KCNK1) is a widely expressed pH-gated two-pore domain K+ channel (K2P) that contributes to cardiac rhythm generation and insulin release from pancreatic beta cells. TWIK1 displays unique properties among K2Ps including low basal activity and inhibition by extracellular protons through incompletely understood mechanisms. Here, we present cryo-EM structures of TWIK1 in lipid nanodiscs at high and low pH that reveal a previously undescribed gating mechanism at the K+ selectivity filter. At high pH, TWIK1 adopts an open conformation. At low pH, protonation of an extracellular histidine results in a cascade of conformational changes that close the channel by sealing the top of the selectivity filter, displacing the helical cap to block extracellular ion access pathways, and opening gaps for lipid block of the intracellular cavity. These data provide a mechanistic understanding for extracellular pH-gating of TWIK1 and illustrate how diverse mechanisms have evolved to gate the selectivity filter of K+ channels.TWIK1 (K2P1.1,  TWIK1 is a pH-gated K + channel highly expressed in brain and heart that contributes to cardiac rhythm and insulin release. Here, Turney et al. use cryo-EM and electrophysiology to show how TWIK1 gates closed in response to lowered pH through conformational changes centered at the selectivity filter. K2Ps assemble as homo- or hetero-dimers, with each subunit containing four transmembrane-spanning helices (TM1–TM4), two selectivity filters (SF1–SF2), two pore helices (PH1–PH2), and two extracellular cap helices (CH1–CH2)2. K2P1.1 or TWIK1 (Tandem of Pore Domains in a Weak Inward Rectifying K+ Channel) was the first K2P to be discovered and is widely expressed, including at high levels in the brain and heart in humans3.Two-pore domain K+ channel that responds to extracellular acidification. TWIK1 is predominantly closed at pH 5.5 and open at pH 7.5 with a midpoint pH ≈ 6.74. H122 has been identified as the extracellular proton sensor and is located directly above the selectivity filter. The TWIK1 selectivity filter is unique among K+ channels, having diverged from the canonical T(L/V/I)G(Y/F)G motif to TTGYG for SF1 and TIGLG for SF25. Under conditions of low pHext and low [K+]ext (<5 mM), TWIK1 reversibly enters a non-selective conductive state rather than close as seen at higher [K+]ext7. This pHext- and [K+]ext -dependent selectivity loss is postulated to underlie the seemingly paradoxical hyperpolarization of kidney and pancreatic β cells upon TWIK1 deletion8 and TWIK1-dependent depolarization of human cardiomyocytes under hypokalemic conditions7.TWIK1 is a pH-gated K9. Consistent with the channel being open at high pH, the TWIK1 selectivity filter adopted a conductive conformation with K+ ions bound at canonical sites S0-S49. However, the ion conduction path was blocked in the intracellular cavity by a detergent or lipid acyl chain bound through a lateral membrane opening (or fenestration) between transmembrane helices TM2 and TM4, suggesting the structure represented a closed state9. The cavity and lateral membrane opening have since been implicated in regulation of other K2Ps by lipids and small molecules2. Acyl chain block of the channel cavity has been observed in structures of TWIK19, TRAAK (K2P4.1)10, and TREK2 (K2P10.1)11 in detergent micelles and TASK2 (K2P5.1) in lipid nanodiscs12. TASK1 (K2P3.1) inhibitors (BAY1000493 and BAY2341237) occupy a similar cavity site to occlude conduction13, while drug binding in the TREK2 fenestration can either activate (BL-1249)14 or inhibit (norfluoxetine)15 channel activity through distinct mechanisms. Exactly how the cavity site is involved in TWIK1 gating is unclear18. Mutational, spectroscopic, and electrophysiological evidence implicate the TWIK1 selectivity filter in gating conformational changes in ways that are distinct from other K+ channels20.Currently, structural insight into TWIK1 comes from a crystal structure determined at pH 8+ selectivity filter, extracellular cap, and intracellular cavity of the channel.The structural and mechanistic basis for TWIK1 pH-gating remains unknown. Here, we present cryo-EM structures of TWIK1 in lipid nanodiscs at high and low pH that, together with electrophysiological interrogation of structure-guided mutants, reveal a previously undescribed gating mechanism involving the KRattus norvegicus TWIK1, which shares 96% sequence identity to human TWIK1, was well-expressed in Pichia pastoris and biochemically suitable for structural studies. Rat TWIK1 displayed K+-selective currents with reversal potentials near predicted equilibrium potentials for K+ (Erev = −80.2 ± 2.3 mV and −6.6 ± 0.5 mV in low (2 mM) and high (96 mM) [K+]ext, respectively ). At high [K+]ext, the channel was strongly inhibited (~90%) by low pHext )  that eliminates intracellular sequestration, precludes possible SUMOylation, and increases functional expression of the channel22.We found that full-length ext Fig. . At low 7)) Fig. . These p2 symmetry of the reconstructions improved map quality. Amino acids W20 to Y281 are clearly defined and modeled in the low pH structure, corresponding to a resolved mass of 59 kDa. The high pH reconstruction is more anisotropic due to preferred orientations of particles  crystal structures display bending of the helical cap off of the two-fold symmetry axis30, movement of the helical cap has not previously demonstrated to contribute to K2P gating.Movement of the SF1-TM2 and SF2-TM4 linkers upon protonation of H122 results in two additional large-scale conformational changes. First, the entire helical cap is displaced upward ~4 Å at low pH Fig. . H122-L12 at pH 7.4–22.6 Å2 at pH 5.5 at its most constricted point  could promote different TWIK1 conformations.The TWIK1 lateral membrane opening at high pH is larger than that observed in other conductive K2P structures, including TRAAK and TASK2  and lipid nanodiscs (TASK212 and TWIK1). A model for TRAAK gating from our group posits that lipid block underlies a long duration TM4 down closed state31. In contrast, though acyl chain binding in the cavity of TREK2 is observed structurally11 and in molecular dynamics simulations32, a model for TREK2 gating based on these and other data does not involve lipid block33. Molecular dynamics simulations of TWIK1 based on the previously reported crystal structure showed acyl chain binding in the cavity, but it was concluded that lipids did not directly block conduction and rather influenced spontaneous dewetting of the pore18. Mutations that increase hydrophilicity of a conserved position facing the interior of K2P cavities increases activity across the family34. We concluded based on structural and functional data that the mechanism for increased activity of TRAAK G158D is elimination of lipid block31. In contrast, others concluded the mechanism for activation of TWIK1 L146N/L146D was rather a reduction in pore dewetting18. Further study is necessary to determine the relevance of direct lipid gating and the degree of interaction between the extracellular gate at the selectivity filter and lipid block through the lateral membrane opening in TWIK1.The physiological relevance of lipid block of K2Ps in the channel cavity is debated. Structural evidence of acyl chain binding in the cavity has been reported for K2Ps in detergent micelles  was recently observed in a rapidly inactivating mutant of Shaker  has been long appreciated to play a central role in the function of many K12. Finally, C-type gating at the selectivity filter in an inactivating mutant of a chimeric Kv1.2-2.1 channel involves only constriction of carbonyls around S1 to disrupt K+ coordination39. The discovery of a previously undescribed gating mechanism in TWIK1 adds to our understanding of the myriad ways in which the selectivity filter can gate K+ channels to control their activity.Other structurally characterized selectivity filter gates are more distinct from what we observe in TWIK1. The TALK-subfamily K2P TASK2, like TWIK1, is inhibited by external protons through a filter gate, but the molecular mechanisms involved are unrelated. The extracellular proton sensor of TASK2 is located further from the pore near the top of TM4 and TASK2 conformational changes at the filter are more subtle, involving rearrangement of coordination sites S0 and S1 that render the channel nonconductiveext under conditions of high [K+]ext  is critical for selectivity changes5 and the selectivity filter is only weakly stabilized by K+ in a conductive conformation20. We observe a large cavity (~78 Å3) behind the selectivity filter in the closed structure reported here created by movement of H122 and T123 that may contribute to reduced filter stability under these conditions. Future studies of TWIK1 at low [K+]ext will reveal how other structural rearrangements account for increased Na+ permeability.The structures reported here support a model for TWIK1 gating by pHext Fig. . Under l10. A gene encoding Rattus norvegicus TWIK1 (Uniprot Q9Z2T2) was codon-optimized for expression in Pichia pastoris, synthesized , and cloned into a modified pPICZ-B vector (Life Technologies Inc). The resulting construct encoded a human rhinovirus 3 C protease-cleavable C-terminal EGFP-10x histidine fusion protein. The resulting construct, TWIK1-SNS-LEVLFQ/GP-(EGFP)-HHHHHHHHHH was used for structural studies and is referred to as TWIK1 in the text for simplicity.Cloning, expression, and purification were performed similarly to that described for the K2P channel TRAAKPichia pastoris strain SMD1163 by electroporation and transformants were selected on YPDS plates with 1 mg/mL zeocin. Expression levels of individual transformants were analyzed by florescence size. For large-scale expression, overnight cultures of cells in YPD + 0.5 mg/mL Zeocin were added to BMGY to a starting OD of 1, and grown overnight at 30 °C to a final OD600 of 25. Cells were centrifuged at 8000 x g for 10 min, and added to BMMY at 27 °C to induce protein expression. Expression continued for ~24 h.Pme1 linearized pPICZ-B plasmid was transformed into Cells were pelleted, flash-frozen in liquid nitrogen, and stored at −80 °C. 60 g of cells were broken by milling (Retsch model MM301) for 5 cycles of 3 minutes at 25 Hz. All subsequent purification steps were carried out at 4 °C. Cell powder was added to 200 mL lysis/extraction buffer , 1 µM AEBSF, 1 mM E64, 1 mg/ml Pepstatin A, 10 mg/ml Soy Trypsin Inhibitor, 1 mM Benzimidine, 1 mg/ml Aprotinin, 1 mg/ml Leupeptin, 1% n-Dodecyl-b-D-Maltopyranoside , 0.2% Cholesterol Hemisuccinate Tris Salt ) and then gently stirred at 4 °C for 3 h. The extraction was then centrifuged at 33,000 × g for 45 minutes. 10 ml Sepharose resin coupled to anti-GFP nanobody was added to the supernatant and stirred gently for 1 h at 4 °C. The resin was collected in a column and washed with 50 mL Buffer 1 , 150 mL Buffer 2 , and 100 mL of Buffer 1. PPX (~0.5 mg) was added into the washed resin in 10 mL Buffer 1 and rocked gently overnight. Cleaved TWIK1 was eluted and concentrated to ~9.6 mL with an Amicon Ultra spin concentrator . The concentrated protein was subjected to size exclusion chromatography using a Superdex 200 Increase 10/300 column  run in Buffer 3  on a NGC system  running ChromLab 6.0. The peak fractions were collected and spin concentrated for reconstitution.10 nmol of freshly purified TWIK1 was reconstituted into nanodiscs with a 2:1:1 DOPE:POPS:POPC lipid mixture  at a final molar ratio of TWIK1:MSP1D1:lipid of 1:5:250 for high pH, or a ratio of TWIK1:MSPE3D1:lipid of 1:2:200 for low pH. Lipids in chloroform were mixed, dried under argon, washed with pentane, dried under argon, and dried under vacuum overnight in the dark. Dried lipids were rehydrated in buffer containing 20 mM Tris, 150 mM KCl, 1 mM EDTA, pH 8.0 and clarified by bath sonication. DDM was added to a final concentration of 8 mM. TWIK1 was mixed with lipids and incubated at 4 °C for 1 h before addition MSPE3D1 protein. After incubation for 30 minutes at 4 °C, 100 mg of Biobeads SM2   was added and the mixture was rotated at 4 °C overnight. The sample was spun down to facilitate removal of solution from the Biobeads and the reconstituted channel was further purified on a Superdex 200 increase column run in 20 mM HEPES pH 7.4, 150 mM KCl, and 1 mM EDTA (high pH) or 20 mM MES pH 5.5, 150 mM KCl, and 1 mM EDTA (low pH). The peak fractions were collected and spin concentrated (50 kDa MWCO) to 1.8 mg/mL (for high pH) or 2.5 mg/ml (for low pH) for grid preparation.The TWIK1 nanodisc samples were centrifuged at 21,000 x g for 10 min at 4 °C. A 3 µL sample was applied to holey carbon, 300 mesh R1.2/1.3 gold grids  that were freshly glow discharged for 30 seconds. Sample was incubated for 5 seconds at 4 °C and 100% humidity prior to blotting with Whatman #1 filter paper for 3 seconds at blot force 1 and plunge-freezing in liquid ethane cooled by liquid nitrogen using a FEI Mark IV Vitrobot .− Å2 s−1 and 9.155 e− Å2 s− and total dose was 49.715 e− Å2 and 50.3523 e− Å2 in pH 7.4 and pH 5.5 datasets, respectively. Nine movies were collected around a central hole position with image shift and defocus was varied from −0.8 to −2.0 µm through SerialEM40. See Table Grids were clipped and transferred to a FEI Talos Arctica electron microscope operated at 200 kV. Fifty frame movies were recorded on a Gatan K3 Summit direct electron detector in super-resolution counting mode with pixel size of 0.5575 Å. The electron dose was 9.039 e43. The contrast transfer function (CTF) parameters for each micrograph were determined using CTFFIND-4.144. For particle picking in TWIK1 at high pH, 1000 particles were picked manually and subjected to reference-free 2D classification in RELION 3.1 to generate reference for autopicking. After initial cleanup through rounds of 2D classification in Relion 3.1, the remaining particles were extracted and imported into cryoSPARC45. CryoSPARC was used to generate an ab initio model with 2 classes and 0 similarity with or without symmetry. Particles belonging to a class with well-defined features were further refined using Homogenous refinement.For TWIK1 in nanodiscs at pH 7.4, 3,652 micrographs were corrected for beam-induced drift using MotionCor2 in Relion 3.1 and the data was binned to 1.115 A/pixel46), subjected to 3D classification , and refined again to produce a 4.5 Å map. Bayesian polishing, refinement, an additional round of 3D classification , and 3D refinement improved the map further to 3.7 Å. CtfRefinement and Particle Subtraction led to a map at 3.6 Å. Particles were then repicked with Topaz47, and subjected to a processing procedure similar to what is described above, leading to a map at 3.4 Å. Particles leading to this map were merged with particles leading to the best map generated before repicking with Topaz, and duplicates were removed, leading to a map at 3.5 Å. This map had less anisotropy than the one produced without Topaz, and allowed for clearer visualization of the C-terminal helix. An additional round of CTF refinement, particle subtraction to remove the contribution of the nanodisc density and subsequent 3D refinement yielded a map at 3.4 Å and used for model building.Particle positions and angles from the final cryoSPARC2 refinement job were input into Relion 3.1 9 and refined into the density for TWIK1 at high pH using Phenix.real_space_refine with Ramachandran and NCS restraints50. In the high pH structure, the bottom of TM2 and the TM2-TM3 linker (T161-A180) are much lower in resolution, possibly due to potential conformational flexibility. For this region, the model was first built in the low pH structure, using a model predicted by AlphaFold251, refined, and then docked into the high pH structure. Molprobity52 was used to evaluate the stereochemistry and geometry of the structure for manual adjustment in Coot53 and refinement in Phenix. Cavity measurements were made with HOLE implemented in Coot54. Figures were prepared using PyMOL, Chimera, ChimeraX, and Prism.Cryo-EM maps were sharpened using Relion LocalResFull-length TWIK1 was cloned into a modified pGEMHE vector using Xho1 and EcoR1 restriction sites such that the mRNA transcript encodes full-length TWIK1 with an additional “SNS” at the C-terminus. Three mutations  were introduced into this construct via inverse PCR to improve trafficking of the channel to the cell membrane, remove any possibility of SUMOylation, and increase basal currents. This construct was used as the background construct for all other mutants in this study, which were also generated via inverse PCR. The following primers were used: I923A/M294Afwd CATGACCAACTGAGCTTC, I923A/M294Arev AACTTGATCCTCATCCTTGT, H122Nfwd CCATTGTCGGATGGT, H122Nrev ACCGGTAGTGGACAA, T123Cfwd TTGTCGGATGGTGGAAAG, T123Crev GTAACCGGTAGTGGACAA, T123Vfwd TTGTCGGATGGTGGAAAG, T123Vrev GTAACCGGTAGTGGACAA, T123Gfwd TTGTCGGATGGTGGAAAG, T123Grev GTAACCGGTAGTGGACAA, T123Dfwd TTGTCGGATGGTGGAAAG, T123Drev GTAACCGGTAGTGGACAA, D230Lfwd CCTGGAGAGGGCTACAAC, D230Lrev GCCGATAGTCGAGAGTGA, D230Nfwd CCTGGAGAGGGCTACAAC, and D230Nrev GCCGATAGTCGAGAGTGA.Xenopus laevis oocytes extracted from anaesthetized frogs. Currents were recorded at 25 °C using two-electrode voltage clamp (TEVC) from oocytes 2 days after mRNA injection. Pipette solution contained 3 M KCl. Bath solution contained either ND96 , or ND96K  at a pH of 8, or 5.5. HEPES was used to buffer each solution to a pH of 8, and MES was to buffer to pH 5.5. Bath volume was kept at 300 uL during recording. Eggs were initially placed in the recording chamber in ND96, with ND96K at pH 8 perfused in the bath afterwards, followed by ND96K at pH 5.5. Currents were recorded and low-pass filtered at 2 kHz using a Dagan TEV-200A amplifier and digitized at 10 kHz with a Sutter Dendrite digitizer.cRNA was transcribed from Nhe1-linearized plasmids in vitro using T7 mMessage mMachine kits, and 2.5–3.0 ng cRNA was injected into Stage V–VI Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2Reporting Summary


Perm1 knockout (KO) mice. The baseline cardiac phenotype of the homozygous Perm1 KO mice appeared normal. However, RNA-sequencing and unbiased pathway analyses showed that homozygous downregulation of PERM1 leads to downregulation of genes involved in fatty acid and carbohydrate metabolism in the heart. Transcription factor binding site analyses suggested that PPARα and PGC-1α are involved in changes in the gene expression profile. Chromatin immunoprecipitation assays showed that PERM1 interacts with the proximal regions of PPAR response elements (PPREs) in endogenous promoters of genes involved in fatty acid oxidation. Co-immunoprecipitation and reporter gene assays showed that PERM1 promoted transcription via the PPRE, partly in a PPARα and PGC-1α dependent manner. These results suggest that endogenous PERM1 is involved in the transcription of genes involved in fatty acid oxidation through physical interaction with PPARα and PGC-1α in the heart in vivo.PERM1 (PGC-1/ERR-induced regulator in muscle 1) is a muscle-specific protein induced by PGC-1 and ERRs. Previous studies have shown that PERM1 promotes mitochondrial biogenesis and metabolism in cardiomyocytes in vitro. However, the role of endogenous PERM1 in the heart remains to be investigated with loss-of-function studies in vivo. We report the generation and characterization of systemic  PERM1 acts as a positive regulator of mitochondrial biogenesis and the oxidative capacity in C2C12 cells in vitro and skeletal muscles in vivo and cultured cardiomyocytes in vitro3. Pathway enrichment analyses revealed that downregulation of PERM1 inhibits cellular metabolism in cultured cardiomyocytes2. The promoter region of the Perm1 gene includes a consensus ERR binding sequence and expression of PERM1 is promoted by PGC-1α and ERRα in vitro5. Conversely, PERM1 also enhances transcriptional activity of ERRα and upregulates a known target of ERRα, Ndufv1 in cardiomyocytes2. These observations suggest that PERM1 possesses an intimate interaction with PGC-1α and ERRα.PERM1 (PGC-1/ERR-induced regulator in muscle 1) is a muscle-specific protein induced by PGC-1α and ERRα and required to express a subset of genes essential for muscle metabolism7. It is also upregulated in the heart during cardiogenesis and postnatal cardiac growth, whereas it is downregulated during pathological hypertrophy and heart failure8. PERM1 confers fatigue resistance to skeletal muscle in vivo through increases in mitochondrial content and oxidative capacity and angiogenesis3. PERM1 also reduces cellular damage resulting from hypoxia and reoxygenation-induced stress and mitigates cell death of cardiomyocytes in vitro8. However, the role of endogenous PERM1 in the pathophysiology of the heart remains unclear due to insufficient characterization of PERM1 loss-of-function mouse models.PERM1 is upregulated by exercise in skeletal muscles and in response to cold stress in inguinal white adipocytes10. PERM1 in the nucleus physically interacts with PGC-1α, thereby regulating nuclear transcription8. PERM1 on the outer mitochondrial membrane interacts with intracellular adapter protein ankyrin B, thereby connecting mitochondria with the sarcolemma10. Furthermore, it has been proposed that PERM1 located on the outer mitochondrial membrane controls the homeostasis of lipid and amino acid metabolites in mitochondria in the heart9. However, how endogenous PERM1 in the nucleus controls transcription of genes involved in mitochondrial biogenesis and oxidative phosphorylation in vivo remains to be clarified, using PERM1 loss-of-function models.Although it has been suggested that there is an intimate interaction between PERM1 and the nuclear PGC-1α-ERRα pathway in the heart and skeletal muscles, the molecular identity of PERM1 remains unclear. Previous studies have shown that PERM1 is located both in the nucleus and the perinuclear space9. However, the relationship between PERM1 and PPARα, in particular, whether and how PERM1 and PPARα interact with one another, and how PERM1 affects the function of PPARα remain unclear. Thus, our goal in this study was to elucidate the role of endogenous PERM1 in the heart in vivo, using Perm1 systemic knockout (KO) mice. We conducted RNA sequencing and bioinformatic analyses and investigated the effect of endogenous PERM1 upon the gene expression profile in the postnatal heart in an unbiased manner. We here report that PPARα plays an important role in mediating the effect of PERM1 upon transcription of genes involved in metabolism in the heart.In this study, we conducted an unbiased pathway analysis in order to identify the functionally relevant signaling mechanisms regulated by endogenous PERM1 in the heart and found that PPARα and PGC-1α are the major mechanisms mediating the effect of PERM1 upon metabolism in the heart in vivo. PPARα is a nuclear receptor that induces genes involved in fatty acid uptake and oxidation. Furthermore, PERM1 and PPARα both interact with PGC-1αPerm1 KO mice is shown in Fig. Perm1 KO mouse hearts compared to in WT mouse hearts  KO, and line 80 Perm 1 (either heterozygous or homozygous) KO mice  KO, and line 80 Perm1 (either heterozygous or homozygous) KO mice , PWd , LVIDd , LVIDs , systolic function EF (ejection fraction), and heart rate (HR), are all similar among WT, line 29 ice Fig. . Organ wPerm1 KO mouse hearts detected 55,451 genes, of which 294 genes were significantly altered by Perm1 deletion   and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The eight most significantly enriched KEGG pathways and ten most significantly enriched GO biological processes in Perm 1 KO hearts are shown in Fig. Perm1 KO mice compared to in WT mice. Of note, downregulation of PPARα target genes was the most prominent change in the Perm1 KO mice. On the other hand, NRIP1 was predicted to be in an activation state  Fig. a. Using ate Fig. c. Taken Perm1 KO and WT mice. RT-PCR analyses showed that mRNA expression of genes involved in fatty acid metabolism, including Cpt1β, Cpt2, Acadm, Lcad and Vlcad, was significantly lower in Perm1 KO mice than in WT mice  family proteins, and CPT29. The changes in the levels of some mitochondrial proteins were accompanied by increases in the levels of phosphatidic acid, phosphatidylinositol and phosphatidylethanolamine, and basic and branched chain amino acids, and decreases in the level of acylcarnitines, without significant alteration in the levels of ATP, ADP, pyruvate, lactate, and TCA cycle intermediates. Whether downregulation of mitochondrial transporter proteins occurs through transcriptional mechanisms remains to be elucidated.A recent proteomic study conducted with systemic 13. PPARα belongs to the PPAR family of ligand-activated nuclear receptors, consisting of three members: alpha, beta/delta, and gamma. Among these receptors, PPARα regulates lipid metabolism18. We found that PERM1 physically interacts with PPARα in the heart. ChIP-qPCR assays indicated that PERM1 interacts with the promoters of genes involved in fatty acid metabolism and regulated by PPARα. Furthermore, downregulation of PERM1 inhibited PPARα-mediated transcription in cultured cardiomyocytes in vitro. Taken together, these results are consistent with the notion that PERM1 interacts with PPARα and positively regulates transcription of PPARα target genes involved in fatty acid metabolism in the heart. The involvement of other transcription factors, including ERRα, in mediating the effect of PERM1 in vivo remains to be investigated.RNA sequencing and transcription factor binding site analyses suggested that downregulation of PERM1 affect gene expression through mechanisms dependent upon PPARα and PGC-1 Fig. c. The an1. In our previous study, we also showed that PERM1 is translocated to the nucleus in response to phenylephrine, a hypertrophic stimulus2. Hence, we hypothesize that PERM1 can interact with PGC1α and PPARα in the nucleus. We here show that PERM1 interacts with PPARα. It has been shown that PGC-1α, a transcription coactivator, interacts with PPARα and stabilizes PPARα binding to the promoters of target genes19. We here also show that PERM1 interacts with PGC-1α and that downregulation of PGC-1α inhibits PERM1-induced stimulation of the PPRE-luciferase reporter. These results suggest that PERM1 stimulates the transcriptional activity of PPARα in a PGC-1α-dependent manner. One possibility is that PERM1 serves as a scaffold, thereby stabilizing PGC-1α-PPARα interaction to upregulate PPARα target genes. A recent study suggested that PERM1 located on the outer mitochondrial membrane affects the levels of phospholipid species9. Whether PERM1 locally affects the level of mitochondrial proteins through transcription-independent mechanisms in the heart remains to be elucidated.How does PERM1 affect the transcriptional activity of PPARα? Currently, the molecular identity of PERM1 remains unclear. It has been reported that PERM1 is located in both the nucleus and the cytosolPerm1 KO mice. The underlying mechanism through which PERM1 regulates carbohydrate metabolism is currently unknown. It has recently been shown that PERM1 is protective against ischemia in cultured cardiomyocytes in vitro8. Since ischemia stabilizes HIF-1α signaling to upregulate glycolysis22, PERM1 may promote expression of genes involved in carbohydrate metabolism through activation of the HIF-1α pathway. Further investigation is needed to test this hypothesis.Our results suggest that mRNA expression of genes involved in carbohydrate metabolism is also downregulated in Perm1 gene26. To minimize this potential problem, we established two lines of KO mice, namely line 29 and line 80, with deletions of 1157 bp and 1346 bp in exon 2, respectively. We confirmed that both lines exhibit complete deletion of PERM1. Both lines showed a similar baseline phenotype after breeding through multiple generations. Thus, it is likely that the deletion of the Perm1 gene specifically causes the phenotype reported here.We used the CRISPR-Cas9 system to generate systemic KO mice. It is possible that genome editing induced a non-specific or off-target alteration in the genome besides the deletion of the DNA segment in exon 2 of the In conclusion, endogenous PERM1 interacts with PPARα and PGC-1α and regulates genes involved in fatty acid in the heart at baseline. These mice should be useful for investigating the role of endogenous PERM1 in vivo at baseline, including during aging, and in response to stress.All methods were carried out in accordance with relevant guidelines and regulations.Perm1 systemic homozygous KO mice (C57BL/6 background) were generated in the Genome Editing Shared Resource of Rutgers-Cancer Institute of New Jersey. Briefly, mouse Perm1 KO was made by coinjecting two CRISPR gRNAs (MilliporeSigma) with Cas9 protein (MilliporeSigma) into C57BL/6J zygotes to generate a deletion in the coding sequence . Founder mice were genotyped to detect the approximate 1.3 kb deletion. Primers Perm1A 5′-ATCCTGGATTTGTGAAGACCCTGC-3′ and Perm1D 5′-ACGGCTTCCTGCTGCTGTCCTG-3′ were used to amplify the alleles. Wild-type alleles in the founders were 1716 bp, whereas deletion alleles were approximately 384 bp, depending on the precise deletion. Founder 80, which was used for subsequent experiments, had a deletion of 1346 bp, which encompassed almost 2/3 of the coding sequence of exon 2. All experiments were performed with randomization and allocation concealment and in a blind fashion. All experiments involving animals were approved by the New Jersey Medical School Institutional Animal Care and Use Committee. All methods are reported in accordance with ARRIVE guidelines (https://arriveguidelines.org) for the reporting of animal experiments.The toes were cut from mice at about 4 weeks of age. The tissue DNA was extracted using tissue extraction buffer . The sample was incubated for 15–20 min at 55 °C and then at 95 °C for 3 min. After that, the sample was neutralized  and the DNA solution was added to PCR premix solution . The primer sequences used were:Perm1 WT Fw:TCTGCCTCGTTCTGTTTCAAAGACTGPerm1 #29 KO Fw:AGCAGCTGGTCAACAGGTGTGTPerm1 #80 KO Fw:TGATGAGTGTGGCTGTACCTCCAPerm1 Rv:CACAGCATCCCAGGCTGCAGAPerm1 homozygous KO, with one band of 260 bp indicate #80 Perm1 homozygous KO, and with two bands indicate heterozygous KO.PCR was carried out using a protocol of 30 cycles of 94 °C for 30 s in the denaturing stage, 60 °C for 30 s in the annealing stage, and 72 °C for 30 s in the extending stage. The PCR product was checked on a TAE gel. Products with one band of 361 bp indicate wild type, with one band of 270 bp indicate #29 4P2O7, 5 mmol/L EDTA, 1:100 diluted Protease Inhibitor Cocktail , and 1:100 diluted Phosphatase Inhibitor Cocktail . Protein amounts were measured by BCA quantification and 20–30 μg were subjected to 10–15% SDS-PAGE. After proteins were transferred to a 0.2 μm PVDF membrane, immunoblots were probed with the indicated antibodies.Heart homogenates were prepared in RIPA lysis buffer containing 50 mmol/L Tris (pH 7.5), 150 mmol/L NaCl, 1% IGEPAL CA-630 (Sigma Aldrich), 0.1% SDS, 0.5% deoxycholic acid, 10 mmol/L NaThe following primary antibodies were used for immunoblots: Anti-Hexokinase II , Anti-GLUT1 , Anti-GLUT4 , Anti-CPT1β , Anti-VLCAD , Anti-Acadm , Anti-PPARα , Anti-PGC-1α , Anti-GAPDH , Anti-Tubulin . Secondary antibodies used were Anti-Rabbit IgG, HRP-link  and Anti-Mouse IgG, HRP-link . In all Western blot images shown in figures, individual lanes correspond to individual mice. Molecular weights (MW) are shown. The signal intensity of Western blots was quantified using ImageJ software and then normalized by the corresponding loading control (Tubulin or GAPDH).Mice were anesthetized using 12 µ/g body weight of 2.5% Avertin (Sigma-Aldrich). Echocardiography was performed by ultrasonography  using a 13-MHz linear transducer. After chest shaving, the mouse was fixed on the platform and needle electrodes were attached for electrocardiography. B-mode and M-mode tracings (seep speed = 100-200 mm/s) were recorded from the parasternal short-axis view at the mid-papillary muscle level.2O2 in PBS to prevent endogenous peroxidation and blocked with 5% BSA in PBS. Cardiomyocyte cross-sectional area was measured from images captured of sections stained with wheat germ agglutinin (WGA). Cardiomyocyte size was measured using ImageJ software. The mean size of cardiomyocytes in WT mice was used as a reference. Interstitial fibrosis was measured using Picro Sirius Red (PSR) staining and ImageJ software. The total percentage of the area of fibrosis was calculated as the sum of red-stained areas divided by total ventricular area. The mean fibrotic area in WT mice was used as a reference.The LV accompanied by the septum was cut into base, middle portion, and apex, fixed with 10% formalin, embedded in paraffin, and sectioned at 4–6 μm thickness. The sections were incubated in 3% HPerm1 KO mice by the TRIzol protocol. WT mice were used as a control group. Samples were eluted in RNase/DNase-free water. Sample quality control, library preparation, sequencing and alignments were performed by the LC Sciences company and Cancer Progression Research Center, National Yang-Ming Chiao-Tung University. The differential expression sequence (DES) gene result was selected based on an adjusted P value less than 0.05. These genes were analyzed using the DAVID Bioinformatics Resource 6.8. According to gene function and pathway annotation, KEGG and GO graphs were designed using GraphPad Prism 8 . The expression levels of indicated fat and carbohydrate metabolism genes in Perm1 KO mice were compared with those in WT mice. The transcription factor analysis was performed by Ingenuity Pathway Analysis . The activation z-score and p-value of overlap indicate the presence of a statistically significant overlap between dataset genes and known targets regulated by a given regulator.Total RNA was extracted from the heart tissue of WT and qRT-PCR was performed using self-designed primers ordered from the IDT company. Tissue RNA was extracted using TRIzol , followed by isopropanol. One µg mRNA was used for reverse transcription using the TB Green Premix Ex Taq II system according to the manufacturer’s instructions . The Cq and starting quantity values from the targeted genes were normalized by the gene expression level of 15S. The ratio of each sample was compared with the average ratio of WT mice.For in vitro experiments, neonatal ventricular cardiomyocytes were plated in 10 cm dishes. Cells were transduced with adenovirus harboring Flag-PERM1. The cells were harvested after one day. Immunoprecipitation was carried out by incubating with anti-Flag M2 affinity gel  overnight at 4 °C. The beads were washed and 2 × sample buffer was added to produce the final sample. For in vivo experiments, hearts were harvested and homogenized in lysis buffer. For immunopreciption wth anti-PERM1 antibody, the lysate was incubated by anti-IgG  or anti-PERM1 antibody  overnight at 4 °C. For immunopreciption with PPARα, the lysate was incubated with anti-IgG  or anti-PPARα antibody  overnight at 4 °C. Protein A/G-Agarose  was added the next day for one hour. The final steps were the same as for in vitro immunoprecipitation. Immunoblot was conducted by primary anti-PPARα , anti-PGC1α  or anti-PERM1 antibody.Perm1 (SI02021775), rat PGC-1α (SI00271012), and rat PPARα (SI01963451) and control siRNA (1022076) were obtained from Qiagen. The siRNA was transfected using Lipofectamine RNAiMax (Invitrogen). Four and a half µl of Lipofectamine RNAiMax was diluted with 125 µL OPTI-MEM and 2 µL of 20 µmol/L siRNA was diluted with 125 µL OPTI-MEM. The diluted Lipofectamine RNAiMax and siRNA were then mixed and incubated at room temperature for 20 min. After incubation, the mixture was added to cardiomyocytes plated on a 3.5 cm dish with 2 mL OPTI-MEM.Small interfering RNA (siRNA) for rat Perm1 sequences were cloned from mouse cDNA. pDC316 plasmid was digested by restriction enzymes. The Perm1-Flag sequence was then cloned into the digested pDC316 plasmid (pDC316-Perm1-Flag). After sequencing, HEK293 cells were used for adenovirus packaging and amplification. Adenovirus harboring β-galactosidase (Ad-LacZ) was used as a control.The 2.Luciferase reporter assays were conducted using a luciferase assay system . Neonatal ventricular cardiomyocytes were plated in a 12-well dish. Reporter plasmids (0.3 µg per well) including 3xPPRE-luc, pGL3-Acox1 promoter, pGL3-Acadm promoter, Acox1-PPRE-luc, Acadm-PPRE-luc and Acadm-PPREmutant-luc was transfected together with PERM1 expression vector  using Lipofectamine 2000  for 24 h. For knockdown experiments, reporter plasmd (0.3 µg per well), mammalian expression vector such as PPARα (pDC36-PPARα) or Perm1 (0.3 µg per well), and siRNA (40 pMol) such as siScrable, siPPARα, siPGC-1α and siPerm1, were transfected with Lipofectamine 2000. pDC316 control vector was used so that total plasmids were equal at 1 µg per well. The cells were harvested in 100 µL Reporter lysis buffer  per well after 2–3 days of transfection. Luminescence was normalized by protein content. The average value of the control group (pure pDC316 vector and siScramble) was expressed as a relative value of 1.0. Reporter plasmids, including PPRE-luciferase, were described previouslyAATGACTGC) were cloned into pGL3basic with 32 bp of minimal promoter (TAGAGGGTATATAATGGAAGCTCGACTTCCAG) to generate Acox1-PPRE-luc, Acadm-PPRE-luc and Acadm-PPREmutant-luc.Mouse endogenous 5′ promoter region of Acox1 (505 bp) and Acadm (700 bp) from start codon were cloned into pGL3 basic vector to generate pGL3-Acox1 promoter and pGL3-Acadm promoter. Endognous PPRE sequence in Acox1 promoter (AACGTGACCTTTGTCCTGGTC), Acadm (GTAAAGGTCACAGCTGACTGC) and its mutant . RT-PCR of the chromatin fragment was conducted using Maxima SYBR Green qPCR master mix . The primers were designed as: FAO activity was analyzed using Fatty Acid Oxiation Assay Kit . Briefly, heart tissues were subjected to homogenization with ice-cold Cell Lysis Solution. The sample was then centrifuged by 14,000 rpm for 5 min, the supernatant was harvested and the protein concentration was determined with the BCA protein assay. The sample was mixed with FAO substrates diluted with the FAO assay solution and incubated 37 °C for 30–60 min. The absorbance at 492 nm was measured.t test and multiple group comparisons were performed by 1-way or 2-way ANOVA, followed by Tukey post-test. A priori power calculations were performed based on data from published studies28 and pilot experiments. The effect size in this study was 1–5 with alpha = 0.05 and power = 0.80. Microsoft Excel 2016 was used for Student’s t tests and GraphPad Prism 9 was used for ANOVA and Tukey post-test. Dot plot was used. All quantified Western blot and cell viability data are shown as values relative to control. The survival rate was calculated by the Kaplan–Meier Curve method.All values in graphs are expressed as the mean Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.


Purpose: To investigate the in vitro anti-skin-aging properties of Cratoxylum formosum extract and encapsulate this plant extract in nanostructured lipid carriers (CFE-NLCs) for dermal application.Methods: The biological properties of the plant extract, including enhanced procollagen type I synthesis and anti-matrix metalloproteinase activity, were evaluated to assess its cosmetic benefits. An artificial neural network (ANN) coupled with K-fold cross-validation was applied to investigate the effects of the formulants and optimize the CFE-NLCs. The physicochemical properties, percutaneous absorption, and irritation potential of the CFE-NLCs were analyzed.Results: Liquid chromatography-mass spectrometry analysis revealed that CFE contained 5-O-caffeoylquinic acid as the vital constituent. Appropriate skin-care properties were also demonstrated with respect to enhanced type I procollagen synthesis and the inhibition of MMP-1, MMP-3, and MMP-9 in primary human dermal fibroblasts. The optimal CFE-NLCs exhibited better skin absorption and biocompatibility and lower irritation potential than the free botanical extract solution.Conclusion: The findings obtained highlight CFE-NLCs as promising skin-care ingredients. However, low stability, a lack of skin absorption, and irritation frequently impede the use of plant extracts containing bioactive molecules in cosmetics. The most popular approach to overcome these limitations is the engineered nanoscale formulation strategy, which has introduced new challenges in the cosmetic field.Recent trends in natural product research have greatly improved the prevention of skin aging and other cellular oxidative stresses.Cratoxylum formosum (Jacq.) Benth. & Hook.f. ex Dyer (Hypericaceae family) are rich in phenolic compounds, among which 5-O-caffeoylquinic acid (5CQA) has been identified as the major component. Studies have reported that C. formosum extract (CFE) exhibits antioxidant activity, cellular protection against oxidative stress, antibacterial activity and anti-nonmelanoma skin cancer activity when used in aqueous form to synthesize ZnO nanosheets, antigenotoxicity, and anti-inflammatory properties.The young leaves of C. formosum leaf extract, exhibits vital biological activities, such as the promotion of type 17 collagen production, the prevention of anionic surfactant-induced itching in the epidermis, protection against ultraviolet-A-induced oxidative stress, and antioxidant, antibacterial, anti-inflammatory, antimutagenic, anticancer, and immunomodulatory properties. Thus, evidence of the health benefits of 5CQA and 5CQA-rich plant extracts supports the possible application of CFE to dermocosmetics.Interestingly, 5CQA, the main component of  Xue et al reported that 5CQA was unstable: cis-5CQA (24% relative content) and methylated 5CQA (1% relative content) degraded after seven days of storage at room temperature under light irradiation. In addition, 5CQA is hydrolyzed to quinic acid, caffeic acid, and cis-caffeic acid when processed in boiling phosphate buffer at pH ≥ 7. Conversely, 5CQA remains stable at pH ≤ 6, even when the compound is heated for more than 6 h in phosphate buffer. In addition, the skin can absorb only a limited amount of 5CQA. The low bioavailability is attributed to the hydrophilicity of 5CQA, which hinders it from passing the lipophilic membrane barrier. In addition, 5CQA has a short half-life and high distribution and elimination rates in the human body. These properties restrict the potential use of this plant extract, especially in water-based cosmetic products.Despite its cosmetic potential, the use of bioactive molecules of CFE is most often impaired by stability constraints or insufficient dermal absorption. Specifically, 5CQA readily undergoes oxidation, is unstable at high temperatures (100–200°C) and neutral to alkaline environments (pH ≥ 7), and undergoes isomerization and methylation during processing and storage. In the cosmetic and pharmaceutical industries, NLCs have received much attention for use in conserving biological properties, controlling release, and enhancing bioavailability. In our preliminary study, some NLC factors were screened to select their relevant ranges for encapsulation of phenolics from CFE. Unfortunately, the implementation of response surface methodology (RSM) neither successfully achieved the required formulation nor modeled the complicated relationship between the studied variables. This result is attributed to the limits of RSM in overcoming the simple relationship between the formulation parameters in a linear or quadratic relationship. Therefore, the optimum NLCs containing plant extracts rich in 5CQA for dermal targeting have yet to be identified, and most current studies still apply a one-factor-at-a-time approach in formulation optimization.Studies have shown that the chemical stability of sensitive molecules can be improved by nanoscale particles, such as transfersomes, nanoparticles, and nanostructured lipid carriers (NLCs). Thus, an artificial neural network (ANN), an intelligent machine learning tool, is chosen instead of RSM to solve complex and nonlinear relationships related to formulation processes without a prior model option. This versatile technology has been used by scientists from various disciplines and has emerged as a particularly attractive technology for the cosmetic industry. This study aimed to (i) investigate the in vitro anti-skin-aging properties of 5CQA-rich CFE, (ii) optimize the encapsulation of this plant extract in nanostructured lipid carriers (CFE-NLCs), and (iii) evaluate its cytotoxicity and irritation effects for dermal applications.2O2 ; and Dulbecco’s modified Eagle’s medium (DMEM), fetal bovine serum (FBS), penicillin-streptomycin, 0.25% trypsin-EDTA, and 3--2,5-diphenyltetrazolium bromide (MTT) . All the chemicals used were of analytical grade.The following chemicals were used in this study: glyceryl behenate ; poloxamer 188, polysorbate 80, ˪-ascorbic acid, and 5CQA ; glyceryl monostearate ; caprylic/capric triglycerides ; HC. formosum were collected from a local field in Ubon Ratchathani province, Thailand. The plant was identified by comparison to the voucher specimen BCY No. 022 deposited in the herbarium of the Faculty of Pharmaceutical Sciences, Ubon Ratchathani University. The leaves were dried at 50°C and sifted through a 40-mesh screen sieve. Extraction of the plant powder was performed using a heat-reflux method  according to the optimized extraction conditions previously reported by the authors. Ethanol was removed under vacuum, and the resulting CFE in aqueous solution was dried in a freeze dryer  before use.Cultivated young leaves of  The instrument consisted of a Dionex UltiMate 3000 RS LC system connected to an LTQ XL linear ion-trap mass spectrometer, and data processing was performed by Xcalibur 2.2 software . The sample (5 mg/mL) (5 µL) was injected into a LiChrospher® RP-18 column  using 0.1% (v/v) formic acid in water (A) and acetonitrile (B) as the eluent. For chromatographic separation, the eluent proportion began at 5% B (5 minutes), increased from 5% B to 50% B (45 minutes), remained constant at 50% B (10 min), and returned to 5% B (2 minutes). The eluent flow was 0.5 mL/min, and the column temperature was maintained at 35°C. The PDA range was set at 190 to 500 nm. Specific conditions for mass spectrometric analysis were set as follows: electrospray ionization, negative and positive ion modes; capillary temperature, 330°C; source heater temperature, 250°C; sheath gas flow, 50 arbitrary units; auxiliary gas flow, 10 arbitrary units; capillary voltage, –45 V; source voltage of negative ion mode, 3 kV; source voltage of positive ion mode, 3.5 kV; source current, 100 µA; normalization collision energy, 35%; mass range, 50–2000 atomic mass units. MSn spectra were generated by collision-induced dissociation using helium as the collision gas. The polyphenolic components of CFE were tentatively identified by comparing their retention times, ultraviolet spectra, and MSn fragmentation patterns to those of authentic compounds and those reported in the literature.Polyphenols in CFE were identified using HPLC-PDA-ESI-MS analysis. The sample (10 µL) was injected into a Hypersil Gold C18 column . The mobile phase consisted of 50 mM phosphoric acid in water (solvent A) and acetonitrile (solvent B) at a flow rate of 0.7 mL/min. The stepwise elution was performed as follows: 5% B for 5 min, 5% B to 50% B in 45 min, 50% B for 10 minutes, and 50% B to 5% B in 2 minutes. The column temperature was 35 ± 0.1°C, and detection was performed at 320 nm. 5CQA was quantified by comparing the peak area obtained with the calibration curve of the authentic chemical.The 5CQA content of CFE was determined using HPLC . HDFn cells were seeded overnight at a density of 5 × 103 cells/well on a 96-well culture plate and then treated with various concentrations of CFE (0–5000 µg/mL) for 24 hours. The culture medium was replaced with 0.5 mg/mL MTT solution, and the cells were incubated for 3 hours at 37°C. The MTT solution was removed, and 100 μL of dimethyl sulfoxide (DMSO) was added to solubilize the formazan product. The intensity of the formazan product was measured at 570 nm using a PowerWave XS2 microplate reader . The relative cell viability of the treatment group was calculated as a percentage of that of the vehicle control group.HDFn cells were grown in DMEM supplemented with 10% FBS, 1% GlutaMax, and 1% penicillin-streptomycin solution according to the method previously reported by this group of authors.5cells/well overnight. The cells were treated with varying concentrations of CFE (0–100 µg/mL) in serum-free medium for 48 hours. After incubation, the cell-free supernatants were collected from each well, and collagen levels were determined using a Human Procollagen I α1 ELISA Kit  following the instructions of the manufacturer. ˪-Ascorbic acid (200 μg/mL) was used as a positive control, and the results were normalized to confluent cell numbers.HDFn cells were incubated in 6‐well plates at a density of 3 × 105cells/well and cultivated for 24 hours. The cells were treated with different concentrations of CFE (0–100 µg/mL) or with 200 μg/mL ˪-ascorbic acid in serum-free medium for 1 h before the addition of lipopolysaccharides (LPSs) (1 µg/mL). After 12 and 24 hours of LPS exposure, the cell-free supernatants were collected from each well and centrifuged at 15 000 rpm and 4°C for 15 min. The MMP-1, MMP-3, and MMP-9 levels in the culture media were measured using MMP-1, MMP-3, and MMP-9 ELISA kits  according to the manufacturer’s instructions.HDFn cells were seeded into 6‐well plates at a density of 3 × 10 The NLCs comprised solid lipids (glyceryl behenate:glyceryl monostearate = 1:1), liquid lipids (caprylic/capric triglyceride), emulsifiers (polysorbate 80:poloxamer 188 = 1:1), and CFE as an active ingredient. The lipid and aqueous phases were separately heated at 80°C for 10 minutes. The preparation temperature did not decompose 5CQA. The hot aqueous phase containing CFE and emulsifier was then added to the lipid phase followed by 10 min of homogenization at 6000 rpm . The particle size in the obtained coarse emulsion was then reduced by applying an ultrasonic cell disruption device  for 10 min . The resulting nanoparticles were cooled to room temperature, stored in N2-flushed glass bottles, and shielded from light for further study. The above procedure was also used to prepare blank NLCs without CFE.The CFE-NLCs were prepared by a high-shear ultrasonic homogenization method.X1), liquid lipids (X2), emulsifiers (X3), and CFE (X4) in the mixture. The hydrodynamic diameter (Y1), polydispersity index (PDI) (Y2), zeta potential (Y3), and entrapment efficiency (%EE) of 5CQA in NLCs (Y4) were assigned as the dependent variables because they are essential features of the nanoparticles. The coded independent variables in the CCRD were calculated from Eq. (1). A central composite rotatable design (CCRD) was applied to optimize the formulation parameters of CFE-NLCs. This statistical design consisted of a 16-factorial design, 8 axial points, and 6-center-point replication. Factorial and axial points were used to estimate the curvature of the model, whereas replicate experiments were used to assess the pure error sum of squares. The independent variables included the proportions of solid lipids  function .function  was applR2 and entropy R2 in the training and validation sets.The optimum ANN model was calculated by changing the number of neurons in the hidden layer and choosing the minimum root-mean-square error (RMSE), mean absolute deviation, and –log likelihood values obtained when achieving the maximum generalized Y) were calculated from each neuron in the hidden layer by summing each neuron and applying the weights as described in Eqs. (3) and (4).The predicted response values .Based on the relative weight predicted by the ANN model, the effect of each independent variable on the response was calculated using Eq. (5). The superscripts  Before measurement, the samples were diluted with ultrapure water to a 1:300 dilution. All measurements were repeated at least three times at 25°C.The hydrodynamic diameter, PDI, and zeta potential of the CFE-NLCs and blank NLCs were determined using a Zetasizer Nano ZS instrument coupled with Dispersion Technology software (version 5) .EE of 5CQA in the CFE-NLCs was determined by the ultrafiltration and centrifugation method. A sample (500 µL) was placed in a sample compartment with a filter membrane  and centrifuged at 5000 rpm for 10 minutes at 4°C . The level of 5CQA in the filtrate was determined by the HPLC-PDA method . The %EE values of 5CQA in NLCs were calculated indirectly using Eq. (6).The %C1 and C2 represent 5CQA in the CFE-NLC dispersion and supernatant, respectively.where  Each sample was diluted in deionized water, placed on carbon tape, and dried at room temperature. The samples were then gold-coated before analysis. SEM images were visualized under low vacuum at a 10 kV accelerating voltage.The morphology of the NLCs was elucidated by SEM .e/400, Mettler-Toledo Corporation, Switzerland). Accurately weighed out freeze-dried samples and their ingredients (5–7 mg) were placed in an aluminum pan and analyzed by heating from 30°C to 100°C at 10°C/min while flushing with 40 mL/min N2. A hermetically sealed empty pan was used as a reference. DSC thermograms were then analyzed using STAR® SW9.30 software.The thermal behaviors of the CFE-NLCs, blank NLCs, and bulk raw materials were examined using a differential scanning calorimeter .w/v) polysorbate 80 to maintain sink conditions. The quantity of 5CQA was then analyzed by the HPLC-PDA method , and the result was expressed as the percentage of cumulative release. The possible release mechanisms according to the zero-order, first-order, Higuchi, Hixon-Crowell, and Korsmeyer-Peppas models were applied to fit the release kinetics.The release profiles of 5CQA in CFE-NLC and free CFE solutions were studied using a dialysis method. Samples (1 mL)  were poured into a preswollen dialysis bag . The bag was dialyzed against phosphate-buffered saline  for 24 hours at 100 rpm and 37°C. The sample (1 mL) was collected at a predetermined time and replaced with an equivalent amount of fresh medium. All media contained 1% ( Test samples (0.5 mL) were applied to the dorsal skin with an effective diffusion area of 1.86 cm2. The receiving chamber was filled with PBS (pH 7.4) containing 1% polysorbate 80 (12 mL) and maintained at 37°C with a surface temperature of 32°C under continuous stirring at 500 rpm. The receiver medium was withdrawn at 1, 3, 6, 12, and 24 hours. After 24 hours, the skin surface was washed with PBS. The stratum corneum was separated from the skin using tape stripping 15 times with 3M Scotch Tape . The 5CQA amounts in the tapes and the remaining chopped skin (viable epidermis and dermis) were extracted in a mixture of methanol and water (50:50 v/v) using a sonicator. The quantity of the extracted 5CQA was then determined by HPLC-PDA.The in vitro skin permeation analysis of CFE-NLCs was evaluated by Franz diffusion cells using free CFE dissolved in propylene glycol as a control group. Porcine ear skin was prepared as described in our previous study. Fertilized hen eggs (Rhode Ireland Red) (weight between 50 and 60 g) were incubated for 9 days in an automated rotating machine  at 37.8 ± 0.3°C and 58.0 ± 2.0% relative humidity. The experiment was validated with 0.9% NaCl (negative control) and 0.1 N NaOH solution (positive control). The test solutions (300 µL) were then added to the CAM, and the irritation effect was observed under a stereomicroscope combined with Image Framework software . The onset times in seconds of vascular hemorrhage, lysis, and coagulation were monitored within 300 s. The irritation scores were calculated according to Eq. (7):The HET-CAM assay was applied to evaluate the irritation potential of CFE-NLCs according to the ICCVAM protocol. The irritation characteristics were rated on the following scale: from 0 to 0.9 as nonirritant; from 1 to 4.9 as mildly irritant; from 5 to 8.9 as moderately irritant; and from 9 to 21 as strongly irritant. The eggs were then frozen at −20°C overnight to kill the embryo at the end of the experiments. The physicochemical stability of the CFE-NLCs was evaluated by storage at 4 ± 2°C, 25 ± 2°C, 40 ± 2°C, and 75 ± 3% relative humidity for 90 days.P < 0.05.All measurements were performed in at least triplicate, and the data obtained are expressed as the means ± standard deviations (SDs). The experimental results were analyzed by analysis of variance (ANOVA) followed by Tukey’s test at – at m/z 353, 191, 179 and 135. The ultraviolet spectrum of the hydroxycinnamic moiety confirmed the identification, with maximum bands at approximately 242 nm and 320–329 nm and a shoulder (sh) at 295–300 nm.The yield of CFE obtained by heat-reflux extraction was 16.90 ± 0.65 wt% (dry basis), and its phytochemicals were characterized by HPLC-PDA-ESI-MS. Several chlorogenic acid derivatives, which are compounds formed by ester bonds between quinic acid and certain transcinnamic acids, were detected in CFE. This result is attributed to the presence of fragmented ions [M–H]3  was predominant in the HPLC chromatogram. This peak revealed the spectral character of caffeoylquinic acid by showing the [M–H]– parent ion at m/z 353 and [M–H]– fragment ions at m/z 191 and 179. This fragmentation pattern is consistent with deprotonated quinic acid and caffeic acid. The potential MSn fragmentation pathway of compound 3 is detailed below. This substance showed deprotonated [M–H]– ions at m/z 353 with cleavage of the entire B-ring, yielding a fragment ion at m/z 191 [M–162–H]–. Additional fragmentation of the precursor ion at m/z 191 triggers a loss of formic acid (CH2O2), opens the A-ring, and produces MS3 fragment ions at m/z 173 [M–180–H]–, m/z 127 [M–226–H]– and m/z 85 [M–268–H]–. The MS2 base peak at m/z 191 with a weak MS2 ion at m/z 179 (<5% base peak) can be used to distinguish individual monoacyl chlorogenic acids. Thus, peak 3 was identified as 5CQA by comparison to the authentic standard and the literature.Peak 3   (UV λmax 198 nm); MS2 at m/z 127(100), 173(83), 85(71), and 93(48); and MS3 at m/z 85(100), 99(40), and 109(47). Thus, 1 was identified as quinic acid. Peak 2  showed an [M–H]– ion at m/z 371, and deprotonation of this compound yielded MS2 with a main fragment ion at m/z 353. The difference in mass between 371 and 353 is 18 Da, which can be explained by the addition of two hydrogen atoms and one oxygen atom to a chlorogenic moiety. The presence of fragment ions at m/z 353, 341, 191, 173, 161, 135, and 111 is indicative of CQA derivatives. Therefore, peak 2 was provisionally identified as dihydroxy-dihydro caffeoylquinic acid. Peak 4 (tR 25 minutes) exhibited a molecular ion at m/z 337 and main fragment ions at m/z 191 [quinic acid–H]– (UV λmax 239 nm) and 173 [quinic acid–H-H2O]– (UV λmax 311 nm). These results indicate that the compound is a derivative of quinic acid or caffeic acid. Peak 4 was therefore tentatively defined as the p-coumaroylquinic acid isomer.Other minor components were peaks 7, and 8 ; Table 35  and 6  showed both an [M–H]– ion at m/z 515 and an [M–H]+ ion at m/z 517, indicating a molecular weight of 516. An [M–H]– ion at m/z 515, fragment ion [M–C9H6O3]– at m/z 353 (caffeoylquinic acid), and fragment ions at m/z 191 [M–H–2C9H6O3]–, m/z 173 [M–H–2C9H6O3–H2O]–, m/z 135 [M–C7H10O5–C9H6O3–COOH]–, and m/z 179 [M–H–C9H6O3–C7H10O5] were noted. These fragmentation patterns are consistent with the identification of the compound as dicaffeoylquinic acid (diCQA). The positions of the caffeic acid substituents in the 1,3-, 1,4- and 1,5-diCQA isomers could be distinguished using MSn fragmentation. Thus, peak 5 was identified as 1,3-diCQA, whereas peak 6 was identified as 3,5-diCQA.Peaks 7 and 8 had similar UV spectra characteristic of a ferulic acid structure . Peak 7 showed a molecular ion at m/z 499. Deprotonation of this molecule produced a secondary ion at m/z 337. The base peak of MS2 (m/z 337) yielded m/z 173 in MS3. These results indicate that this compound was vic-4,5-p-coumaroyl-caffeoylquinic acid. The peak 7 fragmentation pattern was consistent with the previous report’s designation of 4-O-p-coumaryl-5-O-caffeoylquinic acid. Peak 8, with an [M–H]– ion at m/z 483, produced MS2 and MS3 base peaks at m/z 337 and m/z 173, respectively, due to the loss of a coumaroyl unit (146 Da). It was tentatively identified as 4,5-di-O-p-coumaroylquinic acid.Peaks  Overall, 5CQA was assigned as a functional and chemical marker for CFE because it was the vital component and exhibited the desired biological properties. The content of 5CQA, a significant phenolic compound determined by HPLC-PDA, was 241.66 ± 0.07 mg/g plant extract. Aging is not only a cosmetic concern but also a medical issue, as it is a complex process affecting the appearance, structure, mechanism, and function of the skin. Collagen production in naturally aged skin or skin aged by overexposure to ultraviolet radiation decreases with higher levels of MMPs. Reactive oxygen species levels can also be amplified by both intrinsic and extrinsic factors to stimulate mitogen-activating protein kinases. This mechanism can induce activator protein 1, promote the gene expression of MMPs and inhibit type I procollagen synthesis. Regulating cellular oxidative stress, collagen metabolism, and MMP levels is therefore an essential skin-care strategy. The tests below were performed to verify the in vitro effects of CFE for skin care applications.50 of CFE could not be calculated from the experiment . According to this result, CFE is considered a nontoxic substance . Concentrations of plant extract of up to 100 µg/mL were used for further analysis of the biological properties of CFE.The cytotoxicity of CFE to HDFn cells was tested to determine the safe dose of plant extract. The MTT results showed that CFE had no toxic effects on HDFn at concentrations up to 1000 µg/mL, with cell viabilities of > 80%; thus, the ICP < 0.05). The effect was concentration dependent, as shown by the procollagen type I levels of 1268.05 ± 34.46, 1843.40 ± 53.74, and 2388.94 ± 45.69 pg/mL obtained after 48 hours of treatment with 1, 10, and 100 µg/mL CFE, respectively. CFE yielded significantly less stimulation than treatment with 200 µg/mL ˪-ascorbic acid (2893.23 ± 78.72 pg/mL), a positive control that is well known to promote procollagen production.Procollagen synthesis is a crucial factor that directly influences the regenerative process of the skin. To examine the effect of CFE on collagen synthesis, HDFn cells were treated with different concentrations of CFE, and the results are shown in Figure S1b. ELISA analysis revealed that all concentrations of CFE significantly increased type I procollagen synthesis compared with that in the untreated control group (P < 0.05). Interestingly, MMP expression levels decreased significantly in a dose- and time-dependent manner compared with those in LPS-treated cells. CFE at doses of 1, 10 and 100 µg/mL markedly reduced MMP-1 production by 7.51 ± 0.22, 6.75 ± 0.16, and 6.46 ± 0.14 ng/mL at 12 hours of exposure, respectively, and 7.37 ± 0.24, 6.45 ± 0.25, and 6.24 ± 0.27 ng/mL at 24 hours of treatment, respectively. A similar trend was also observed for MMP-3 and MMP-9 levels: higher doses corresponded to greater potency. A possible explanation could be that polyphenols in CFE can chelate metal ions, decreasing the free zinc concentration needed for MMPs.MMPs are a family of zinc-containing proteinases that cause extracellular matrix protein degradation. Increased production of MMP enzymes is not only linked with inflammation of human tissues but also associated with the degradation of collagen, which is related to natural aging and photoaging. In this study, extracellularly secreted MMP-1 (collagenase 1), MMP-3 (stromelysin 1), and MMP-9 (gelatinase B) were examined because the combined action of these enzymes can completely degrade collagen and components of the elastic network, leading to the formation of wrinkles in the skin. LPS-treated HDFn (1 µg/mL) increased the expression of MMP-1 , MMP-3 , and MMP-9  by more than twofold compared with that in untreated control cells  > 0.82. In addition, low and randomly dispersed residues were observed for both datasets, revealing that the errors were not correlated and had the same variances. These results suggested that the derived mathematical equations were acceptable and could be used to predict the response variables in the design space. The obtained hidden layer (H) codes are described by Eq. (8):Several cross-validation methods have been implemented for ANN modeling, including the jackknife test (K-fold and leave-one-out), bootstrapping, the Monte Carlo test, the three-way split test, and the disjoint set test. This study applied K-fold cross-validation to run the algorithm. Unlike the three-way split test, the K-fold method (K = 5) contained only two datasets; random division into 80% for training and validation and 20% for testing subgroups was performed in our analysis . The preectively , was choectively . The corH1 = TanH(0.5(0.69X1 – 0.09X2 – 0.28X3 – 2.79X4 + 3.07));H2 = TanH(0.5(–0.66X1 – 0.26X2 – 1.99X3 –0.62X4 + 18.45));H3 = TanH(0.5(–0.24X1 + 0.07X2 – 0.07X3 – 2.57X4 + 0.50));H4 = TanH(0.5(0.22X1 + 0.26X2 – 0.29X3 – 1.00X4 – 4.35));H5 = TanH(0.5(0.05X1 – 0.22X2 + 0.74X3 + 2.24X4 + 1.08));H6 = TanH(0.5(0.09X1 + 0.05X2 – 1.88X3 + 4.23X4 – 2.99));H7 = TanH(0.5(0.05X1 – 0.14X2 – 1.91X3 + 2.81X4 + 7.28));H8 = TanH(0.5(–1.22X1 + 0.13X2 + 0.66X3 + 0.01X4 + 2.31));H9 = TanH(0.5(–0.92X1 – 0.08X2 – 1.42X3 – 2.40X4 + 14.92));HH1 = TanH(0.5(–2.47H1 + 1.80H2 – 1.04H3 + 0.17H4 + 2.64H5 + 2.81H6 + 2.45H7 + 0.76H8 – 4.03H9 + 1.97));HH2 = TanH(0.5(–0.58H1 + 3.96H2 – 0.95H3 + 1.12H4 – 2.31H5 – 2.05H6 + 1.00H7 – 1.42H8 + 0.14H9 – 0.61));HH3 = TanH(0.5(–0.55H1 + 2.30H2 + 0.51H3 + 0.31H4 – 1.62H5 + 0.14H6 + 0.49H7 – 0.77H8 + 4.15H9 –1.34));HH4 = TanH(0.5(0.81H1 – 0.25H2 + 0.48H3 – 5.18H4 + 0.60H5 – 0.70H6 – 0.78H7 + 1.88H8 + 2.67H9 + 0.34));HH5 = TanH(0.5(2.41H1 – 1.86H2 – 1.43H3 + 1.12H4 – 1.49H5 – 0.55H6 + 3.74H7 – 1.08H8 – 0.14H9 + 2.29));HH6 = TanH(0.5(0.12H1 + 2.43H2 – 1.94H3 – 0.92H4 –1.63H5 – 2.39H6 + 1.14H7 – 1.90H8 + 0.50H9 – 0.97));HH7 = TanH(0.5(–0.64H1 – 0.17H2 – 1.41H3 – 0.68H4 + 0.32H5 – 2.35H6 + 0.73H7 – 1.95H8 – 0.18H9 – 0.92));HH8 = TanH(0.5 (0.10H1 + 0.87H2 – 1.34H3 – 1.35H4 – 0.56H5 – 3.26H6 + 1.15H7 – 0.77H8 – 0.94H9 – 0.82)); andHH9 = TanH(0.5(–1.09H1 – 2.39H2 – 2.54H3 – 0.35H4 + 0.40H5 – 1.37H6 – 0.10H7 + 0.05H8 + 1.26H9 – 1.94)) (8) The relationship between the responses of the CFE-NLCs and the tested independent variables is shown by the final layer codes (Eqs. 9–12).Y1 (nm) = 18.19HH1 – 40.03HH2 + 26.22HH3 – 146.97HH4 – 78.91HH5 + 180.00HH6 + 121.12HH7 – 112.00HH8 – 102.29HH9 + 170.31; (9)Y2 = –0.02HH1 + 0.09HH2 – 0.04HH3 – 0.07HH4 – 0.10HH5 + 0.20HH6 + 0.03HH7 – 0.13HH8 + 0.13HH9 + 0.30; (10)Y3 (mV) = –2.54HH1 + 0.15HH2 – 1.86HH3 + 0.35HH4 + 0.94HH5 + 2.50HH6 – 0.33HH7 – 0.10HH8 + 3.16HH9 – 10.73; and (11)Y4 (%) = 3.90HH1 + 29.57HH2 – 10.98HH3 – 1.71HH4 – 5.88HH5 – 18.64HH6 – 12.30HH7 + 14.02HH8 + 11.59HH9 + 61.43 (12) In this study, K-fold cross-validation strengthened the overfitting network. By running the algorithm, the initial datasets were randomly split into training and testing subgroups. K rounds (an appropriate K of 5 was selected in this study) of training-validation-testing were performed on different, nonoverlapping, and equally proportioned training, validation and testing sets. This strategy could mitigate errors in applications with unseen data, as supported elsewhere.Overfitting of a built ANN model may occur when any learning system matches its training set almost perfectly but continually struggles with unseen data.Overall, the applied computerized modeling approach was successful in fitting the NLC model. The ANN approach used in this study has a number of advantages. This algorithm effectively handles a large number of variables with varying degrees of complexity by generating a solution with a high predictive accuracy. It is capable of completing tasks that are inaccessible to nonlinear RSM models. Due to its parallel nature, ANN technology produces high-quality output even in the presence of noise and can continue operating uninterrupted even if the network fails. However, ANNs have some drawbacks in that they require a large amount of data for trial and error to emulate the appropriate architecture. As a result of this feature, the training data required a lengthy processing period. Other process parameters were kept constant throughout the trials to avoid interference. Setting the temperature of the oil and aqueous phases to 80°C was sufficient to melt the solid lipids without decomposition of 5CQA in CFE during formulation preparation. This temperature produced desired droplets of coarse oil in the water emulsion. Another factor to consider is the particle size reduction process for NLCs using high-speed homogenization and probe sonication methods. The prepared nanoparticles should have a particle size of less than 500 nm to be delivered to the skin. Both methods produce a proper length, which contributes to good NLC quality. The particle size reduction time of 10 minutes obtained using a high-speed homogenizer resulted in a satisfactory coarse emulsion. Additionally, when a probe sonicator was used for 10 minutes, a sufficiently fine stable emulsion in the nanometer range was produced. Beyond this time limit, the particle size of NLCs could not be reduced further.In this study, the experimental design was limited to four formulation variables: the proportions of solid lipids, liquid lipids, surfactant, and plant extract. These parameters and their associated ranges were chosen in light of our preliminary findings.Ij of each input variable with respect to the output was calculated based on the weights and biases of each neuron in the hidden layer of the developed ANN models. As shown in Figure S3, all the factors studied affected the properties of the NLCs. The proportion of emulsifiers (X3) was the main factor influencing the size of the nanoparticles (Ij = 67.70%), followed by the liquid lipid content (X2) (Ij = 42.60%), solid lipid content (X1) (Ij = 41.80%), and CFE content (X4) (Ij = 8.10%). The particle size distribution of CFE-NLCs was highly affected by the proportion of liquid lipids (X2) (Ij = 67.80%), while the proportion of emulsifiers had the greatest effect on the zeta potential (Ij = 68.80%). A similar pattern of Ij for each input factor was observed for the response of both particle size and 5CQA %EE . Overall, the influence of each factor on all responses could be ranked from highest to lowest as follows: X3 (59.70%) > X2 (49.50%) > X1 (42.10%) > X4 (32.10%).The  Three-dimensional (3D) surface plots were then constructed from the nonlinear models given in Eqs. (8)–(12) to understand the interactive relationships between each factor and the dependent variables. Each plot of two independent variables affected the responses of the CFE-NLCs. The remaining independent variables were fixed to be constant at zero. Enhanced bioavailability of active ingredients is expected in the presence of nanosized carriers compared to that in the raw complex matrix. The composition of the formulation significantly affected the particle size of CFE-NLCs (P < 0.05). As demonstrated in X3) was the parameter that most strongly affected the particle size of the CFE-NLCs, followed by the liquid lipid content (X2) and solid lipid content (X1). This impact can be attributed to the ability of emulsifiers to reduce interfacial tension by adsorbing at the oil-water interface and creating a tightly packed surfactant film. Increasing the solid lipid content above 6.5 wt% increased the size of the nanoparticles . Qadir et al stated that with a total lipid content of 3.2 wt% and a surfactant mixture content of 1.6 wt%, optimum NLCs coencapsulating Smilax china and Salix alba methanolic extracts could be achieved. In addition, appropriate polyphenol-rich Hibiscus sabdariffa extract-loaded NLCs consisted of 2.21 wt% total lipids and 1.93 wt% surfactant. On the other hand, a negative effect was observed in the case of the X2 and X3 variables, meaning that smaller NLCs were obtained at higher concentrations of liquid lipid and emulsifier  (67.80%) and exhibited a decreasing trend when the input value was greater than 29% of the total lipid content . This phenomenon was attributed to the vigorous homogenization: cavitation detached nanoemulsion droplets with a high content of liquid lipids and therefore softer structures than droplets with a lower content of liquid lipids, which were more rigid. Other researchers reported a similar finding. Similarly, a proportion of emulsifier greater than 3.30 wt% resulted in a low PDI of nanoparticles because such proportions were adequate to stabilize the newly formed fine droplets . Nevertheless, the PDI increased when the proportion of solid lipids was greater than 6 wt%  because the high density of the nanoemulsion droplets hampered the ability of the high-speed homogenizer and ultrasound to disrupt them in the particle size reduction process.PDI can be used to assess the distribution of the particle size of CFE-NLCs . This index has a value between 0 and 1; a value less than 0.3 indicates high homogeneity. Theoretically, long-term stability can be expected for nanoparticles with zeta potential values greater than ± 25 mV . However, there are still exceptions for some nanoparticles prepared using nonionic surfactants with low or no surface charge; the delivery system can be stabilized with a steric effect derived from the side chain of the surfactant used. The role of poloxamer 188 in preventing eventual agglomeration due to interparticle interactions, including van der Waals interactions, hydrophobic interactions, and hydrogen bonding, has been reported elsewhere.Zeta potential is a measurement of the surface charge at the Stern layer of nanoparticles in a colloidal solution and can predict the stability of colloidal systems.-1 water species and ionized phenolic acids derived from CFE.The zeta potential of the CFE-NLCs was found to be between –5.79 mV and –14.87 mV . Increasing the proportion of emulsifier in the formulation above 4.5 wt% resulted in a lower zeta potential of almost zero , which was consistent with the effect of total lipid content . A more negative zeta potential value was obtained by increasing the proportions of liquid lipids and CFE . This negative surface charge was not attributed to the nonionic surfactant used but might be linked to free fatty acids or the oil-water interface adsorption of OHX2) and emulsifier (X3) showed a highly nonlinear effect on the encapsulation of the target compounds. The encapsulation of 5CQA increased rapidly in the presence of liquid lipids and emulsifier at approximately 30% to 40% of total lipids and 3 wt% to 4 wt%, respectively  should be composed of 4.80 wt% X1, 30.00% X2 , 3.50 wt% X3, and 1.65 wt% X4. Three batches of CFE-NLCs were then prepared to confirm the model accuracy. There were no statistically significant differences between the predicted values  and the experimental values (P > 0.05) . These results suggest that the predicted ANN models are not biased compared with the experimented values. The developed CFE-NLCs showed a mean hydrodynamic diameter of 63.32 ± 4.22 nm. The small size of the nanoparticles should play an important role in promoting good stability because the particles remain in Brownian motion, which prevents sedimentation. The zeta potential value of the CFE-NLC dispersion was –11.20 ± 0.40 mV. These results suggest that electrostatic force is one of the mechanisms used to resist flocculation and sedimentation of the nanoparticles, along with a steric hindrance effect. This property plays an important role in the long-term stability of nanoparticles.The target NLCs should have a minimized particle size, good homogeneity, and low zeta potential, whereas the %EE of 5CQA should be maximized . A desirEE of 5CQA in NLCs was 84.72 ± 0.20%, indicating that a high amount of this substance was encapsulated in the NLCs, while the remaining 5CQA was available in the continuous phase. The trapping of polyphenols derived from Hibiscus sabdariffa extract by NLCs showed results similar to our findings. Similar findings were also reported in previous research: the %EE of green robusta coffee bean extract in NLCs was approximately 73%. These results may have occurred because certain polyphenols are not encapsulated in NLCs but combine with surfactants to form micelles. This unencapsulated 5CQA is expected to be released immediately at the site of action, which is a property of a good sustained delivery system.The %The physical characteristics of CFE-NLCs are shown in Figure S6. The addition of CFE to the NLCs resulted in a change from opaque white to pale yellow . The resulting CFE-NLCs had a hydrodynamic diameter between 28 and 142 nm (63.32 ± 4.22 nm) with good reproducibility . SEM was used to analyze the microstructure of the CFE-NLCs. The morphology of CFE-NLCs  and blank NLCs  showed a spherical shape with a narrow size distribution and good dispersion. The particle sizes of the formulations established were close to 65 nm, which is similar to the values determined by photon correlation spectroscopy . The small difference between the particle sizes determined by the two methods can be attributed to the differences in the sample preparation process and the measurement principle. A spherical shape of developed NLCs consisting of different formulation compositions was also documented in previous studies.DSC analysis was employed to investigate the thermal behavior of the CFE-NLCs and their excipients. The thermograms in Figure S7 show that glyceryl behenate, a physical mixture of glyceryl behenate and glyceryl monostearate (1:1), glyceryl monostearate, and poloxamer 188 had melting temperature peaks at 77.47°C, 74.53°C, 65.50°C, and 60.18°C, respectively. The onset time, end time, and melting temperatures of the blank NLCs and CFE-NLCs decreased compared to those of the corresponding bulk materials. The melting curves of the blank NLCs displayed three endothermic peaks at 47.24°C, 71.28°C, and 71.78°C, which indicated that the melting temperature of the solid lipids decreased when NLCs were formulated because the NLCs had less of a crystalline lattice than the bulk materials. In addition, the CFE-NLCs showed no sharp peak, indicating a heterogeneous crystalline structure in the nanoparticles. The onset and melting temperatures of both CFE-NLCs and empty NLCs remained above 40°C, indicating that the formulations formed were in a solid state at human body temperature (37°C). The fabricated nanoparticles need to be in a solid state at body temperature to boost the stability of the delivery system and regulate the release of the active ingredient, as described elsewhere.The addition of CFE to the NLCs reduced the melting temperature peaks to 42.28°C, 55.92°C, and 63.59°C. The lower melting point of the CFE-NLCs than that of the blank NLCs can be ascribed to the dispersion of CFE in the lipid matrix of the nanoparticles. A minor endothermal peak for CFE at 71.28°C was also observed, but this peak disappeared when CFE was loaded into the NLCs. This result can be attributed to the almost complete dissolution of plant extract in the developed carriers or to the solubilization of the plant extract in the lipid matrix when the sample was heated.–1 and 2900 cm–1, representing the stretching of intramolecular O-H and C-H bonds, respectively, in aromatic compounds. The bands at approximately 1700 cm–1 and 859 cm–1) correspond to C = O stretching vibrations and OH-H bending vibrations, respectively, of carboxylic acid groups. C = C stretching in aromatic compounds is represented by the band at 1600 cm–1. The absorption band of CH3 (methylene groups) is located at 1398 cm–1, and the C-O vibrations of phenolic alcohols correspond to the bands at 1180 cm–1 and 950 cm–1. The band at 709 cm–1 represents the C-H stretching of aromatic compounds.Interactions between the CFE and the formulation excipients were investigated using FTIR, and the results are shown in Figure S8. The fingerprint of the CFE displayed absorption bands at 3300 cm–1 and 1700 cm–1. No shifts in valency vibrations or new peaks appeared, indicating no chemical modification of the nanocarriers. The spectrum of the CFE-NLCs was almost the same as that of the blank NLCs. This finding is also consistent with the results of other studies showing that the active ingredient is trapped inside NLCs without chemically interacting with the formulation excipients.Concerning the CFE-NLC spectrum, the most significant changes observed in the fingerprint region indicated that CFE was present in the lipid matrix. Owing to the C-H and C = O vibrations of the lipids used in the formulation, the absorption band showed stronger signals at 2900 cm 5CQA showed a sustained release rate between 3 hours (22.58 ± 3.24%) and 24 hours (61.12 ± 3.17%). This occurrence should be due to the diffusion of 5CQA from the core of the NLC particles to the outer aqueous solution.The release profiles of 5CQA from CFE-NLCs against PBS (pH 7.4) for 24 hours at 37°C are shown in Figure S9a. 5CQA in the free CFE solution was entirely released within 3 hours. In contrast, 5CQA from NLCs showed a biphasic release pattern beginning with a burst release at the initial stage, followed by a slower sustained release phase. In the first two hours, 19.74 ± 1.21% 5CQA was released from the CFE-NLCs. These phenomena should be attributed to the release of 5CQA-enriched NLC shells, 5CQA solubilized in surfactant micelles, and free 5CQA molecules. Various mathematical models were then applied to study the kinetic release of 5CQA from CFE-NLCs. The results showed that 5CQA release had R2 values of 0.9926, 0.9660, 0.9541, 0.9335, and 0.8820 when fitted to the Higuchi, Korsmeyer-Peppas, first-order, Hixon-Crowell, and zero-order models, respectively. These release kinetics are most consistent with the Higuchi model, indicating that this bioactive molecule is released from NLCs by dissolution and diffusion mechanisms.The chemical marker showed a biphasic release pattern due to the difference in melting temperature between the solid lipids (glyceryl behenate+glyceryl monostearate) and liquid lipids (caprylic/capric triglyceride). Solid lipids have a higher melting temperature, leading to the initial crystallization of particles with little liquid lipids or a liquid lipid-free core. Liquid lipids, which are mobile liquids at room temperature, are deposited on the particles’ outer shell, leading to the formation of a phenolic compound-enriched shell. As a result, the loading of CFEs into NLCs could be used to accelerate the onset of action of their anti-skin-aging properties, followed by a continued release period.2 accumulation of 5CQA in the stratum corneum, while that in the viable epidermis and dermis was 17.12 ± 2.31 µg/cm2. This result suggests that the developed nanocarriers might have formed drug depots in the stratum corneum. The skin permeation into the viable epidermis and dermis layer was 2.31-fold greater than that of the free drug solution. This phenomenon occurred likely due to the small particle size and occlusive effect of the developed nanoparticles. Concerning the control group, propylene glycol can act as a permeation enhancer by solubilizing keratin in the stratum corneum, thus improving the permeation of 5CQA. CFE-NLCs facilitate the absorption of active compounds by the skin with minimal systemic loss and may promote the bioavailability of CFE. The results from this study and previously published data support this conclusion.The skin permeation profiles of active ingredients from CFE-NLCs and free CFE dissolved in propylene glycol were quantitatively analyzed using Franz diffusion cells. The results showed that the quantity of 5CQA that permeated through the porcine ear skin to the receptor medium was not detectable after 24 hours of incubation of the formulations. The tape stripping technique was used to isolate phytochemicals in the stratum corneum, and the retained 5CQA was extracted from the remaining skin (both viable epidermis and dermis). Figure S9b shows that the 5CQA from CFE-NLCs was localized mainly in the stratum corneum layer. The CFE-NLCs displayed 143.21 ± 7.98 µg/cmP < 0.001). Several factors can influence the cytotoxicity of NLCs, including nanocarrier particle size and the nature of the liquid lipids, solid lipids, and nonionic surfactants. In this study, the lipids used in NLC formulations are well recognized as generally recognized as safe (GRAS) substances, and their ingredients are intended for topical application. These excipients could be considered to be highly biocompatible, as supported by other researchers.In Figure S9c, the cell viability percentages of HDFn are plotted as a function of the concentrations of the CFE-NLCs and blank NLCs. At a concentration of 5000 µg/mL NLCs, which corresponded to 92 μg/mL CFE inNLCs, both tested nanoparticles exhibited mild toxicity to the test cells (cell viability > 80%). In contrast, doxorubicin HCl (10 μM), a positive control, significantly reduced cell viability to 31.41 ± 0.45% (P < 0.001) (P > 0.05) (P < 0.05). A possible reason is the high %EE of 5CQA and controlled release behavior of NLCs, resulting in less irritation in the HET-CAM assay. Thus, CFE-NLCs are mild, tolerable irritants and therefore suitable for the skin.The HET-CAM test, an alternative model to animal experiments, was used to assess the potential for irritation of CFE-NLCs against vascular toxicity. NaCl solution (0.9% w/v) caused no change in the membrane (irritation score = 0.00 ± 0.00), while 0.1 N NaOH solution caused severe irritation (19.49 ± 0.46) (< 0.001) . The pos< 0.001) . The bla > 0.05) . This ouP < 0.05). A plausible and useful theory attributes the small loss of trapping capacity of 5CQA to the repulsion of encapsulated substances to the surrounding aqueous phase during storage.One of the key findings of this study was that the optimized NLCs could improve the physicochemical stability of CFE. As seen in Figure S10a−g, CFE-NLCs were stable after storage at 4 ± 2°C and 25 ± 2°C for up to 90 days, suggesting satisfactory stability of the formed colloidal system. At 90 days of storage at 40 ± 2°C, minor changes in some properties of the CFE-NLCs, including the particle size, PDI, zeta potential, and %EE of the active compound, were observed (P > 0.05). Nitthikan et al reported similar observations in their experiments. NLCs containing green robusta coffee bean extract exhibited stable chemical and DPPH• free radical scavenging activities when the formulations were stored at 4°C and 30°C for 90 days. This finding is attributed to chemical deterioration. NLCs could help reduce the loss of 5CQA in the formulation and enhance the water solubility of CFE. In addition to indicating the value of this plant extract, the results obtained may lead to the use of other botanical extracts containing high 5CQA levels.Concerning chemical stability, there was no alteration in the content of 5CQA in either CFE-NLCs or free CFE for up to 90 days , is gratefully acknowledged. The authors declare no conflicts of interest. Not applicable.Supplementary file 1 contains Figures S1-S10.Click here for additional data file.