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ACS Nano
ACS Nano
nn
ancac3
ACS Nano
1936-0851
1936-086X
American Chemical Society

39167921
10.1021/acsnano.4c02012
Article
Donepezil Nanoemulsion Induces a Torpor-like State with Reduced Toxicity in Nonhibernating Xenopus laevis Tadpoles
Plaza Oliver Maria †‡§
Gardner Erica †
Lin Tiffany †
Sheehan Katherine †
Sperry Megan M. †
Lightbown Shanda †
Martínez Manuel Ramsés †
del Campo Daniela †
Fotowat Haleh †
Lewandowski Michael †
Takeda Takako †
C. Pauer Alexander †
Kaushal Shruti †
Gnyawali Vaskar †
https://orcid.org/0000-0001-7774-732X
Lozano Maria V. ‡§
Santander Ortega Manuel J. ‡§
Novak Richard †
Super Michael †
https://orcid.org/0000-0002-4319-6520
Ingber Donald E. *†∥⊥
† Wyss Institute for Biologically Engineering at Harvard University, Boston, Massachusetts 02215, United States
‡ Development and Evaluation of Nanodrugs (DEVANA) Group, Faculty of Pharmacy and Biomedicine Institute at University of Castilla-La Mancha, 02008 Albacete, Spain
§ Castilla-La Mancha Health Research Institute (IDISCAM), 02071 Albacete, Spain
∥ Vascular Biology Program & Department of Surgery, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts 02115, United States
⊥ Harvard John A. Paulson School of Engineering and Applied Sciences, Boston, Massachusetts 02134, United States
* Email: don.ingber@wyss.harvard.edu.
21 08 2024
03 09 2024
18 35 2399124003
09 02 2024
21 06 2024
20 06 2024
© 2024 The Authors. Published by American Chemical Society
2024
The Authors
https://creativecommons.org/licenses/by-nc-nd/4.0/ Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Achieving a reversible decrease of metabolism and other physiological processes in the whole organism, as occurs in animals that experience torpor or hibernation, could contribute to increased survival after serious injury. Using a Bayesian network tool with transcriptomic data and chemical structure similarity assessments, we predicted that the Alzheimer’s disease drug donepezil (DNP) could be a promising candidate for a small molecule drug that might induce a torpor-like state. This was confirmed in a screening study with Xenopus laevis tadpoles, a nonhibernator whole animal model. To improve the therapeutic performance of the drug and minimize its toxicity, we encapsulated DNP in a nanoemulsion formulated with low-toxicity materials. This formulation is composed of emulsified droplets <200 nm in diameter that contain 1.250 mM DNP, representing ≥95% encapsulation efficiency. The DNP nanoemulsion induced comparable torpor-like effects to those produced by the free drug in tadpoles, as indicated by reduced swimming motion, cardiac beating frequency, and oxygen consumption, but with an improved biodistribution. Use of the nanoemulsion resulted in a more controlled increase of DNP concentration in the whole organism compared to free DNP, and to a higher concentration in the brain, which reduced DNP toxicity and enabled induction of a longer torpor-like state that was fully reversible. These studies also demonstrate the potential use of Xenopus tadpoles as a high-throughput in vivo screen to assess the efficacy, biodistribution, and toxicity of drug-loaded nanocarriers.

donepezil
nanoemulsion
torpor
Xenopus laevis
tadpoles
Army Research Office 10.13039/100000183 W911NF-19-2-0027 Junta de Comunidades de Castilla-La Mancha 10.13039/501100011698 SBPLY/21/180501/000077 European Regional Development Fund 10.13039/501100008530 SBPLY/21/180501/000077 Universidad de Castilla-La Mancha 10.13039/501100007480 UNI/551/2021 Ministerio de Ciencia e InnovaciÃ³n 10.13039/501100004837 PID2021-122703NA-I00 Ministerio de Ciencia, InnovaciÃ³n y Universidades 10.13039/100014440 UNI/551/2021 Defense Advanced Research Projects Agency 10.13039/100000185 W911NF-19-2-0027 document-id-old-9nn4c02012
document-id-new-14nn4c02012
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pmcIntroduction

Hibernation and torpor enable some animals to survive under harsh environmental conditions, including extreme temperatures and low food availability. This adaptative response actively reduces their physical activity and body temperature, as well as oxygen consumption, cardiac beating frequency, and metabolic state.1,2 The extraordinary ability of these animals to cope with otherwise lethal circumstances has raised great interest in emergency medicine.3 Patients suffering massive hemorrhage or cardiac arrest after serious trauma rarely survive if they cannot be rapidly treated. Thus, artificially inducing a reversible torpor-like state in the whole organism could save critical time and avoid irreversible organ injury. Currently, hypothermia is used clinically to decrease metabolism and ensure organ preservation during processes, such as cardiac surgery or organ transplants.4,5 Unfortunately, hypothermia is challenging to implement in emergency situations that occur in remote settings where specialized personnel may not be present, and the immediate availability of resources is limited.

Although the mechanisms that underlie hibernation and torpor are complex and are only poorly understood, it is known that the central nervous system plays a relevant role.6−8 For example, a torpor-like state was induced in rodents for 24 h following ultrasound application to the hypothalamus.9 However, despite the undeniable interest in this device-based approach, its translatability to humans and applicability in the clinic are still unknown. Another alternative would be to develop a small molecule drug that can be administered to artificially induce a torpor-like state, which also could be implemented at home, in ambulances, or in remote areas. Several compounds have been proposed to achieve this, including the gas H2S,10−12 AMP or adenosine agonists,13,14 and neural signaling metabolites.15 We also recently demonstrated that the delta opioid agonist SNC80 can induce a torpor-like state in nonhibernating Xenopus laevis tadpoles as well as significantly slow metabolism in excised pig hearts and limbs.16 However, SNC80 is not approved for clinical use due to its potential convulsant activity.17

In the current study, we set out to identify existing FDA-approved drugs that might be repurposed as a “biostasis therapeutic” that induces a reversible torpor-like state. To accomplish this, we leveraged a high-throughput, whole-organism, Xenopus laevis tadpole screen18 to test drugs that we identified using the computational Network Models for Causally Aware Discovery (NeMoCAD) algorithm that uses machine-learning-based Bayesian network analysis for drug repurposing.19,20 We also used a nanotechnology-based drug delivery approach to improve the biodistribution, efficacy, and duration of action of the biostasis inducer we identified while decreasing its toxicity.

Results and Discussion

Achieving a reversible torpor-like state (defined here as a generalized decrease of biological activity and metabolism) could increase survival possibilities in emergency situations that occur in isolated areas with limited availability of resources. In previous work, we demonstrated that SNC80 can induce a torpor-like state in nonhibernating Xenopus laevis tadpoles.16 In the present study, we aimed to identify an FDA-approved compound that could induce a torpor-like state with higher potential translatability to the clinic. Using RNA sequencing data from tadpoles treated with SNC80 and our previously described NeMoCAD drug repurposing tool (Figure 1a),19,20 378 compounds were predicted to mimic this state of physiological slowing, including 197 FDA-approved drugs. We then evaluated the predicted compounds for structural similarity to SNC80, using two-dimensional chemical fingerprints from PubChem and calculation of the Tanimoto coefficient.21 This led to the identification of donepezil (DNP), which exhibited the highest structural similarity to SNC80 across the compounds predicted by NeMoCAD (Figure 1b). DNP is a reversible inhibitor of acetylcholinesterase approved by the FDA for the improvement of cognition and behavior in patients suffering from Alzheimer’s disease.22 Interestingly, DNP has been reported to induce a lethargic state, including bradycardia and confusion, in patients with Alzheimer’s disease receiving an overdose of this drug.23 Thus, DNP became a lead candidate for our next studies.

Figure 1 Biostasis drug selection methodology based on (a) drug predictions obtained with Network Models for Causally Aware Discovery (NeMoCAD) using transcriptional inputs and (b) chemical similarity of the predicted compounds to SNC80. LINCS: Library of Integrated Network-Based Cellular Signatures. CTD: Comparative Toxicogenomics Database. KEGG: Kyoto Encyclopedia of Genes and Genomes. TRRUST: Transcriptional regulatory relationships unraveled by sentence-based text-mining.

Following the NeMoCAD results, we next explored whether DNP could induce a torpor-like state in vivo using Xenopus laevis tadpoles as a high-throughput, nonhibernating animal model. To identify a relevant dose, we first carried out cytotoxicity studies using lactate dehydrogenase (LDH) in cultured human Caco-2 intestinal epithelial cells. We tested a range of DNP doses from 12.5 to 100 μM and found that the half-maximal lethal concentration (LD50) was not reached, even at the highest DNP dose tested (100 μM; Figure S1), indicating a low cytotoxicity profile of DNP after a 4 h treatment.

Based on these results, we then treated tadpoles with 50 or 100 μM DNP for 4 h. We previously demonstrated that a reduction of swimming motion indicates the induction of a torpor-like state in tadpoles, and that recovered tadpoles showed normal swimming activity after treatment with a biostasis inducer.16 However, although all DNP-treated tadpoles decreased their swimming motion, none of these animals demonstrated reversible responses (data not shown). Therefore, we decreased the treatment time to 2 h and screened similar and lower DNP concentrations (100, 50, 20, and 10 μM). This dose–response study revealed that only tadpoles treated with 50 μM DNP reduced their swimming motion in a reversible manner (Figure 2a, b). The evident differences between the in vitro results with Caco-2 cells and these in vivo results encouraged the use of tadpoles as a potentially more physiological way to screen drug toxicity before moving to large animal studies. In any case, these pilot studies in tadpoles allowed us to confirm the potential of DNP to act as a torpor-like inducer and to select a 50 μM dose and 2 h treatment time for subsequent studies.

Figure 2 Effect of different concentrations of DNP on the swimming motion of tadpoles (n = 3 replicates with 10 tadpoles per replicate and condition) expressed by (a) Normalized movement index, being 0 indicative of lack of swimming and 1 of maximal swimming. (b) Area under the curve (AUC) of tadpole motion, calculated from movement index data. A decrease in the AUC of tadpole motion implies efficacy of the treatment with that dose of DNP. The survival of tadpoles after the treatment (in both immediate and 24 h recovery) is indicated by AUC values close to the values obtained for untreated tadpoles (0 μM DNP), while decreased AUC during the recovery shows toxicity (irreversible treatment due to overdosing).

To reduce the toxicity of DNP for this application, which would likely require induction of a torpor state for longer periods of time, we encapsulated the drug into nanocarriers. Nanoemulsions, liposomes, lipid nanoparticles, and other types of nanocarriers have been shown to minimize the toxicity of their cargo molecules, as well as provide additional biopharmaceutical advantages, such as increased bioavailability and targeted delivery.24,25 Considering the physicochemical properties of DNP and the final aim of the formulation, we decided to use nanoemulsions to encapsulate DNP (Figure 3a). The rational design of the formulation allowed us to minimize the number of excipients, resulting in an oily core of soybean oil emulsified with soy lecithin. We also included a low concentration (1 mg/mL) of Pluronic F-127 to confer additional stability. These components are generally regarded as safe and have been previously used in food, cosmetic, and drug delivery applications.26

Figure 3 Design and characterization of DNP nanoemulsions. (a) Schematic illustration of DNP nanoemulsions, which are based on an oily core dispersed in a water phase and stabilized by lecithin. (b) DNP nanoemulsions size distribution. (c) Representative TEM images of DNP nanoemulsions, showing their spherical shape. (d, e) Stability of DNP nanoemulsions stored at 4 °C, based on their physicochemical properties (d) and encapsulated DNP into the oily core of nanoemulsions (e) (n = 3 replicates, with 2 measurements per replicate).

Control (empty) and DNP-loaded nanoemulsions were formulated using a solvent displacement method under mild conditions and they displayed a hydrodynamic mean diameter of 190 ± 8 nm and 188 ± 8 nm, respectively. The high hydrophobicity of the oily core, conferred by the long-chain fatty acids in soybean oil, enabled the accommodation of DNP up to a final concentration of 1.25 mM with a high encapsulation efficacy (≥95%). Both nanoemulsions showed a narrow size distribution (polydispersion <0.200, Figure 3b) and negative superficial charge of −35 ± 7 mV (control) and −32 ± 5 mV (DNP-loaded). Transmission electron microscopy (TEM) showed that the nanoemulsions were composed of spherical droplets and confirmed their mean diameters obtained by dynamic light scattering (Figure 3c). Given the similar physicochemical properties of control and drug-loaded nanoemulsions, as well as the high encapsulation efficacy achieved, it is likely that DNP is primarily located inside the oily matrix of the nanoemulsion.27

Storage stability is an important requirement to enable the commercial and clinical translation of nanoemulsions. If not properly formulated, nanoemulsions are unstable, leading to massive aggregation and phase separation.28 Importantly, we found that both the control and DNP nanoemulsions stored at 4 °C showed a satisfactory stability profile, maintaining their physicochemical properties for at least 4 months (Figures S2 and 3d, respectively). Moreover, the DNP nanoemulsions did not show any significant leakage of the drug during this period (≤5%, Figure 3e).

Once the nanoemulsions were properly characterized, we then focused on assessing their potential to deliver DNP as an inducer of a reversible torpor-like state using Xenopus laevis tadpoles as a nonhibernator, whole animal model. Previous work using tadpoles and nanocarriers focused on the toxicity of metal-based nanoparticles29−33 or on the effects of lipid enrichment based on empty liposomes.34−36 In this study, we propose the use of this in vivo whole organism model to test therapeutic delivery using drug-loaded nanocarriers.

Tadpoles were treated by dispersing the free drug or nanoemulsion directly within their culture medium. The nanoemulsion remained perfectly stable in this medium with no sign of aggregation or flocculation, and it maintained its physicochemical properties, as confirmed using dynamic light scattering. DNP was not released to the medium from the nanoemulsion, as confirmed by HPLC (<5% release after 24 h).

The group treated with the control nanoemulsion for 8 h did not show any apparent difference in swimming movement or viability compared to the untreated group, confirming the safety of this nanoemulsion for drug delivery. When we compared the effects of treating the tadpoles with 50 μM DNP as a free drug or when loaded in the nanoemulsion for up to 8 h, we found that both groups entered a torpor-like state; importantly, however, only the DNP nanoemulsion group exhibited reversible effects (Figure 4a). As previously observed, tadpoles treated with 50 μM free DNP did not survive longer than ∼3 h and they exhibited severe morphological alterations (Figure 4b). In contrast, tadpoles treated with the same dose of DNP, but formulated as a nanoemulsion, showed a 100% survival rate after 2 h and ∼70% after 8 h, with no relevant morphological alterations. Collectively, these results showed the promise of using this nanoemulsion formulation to induce a torpor-like state more safely and to sustain this for longer times compared to the same dose of free DNP.

Figure 4 Toxicity of DNP and DNP nanoemulsion in Xenopus laevis tadpoles. (a) Survival probability of tadpoles treated for increasing periods of time. Results derived from control and control nanoemulsion groups overlay (100% survival at the last time point) (n = 10 per time point and group). (b) Representative bright-field microscopy images of tadpoles 24 h after their treatment with DNP or DNP nanoemulsion for increasing periods of time. Alterations of morphology were observed for 100% (n = 10) of the tadpoles treated with free DNP for 4 or 8 h, but the appearance of recovered tadpoles treated with DNP nanoemulsion was comparable to the observed for control and control nanoemulsion groups (not shown).

We also explored whether the use of the nanoemulsion influences DNP uptake by tadpoles by analyzing DNP concentrations within whole tadpole lysates collected over the 8 h treatment period. Beginning after approximately 1 h, tadpoles treated with free drug exhibited a nearly linear increase of DNP concentration over study time, while levels of DNP tapered off in the nanoemulsion group (Figure 5a). Interestingly, for all of the time points, the DNP concentration was significantly higher for the groups treated with the free drug compared to those treated with the DNP nanoemulsion. Given the effects on swimming we observed, these findings suggest that the use of the nanoemulsion decreases DNP toxicity while maintaining a therapeutic effect by altering the drug’s pharmacokinetic profile and preventing the rise to high concentrations that result when a free drug is administered.

Figure 5 In vivo concentration and biodistribution of DNP and DNP nanoemulsion in Xenopus laevis tadpoles. (a) DNP concentration within whole tadpole lysates quantified by Mass spectrometry (n = 3 replicates per group and time point with 3 tadpoles per replicate). (b) Biodistribution of DNP after treatment of tadpoles with DNP or DNP nanoemulsion for 1 h (n ≥ 6 replicates per group and body region) assessed by MALDI-ToF. GI: gastrointestinal. Statistical comparisons were performed using two-way ANOVA with Tukey’s (a) or Sidak’s (b) corrections for multiple comparisons. (c) MALDI-ToF representative positive ion images (380.492 m/z [M + H]+) of DNP distribution in tadpoles treated for 1 h. Each pixel represents a mass spectrum. White dashes represent regions of the brain. (d) Representative histology and MALDI-ToF positive ion images of DNP distribution in the tadpole brain at 380.492 m/z [M + H]+. Each pixel represents a mass spectrum. Tadpoles were treated for 1 h. Scale bar represents 50 μm.

In addition, we analyzed the biodistribution of both free and encapsulated DNP using matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS) spatial imaging. To ensure tadpole viability, we evaluated the biodistribution of DNP after 1 h of treatment based on our earlier results (Figure 4a). These studies revealed that DNP appeared in different areas of the tadpoles, including the gastrointestinal tract, the gills, the muscle, and the brain, suggesting a full-body distribution with both formulations (Figure 5b,c). Interestingly, however, the DNP concentration was significantly higher in the brains of the tadpoles treated with the nanoemulsion than in animals treated with free DNP (Figure 5b,d), which supports the reported central role that the central nervous system plays in the regulation of hibernation and torpor.6−8,37−39 Indeed, both intracranial injection of drugs and ultrasound applications targeting regions in the central nervous system have been reported to induce a torpor-like state in nonhibernating rodents.9,40,41 Thus, the ability of the nanoemulsion to attain a higher DNP concentration in the brain, while maintaining lower total systemic levels, may in part explain the increased efficacy and decreased toxicity we observed using this formulation compared with administering free DNP.

In this study, we administered the DNP nanoemulsion by adding it to the tadpoles’ culture medium, and thus, we could not control the route of absorption as different mucosal sites were available for the absorption process, including their skin and gastrointestinal tract, which are both covered by a protective layer of mucus.42 However, considering the biodistribution results, the significantly higher DNP concentrations achieved in the whole tadpole after the 1 h treatment with the free drug (Figure 5a), and that past work has shown increased absorption via oral and nasal routes,43,44 it is possible that the DNP nanoemulsion is absorbed via a different route compared to the free drug (e.g., via nasal and oral routes rather than skin and oral). For example, the absorption of DNP nanoemulsions through nasal mucosa also could deliver DNP directly to the brain via the olfactory bulb. Absorbed nanoemulsions also could lead to increased DNP concentrations in the brain by improving their transport across the blood-brain barrier. Future studies will be necessary to investigate these possibilities and to obtain better insight into the role that nanoemulsion plays in DNP biodistribution and brain penetration.

In our next set of studies, we assessed the ability of DNP to induce a torpor-like state in naturally nonhibernating Xenopus laevis tadpoles and the impact of using the nanoemulsion delivery approach. Hibernation and torpor involve a generalized reduction in physical activity, metabolism, temperature, and cardiac frequency. We did not analyze changes in temperature because Xenopus laevis is an ectothermic animal. In contrast, we previously demonstrated that tadpoles in a torpor-like state reduce their swimming activity to save energy.16 Thus, we first studied the effect of treating tadpoles with 50 μM DNP on their swimming activity when delivered either as a free drug or encapsulated in a nanoemulsion. After 1 h treatment with free DNP, tadpole motion decreased by almost 80%, and they recovered swimming activity comparable to that in the control group when they were transferred to a fresh medium (Figure 6a). This swimming reduction was reversible after 2 h (Figure 6b), but it was irreversible after 4 h (Figure 6c) or 8 h (Figure 6d) treatments. These results made sense considering the toxicity shown by free DNP described above. In contrast, tadpoles treated with the same DNP dose formulated as a nanoemulsion decreased their swimming motion by ∼40% after 1 h and by ∼65% after 2, 4, or 8 h (Figure 6a–d). Most importantly, this reduction was reversible after all of the treatment times tested (Figure 6d). The control nanoemulsion lacking the drug did not have any effect on the swimming activity (Figure 6a–d), so the results observed with the DNP nanoemulsion clearly resulted from the delivery of the encapsulated drug.

Figure 6 Effect of DNP and DNP nanoemulsion on (a–e) swimming motion (n = 2 replicates with 10 tadpoles per replicate and condition). Tadpoles were treated for (a) 1 h, (b) 2, (c) 4, or (d) 8 h, and then they were let to recover; and (e, f) Cardiac frequency (n = 10 tadpoles per group and time point). Statistical comparisons (e, f) were performed using 2-way ANOVA with Tukey’s corrections for multiple comparisons. Tadpoles not surviving 24 h after the treatment (0 heart beats per min) were not included in the graph nor considered for the statistical analysis (f).

Because hibernation and torpor are normally associated with a reversible and profound reduction in heart rate,1 we next measured the effects of the different DNP formulations on cardiac frequency in the tadpoles over 8 h. Irrespective of the treatment duration, tadpoles treated with free DNP (50 μM) showed a significant reduction in the heart rate, compared to the control group (Figure 6e). Interestingly, clinical overdoses of donepezil have been found to induce bradycardia in Alzheimer's disease patients as well.23 Tadpoles treated with free DNP for up to 2 h showed a ∼ 50% reduction in the heart rate, which is lower than the ∼75% reduction reported in mice under torpor.45 However, in contrast to mice, tadpoles do not normally experience torpor, and thus, the decrease in cardiac frequency shows that a torpor-like state can be artificially achieved using this dose of DNP. Tadpoles treated for 1 or 2 h recovered 24 h post-treatment, showing cardiac activity comparable to that of the control group (Figure 6f). On the other hand, increasing the treatment time to 4 or 8 h led to a marked reduction of the heart rate (Figure 6e). This time-dependent decrease of the heart rate observed for free DNP correlates with the close-to-linear drug concentration increase over time in the tadpoles (Figure 5a). Consistent with the toxicity studies detailed above, tadpoles did not recover after prolonged treatments (4 or 8 h; Figure 6f). Indeed, the dramatic decrease in heart rate observed in tadpoles after 4 or 8 h could explain the irreversibility of the treatment after these times. This hypothesis is consistent with the need to administer atropine as an antidote for severe donepezil overdose, described in humans to avoid cardiac arrest.23

In contrast, while tadpoles treated with the same DNP dose formulated as a nanoemulsion also showed a significantly slowed heart rate, the cardiac suppression effect of the encapsulated DNP remained constant over the 8 h treatment period (Figure 6e). This effect again correlates with the lower concentration of DNP that is sustained over time in vivo using the nanoemulsion delivery approach (Figure 5a), and most importantly, this difference in pharmacokinetics enabled the tadpoles that survived (70% for both 4 and 8 h treatments) to almost fully recover a normal cardiac frequency 24 h after treatment (Figure 6f).

Another relevant goal of hibernation and torpor is to minimize energy expenditure to survive when food availability is limited. This can be achieved by a complex and regulated decrease of metabolism in the whole body, which entails a profound reduction in oxygen consumption.1,2 To evaluate the effect of DNP on oxygen consumption, we first cultured untreated tadpoles in sealed vials with integrated oxygen sensors and determined that it took ∼3 h for them to consume all the oxygen available in the vial. When we quantified oxygen consumption by tadpoles treated in sealed vials containing 50 μM free DNP for 3 h, we observed significantly lower oxygen consumption compared to the control group (Figure 7). When we carried out this study with the same dose of encapsulated DNP, the oxygen consumption was also dramatically lower, showing no significant differences compared to the free drug, whereas the control unloaded nanoemulsion did not have any effect on oxygen consumption.

Figure 7 Effect of DNP and DNP nanoemulsion on oxygen consumption (n = 10 replicates in control group and n = 11 replicates in the rest of groups, with 2 tadpoles per replicate). The graph refers to the first 3 h of treatment, which was the time used by tadpoles in the control group to consume ≈100% of the oxygen available. Statistical comparisons were performed using 1-way ANOVA.

Collectively, these data demonstrate that encapsulating DNP within the nanoemulsion greatly improved the drug’s ability to induce a reversible torpor-like state in nonhibernating tadpoles, while at the same time greatly reducing its toxicity. We have previously demonstrated that results obtained in tadpoles highly correlate with those observed in other vertebrates,16 so we believe that there is a high likelihood that the DNP nanoemulsion will be able to induce a reversible torpor-like state in other nonhibernating animals. Also, the good safety profile of this DNP nanoemulsion shown in vivo and its potential to be absorbed via a mucosal route and reach the brain could extend the use of DNP nanoemulsions for additional applications, such as the treatment of dementia disorders.

Study Limitations

In this article, we describe a DNP nanoemulsion that can artificially induce a reversible torpor-like state in tadpoles. Despite the exciting results, we are aware that there are some limitations to be addressed in future work. First, future studies will need to provide greater insight into the mechanism of action that underlies the torpor-like-inducing activity of DNP. Gaining this type of information could also help to develop on-demand recovery therapies. Second, to ensure the translatability of the DNP nanoemulsion developed in this work, the formulation will need to be scaled up to produce larger volumes so that validation studies in larger animals can be carried out. Scale-up of manufacturing could be achieved, for example, by using microfluidics methods to prepare the nanoemulsion, as previously reported.46 In addition, the dosing regimen of DNP nanoemulsions and timing intervals could be explored in the future to further optimize the balance between the toxicity and efficacy of the treatment. Lastly, while we have recently demonstrated that results observed in tadpoles highly correlate with those obtained in other vertebrates including humans,16 it will be necessary to test the biostasis potential of DNP nanoemulsions in other nonhibernating larger animal models to facilitate clinical translation. For this, the stability of the nanoemulsion in the corresponding administration medium should be properly studied.

Conclusions

Achieving a reversible torpor-like state in a whole organism could increase the chance of its survival after suffering a serious accident. In this work, we show the promise of using the drug DNP, which is currently widely used worldwide by patients suffering from Alzheimer’s disease, to artificially induce a torpor-like state in Xenopus laevis tadpoles that naturally do not hibernate or experience torpor. However, while free DNP drugs can suppress metabolic activity in tadpoles, their use was limited by their toxicity, which appeared after administration for more than 2–3 h. To improve the performance of DNP as an inducer of a torpor-like state, we encapsulated it within a nanoemulsion, which enabled us to modulate its uptake, pharmacokinetics, and biodistribution in a manner that significantly reduced its toxicity while maintaining its efficacy. This enabled the induction of longer, reversible, torpor-like states in the tadpoles by the DNP nanoemulsion, as demonstrated by reduced mobility, slower cardiac frequency, and lower oxygen consumption. These findings raise the possibility that the administration of DNP nanoemulsions could be used in emergency medical or veterinary situations as an interesting approach to gain critical time and prevent irreversible organ injury before the patient can be transported or admitted to a hospital. Additional advantages of this approach include DNP’s previous approval for clinical use by the FDA, low toxicity of the nanoemulsions, manufacturing scalability, and the possibility to administer treatments without the need for trained personnel (e.g., using noninvasive mucosal routes). These advantages can shorten the path toward clinical translation and help reach patients in need. In addition, this work demonstrates the potential of using Xenopus laevis as a whole animal model to evaluate the toxicity, biodistribution, and pharmacodynamics of drug-loaded nanocarriers. We envisage that its broader application in the field could help accelerate the development and screening of drug-loaded nanocarriers, avoiding pitfalls that occur based on studies with cell cultures and reducing the need for more complex and ethically questionable animal models.

Materials and Methods

Reagents

Lecithin (Epikuron 145 V) was kindly donated by Cargil (Spain). Donepezil hydrochloride was acquired from T.C.I (USA), while donepezil free base and donepezil hydrochloride-d4 were purchased from Cayman Chemical Company (USA). Amikon ultracentrifugal tubes were acquired from Millipore-Sigma (USA). Dulbecco’s Modified Eagle Minimal Essential Medium (DMEM), fetal, bovine serum (FBS), penicillin-streptomycin, and formic acid were purchased from ThermoFisher Scientific (USA). The phosphotungstic acid solution was purchased from Electron Microscopy Sciences (USA). Tricaine was acquired from Syndel (USA). The rest of the material used in this work was purchased from Sigma-Aldrich (USA).

Drug Predictions

For drug prediction studies, we used the NeMoCAD tool following methods detailed in prior publications.19,20 Briefly, NeMoCAD uses a combined gene–gene and gene-drug network analysis to computationally predict existing compounds that would mimic or reverse a particular transcriptomic state. Transcriptome-wide differential expression profiles are identified between two biological states (untreated and treated) in the input transcriptomic data set, and this profile is used to define the target normalization signature. In this case, the target signature was defined as the subset of genes whose expression levels need to be mimicked or reversed to induce a torpor-like state in an awake organism. Then, two different analyses were carried out: (1) pairwise analysis comparing the gene expression profiles of compounds found in the LINCS database and the target normalization signature and (2) predictions that incorporated gene–gene dependencies based on Bayesian network analysis. The network architecture included regulatory and drug-gene interactions that were defined using publicly available databases of gene–gene interactions based on single gene knockout data sets in human cells (KEGG, TRRUST) and reference transcriptional signatures of drugs (LINCS, CTD).47−51 The network generated from databases and the transcriptomic information were used as input for a message-passing algorithm (e.g., loopy belief propagation algorithm). Then, the marginal probability distributions of drugs being “on”, given the expression state of every gene, were computed using the joint probability distribution. Drugs with a low probability (<0.5) were excluded from prediction lists. Lastly, drugs were ranked based on the combination score derived from the correlation metrics (Pearson correlation and cross-entropy) to generate a list of compounds that are predicted to induce a torpor-like state. In addition, we defined structural similarity scores to SNC80 based on the Tanimoto coefficient, calculated using the PubChem 2Dfingerprint.21,52

Effect of DNP on Cell Viability

In vitro cytotoxicity of DNP was assessed by using the LDH method. For that, we used the CytoTox-ONE Homogenous Membrane Integrity Assay (Promega, USA) following the manufacturer's protocol,53 and Caco-2 cells (ATCC) from passages 25–29. Cells were cultured in DMEM with 20% FBS and 1% penicillin streptomycin and seeded 24 h before the assay at 10,000 cells/well in 96-well tissue culture-treated plates (Corning, Falcon, USA). Cells were exposed to a range of DNP concentrations (12.5, 25, 50, or 100 μM) in 0.5% (v/v) DMSO. Lysis buffer provided with the assay kit (Triton X-100) was added to select wells as a control for cell death (cytotoxicity control). Cytotoxicity values were quantified with fluorescence (560 Excitation/590 Emission) and calculated according to the manufacturer’s protocol.53 Data were normalized to nontreated cells.

Preparation of Nanoemulsions

We formulated control and DNP nanoemulsions following the solvent displacement technique.27,54,55 For this, the organic and aqueous phases were separately prepared. The organic phase included 20 mg of soy lecithin and 63 μL of soy oil in a mixture of acetone/ethanol. The aqueous phase was a solution of Pluronic F-127 in ultrapure water (0.02% w/v). The organic phase was added to the aqueous phase and stirred for 10 min, allowing for the spontaneous formation of nanoemulsions. Lastly, organic solvents were removed, and the final volume was adjusted to 2 mL using rotary evaporation (Buchi, USA). To obtain DNP nanoemulsions, the drug was included in the ethanolic fraction of the organic phase, achieving a loading of 1.250 mM. For these experiments, DNP free base was used to maximize its encapsulation into the oily core of the nanoemulsions.

Characterization of Nanoemulsions

The physicochemical properties of the nanoemulsions (hydrodynamic mean diameter, polydispersion index, and zeta potential) were analyzed by using a Nanosizer (Malvern, UK). Samples were first diluted in phosphate buffer 2 mM (pH = 7). The hydrodynamic mean size and the polydispersion index of nanoemulsions were assessed through dynamic light scattering and the zeta potential based on their electrophoretic mobility. The morphology of the nanoemulsions was visualized by an HT7800 transmission electron microscope (Hitachi, Japan) operating at 100 kV and 10.8 μA. Diluted nanoemulsions were added to porous carbon-coated grids (CF200H–Cu, EMS) and adsorbed for 1 min before staining with a phosphotungstic acid solution (2% w/v).

Quantification of DNP in Nanoemulsions

DNP concentration was quantified by reverse-phase high-performance liquid chromatography (HPLC), using a method adapted from the literature,56,57 and an Agilent 1200 model coupled with a diode array detector and equipped with a C18 Zorbax Eclipse Plus column (100 × 4.6 mm, particle size 3.5 μm) (Agilent, US). The organic phase was 0.1% (v/v) formic acid in acetonitrile, and the aqueous phase was 0.1% (v/v) formic acid in ultrapure water. The mobile phase was eluted in gradient as follows: 95% aqueous from 0 to 1 min, 95% organic from 1 to 5 min, and back to 95% aqueous from 5 to 6 min. The flow rate and injection volume were 0.7 mL/min and 10 uL, respectively. The DAD detection wavelength was 268 nm. The retention time was 5.53 ± 0.05 min. We obtained good linearity over the range 0.4–200 μg/mL (R2> 0.999 and CV ≤ 5%) and a quantification limit of 0.4 μg/mL.

DNP Encapsulation Efficacy Assessment

We calculated the encapsulation efficacy in DNP nanoemulsions by the quantification of nonencapsulated DNP. Briefly, DNP nanoemulsions were added to the top of centrifuge filtration tubes (100,000 MWCO, Merck Millipore) and centrifuged at 1500 rcf at 4 °C for 20 min. DNP in the filtrate was quantified by HPLC, as described above, and the DNP encapsulation efficacy was calculated as follows:

where C0 refers to the theoretical DNP concentration in DNP-nanoemulsions and C to its concentration in the filtrate, quantified by HPLC.

Storage Stability of Nanoemulsions

The long-term storage stability of control and DNP nanoemulsions under refrigerated (4 °C) conditions was evaluated by the periodic measurement of the nanoemulsions’ physicochemical properties and DNP release following the protocols described above.

In Vivo Studies in Xenopus laevis Tadpoles

Ethical Statement

All the studies using Xenopus laevis were carried out using our following ethical procedures and previously approved by Tufts University Department of Laboratory Animal Medicine (protocol M2014-79), by the Institutional Animal Care and Use Committees (IACUC), and by the Office of the IACUC at Harvard Medical School (protocol IS00000658-3).

Xenopus laevis Husbandry

Xenopus laevis embryos were fertilized in vitro following previously described protocols.58 Embryos and tadpoles were kept to a 12:12 h dark-light cycle and housed using Marc’s Modified Ringer’s solution (MMR, pH 7.8) at 18 °C. The experimental procedures were performed using tadpoles at stages 46–49, using the staging criteria from Nieuwkoop and Faber.59 In all the experiments, we maintained the ratio of 1 mL of treatment per tadpole. At the end of the experiments, tadpoles were euthanized by immersion in 0.2% (w/v) tricaine for 30 min, bleached, and disposed.

Toxicity Assessment

Tadpoles were exposed to the corresponding treatment and time conditions (see results and discussion section) (n = 10 tadpoles per condition) in 12-well plates (Corning, Falcon, USA). After each treatment, tadpoles were transferred to fresh MMR media and allowed to recover overnight at 18 C with a normal light/dark cycle. The next day, we calculated their survival rate, and we collected bright-field microscopy images to study possible morphological alterations.

Quantification of DNP in Tadpoles

Tadpoles were exposed to the corresponding treatment for 0, 1, 2, 4, or 8 h (n = 3 replicates with N = 3 tadpoles each per treatment and time point) in 12-well plates. After each treatment, tadpoles were euthanized using 0.2% (w/v) chilled tricaine for 5 min. They were weighted and transferred to bead mill tubes containing 200 uL of chilled chemical-grade water. Last, this mix was homogenized for 1 min using a Tissue Lyser (model II, Qiagen, USA) and DNP was quantified by mass spectrometry, using an Agilent 6460 Triple Quad Mass Spectrometer (USA) coupled to a 1290 LC Column Phenomenex Kinetex C18 1.7 um,150 × 2.1 mm. The organic phase was 0.1% (v/v) formic acid in acetonitrile and the aqueous phase was 0.1% (v/v) formic acid in ultrapure water. The mobile phase was eluted in a gradient, using a flow rate of 0.2 mL/min. Injection volume: 4 μL. DNP D4 was used as an internal standard. We obtained good linearity over the range 0–200 μM (R2 > 0.999). Results were expressed in terms of nmol DNP/g tadpole.

Biosdistribution

Tadpoles were exposed to the indicated treatment for 1 h (n = 5 tadpoles per condition) in 12-well plates, and then, tadpoles were euthanized using chilled tricaine 0.2% (w/v), embedded in gelatin (0.11 g/mL) and stored in −80 C. Embedded tadpoles were sectioned into 16 μm-thick slices using a cryostat (Leica Microsystems, model CM1850, Germany) onto indium tin oxide (ITO)-coated glass slides (Bruker Daltonics, USA) and immediately placed in a vacuum desiccator before matrix application (n = 3 sections per slide). The matrix solution, freshly prepared for each application, was composed of 2,4-dihydroxybenzoic acid (40 mg/mL) in 0.1% formic acid, methanol/water 1:1 (v/v). The HTX-sprayer nebulizer (HTX Technologies, USA) was used to apply the matrix at 80 °C at 24 passes over the sample, at a flow rate of 50 μL/min, 10 psi pressure, and a track speed at 1250 mm/min. Before imaging, DNP was spotted with tadpoles’ tissue lysate to determine the best matrix for an optimal signal-to-noise ratio and to identify which adducts were detectable for each compound for imaging. In situ MALDI-ToF imaging was acquired using the rapifleX (Bruker Daltonics, USA) in positive ion mode at 1000 Hz in the mass range 300–990 m/z. The laser raster step spacing was set to 45 μm step size at 500 shots per pixel. External calibration was performed using a red phosphorus slurry drop cast on a region of the matrix-coated ITO slide without tissue. Preliminary processing of the data was performed using FlexAnalysis (Bruker Daltonics, USA). Images were normalized by the total ion count and baseline-corrected using the Top Hat algorithm. After MALDI-ToF MSI acquisition, ITO slides were stained for H&E and imaged using the Cytation 5 (Agilent, USA) and Epsilon scanner at 3000 dpi to select regions of interest using the open-source program, Qupath.48. The mean signal intensity of the defined regions of interest was obtained at [M + H]+ of DNP.

Swimming Performance

Tadpoles were exposed to the indicated treatment for 1, 2, 4, or 8 h (n = 2 replicates with N = 10 tadpoles each per treatment and time point) in 60 mm dishes placed on an illuminated background. Tadpole swimming activity was recorded using a camera (Sony Alpha a6100 model) equipped with a 16 mm objective (Sony, Japan) and evaluated using Matlab software (version 9.14 USA). Frame-to-frame displacements were tracked every 0.5 min and associated with a 0–1 movement index (being 0 indicative of lack of motion and 1 indicative of maximal motion). Then, they were transferred to fresh MMR media and allowed to recover overnight at 18 C with a normal light/dark cycle. The next day, this protocol was repeated to study the recovery of normal swimming motion.

Cardiac Frequency

Tadpoles were exposed to the indicated treatment for 0, 1, 2, 4, or 8 h (n = 10 tadpoles per treatment and time point) in 12-well plates. After each time point, they were briefly immersed in tricaine 0.01% (w/v) and they were ventrally oriented to enable localization of the heart. Videos were recorded using a ZEISS Axio Zoom. V16 microscope and ZEN software (Blue edition, version 3.1, Germany), with the acquisition speed set at 1000 fps. After the experiment, tadpoles were transferred to fresh MMR and allowed to recover overnight at 18 C with a normal light/dark cycle. We repeated this protocol the next day to study their recovery of normal cardiac frequency. Lastly, heartbeats per minute were counted in all of the recorded videos by three blinded and independent assessors.

Oxygen Consumption

Tadpoles were exposed to the indicated treatment (n ≥ 10 replicates with N = 2 tadpoles each per treatment) in sealed vials with integrated oxygen sensors. Oxygen saturation was measured using PreSens oxygen software (Germany). The oxygen consumption rate was calculated for each sample using a linear fit of normalized oxygen saturation data over the first 3 h using GraphPad Prism.

Statistical Analysis

Results are expressed as mean ± standard deviation unless otherwise stated. Statistical analysis was performed using GraphPad Prism software (version 10.0.2 (232), USA). Statistical tests are specified in each figure. The levels of significance are indicated in the figures as follows: *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; ns: not significant.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsnano.4c02012.Effect of DNP on cell viability in Caco-2 cells, assessed using the LDH method; stability of control nanoemulsion stored at 4 °C, based on its physicochemical properties (PDF)

Supplementary Material

nn4c02012_si_001.pdf

Author Contributions

M.S., R.N., and D.E.I. conceived and directed the work. M.M.S., T.T., and S.K. performed drug prediction studies. K.S. carried out a cytotoxicity study and analyzed its derived data. M.P.O. and E.G. performed toxicity and swimming studies in tadpoles, while M.P.O. and M.M.S. evaluated the cardiac frequency of the tadpoles. E.G., M.P.O., and R.M. worked on the oxygen study. E.G., M.P.O., K.S., and S.L. participated in the drug quantification in tadpoles. T.L. and M.L. carried out the biodistribution study. M.P.O., S.L., D.DC., K.S., H.F., and T.L. analyzed data derived from studies with tadpoles. M.P.O. and A.C.P. were in charge of drug quantification by HPLC. R.M. completed TEM imaging. M.V.L., M.S.O., and M.P.O. designed the nanoemulsions. M.P.O. and V.G. worked on the formulation process, with the guidance of M.V.L. and M.S.O. M.P.O., M.S.O., M.V.L, M.S., and D.E.I. drafted the manuscript. All authors read, approved, and provided critical input to the manuscript.

The authors declare no competing financial interest.

Acknowledgments

The authors deeply acknowledge the funding from the Army Research Office/DARPA under Cooperative Agreement Number W911NF-19-2-0027. The conclusions derived from this document should not be interpreted as representing any official policies, either expressed or implied, of the Army Research Office/DARPA or the US government. The US government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. The authors also acknowledge the funding from grant PID2021-122703NA-I00 financed by MICIU/AEI/10.13039/501100011033 and by FEDER/UE. The authors thank the support of Junta de Comunidades de Castilla-La Mancha and the European Union by the European Regional Development Fund (SBPLY/21/180501/000077). M.P.-O. acknowledges the financial support from the Margarita Salas postdoctoral grant cofunded by the Spanish Ministry of Universities and the University of Castilla-La Mancha (NextGenerationEU UNI/551/2021). Authors thank E. Switzer for Xenopus laevis embryo fertilization; R. Colon and members of the Levin Lab at Tufts University for assistance with Xenopus laevis embryo husbandry and transport organization, and the Harvard Center for Mass Spectrometry, particularly C. Vidoudez, for DNP quantification in tadpoles. TEM imaging was performed at the Harvard University Center for Nanoscale Systems; a member of the National Nanotechnology Coordinated Infrastructure Network, which is supported by the National Science Foundation under NSF award no. ECCS-2025158. Graphical abstracts and Figures 1a and 2a were created using BioRender and have the appropriate publication permission.

Abbreviations

CTD comparative toxicogenomic database

DNP donepezil

HPLC high performance liquid chromatography

IC50 maximum inhibitory concentration

KEGG kyoto encyclopedia of genes and genomes

LDH lactate dehydrogenase

LINCS library of integrated network-based cellular signatures

MALDI-TOF matrix-assisted laser desorption/ionization equipped with a time-of-flight detector

TEM transmission electron microscopy

TRRUST transcriptional regulatory relationships unraveled by sentence-based text-mining
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References

Andrews M. T. Advances in Molecular Biology of Hibernation in Mammals. BioEssays 2007, 29 (5 ), 431–440. 10.1002/bies.20560.17450592
Horii Y. ; Shiina T. ; Shimizu Y. The Mechanism Enabling Hibernation in Mammals. Adv. Exp. Med. Biol. 2018, 1081 , 45–60. 10.1007/978-981-13-1244-1_3.30288703
Cerri M. The Central Control of Energy Expenditure: Exploiting Torpor for Medical Applications. Annu. Rev. Physiol. 2017, 79 , 167–186. 10.1146/annurev-physiol-022516-034133.27813827
Yamada K. P. ; Kariya T. ; Aikawa T. ; Ishikawa K. Effects of Therapeutic Hypothermia on Normal and Ischemic Heart. Front. Cardiovasc. Med. 2021, 8 , 1–10. 10.3389/fcvm.2021.642843.
Polderman K. H. Application of Therapeutic Hypothermia in the Intensive Care Unit: Opportunities and Pitfalls of a Promising Treatment Modality - Part 2: Practical Aspects and Side Effects. Intensive Care Med. 2004, 30 (5 ), 757–769. 10.1007/s00134-003-2151-y.14767590
Takahashi T. M. ; Sunagawa G. A. ; Soya S. ; Abe M. ; Sakurai K. ; Ishikawa K. ; Yanagisawa M. ; Hama H. ; Hasegawa E. ; Miyawaki A. ; Sakimura K. ; Takahashi M. ; Sakurai T. A Discrete Neuronal Circuit Induces a Hibernation-like State in Rodents. Nature 2020, 583 (7814 ), 109–114. 10.1038/s41586-020-2163-6.32528181
Drew K. L. ; Buck C. L. ; Barnes B. M. ; Christian S. L. ; Rasley B. T. ; Harris M. B. Central Nervous System Regulation of Mammalian Hibernation: Implications for Metabolic Suppression and Ischemia Tolerance. J. Neurochem. 2007, 102 (6 ), 1713–1726. 10.1111/j.1471-4159.2007.04675.x.17555547
Hrvatin S. ; Sun S. ; Wilcox O. F. ; Yao H. ; Lavin-Peter A. J. ; Cicconet M. ; Assad E. G. ; Palmer M. E. ; Aronson S. ; Banks A. S. ; Griffith E. C. ; Greenberg M. E. Neurons That Regulate Mouse Torpor. Nature 2020, 583 (7814 ), 115–121. 10.1038/s41586-020-2387-5.32528180
Yang Y. ; Yuan J. ; Field R. L. ; Ye D. ; Hu Z. ; Xu K. ; Xu L. ; Gong Y. ; Yue Y. ; Kravitz A. V. ; Bruchas M. R. ; Cui J. ; Brestoff J. R. ; Chen H. Induction of a Torpor-like Hypothermic and Hypometabolic State in Rodents by Ultrasound. Nat. Metab. 2023, 5 (5 ), 789–803. 10.1038/s42255-023-00804-z.37231250
Aslami H. ; Schultz M. ; Juffermans N. Potential Applications of Hydrogen Sulfide-Induced Suspended Animation. Curr. Med. Chem. 2009, 16 (10 ), 1295–1303. 10.2174/092986709787846631.19355886
Lou L. X. ; Geng B. ; Du J. B. ; Tang C. S. Hydrogen Sulphide-Induced Hypothermia Attenuates Stress-Related Ulceration in Rats. Clin. Exp. Pharmacol. Physiol. 2008, 35 (2 ), 223–228. 10.1111/j.1440-1681.2007.04812.x.17941893
Blackstone E. ; Morrison M. ; Roth M. B. H2S Induces a Suspended Animation–Like State in Mice. Science (80-.). 2005, 308 (April ), 518 10.1126/science.1108581.
Ghosh S. ; Indracanti N. ; Joshi J. ; Ray J. ; Indraganti P. K. Pharmacologically Induced Reversible Hypometabolic State Mitigates Radiation Induced Lethality in Mice. Sci. Rep. 2017, 7 (1 ), 1–14. 10.1038/s41598-017-15002-7.28127051
Carlin J. L. ; Jain S. ; Gizewski E. ; Wan T. C. ; Tosh D. K. ; Xiao C. ; Auchampach J. A. ; Jacobson K. A. ; Gavrilova O. ; Reitman M. L. Hypothermia in Mouse Is Caused by Adenosine A1 and A3 Receptor Agonists and AMP via Three Distinct Mechanisms. Neuropharmacology 2017, 114 , 101–113. 10.1016/j.neuropharm.2016.11.026.27914963
Drew K. L. ; Frare C. ; Rice S. A. Neural Signaling Metabolites May Modulate Energy Use in Hibernation. Neurochem. Res. 2017, 42 , 141–150. 10.1007/s11064-016-2109-4.27878659
Sperry M. M. ; Charrez B. ; Fotowat H. ; Gardner E. ; Pilobello K. ; Izadifar Z. ; Lin T. ; Kuelker A. ; Kaki S. ; Lewandowski M. ; Lightbown S. ; Martinez R. ; Marquez S. ; Moore J. ; Plaza-Oliver M. ; M. Sesay A. ; Shcherbina K. ; Sheehan K. ; Takeda T. ; Del Campo D. ; Andrijauskaite E. Identification of Pharmacological Inducers of a Reversible Hypometabolic State for Whole Organ Preservation. eLife Med. 2024, 1–39. 10.7554/eLife.93796.1.
Danielsson I. ; Gasior M. ; Stevenson G. W. ; Folk J. E. ; Rice K. C. ; Negus S. S. Electroencephalographic and Convulsant Effects of the Delta Opioid Agonist SNC80 in Rhesus Monkeys. Pharmacol., Biochem. Behav. 2006, 85 (2 ), 428–434. 10.1016/j.pbb.2006.09.012.17112570
Maia L. A. ; Velloso I. ; Abreu J. G. Advances in the Use of Xenopus for Successful Drug Screening. Expert Opin. Drug Discovery 2017, 12 (11 ), 1153–1159. 10.1080/17460441.2017.1367281.
Sperry M. M. ; Oskotsky T. T. ; Marić I. ; Kaushal S. ; Takeda T. ; Horvath V. ; Powers R. K. ; Rodas M. ; Furlong B. ; Soong M. ; Prabhala P. ; Goyal G. ; Carlson K. E. ; Wong R. J. ; Kosti I. ; Le B. L. ; Logue J. ; Hammond H. ; Frieman M. ; Stevenson D. K. ; Ingber D. E. ; Sirota M. ; Novak R. Target-Agnostic Drug Prediction Integrated with Medical Record Analysis Uncovers Differential Associations of Statins with Increased Survival in COVID-19 Patients. PLoS Comput. Biol. 2023, 19 (5 ), e1011050 10.1371/journal.pcbi.1011050.37146076
Novak R. ; Lin T. ; Kaushal S. ; Sperry M. ; Vigneault F. ; Gardner E. ; Loomba S. ; Shcherbina K. ; Keshari V. ; Dinis A. ; Vasan A. ; Chandrasekhar V. ; Takeda T. ; Turner J. R. ; Levin M. ; Paulson H. J. A. ; Ingber D. E. Target-Agnostic Discovery of Rett Syndrome Therapeutics by Coupling Computational Network Analysis and CRISPR-Enabled in Vivo Disease Modeling. bioRxiv 2022, 10.1101/2022.03.20.485056.
Chen X. ; Reynolds C. H. Performance of Similarity Measures in 2D Fragment-Based Similarity Searching: Comparison of Structural Descriptors and Similarity Coefficients. J. Chem. Inf. Comput. Sci. 2002, 42 (6 ), 1407–1414. 10.1021/ci025531g.12444738
Adlimoghaddam A. ; Neuendorff M. ; Roy B. ; Albensi B. C. A Review of Clinical Treatment Considerations of Donepezil in Severe Alzheimer’s Disease. CNS Neurosci. Ther. 2018, 24 (10 ), 876–888. 10.1111/cns.13035.30058285
Shepherd G. ; Klein-Schwartz W. ; Edwards R. Donepezil Overdose: A Tenfold Dosing Error. Ann. Pharmacother. 1999, 33 (7–8 ), 812–815. 10.1345/aph.18273.10466911
Majumder J. ; Taratula O. ; Minko T. Nanocarrier-Based Systems for Targeted and Site Specific Therapeutic Delivery. Adv. Drug Delivery Rev. 2019, 144 , 57–77. 10.1016/j.addr.2019.07.010.
Mitchell M. J. ; Billingsley M. M. ; Haley R. M. ; Wechsler M. E. ; Peppas N. A. ; Langer R. Engineering Precision Nanoparticles for Drug Delivery. Nat. Rev. Drug Discovery 2021, 20 (2 ), 101–124. 10.1038/s41573-020-0090-8.33277608
McClements D. J. ; Rao J. Food-Grade Nanoemulsions: Formulation, Fabrication, Properties, Performance, Biological Fate, and Potential Toxicity. Crit. Rev. Food Sci. Nutr. 2011, 51 (4 ), 285–330. 10.1080/10408398.2011.559558.21432697
Lozano M. V. ; Torrecilla D. ; Torres D. ; Vidal A. ; Domínguez F. ; Alonso M. J. Highly Efficient System to Deliver Taxanes into Tumor Cells: Docetaxel-Loaded Chitosan Oligomer Colloidal Carriers. Biomacromolecules 2008, 9 (8 ), 2186–2193. 10.1021/bm800298u.18637687
McClements D. J. Nanoemulsion-Based Oral Delivery Systems for Lipophilic Bioactive Components: Nutraceuticals and Pharmaceuticals. Ther. Delivery 2013, 4 (7 ), 841–857. 10.4155/tde.13.46.
Bacchetta R. ; Santo N. ; Fascio U. ; Moschini E. ; Freddi S. ; Chirico G. ; Camatini M. ; Mantecca P. Nano-Sized CuO, TiO2 and ZnO Affect Xenopus Laevis Development. Nanotoxicology 2012, 6 (4 ), 381–398. 10.3109/17435390.2011.579634.21574813
Bacchetta R. ; Moschini E. ; Santo N. ; Fascio U. ; Del Giacco L. ; Freddi S. ; Camatini M. ; Mantecca P. Evidence and Uptake Routes for Zinc Oxide Nanoparticles through the Gastrointestinal Barrier in Xenopus Laevis. Nanotoxicology 2014, 8 (7 ), 728–744. 10.3109/17435390.2013.824128.23848496
Colombo A. ; Saibene M. ; Moschini E. ; Bonfanti P. ; Collini M. ; Kasemets K. ; Mantecca P. Teratogenic Hazard of BPEI-Coated Silver Nanoparticles to Xenopus Laevis. Nanotoxicology 2017, 11 (3 ), 405–418. 10.1080/17435390.2017.1309703.28318347
Bonfanti P. ; Colombo A. ; Saibene M. ; Fiandra L. ; Armenia I. ; Gamberoni F. ; Gornati R. ; Bernardini G. ; Mantecca P. Iron Nanoparticle Bio-Interactions Evaluated in Xenopus Laevis Embryos, a Model for Studying the Safety of Ingested Nanoparticles. Nanotoxicology 2020, 14 (2 ), 196–213. 10.1080/17435390.2019.1685695.31718350
Ismail T. ; Lee H. K. ; Kim C. ; Kim Y. ; Lee H. ; Kim J. H. ; Kwon S. ; Huh T. L. ; Khang D. ; Kim S. H. ; Choi S. C. ; Lee H. S. Comparative Analysis of the Developmental Toxicity in Xenopus Laevis and Danio Rerio Induced by Al2O3 Nanoparticle Exposure. Environ. Toxicol. Chem. 2019, 38 (12 ), 2672–2681. 10.1002/etc.4584.31470468
Báez-Pagán C. A. ; del Hoyo-Rivera N. ; Quesada O. ; Otero-Cruz J. D. ; Lasalde-Dominicci J. A. Heterogeneous Inhibition in Macroscopic Current Responses of Four Nicotinic Acetylcholine Receptor Subtypes by Cholesterol Enrichment. J. Membr. Biol. 2016, 249 (4 ), 539–549. 10.1007/s00232-016-9896-z.27116687
Walrant A. ; Saxton D. S. ; Correia G. P. ; Gallop J. L. Triggering Actin Polymerization in Xenopus Egg Extracts from Phosphoinositide-Containing Lipid Bilayers; Elsevier Ltd, 2015; Vol. 128 .
Rafikova E. R. ; Melikov K. ; Ramos C. ; Dye L. ; Chernomordik L. V. Transmembrane Protein-Free Membranes Fuse into Xenopus Nuclear Envelope and Promote Assembly of Functional Pores. J. Biol. Chem. 2009, 284 (43 ), 29847–29859. 10.1074/jbc.M109.044453.19696024
Zhao Z. D. ; Yang W. Z. ; Gao C. ; Fu X. ; Zhang W. ; Zhou Q. ; Chen W. ; Ni X. ; Lin J. K. ; Yang J. ; Xu X. H. ; Shen W. L. A Hypothalamic Circuit That Controls Body Temperature. Proc. Natl. Acad. Sci. U. S. A. 2017, 114 (8 ), 2042–2047. 10.1073/pnas.1616255114.28053227
Ambler M. ; Hitrec T. ; Wilson A. ; Cerri M. ; Pickering A. Neurons in the Dorsomedial Hypothalamus Promote, Prolong, and Deepen Torpor in the Mouse. J. Neurosci. 2022, 42 (21 ), 4267–4277. 10.1523/JNEUROSCI.2102-21.2022.35440490
Sallmen T. ; Lozada A. F. ; Anichtchik O. V. ; Beckman A. L. ; Leurs R. ; Panula P. Changes in Hippocampal Histamine Receptors across the Hibernation Cycle in Ground Squirrels. Hippocampus 2003, 13 (6 ), 745–754. 10.1002/hipo.10120.12962318
Cerri M. ; Mastrotto M. ; Tupone D. ; Martelli D. ; Luppi M. ; Perez E. ; Zamboni G. ; Amici R. The Inhibition of Neurons in the Central Nervous Pathways for Thermoregulatory Cold Defense Induces a Suspended Animation State in the Rat. J. Neurosci. 2013, 33 (7 ), 2984–2993. 10.1523/JNEUROSCI.3596-12.2013.23407956
Tupone D. ; Madden C. J. ; Morrison S. F. Central Activation of the A1 Adenosine Receptor (A1AR) Induces a Hypothermic, Torpor-like State in the Rat. J. Neurosci. 2013, 33 (36 ), 14512–14525. 10.1523/JNEUROSCI.1980-13.2013.24005302
Dubaissi E. ; Rousseau K. ; Hughes G. W. ; Ridley C. ; Grencis R. K. ; Roberts I. S. ; Thornton D. J. Functional Characterization of the Mucus Barrier on the Xenopus Tropicalis Skin Surface. Proc. Natl. Acad. Sci. U. S. A. 2018, 115 (4 ), 726–731. 10.1073/pnas.1713539115.29311327
Plaza-Oliver M. ; Santander-Ortega M. J. ; Lozano M. V. Current Approaches in Lipid-Based Nanocarriers for Oral Drug Delivery. Drug Delivery Transl. Res. 2021, 11 (2 ), 471–497. 10.1007/s13346-021-00908-7.
Formica M. L. ; Real D. A. ; Picchio M. L. ; Catlin E. ; Donnelly R. F. ; Paredes A. J. On a Highway to the Brain: A Review on Nose-to-Brain Drug Delivery Using Nanoparticles. Appl. Mater. Today 2022, 29 , 101631 10.1016/j.apmt.2022.101631.
Swoap S. J. ; Gutilla M. J. Cardiovascular Changes during Daily Torpor in the Laboratory Mouse. Am. J. Physiol.: Regul., Integr. Comp. Physiol. 2009, 297 (3 ), 769–774. 10.1152/ajpregu.00131.2009.
Fathordoobady F. ; Sannikova N. ; Guo Y. ; Singh A. ; Kitts D. D. ; Pratap-Singh A. Comparing Microfluidics and Ultrasonication as Formulation Methods for Developing Hempseed Oil Nanoemulsions for Oral Delivery Applications. Sci. Rep. 2021, 11 (1 ), 1–12. 10.1038/s41598-020-79161-w.33414495
Kanehisa M. ; Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000, 28 , 27–30. 10.1093/nar/28.1.27.10592173
Han H. ; Shim H. ; Shin D. ; Shim J. E. ; Ko Y. ; Shin J. ; Kim H. ; Cho A. ; Kim E. ; Lee T. ; Kim H. ; Kim K. ; Yang S. ; Bae D. ; Yun A. ; Kim S. ; Kim C. Y. ; Cho H. J. ; Kang B. ; Shin S. ; Lee I. TRRUST: A Reference Database of Human Transcriptional Regulatory Interactions. Sci. Rep. 2015, 5 , 1–11. 10.1038/srep11432.
The Library of Integrated Network-Based Cellular Signatures (LINCS) Program from the NIH, 2023. https://lincsproject.org/ (accessed Jun 19, 2024).
Davis A. P. ; Wiegers T. C. ; Johnson R. J. ; Sciaky D. ; Wiegers J. ; Mattingly C. J. Comparative Toxicogenomics Database (CTD): Update 2023. Nucleic Acids Res. 2023, 51 (D1 ), D1257–D1262. 10.1093/nar/gkac833.36169237
Musa A. ; Tripathi S. ; Dehmer M. ; Yli-Harja O. ; Kauffman S. A. ; Emmert-Streib F. Systems Pharmacogenomic Landscape of Drug Similarities from LINCS Data: Drug Association Networks. Sci. Rep. 2019, 9 (1 ), 1–16. 10.1038/s41598-019-44291-3.30626917
Bethesda M. PubChem Substructure Fingerprint. Natl. Cent. Biotechnol. 2009, 1–21.
CytoTox-ONE TM Homogeneous Membrane Integrity Assay. Technical Bulletin. Promega 2009, 1–14.
Lozano M. V. ; Lollo G. ; Alonso-Nocelo M. ; Brea J. ; Vidal A. ; Torres D. ; Alonso M. J. Polyarginine Nanocapsules: A New Platform for Intracellular Drug Delivery. J. Nanoparticle Res. 2013, 15 (3 ), 1515 10.1007/s11051-013-1515-7.
Santander-Ortega M. J. ; Plaza-Oliver M. ; Rodríguez-Robledo V. ; Castro-Vázquez L. ; Villaseca-González N. ; González-Fuentes J. ; Cano E. L. ; Marcos P. ; Lozano M. V. ; Arroyo-Jiménez M. M. PEGylated Nanoemulsions for Oral Delivery: Role of the Inner Core on the Final Fate of the Formulation. Langmuir 2017, 33 (17 ), 4269–4279. 10.1021/acs.langmuir.7b00351.28391698
Lee C. Bin ; Min J. S. ; Chae S. U. ; Kim H. M. ; Jang J. H. ; Jung I. H. ; Zheng Y. F. ; Ryu J. H. ; Bae S. K. Simultaneous Determination of Donepezil, 6-O-Desmethyl Donepezil and Spinosin in Beagle Dog Plasma Using Liquid Chromatography–tandem Mass Spectrometry and Its Application to a Drug-Drug Interaction Study. J. Pharm. Biomed. Anal. 2020, 178 , 112919 10.1016/j.jpba.2019.112919.31654856
Pappa H. ; Farrú R. ; Vilanova P. O. ; Palacios M. ; Pizzorno M. T. A New HPLC Method to Determine Donepezil Hydrochloride in Tablets. J. Pharm. Biomed. Anal. 2002, 27 (1–2 ), 177–182. 10.1016/S0731-7085(01)00499-X.11682224
Sperry M. M. ; Novak R. ; Keshari V. ; Dinis A. L. M. ; Cartwright M. J. ; Camacho D. M. ; Paré J. F. ; Super M. ; Levin M. ; Ingber D. E. Enhancers of Host Immune Tolerance to Bacterial Infection Discovered Using Linked Computational and Experimental Approaches. Adv. Sci. 2022, 9 , 2200222 10.1002/advs.202200222.
Faber J. ; Nieuwkoop P. D. Normal Table of Xenopus Laevis (Daudin): A Systematical & Chronological Survey of the Development from the Fer-Tilized Egg till the End of Metamorphosis, 1st ed.; Garland Science: New York, 1994.
