascular endothelial cells is independent of caveolin, clathrin, and PDZK1. Front. Physiol. 2017, 8, 841. [Google Scholar] [CrossRef] [PubMed]
  33. Robert, J.; Stukas, S.; Button, E.; Cheng, W.H.; Lee, M.; Fan, J.; Wilkinson, A.; Kulic, I.; Wright, S.D.; Wellington, C.L. Reconstituted high-density lipoproteins acutely reduce soluble brain Aβ levels in symptomatic APP/PS1 mice. Biochim. Biophys. Acta 2016, 1862, 1027–1036. [Google Scholar] [CrossRef] [PubMed]
  34. Armstrong, S.M.; Sugiyama, M.G.; Fung, K.Y.Y.; Gao, Y.; Wang, C.; Levy, A.S.; Azizi, P.; Roufaiel, M.; Zhu, S.N.; Neculai, D.; et al. A novel assay uncovers an unexpected role for SR-BI in LDL transcytosis. Cardiovasc. Res. 2015, 108, 268–277. [Google Scholar] [CrossRef] [PubMed]
  35. Hottman, D.A.; Chernick, D.; Cheng, S.; Wang, Z.; Li, L. HDL and cognition in neurodegenerative disorders. Neurobiol. Dis. 2014, 72, 22–36. [Google Scholar] [CrossRef] [PubMed]
  36. Velagapudi, S.; Yalcinkaya, M.; Piemontese, A.; Meier, R.; Norrelykke, S.F.; Perisa, D.; Rzepiela, A.; Stebler, M.; Stoma, S.; Zanoni, P.; et al. VEGF-A regulates cellular localization of SR-BI as well as transendothelial transport of HDL but not LDL. Arterioscler. Thromb. Vasc. Biol. 2017, 37, 794–803. [Google Scholar] [CrossRef] [PubMed]
  37. Choi, H.J.; Seo, E.H.; Yi, D.; Sohn, B.K.; Choe, Y.M.; Byun, M.S.; Lee, J.M.; Woo, J.I.; Lee, D.Y. Amyloid-independent amnestic mild cognitive impairment and serum apolipoprotein A1 levels. Am. J. Geriatr. Psychiatry 2016, 24, 144–153. [Google Scholar] [CrossRef] [PubMed]
  38. Kitamura, Y.; Usami, R.; Ichihara, S.; Kida, H.; Satoh, M.; Tomimoto, H.; Murata, M.; Oikawa, S. Plasma protein profiling for potential biomarkers in the early diagnosis of Alzheimer’s disease. Neurol. Res. 2017, 39, 231–238. [Google Scholar] [CrossRef] [PubMed]
  39. Lazarus, J.; Mather, K.A.; Armstrong, N.J.; Song, F.; Poljak, A.; Thalamuthu, A.; Lee, T.; Kochan, N.A.; Brodaty, H.; Wright, M.J.; et al. DNA methylation in the apolipoprotein-A1 gene is associated with episodic memory performance on healthy older individuals. J. Alzheimers Dis. 2015, 44, 175–182. [Google Scholar] [PubMed]
  40. Ma, C.; Li, J.; Bao, Z.; Ruan, Q.; Yu, Z. Serum levels of apoA1 and apoA2 are associated with cognitive status in older men. Biomed. Res. Int. 2015, 2015, 481621. [Google Scholar] [CrossRef] [PubMed]
  41. Slot, R.E.; Van Harten, A.C.; Kester, M.I.; Jongbloed, W.; Bouwman, F.H.; Teunissen, C.E.; Scheltens, P.; Veerhuis, R.; van der Flier, W.M. Apolipoprotein A1 in cerebrospinal fluid and plasma and progression to Alzheimer’s disease in non-demented elderly. J. Alzheimers Dis. 2017, 56, 687–697. [Google Scholar] [CrossRef] [PubMed]
  42. Yin, Z.G.; Li, L.; Cui, M.; Zhou, S.M.; Yu, M.M.; Zhou, H.D. Inverse relationship between apolipoprotein A-I and cerebral white matter lesions: A cross-sectional study in middle-aged and elderly subjects. PLoS ONE 2014, 9, e97113. [Google Scholar] [CrossRef] [PubMed]
  43. Weekman, E.M.; Sudduth, T.L.; Caverly, C.N.; Kopper, T.J.; Phillips, O.W.; Powell, D.K.; Wilcock, D.M. Reduced efficacy of anti-Aβ immunotherapy in a mouse model of amyloid deposition and vascular cognitive impairment comorbidity. J. Neurosci. 2016, 36, 9896–9907. [Google Scholar] [CrossRef] [PubMed]
  44. Nelson, A.R.; Sweeney, M.D.; Sagare, A.P.; Zlokovic, B.V. Neurovascular dysfunction and neurodegeneration in dementia and Alzheimer’s disease. Biochim. Biophys. Acta 2016, 1862, 887–900. [Google Scholar] [CrossRef] [PubMed]
  45. Kapasi, A.; Schneider, J.A. Vascular contributions to cognitive impairment, clinical Alzheimer’s disease, and dementia in older persons. Biochim. Biophys. Acta 2016, 1862, 878–886. [Google Scholar] [CrossRef] [PubMed]
  46. McAleese, K.L.; Alafuzoff, I.; Charidimou, A.; De Reuck, J.; Grinberg, L.T.; Hainsworth, A.H.; Hortobagyi, T.; Ince, P.; Jellinger, K.; Gao, J.; et al. Post-mortem assessment in vascular dementia: Advances and aspirations. BMC Med. 2016, 14, 129. [Google Scholar] [CrossRef] [PubMed]
  47. Noh, Y.; Seo, S.W.; Jeon, S.; Lee, J.M.; Kim, J.S.; Lee, J.H.; Kim, J.H.; Kim, G.H.; Ye, B.S.; Cho, H.; et al. The role of cerebrovascular disease in amyloid deposition. J. Alzheimers Dis. 2016, 54, 1015–1026. [Google Scholar] [CrossRef] [PubMed]
  48. Hishikawa, N.; Fukui, Y.; Sato, K.; Kono, S.; Yamashita, T.; Ohta, T.; Deguchi, K.; Abe, K. Cognitive and affective functions in Alzheimer’s disease patients with metabolic syndrome. Eur. J. Neurol. 2016, 23, 339–345. [Google Scholar] [CrossRef] [PubMed]
  49. Gutierrez, J.; Honig, L.; Elkind, M.S.; Mohr, J.P.; Goldman, J.; Dwork, A.J.; Morgello, S.; Marshall, R.S. Brain arterial aging and its relationship to Alzheimer dementia. Neurology 2016, 86, 1507–1515. [Google Scholar] [CrossRef] [PubMed]
  50. Nagata, K.; Yamazaki, T.; Takano, D.; Maeda, T.; Fujimaki, Y.; Nakase, T.; Sato, Y. Cerebral circulation in aging. Ageing Res. Rev. 2016, 30, 49–60. [Google Scholar] [CrossRef] [PubMed]
  51. Calabrese, V.; Giordano, J.; Signorile, A.; Ontario, M.L.; Castorina, S.; de Pasquale, C.; Eckert, G.; Calabrese, E.J. Major pathogenic mechanisms in vascular dementia: Roles of cellular stress response and hormesis inneuroprotection. J. Neurosci. Res. 2016, 94, 1588–1603. [Google Scholar] [CrossRef] [PubMed]
  52. Toth, P.; Tarantini, S.; Csiszar, A.; Ungvari, Z.I. Functional vascular contributions to cognitive impairment and dementia: Mechanisms and consequences of cerebral autoregulatory dysfunction, endothelial impairment, and neurovascular uncoupling in aging. Am. J. Physiol. Heart Circ. Physiol. 2017, 312, H1–H20. [Google Scholar] [CrossRef] [PubMed]
  53. Devraj, K.; Poznanovic, S.; Spahn, C.; Schwall, G.; Harter, P.N.; Mittelbronn, M.; Antoniello, K.; Paganetti, P.; Muhs, A.; Heilemann, M.; et al. BACE-1 is expressed in the blood–brain barrier endothelium and is upregulated in a murine model of Alzheimer’s disease. J. Cereb. Blood Flow Metab. 2016, 36, 1281–1294. [Google Scholar] [CrossRef] [PubMed]
  54. Chao, A.C.; Lee, T.C.; Juo, S.H.; Yang, D.I. Hyperglycemia increases the production of amyloid β-peptide leading to decreased endothelial tight junction. CNS Neurosci. Ther. 2016, 22, 291–297. [Google Scholar] [CrossRef] [PubMed]
  55. Khalil, R.B.; Khoury, E.; Koussa, S. Linking multiple pathogenic pathways in Alzheimer’s disease. World J. Psychiatry 2016, 6, 208–214. [Google Scholar] [CrossRef] [PubMed]
  56. Festoff, B.W.; Sajja, R.K.; van Dreden, P.; Cucullo, L. HGMB1 and thrombin mediate the blood–brain barrier dysfunction acting as biomarkers of neuroinflammation and progression to neurodegeneration in Alzheimer’s disease. J. Neuroinflamm. 2016, 13, 194. [Google Scholar] [CrossRef] [PubMed]
  57. Gangoda, S.V.; Butlin, M.; Gupta, V.; Chung, R.; Avolio, A. Pulsatile stretch alters expression and processing of amyloid precursor protein in human cerebral endothelial cells. J. Hypertens. 2016, 34, e24. [Google Scholar] [CrossRef]
  58. Roberts, A.M.; Jagadapillai, R.; Vaishnav, R.A.; Friedland, R.P.; Drinovac, R.; Lin, X.; Gozal, E. Increased pulmonary arteriolar tone associated with lung oxidative stress and nitric oxide in a mouse model of Alzheimer’s disease. Physiol. Rep. 2016, 4, e12953. [Google Scholar] [CrossRef] [PubMed]
  59. Shang, S.; Yang, Y.M.; Zhang, H.; Tian, L.; Jiang, J.S.; Dong, Y.B.; Zhang, K.; Li, B.; Zhao, W.D.; Fang, W.G.; et al. Intracerebral GM-CSF contributes to transendothelial monocyte migration in APP/PS1 Alzheimer’s disease mice. J. Cereb. Blood Flow Metab. 2016, 36, 1987–1991. [Google Scholar] [CrossRef] [PubMed]
  60. Austin, S.A.; Katusic, Z.S. Loss of endothelial nitric oxide synthase promotes p25 generation and tau phosphorylation in a murine model of Alzheimer’s disease. Circ. Res. 2016, 119, 1128–1134. [Google Scholar] [CrossRef] [PubMed]
  61. Katusic, Z.S.; Austin, S.A. Neurovascular protective function of endothelial nitric oxide. Circ. J. 2016, 80, 1499–1503. [Google Scholar] [CrossRef] [PubMed]
  62. Wang, L.; Du, Y.; Wang, K.; Xu, G.; Luo, S.; He, G. Chronic cerebral hypoperfusion induces memory deficits and facilitates Aβ generation in C57BL/6J mice. Exp. Neurol. 2016, 283, 353–364. [Google Scholar] [CrossRef] [PubMed]
  63. Kyrtsos, C.R.; Baras, J.S. Modeling the role of the glymphatic pathway and cerebral blood vessel properties in Alzheimer’s disease pathogenesis. PLoS ONE 2015, 10, e0139574. [Google Scholar] [CrossRef] [PubMed]
  64. Kalaria, R.N.; Akinyemi, R.; Ihara, M. Stroke injury, cognitive impairment and vascular dementia. Biochim. Biophys. Acta 2016, 1862, 915–925. [Google Scholar] [CrossRef] [PubMed]
  65. Khan, A.; Kalaria, R.N.; Corbett, A.; Ballard, C. Update on vascular dementia. J. Geriatr. Psychiatry Neurol. 2016, 29, 281–301. [Google Scholar] [CrossRef] [PubMed]
  66. Austin, S.A.; Santhanam, A.V.; d’Uscio, L.V.; Katusic, Z.S. Regional heterogeneity of cerebral microvessels and brain susceptibility to oxidative stress. PLoS ONE 2015, 10, e0144062. [Google Scholar] [CrossRef] [PubMed]
  67. Toda, N.; Okamura, T. Cigarette smoking impairs nitric oxide-mediated cerebral blood flow increase: Implications for Alzheimer’s disease. J. Pharmacol. Sci. 2016, 131, 223–232. [Google Scholar] [CrossRef] [PubMed]
  68. Uiterwijk, R.; Huijts, M.; Staals, J.; Rouhl, R.P.; De Leeuw, P.W.; Kroon, A.A.; van Oostenbrugge, R.J. Endothelial activation is associated with cognitive performance in patients with hypertension. Am. J. Hypertens. 2016, 29, 464–469. [Google Scholar] [CrossRef] [PubMed]
  69. Kamat, P.K.; Kyles, P.; Kalani, A.; Tyagi, N. Hydrogen sulfide ameliorates homocysteine-induced Alzheimer’s disease-like pathology, blood–brain barrier disruption, and synaptic disorder. Mol. Neurobiol. 2016, 53, 2451–2467. [Google Scholar] [CrossRef] [PubMed]
  70. Iadecola, C. Untangling neurons with endothelial nitric oxide. Circ. Res. 2016, 119, 1052–1054. [Google Scholar] [CrossRef] [PubMed]
  71. Wang, Y.J. Lessons from immunotherapy for Alzheimer’s disease. Nat. Rev. Neurol. 2014, 10, 188–189. [Google Scholar] [CrossRef] [PubMed]
  72. Krstic, D.; Knuesel, I. Deciphering the mechanism underlying late-onset Alzheimer’s disease. Nat. Rev. Neurol. 2013, 9, 25–34. [Google Scholar] [CrossRef] [PubMed]
  73. D’Arrigo, J. Stable Nanoemulsions: Self-Assembly in Nature and Nanomedicine; Elsevier: Amsterdam, The Netherlands, 2011; 415p, ISBN 978-0-444-53798-0. [Google Scholar]
  74. Barbarese, E.; Ho, S.Y.; D’Arrigo, J.S.; Simon, R.H. Internalization of microbubbles by tumor cells in vivo and in vitro. J. Neurooncol. 1995, 26, 25–34. [Google Scholar] [CrossRef] [PubMed]
  75. Beydoun, R.; Hamood, M.A.; Gomez Zubeita, M.; Kondapalli, K.C. Na+/H+ exchanger 9 regulates iron mobilization at the blood–brain barrier in response to iron starvation. J. Biol. Chem. 2017, 292, 4293–4301. [Google Scholar] [CrossRef] [PubMed]
  76. McCarthy, R.C.; Kosman, D.J. Iron transport across the blood–brain barrier: Development, neurovascular regulation and cerebral amyloid angiopathy. Cell. Mol. Life Sci. 2015, 72, 709–727. [Google Scholar] [CrossRef] [PubMed]
  77. Pirpamer, L.; Hofer, E.; Gesierich, B.; De Guio, F.; Freudenberger, P.; Seiler, S.; Duering, M.; Jouvent, E.; Duchesnay, E.; Dichgans, M.; et al. Determinants of iron accumulation in the normal aging brain. Neurobiol. Aging 2016, 43, 149–155. [Google Scholar] [CrossRef] [PubMed]
  78. Dalkara, T.; Alarcon-Martinez, L. Cerebral microvascular pericytes and neurogliovascular signaling in health and disease. Brain Res. 2015, 1623, 3–17. [Google Scholar] [CrossRef] [PubMed]
  79. Daulatzai, M.A. Cerebral hypoperfusion and glucose hypometabolism: Key pathophysiological modulators promote neurodegeneration, cognitive impairment, and Alzheimer’s disease. J. Neurosci. Res. 2017, 95, 943–972. [Google Scholar] [CrossRef] [PubMed]
  80. Tarantini, S.; Tran, C.H.; Gordon, G.R.; Ungvari, Z.; Csiszar, A. Impaired neurovascular coupling in aging and Alzheimer’s disease: Contribution of astrocyte dysfunction and endothelial impairment to cognitive decline. Exp. Gerontol. 2016, 94, 52–58. [Google Scholar] [CrossRef] [PubMed]
  81. Barros, L.F.; San Martin, A.; Ruminot, I.; Sandoval, P.Y.; Fernandez-Moncada, I.; Baeza-Lehnert, F.; Arce-Molina, R.; Contreras-Baeza, Y.; Cortés-Molina, F.; Galaz, A.; et al. Near-critical GLUT1 and neurodegeneration. J. Neurosci. Res. 2017, 95, 2267–2274. [Google Scholar] [CrossRef] [PubMed]
  82. Jais, A.; Solas, M.; Backes, H.; Chaurasia, B.; Kleinridders, A.; Theurich, S.; Mauer, J.; Steculorum, S.M.; Hampel, B.; Goldau, J.; et al. Myeloid-cell derived VEGF maintains brain glucose uptake and limits cognitive impairment in obesity. Cell 2016, 165, 882–895. [Google Scholar] [CrossRef] [PubMed]
  83. Keaney, J.; Campbell, M. The dynamic blood–brain barrier. FEBS J. 2015, 282, 4067–4079. [Google Scholar] [CrossRef] [PubMed]
  84. Harik, S.I. Changes in the glucose transporter of brain capillaries. Can. J. Physiol. Pharmacol. 1992, 70 (Suppl. 1), S113–S117. [Google Scholar] [CrossRef] [PubMed]
  85. Horwood, N.; Davies, D.C. Immunolabelling of hippocampal microvessel glucose transporter protein is reduced in Alzheimer’s disease. Virchows Arch. 1994, 425, 69–72. [Google Scholar] [CrossRef] [PubMed]
  86. Winkler, E.A.; Nishida, Y.; Sagare, A.P.; Rege, S.V.; Bell, R.D.; Perlmutter, D.; Sengillo, J.D.; Hillman, S.; Kong, P.; Nelson, A.R.; et al. GLUT1 reductions exacerbate Alzheimer’s disease vasculo-neuronal dysfunction and degeneration. Nat. Neurosci. 2015, 18, 521–533. [Google Scholar] [CrossRef] [PubMed]
  87. An, Y.; Varma, V.R.; Varma, S.; Casanova, R.; Dammer, E.; Pletnikova, O.; Chia, C.W.; Egan, J.M.; Ferrucci, L.; Troncoso, J.; et al. Evidence for brain glucose dysregulation in Alzheimer’s disease. Alzheimer’s Dement. 2017, 2017, 1–12. [Google Scholar] [CrossRef]
  88. Yamazaki, Y.; Kanekiyo, T. Blood–brain barrier dysfunction and the pathogenesis of Alzheimer’s disease. Int. J. Mol. Sci. 2017, 18, 1965. [Google Scholar] [CrossRef] [PubMed]
  89. Kelleher, R.J.; Soiza, R.L. Evidence of endothelial dysfunction in the development of Alzheimer’s disease: Is Alzheimer’s a vascular disorder? Am. J. Cardiovasc. Dis. 2013, 3, 197–226. [Google Scholar] [PubMed]
  90. Tenreiro, M.M.; Ferreira, R.; Bernardino, L.; Brito, M.A. Cellular response of the blood–brain barrier to injury: Potential biomarkers and therapeutic targets for brain regeneration. Neurobiol. Dis. 2016, 91, 262–273. [Google Scholar] [CrossRef] [PubMed]
  91. Yoon, C.Y.; Steffen, L.M.; Gross, M.D.; Launer, L.J.; Odegaard, A.; Reiner, A.; Sanchez, O.; Yaffe, K.; Sidney, S.; Jacobs, D.R., Jr. Circulating cellular adhesion molecules and cognitive function: The coronary artery risk development in young adults study. Front. Cardiovasc. Med. 2017. [Google Scholar] [CrossRef] [PubMed]
  92. Montagne, A.; Zhao, Z.; Zlokovic, B.V. Alzheimer’s disease: A matter of blood–brain barrier dysfunction? J. Exp. Med. 2017, 214, 3151–3169. [Google Scholar] [CrossRef] [PubMed]
  93. Beishon, L.; Haunton, V.J.; Panerai, R.B.; Robinson, T.G. Cerebral hemodynamics in mild cognitive impairment: A systematic review. J. Alzheimers Dis. 2017, 59, 369–385. [Google Scholar] [CrossRef] [PubMed]
  94. Love, S.; Miners, J.S. Small vessel disease, neurovascular regulation and cognitive impairment: Post-mortem studies reveal a complex relationship, still poorly understood. Clin. Sci. (Lond.) 2017, 131, 1579–1589. [Google Scholar] [CrossRef] [PubMed]
  95. Wang, P.; Wu, Q.; Wu, W.; Li, H.; Guo, Y.; Yu, P.; Gao, G.; Shi, Z.; Zhao, B.; Chang, Y.Z. Mitochondrial ferritin deletion exacerbates β-amyloid-induced neurotoxicity in mice. Oxid. Med. Cell Longev. 2017, 2017, 1020357. [Google Scholar] [CrossRef] [PubMed]
  96. Lourenco, C.F.; Ledo, A.; Barbosa, R.M.; Laranjinha, J. Neurovascular uncoupling in the triple transgenic model of Alzheimer’s disease: Impaired cerebral blood flow response to neuronal-derived nitric oxide signaling. Exp. Neurol. 2017, 291, 36–43. [Google Scholar] [CrossRef] [PubMed]
  97. Castillo-Carranza, D.L.; Nilson, A.N.; Van Skike, C.E.; Jahrling, J.B.; Patel, K.; Garach, P.; Gerson, J.E.; Sengupta, U.; Abisambra, J.; Nelson, P.; et al. Cerebral microvascular accumulation of tau oligomers in Alzheimer’s disease and related tauopathies. Aging Dis. 2017, 8, 257–266. [Google Scholar] [CrossRef] [PubMed]
  98. Dudvarski Stankovic, N.; Teodorczyk, M.; Ploen, R.; Zipp, F.; Schmidt, M.H. Microglia–blood vessel interactions: A double-edged sword in brain pathologies. Acta. Neuropathol. 2016, 131, 347–363. [Google Scholar] [CrossRef] [PubMed]
  99. Michalicova, A.; Banks, W.A.; Legath, J.; Kovac, S.A. Tauopathies—Focus on changes at the neurovascular unit. Curr. Alzheimer Res. 2017, 14, 790–801. [Google Scholar] [CrossRef] [PubMed]
  100. Sorop, O.; Olver, T.D.; van deWouw, J.; Heinonen, I.; van Duin, R.W.; Duncker, D.J.; Merkus, D. The microcirculation: A key player in obesity-associated cardiovascular disease. Cardiovasc. Res. 2017, 113, 1035–1045. [Google Scholar] [CrossRef] [PubMed]
  101. Lee, L.L.; Aung, H.H.; Wilson, D.W.; Anderson, S.E.; Rutledge, J.C.; Rutkowsky, J.M. Triglyceride-rich lipoprotein lipolysis products increase blood–brain barrier transfer coefficient and induce astrocyte lipid droplets and cell stress. Am. J. Cell Physiol. 2017, 312, C500–C516. [Google Scholar] [CrossRef] [PubMed]
  102. Stukas, S.; Robert, J.; Wellington, C.L. High-density lipoproteins and cerebrovascular integrity in Alzheimer’s disease. Cell Metab. 2014, 19, 574–591. [Google Scholar] [CrossRef] [PubMed]
  103. Swaminathan, S.K.; Ahlschwede, K.M.; Sarma, V.; Curran, G.L.; Omtri, R.S.; Decklever, T.; Lowe, V.J.; Poduslo, J.F.; Kandimalla, K.K. Insulin differentially affects the distribution kinetics of amyloid β 40 and 42 in plasma and brain. J. Cereb. Blood Flow Metab. 2017. [Google Scholar] [CrossRef] [PubMed]
  104. Guilaine, B.; Emily, B.; Sonja, S.; Cheryl, W. The pleiotropic vasoprotective functions of high density lipoproteins (HDL). J. Biomed. Res. 2017. [Google Scholar] [CrossRef]
  105. D’Arrigo, J. Surfactant Mixtures, Stable Gas-in-Liquid Emulsions, and Methods for the Production of such Emulsions from Said Mixtures. U.S. Patent No. 4,684,479A, 4 August 1987. [Google Scholar]
  106. D’Arrigo, J. Method for the Production of Medical-Grade Lipid-Coated Microbubbles, Paramagnetic Labeling of such Microbubbles and Therapeutic Uses of Microbubbles. U.S. Patent No. 5,215,680A, 1 July 1993. [Google Scholar]
  107. Garg, G.; Saraf, Sh.; Saraf, Sw. Cubosomes: An overview. Biol. Pharm. Bull. 2007, 30, 350–353. [Google Scholar] [CrossRef] [PubMed]
  108. Tanford, C. The Hydrophobic Effect: Formation of Micelles and Biological Membranes; Wiley: New York, NY, USA, 1973; 200p. [Google Scholar]
  109. Boyd, B.J.; Whittaker, D.V.; Khoo, S.M.; Davey, G. Lyotropic liquid crystalline phases formed from glycerate surfactants as sustained release drug delivery systems. Int. J. Pharm. 2006, 309, 218–226. [Google Scholar] [CrossRef] [PubMed]
  110. Pouton, C.W. Properties and uses of common formulation lipids, surfactants and cosurfactants. In Proceedings of the AAPS Workshop, Effective Utilization of Lipid-Based Systems to Enhance the Delivery of Poorly Soluble Drugs: Physicochemical, Biopharmaceutical and Product Development Considerations, Bethesda, MD, USA, 5–6 March 2007; Constantinides, P.P., Porter, C.J.H., Eds.; AAPS: Arlington, VA, USA, 2007. [Google Scholar]
  111. Small, D.M. The behavior of biological lipids. Pure Appl. Chem. 1981, 53, 2095–2103. [Google Scholar] [CrossRef]
  112. Kaasgaard, T.; Drummond, C.J. Ordered 2-D and 3-D nano-structured amphiphile self-assembly materials stable in excess solvent. Phys. Chem. Chem. Phys. 2006, 8, 4957–4975. [Google Scholar] [CrossRef] [PubMed]
  113. Shearman, G.C.; Khoo, B.J.; Motherwell, M.L.; Brakke, K.A.; Ces, O.; Conn, C.E.; Seddon, J.M.; Templer, R.H. Calculations of and evidence for chain packing stress in inverse lyotropic bicontinuous cubic phases. Langmuir 2007, 23, 7276–7285. [Google Scholar] [CrossRef] [PubMed]
  114. Rizwan, S.B.; Dong, Y.D.; Boyd, B.J.; Rades, T.; Hook, S. Characterization of bicontinuous cubic liquid crystalline systems of phytantriol and water using cryo field emission scanning electron microscopy (cryo FESEM). Micron 2007, 38, 478–485. [Google Scholar] [CrossRef] [PubMed]
  115. Yaghmur, A.; de Campo, L.; Sagalowicz, L.; Leser, M.E.; Glatter, O. Emulsified microemulsions and oil-containing liquid crystalline phases. Langmuir 2005, 21, 569–577. [Google Scholar] [CrossRef] [PubMed]
  116. Yaghmur, A.; de Campo, L.; Sagalowicz, L.; Leser, M.E.; Glatter, O. Control of the internal structure of MLO-based isasomes by the addition of diglycerol monooleate and soybean phosphatidylcholine. Langmuir 2006, 22, 9919–9927. [Google Scholar] [CrossRef] [PubMed]
  117. Gustafsson, J.; Ljusberg-Wahren, H.; Almgren, M.; Larsson, K. Submicron particles of reversed lipid phases in water stabilized by a nonionic amphiphilic polymer. Langmuir 1997, 13, 6964–6971. [Google Scholar] [CrossRef]
  118. De Campo, L.; Yaghmur, A.; Sagalowicz, L.; Leser, M.E.; Watzke, H.; Glatter, O. Reversible phase transitions in emulsified nanostructured lipid systems. Langmuir 2004, 20, 5254–5261. [Google Scholar] [CrossRef] [PubMed]
  119. Yaghmur, A.; de Campo, L.; Salentinig, S.; Sagalowicz, L.; Leser, M.E.; Glatter, O. Oil-loaded monolinolein-based particles with confined inverse discontinuous cubic structure (Fd3m). Langmuir 2006, 22, 517–521. [Google Scholar] [CrossRef] [PubMed]
  120. Amselem, S.; Friedman, D. Solid Fat Nanoemulsions. U.S. Patent No. 5,662,932A, 2 September 1997. [Google Scholar]
  121. Larsson, K. Aqueous dispersions of cubic lipid–water phases. Curr. Opin. Colloid Interface Sci. 2000, 5, 64–69. [Google Scholar] [CrossRef]
  122. Luzzati, V. Biological significance of lipid polymorphism: The cubic phases. Curr. Opin. Struct. Biol. 1997, 7, 661–668. [Google Scholar] [CrossRef]
  123. Seddon, J.M.; Zeb, N.; Templer, R.H.; McElhaney, R.N.; Mannock, D.A. An Fd3m lyotropic cubic phase in a binary glycolipid/water system. Langmuir 1996, 12, 5250–5253. [Google Scholar] [CrossRef]
  124. Sagalowicz, L.; Leser, M.E.; Watzke, H.J.; Michel, M. Monoglyceride self-assembly structures as delivery vehicles. Trends Food Sci. Tech. 2006, 17, 204–214. [Google Scholar] [CrossRef]
  125. Abraham, T.; Hato, M.; Harai, M. Glycolipid based cubic nanoparticles: Preparation and structural aspects. Colloids Surf. B Biointerfaces 2004, 35, 107–117. [Google Scholar] [CrossRef] [PubMed]
  126. Kuntsche, J.; Koch, M.H.J.; Drechsler, M.; Bunjes, H. Crystallization behavior of supercooled smectic cholesteryl myristate nanoparticles containing phospholipids as stabilizers. Colloids Surf. B Biointerfaces 2005, 44, 25–35. [Google Scholar] [CrossRef] [PubMed]
  127. Kuntsche, J.; Westesen, K.; Drechsler, M.; Koch, M.H.J.; Bunjes, H. Supercooled smectic nanoparticles: A potential novel carrier system for poorly water-soluble drugs. Pharm. Res. 2004, 21, 1834–1843. [Google Scholar] [CrossRef] [PubMed]
  128. Bing, C.; Ladouceur-Wodzak, M.; Wanner, C.R.; Shelton, J.M.; Richardson, J.A.; Chopra, R. Trans-cranial opening of the blood–brain barrier in targeted regions using a stereotaxic brain axis and focused ultrasound energy. J. Ther. Ultrasound 2014, 2. [Google Scholar] [CrossRef] [PubMed]
  129. Lammers, T.; Koczera, P.; Fokong, S.; Gremse, F.; Ehling, J.; Vogt, M.; Pich, A.; Storm, G.; van Zandvoort, M.; Kiessling, F. Theranostic USPIO-loaded microbubbles for mediating and monitoring blood–brain barrier permeation. Adv. Funct. Mater. 2015, 25, 36–43. [Google Scholar] [CrossRef] [PubMed]
  130. Marquet, F.; Tung, Y.S.; Teichert, T.; Ferrera, V.P.; Konofagou, E.E. Noninvasive, transient and selective blood–brain barrier opening in non-human primates in vivo. PLoS ONE 2011, 6, e22598. [Google Scholar] [CrossRef] [PubMed]
  131. Goliaei, A.; Adhikari, U.; Berkowitz, M.L. Opening of the blood–brain barrier tight junction due to shock wave induced bubble collapse: A molecular dynamics simulation study. ACS Chem. Neurosci. 2015, 6, 1296–1301. [Google Scholar] [CrossRef] [PubMed]
  132. Adhikari, U.; Goliaei, A.; Berkowitz, M.L. Mechanism of membrane poration by shock wave induced nanobubble collapse: A molecular dynamics study. J. Phys. Chem. B 2015, 119, 6225–6234. [Google Scholar] [CrossRef] [PubMed]
  133. Delalande, A.; Leduc, C.; Midoux, P.; Postema, M.; Pichon, C. Efficient gene delivery by sonoporation is associated with microbubble entry into cells and the clathrin-dependent endocytosis pathway. Ultrasound Med. Biol. 2015, 41, 1913–1926. [Google Scholar] [CrossRef] [PubMed]
  134. Kotopoulis, S.; Dimcevski, G.; Gilja, O.H.; Hoem, D.; Postema, M. Treatment of human pancreatic cancer using combined ultrasound, microbubbles, and gemcitabine: A clinical case study. Med. Phys. 2013, 40, 072902. [Google Scholar] [CrossRef] [PubMed]
  135. Kotopoulis, S.; Delalande, A.; Popa, M.; Mamaeva, V.; Dimcevski, G.; Gilja, O.H.; Postema, M.; Gjertsen, B.T.; McCormack, E. Sonoporation-enhanced chemotherapy significantly reduces primary tumour burden in an orthotopic pancreatic cancer xenograft. Mol. Imaging Biol. 2014, 16, 53–62. [Google Scholar] [CrossRef] [PubMed]
  136. D’Arrigo, J.S. Nanotherapy for Alzheimer’s. Chem. Eng. News 2015, 93, 2. [Google Scholar]
  137. Paefgen, V.; Doleschel, D.; Kiessling, F. Evolution of contrast agents for ultrasound imaging and ultrasound-mediated drug delivery. Front. Pharm. 2015, 6, 197. [Google Scholar] [CrossRef] [PubMed]
  138. Qin, J.; Wang, T.Y.; Willmann, J.K. Sonoporation: Applications for cancer therapy. Adv. Exp. Med. Biol. 2016, 880, 263–291. [Google Scholar] [PubMed]
  139. Aubry, J.F.; Tanter, M. MR-guided transcranial focused ultrasound. Adv. Exp. Med. Biol. 2016, 880, 97–111. [Google Scholar] [PubMed]
  140. Castle, J.; Feinstein, S.B. Drug and gene delivery using sonoporation for cardiovascular disease. Adv. Exp. Med. Biol. 2016, 880, 331–338. [Google Scholar] [PubMed]
  141. Burgess, A.; Hynynen, K. Microbubble-assisted ultrasound for drug delivery in the brain and central nervous system. Adv. Exp. Med. Biol. 2016, 880, 293–308. [Google Scholar] [PubMed]
  142. Bouakaz, A.; Zeghimi, A.; Doinikov, A.A. Sonoporation: Concept and mechanisms. Adv. Exp. Med. Biol. 2016, 880, 175–189. [Google Scholar] [PubMed]
  143. Skachkov, I.; Luan, Y.; van der Steen, A.F.W.; de Jong, N.; Kooiman, K. Targeted microbubble mediated sonoporation of endothelial cells in vivo. IEEE Trans. Ultrason. Ferrelectr. Freq. Control 2014, 61, 1661–1667. [Google Scholar] [CrossRef] [PubMed]
  144. Caskey, C.F.; Stieger, S.M.; Qin, S.; Dayton, P.A.; Ferrara, K.W. Direct observations of ultrasound microbubble contrast agent interaction with the microvessel wall. J. Acoust. Soc. Am. 2007, 122, 1191–1200. [Google Scholar] [CrossRef] [PubMed]
  145. Choi, J.J.; Wang, S.; Brown, T.R.; Small, S.A.; Duff, K.E.; Konofagou, E.E. Noninvasive and transient blood–brain barrier opening in the hippocampus of Alzheimer’s double transgenic mice using focused ultrasound. Ultrason. Imaging 2008, 30, 189–200. [Google Scholar] [CrossRef] [PubMed]
  146. Choi, J.J.; Selert, K.; Vlachos, F.; Wong, A.; Konofagou, E.E. Noninvasive and localized neuronal delivery using short ultrasonic pulses and microbubbles. Proc. Natl. Acad. Sci. USA 2011, 108, 16539–16544. [Google Scholar] [CrossRef] [PubMed]
  147. Konofagou, E.E. Optimization of the ultrasound-induced blood–brain barrier opening. Theranostics 2012, 2, 1223–1237. [Google Scholar] [CrossRef] [PubMed]
  148. McDannold, N.; Arvanitis, C.D.; Vykhodtseva, N.; Livingstone, M.S. Temporary disruption of the blood–brain barrier by use of ultrasound and microbubbles: Safety and efficacy evaluation in rhesus macaques. Cancer Res. 2012, 72, 3652–3663. [Google Scholar] [CrossRef] [PubMed]
  149. Raymond, S.B.; Skoch, J.; Hynynen, K.; Bacskai, B.J. Multiphoton imaging of ultrasound/Optison mediated cerebrovascular effects in vivo. J. Cereb. Blood Flow Metab. 2007, 27, 393–403. [Google Scholar] [CrossRef] [PubMed]
  150. Wu, S.Y.; Sanchez, C.S.; Samiotaki, G.; Buch, A.; Ferrera, V.P.; Konofagou, E.E. Characterizing focused-ultrasound mediated drug delivery to the heterogeneous primate brain in vivo with acoustic monitoring. Sci. Rep. 2016, 6, 37094. [Google Scholar] [CrossRef] [PubMed]
  151. Song, K.H.; Fan, A.C.; Hinkle, J.J.; Newman, J.; Borden, M.; Harvey, B.K. Microbubble gas volume: A unifying dose parameter in blood–brain barrier opening by focused ultrasound. Theranostics 2017, 7, 144–152. [Google Scholar] [CrossRef] [PubMed]
  152. Chu, P.C.; Chai, W.Y.; Tsai, C.H.; Kang, S.T.; Yeh, C.K.; Liu, H.L. Focused ultrasound-induced blood–brain barrier opening: Association with mechanical index and cavitation index analyzed by dynamic contrast-enhanced magnetic-resonance imaging. Sci. Rep. 2016, 6, 33264. [Google Scholar] [CrossRef] [PubMed]
  153. Miller, D.B.; O’Callaghan, J.P. New horizons for focused ultrasound (FUS)—Therapeutic applications in neurodegenerative diseases. Metabolism 2017, 69, S3–S7. [Google Scholar] [CrossRef] [PubMed]
  154. Sierra, C.; Acosta, C.; Chen, C.; Wu, S.Y.; Karakatsani, M.E.; Bernal, M.; Konofagou, E.E. Lipid microbubbles as a vehicle for targeted drug delivery using focused ultrasound-induced blood–brain barrier opening. J. Cereb. Blood Flow Metab. 2017, 37, 1236–1250. [Google Scholar] [CrossRef] [PubMed]
  155. Sun, T.; Samiotaki, G.; Wang, S.; Acosta, C.; Chen, C.C.; Konofagou, E.E. Acoustic cavitation-based monitoring of the reversibility and permeability of ultrasound-induced blood–brain barrier opening. Phys. Med. Biol. 2015, 60, 9079–9094. [Google Scholar] [CrossRef] [PubMed]
  156. Poon, C.; McMahon, D.; Hynynen, K. Noninvasive and targeted delivery of therapeutics to the brain using focused ultrasound. Neuropharmacology 2017, 120, 20–37. [Google Scholar] [CrossRef] [PubMed]
  157. Carpentier, A.; Canney, M.; Vignot, A.; Reina, V.; Beccaria, K.; Horodyckid, C.; Karachi, C.; Leclercq, D.; Lafon, C.; Chapelon, J.Y.; et al. Clinical trial of blood–brain barrier disruption by pulsed ultrasound. Sci. Transl. Med. 2016, 8, 343re2. [Google Scholar] [CrossRef] [PubMed]
  158. Leinenga, G.; Gotz, J. Scanning ultrasound removes amyloid-β and restores memory in an Alzheimer’s disease mouse model. Sci. Transl. Med. 2015, 7, 278ra33. [Google Scholar] [CrossRef] [PubMed]
  159. Torrice, M. Alzheimer’s therapy goes acoustic. Chem. Eng. News 2015, 93, 5. [Google Scholar]
  160. Keaney, J.; Walsh, D.M.; O’Malley, T.; Hudson, N.; Crosbie, D.E.; Loftus, T.; Sheehan, F.; McDaid, J.; Humphries, M.M.; Callanan, J.J.; et al. Autoregulated paracellular clearance of amyloid-β across the blood–brain barrier. Sci. Adv. 2015, 1, e1500472. [Google Scholar] [CrossRef] [PubMed]
  161. Alexopoulos, P.; Gleixner, L.S.; Werle, L.; Buhl, F.; Thierjung, N.; Giourou, E.; Kagerbauer, S.M.; Gourzis, P.; Kubler, H.; Grimmer, T.; et al. Plasma levels of soluble amyloid precursor protein β in symptomatic Alzheimer’s disease. Eur. Arch. Psychiatry Clin. Neurosci. 2017. [Google Scholar] [CrossRef] [PubMed]
  162. Aryal, M.; Arvanitis, C.D.; Alexander, P.M.; McDannold, N. Ultrasound-mediated blood–brain barrier disruption for targeted drug delivery in the central nervous system. Adv. Drug Deliv. Res. 2014, 72, 94–109. [Google Scholar] [CrossRef] [PubMed]
  163. Xie, F.; Boska, M.D.; Lof, J.; Uberti, M.G.; Tsutsui, J.M.; Porter, T.R. Effects of transcranial ultrasound and intravenous microbubbles on blood–brain barrier permeability in a large animal model. Ultrasound Med. Biol. 2008, 34, 2028–2034. [Google Scholar] [CrossRef] [PubMed]
  164. Dasgupta, A.; Liu, M.; Ojha, T.; Storm, G.; Kiessling, F.; Lammers, T. Ultrasound-mediated drug delivery to the brain: Principles, progress and prospects. Drug Discov. Today Technol. 2016, 20, 41–48. [Google Scholar] [CrossRef] [PubMed]
  165. Helfield, B.; Chen, X.; Watkins, S.C.; Villanueva, R.S. Biophysical insight into mechanisms of sonoporation. Proc. Natl. Acad. Sci. USA 2016, 113, 9983–9988. [Google Scholar] [CrossRef] [PubMed]
  166. Van Rooij, T.; Skachkov, I.; Beekers, I.; Lattwein, K.R.; Voorneveld, J.D.; Kokhuis, T.J.; Bera, D.; Luan, Y.; van der Steen, A.F.; de Jong, N.; et al. Viability of endothelial cells after ultrasound-mediated sonoporation: Influence of targeting, oscillation, and displacement of microbubbles. J. Control. Release 2016, 238, 197–211. [Google Scholar] [CrossRef] [PubMed]
  167. De Cock, I.; Zagato, E.; Braeckmans, K.; Luan, Y.; de Jong, N.; De Smedt, S.C.; Lentacker, I. Ultrasound and microbubble mediated drug delivery: Acoustic pressure as determinant for uptake via membrane pores or endocytosis. J. Control. Release 2015, 197, 20–28. [Google Scholar] [CrossRef] [PubMed]
  168. Shapiro, G.; Wong, A.; Bez, M.; Yang, F.; Tam, S.; Even, L.; Sheyn, D.; Ben-David, S.; Tawackoli, W.; Pelled, G.; et al. Multiparameter evaluation of in vivo gene delivery using ultrasound-guided, microbubble-enhanced sonoporation. J. Control. Release 2016, 223, 157–164. [Google Scholar] [CrossRef] [PubMed]
  169. Andreone, B.J.; Chow, B.W.; Tata, A.; Lacoste, B.; Ben-Zvi, A.; Bullock, K.; Deik, A.A.; Ginty, D.D.; Clish, C.B.; Gu, C. Blood–brain barrier permeability is regulated by lipid transport-dependent suppression of caveolae-mediated transcytosis. Neuron 2017, 94, 581–594.e5. [Google Scholar] [CrossRef] [PubMed]
  170. Ben-Zvi, A.; Lacoste, B.; Kur, E.; Andreone, B.; Mayshar, Y.; Yan, H.; Gu, C. MFSD2A is critical for the formation and function of the blood–brain barrier. Nature 2014, 509, 507–511. [Google Scholar] [CrossRef] [PubMed]
  171. Chow, B.W.; Gu, C. Gradual suppression of transcytosis governs functional blood–retinal barrier formation. Neuron 2017, 93, 1325–1333. [Google Scholar] [CrossRef] [PubMed]
  172. Aw, M.S.; Paniwnyk, L.; Losic, D. The progressive role of acoustic cavitation for non-invasive therapies, contrast imaging and blood-tumor permeability enhancement. Expert Opin. Drug Deliv. 2016, 13, 1383–1396. [Google Scholar] [CrossRef] [PubMed]
  173. Park, J.; Fan, Z.; Kumon, R.E.; El-Sayed, M.E.; Deng, C.X. Modulation of intracellular Ca2+ concentration in brain microvascular endothelial cells in vitro by acoustic cavitation. Ultrasound Med. Biol. 2010, 36, 1176–1187. [Google Scholar] [CrossRef] [PubMed]
  174. Alonso, A.; Reinz, E.; Jenne, J.W.; Fatar, M.; Schmidt-Glenewinkel, H.; Hennerici, M.G.; Meairs, S. Reorganization of gap junctions after focused ultrasound blood–brain barrier opening in the rat brain. J. Cereb. Blood Flow Metab. 2010, 30, 1394–1402. [Google Scholar] [CrossRef] [PubMed]
  175. Alonso, A.; Reinz, E.; Fatar, M.; Hennerici, M.G.; Meairs, S. Clearance of albumin following ultrasound-induced blood–brain barrier opening is mediated by glial but not neuronal cells. Brain Res. 2011, 1411, 9–16. [Google Scholar] [CrossRef] [PubMed]
  176. Aslund, A.K.O.; Snipstad, S.; Healey, A.; Kvale, S.; Torp, S.H.; Sontum, P.C.; de Lange Davies, C.; van Wamel, A. Efficient enhancement of blood–brain barrier permeability using acoustic cluster therapy (ACT). Theranostics 2017, 7, 23–30. [Google Scholar] [CrossRef] [PubMed]
  177. Delalande, A.; Kotopoulis, S.; Postema, M.; Midoux, P.; Pichon, C. Sonoporation: Mechanistic insights and ongoing challenges for gene transfer. Gene 2013, 525, 191–199. [Google Scholar] [CrossRef] [PubMed]
  178. Meairs, S. Facilitation of drug transport across the blood–brain barrier with ultrasound and microbubbles. Pharmaceutics 2015, 7, 275–293. [Google Scholar] [CrossRef] [PubMed]
  179. Meng, Y.; Volpini, M.; Black, S.; Lozano, A.M.; Hynynen, K.; Lipsman, N. Focused US as a novel strategy for Alzheimer’s disease therapeutics. Ann. Neurol. 2017, 81, 611–617. [Google Scholar] [CrossRef] [PubMed]
  180. Horodyckid, C.; Canney, M.; Vignot, A.; Boisgard, R.; Drier, A.; Huberfeld, G.; François, C.; Prigent, A.; Santin, M.D.; Adam, C.; et al. Safe long-term repeated disruption of the blood–brain barrier using an implantable ultrasound device: A multiparametric study in a primate model. J. Neurosurg. 2017, 126, 1351–1361. [Google Scholar] [CrossRef] [PubMed]
  181. O’Reilly, M.A.; Hough, O.; Hynynen, K. Blood–brain barrier closure time after controlled ultrasound-induced opening is independent of opening volume. J. Ultrasound Med. 2017, 36, 475–483. [Google Scholar] [CrossRef] [PubMed]
  182. Sennoga, C.A.; Kanbar, E.; Auboire, L.; Dujardin, P.A.; Fouan, D.; Escoffre, J.M.; Bouakaz, A. Microbubble-mediated ultrasound drug-delivery and therapeutic monitoring. Expert Opin. Drug Deliv. 2017, 14, 1031–1043. [Google Scholar] [CrossRef] [PubMed]
  183. Baranova, I.N.; Vishnyakova, T.G.; Bocharov, A.V.; Kurlander, R.; Chen, Z.; Kimelman, M.L.; Remaley, A.T.; Csako, G.; Thomas, F.; Eggerman, T.L.; et al. Serum amyloid A binding to CLA-1 (CD36 and LIMPII analogous-1) mediates serum amyloid A protein-induced activation of ERK1/2 and p38 mitogen-activated protein kinases. J. Biol. Chem. 2005, 280, 8031–8040. [Google Scholar] [CrossRef] [PubMed]
  184. Wasan, K.M.; Brocks, D.R.; Lee, S.D.; Sachs-Barrable, K.; Thornton, S.J. Impact of lipoproteins on the biological activity and disposition of hydrophobic drugs: Implications for drug discovery. Nat. Rev. Drug Discov. 2008, 7, 84–99. [Google Scholar] [CrossRef] [PubMed]
  185. Out, R.; Kruijt, J.K.; Rensen, P.C.; Hildebrand, R.B.; de Vos, P.; van Eck, M.; Van Berkel, T.J. Scavenger receptor BI plays a role in facilitating chylomicron metabolism. J. Biol. Chem. 2004, 279, 18401–18406. [Google Scholar] [CrossRef] [PubMed]
  186. Rensen, P.C.N.; van Dijk, M.C.M.; Havenaar, E.C.; Bijsterbosch, M.K.; Kruijt, J.K.; van Berkel, T.J.C. Selective liver targeting of antivirals by recombinant chylomicrons: A new therapeutic approach to hepatitis B. Nat. Med. 1995, 1, 221–225. [Google Scholar] [CrossRef] [PubMed]
  187. Williams, K.J.; Scanu, A.M. Uptake of endogenous cholesterol by a synthetic lipoprotein. Biochim. Biophys. Acta 1986, 875, 183–194. [Google Scholar] [CrossRef]
  188. Levine, D.M.; Gordon, B.R.; Parker, T.S.; Rubin, A.L.; Saal, S.D.; Simon, S.R. Reconstituted HDL Particles and Uses Thereof. U.S. Patent No. 5,128,318A, 7 July 1992. [Google Scholar]
  189. Lund-Katz, S.; Phillips, M.C. High-density lipoprotein structure–function and role in reverse cholesterol transport. Subcell Biochem. 2010, 51, 183–227. [Google Scholar] [PubMed]
  190. Lacko, A.G.; Nair, N.; Prokai, L.; McConathy, W.J. Prospects and challenges of the development of lipoprotein-based formulations for anti-cancer drugs. Expert Opin. Drug Deliv. 2007, 4, 665–675. [Google Scholar] [CrossRef] [PubMed]
  191. Azeem, A.; Rizwan, M.; Ahmad, F.J.; Iqbal, Z.; Khar, R.K.; Aqil, M.; Talegaonkar, S. Nanoemulsion components screening and selection: A technical note. AAPS PharmSciTech 2009, 10, 69–76. [Google Scholar] [CrossRef] [PubMed]
  192. Sagar, G.H.; Arunagirinathan, M.A.; Bellare, J.R. Self-assembled surfactant nano-structures important in drug-delivery: A review. Indian J. Exp. Biol. 2007, 45, 133–159. [Google Scholar]
  193. Anton, N.; Benoit, J.P.; Saulnier, P. Design and production of nanoparticles formulated from nano-emulsion templates: A review. J. Control. Release 2008, 128, 185–199. [Google Scholar] [CrossRef] [PubMed]
  194. Bansal, T.; Mustafa, G.; Khan, Z.I.; Ahmad, F.J.; Khar, R.K.; Talegaonkar, S. Solid self-nanoemulsifying delivery systems as a platform technology for formulation of poorly soluble drugs. Crit. Rev. Ther. Drug Carrier Syst. 2008, 25, 63–116. [Google Scholar] [CrossRef] [PubMed]
  195. Sadurni, N.; Solans, C.; Azemar, N.; Garcia-Celma, M.J. Studies on the formation of O/W nano-emulsions, by low-energy emulsification methods, suitable for pharmaceutical applications. Eur. J. Pharm. Sci. 2005, 26, 438–445. [Google Scholar] [CrossRef] [PubMed]
  196. Tresset, G. The multiple faces of self-assembled lipidic systems. PMC Biophys. 2009, 2, 3. [Google Scholar] [CrossRef] [PubMed]
  197. Hato, M.; Yamashita, J.; Shiono, M. Aqueous phase behavior of lipids with isoprenoid type hydrophobic chains. J. Phys. Chem. B 2009, 113, 10196–10209. [Google Scholar] [CrossRef] [PubMed]
  198. Barauskas, J.; Cervin, C.; Tiberg, F.; Johnsson, M. Structure of lyotropic self-assembled lipid nonlamellar liquid crystals and their nanoparticles in mixtures of phosphatidyl choline and α-tocopherol (vitamin E). Phys. Chem. Chem. Phys. 2008, 10, 6483–6485. [Google Scholar] [CrossRef] [PubMed]
  199. Efrat, R.; Aserin, A.; Garti, N. On structural transitions in a discontinuous micellar cubic phase loaded with sodium diclofenac. J. Colloid Interface Sci. 2008, 321, 166–176. [Google Scholar] [CrossRef] [PubMed]
  200. Yaghmur, A.; Laggner, P.; Almgren, M.; Rappolt, M. Self-assembly in monoelaidin aqueous dispersions: Direct vesicles to cubosomes transition. PLoS ONE 2008, 3, e3747. [Google Scholar] [CrossRef] [PubMed]
  201. Yaghmur, A.; Glatter, O. Characterization and potential applications of nanostructured aqueous dispersions. Adv. Colloid Interface Sci. 2009, 147–148, 333–342. [Google Scholar] [CrossRef] [PubMed]
  202. Vandoolaeghe, P.; Rennie, A.R.; Campbell, R.A.; Nylander, T. Neutron reflectivity studies of the interaction of cubic phase nanoparticles with phospholipid bilayers of different coverage. Langmuir 2009, 25, 4009–4020. [Google Scholar] [CrossRef] [PubMed]
  203. Vandoolaeghe, P.; Barauskas, J.; Johnsson, M.; Tiberg, F.; Nylander, T. Interaction between lamellar (vesicles) and nonlamellar lipid liquid-crystalline nanoparticles as studied by time-resolved small-angle X-ray diffraction. Langmuir 2009, 25, 3999–4008. [Google Scholar] [CrossRef] [PubMed]
  204. Yaghmur, A.; Kriechbaum, M.; Amenitsch, H.; Steinhart, M.; Laggner, P.; Rappolt, M. Effects of pressure and temperature on the self-assembled fully hydrated nanostructures of monoolein–oil systems. Langmuir 2010, 26, 1177–1185. [Google Scholar] [CrossRef] [PubMed]
  205. Fong, W.K.; Hanley, T.; Boyd, B.J. Stimuli responsive liquid crystals provide “on-demand” drug delivery in vitro and in vivo. J. Control. Release 2009, 135, 218–226. [Google Scholar] [CrossRef] [PubMed]

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