Dual-targeting tigecycline nanoparticles for treating intracranial infections caused by multidrug-resistant Acinetobacter baumannii

Dual-targeting tigecycline nanoparticles for treating intracranial infections caused by multidrug-resistant Acinetobacter baumannii | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dual-targeting tigecycline nanoparticles for treating intracranial infections caused by multidrug-resistant Acinetobacter baumannii Xing Lan, Shugang Qin, Huan Liu, Mengran Guo, Yupei Zhang, Xinyang Jin, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3807612/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Mar, 2024 Read the published version in Journal of Nanobiotechnology → Version 1 posted 7 You are reading this latest preprint version Abstract Multidrug-resistant (MDR) Acinetobacter baumannii ( A. baumannii ) is a formidable pathogen responsible for severe intracranial infections post-craniotomy, exhibiting a mortality rate as high as 71%. Tigecycline (TGC), a broad-spectrum antibiotic, emerged as a potential therapeutic agent for MDR A. baumannii infections. Nonetheless, its clinical application was hindered by a short in vivo half-life and limited permeability through the blood-brain barrier (BBB). In this study, we developed a novel nanocarrier, integrating a dual-targeting peptide Aβ11 and Tween 80 modification (Aβ11/T80@CSs), specifically designed to enhance TGC delivery to the brain for treating A. baumannii -induced intracranial infections. Our findings demonstrated that Aβ11/T80@CSs nanocarriers successfully traversed the BBB and effectively delivered TGC into the cerebrospinal fluid (CSF), leading to a significant therapeutic response in a model of MDR A. baumannii intracranial infection. This study offers initial evidence and a platform for the application of brain-targeted nanocarrier delivery systems, showcasing their potential in administering water-soluble anti-infection drugs for intracranial infection treatments, and suggesting promising avenues for clinical translation. nanoparticles blood-brain barrier multidrug-resistant Acinetobacter baumannii Tigecycline intracranial infection Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Acinetobacter baumannii ( A. baumannii ), a notorious nosocomial pathogen, was identified as a primary cause of severe intracranial infections and associated complications 1 . Recent data indicated a rising trend in the incidence of postoperative intracranial infections attributable to A. baumannii , accounting for 15.7%-24.2% of cases 2 , 3 . The proliferation of multidrug resistance (MDR) in A. baumannii , fueled by antibiotic misuse, rendered the treatment of such infections exceedingly challenging 4 . Reports highlighted that MDR A. baumannii showed resistance to multiple antibiotic classes, including β-lactams, cephalosporins, and carbapenems, with the MDR rate escalating from 23–63%, a rate fourfold higher than that observed in other MDR Gram-negative bacteria like Pseudomonas aeruginosa and Klebsiella pneumoniae 5 . The World Health Organization identified carbapenem-resistant A. baumannii as a critical threat to global health 6 . Alarmingly, limited pharmaceutical options were available for treating MDR A. baumannii , primarily tigecycline and colistin 7 , 8 . Tigecycline (TGC), a new-generation tetracycline antibiotic, emerged as the most potent treatment against intracranial infections caused by MDR A. baumannii 9 . TGC functioned by binding to the 30S ribosomal subunit, thereby inhibiting bacterial protein synthesis through prevention of tRNA binding at the ribosomal A site, ultimately stalling bacterial growth 10 , 11 . Notably, TGC retained efficacy against MDR strains by circumventing resistance mechanisms such as ribosomal protection and antibiotic efflux, a significant advantage over minocycline 12 , 13 . However, TGC’s limited permeability through the blood-brain barrier (BBB) posed challenges in attaining adequate drug concentrations in the cerebrospinal fluid (CSF). Intraventricular injection, often employed for treating MDR A. baumannii intracranial infections, carried a heightened risk of secondary infections 14 . Consequently, the development of a safe and effective TGC brain-targeted delivery system was deemed essential. Nano-delivery systems have demonstrated the capability to precisely target specific organs and cells, and to extend the duration of blood circulation, thereby enhancing the efficacy and safety of drugs. This approach offered an innovative strategy for transporting drugs across the blood-brain barrier (BBB), yet reports on targeted therapy for intracranial infections remained sparse. Recently, antibacterial peptides and itraconazole were formulated into brain-targeted delivery systems for intracranial infection treatment, although their preparation processes were complex 15 – 17 . β-Amyloid (Aβ1–40), a peptide resulting from the proteolytic cleavage of the amyloid precursor protein, circulated in blood, cerebrospinal fluid (CSF), and interstitial fluid. Aβ1–40 was capable of crossing the BBB by binding to low-density lipoproteins (LDL, such as ApoE and ApoA) and LDL receptor-related protein 1 (LRP1) 18 – 20 . A fragment of Aβ1–40, Aβ25–35 (Aβ11), exhibited similar functionality 21 . Studies indicated that Aβ11 could be safely modified onto the surface of nanocarriers for brain targeting 22 , 23 . Tween 80 (T80), a nonionic surfactant, was observed to enhance the accumulation of nanoparticles in brain endothelial cells of the BBB 24 . Moreover, nanoparticles modified with T80 were reported to adsorb LDL in blood and be uptaken by BBB endothelial cells via interaction with LRP1 25 . Additionally, T80 was found to inhibit the active efflux of P-glycoprotein, increasing the brain uptake of nanoparticles 26 . These findings suggested that the Aβ11 and T80 dual-modified nano-delivery system held significant potential for the brain-targeted delivery of Tigecycline (TGC) to treat intracranial infections. In this study, we introduced a pioneering method to prepare core-shell nanoparticles modified with Aβ11 and Tween 80 (Aβ11/T80@CSs) for delivering water-soluble TGC into the CSF by traversing the BBB. We discovered that the Aβ11/T80@CSs brain-targeting nano-delivery system could enhance the encapsulation efficiency of water-soluble drugs, prolong TGC's in vivo circulation time, and improve its bioavailability. The Aβ11/T80@CSs system facilitated TGC distribution in the brain and augmented its efficacy against MDR A. baumannii in a mouse model of intracranial infection. Our findings provided a foundational framework for further development of brain-targeting nano-delivery systems in the treatment of intracranial infections caused by MDR bacteria. EXPERIMENTAL SECTION Materials Tigecycline, with a purity exceeding 98%, was procured from Suo Laibao Biotechnology Co., Ltd. The Aβ11 peptide, featuring an additional cysteine at its C-terminus (Aβ11-Cys), was synthesized by Qiang Yao Biochem Ltd., Hubei, China. The C-terminal amidated Aβ11-Cys peptide sequence was NH2-CGSNKGAIIGLM-CONH2. Mal-PEG2000-Chol was acquired from Pengshuo Biotechnology Co. Ltd., Chengdu, China. Various forms of mPEG-PLGA, PLGA, and PLGA-PEG-PLGA, all with a molecular weight of 15 kDa and varying lactide to glycolide ratios, were purchased from Jinan Daigang Biomaterial Co., Ltd., Jinan, China. Poly (vinyl alcohol) (PVA) with a molecular weight range of 30–70 kDa, Tween 80, and 3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide (MTT) were obtained from Chengdu Real Biotechnology Co., Ltd., Chengdu, China. 1,1'-Dioctadecyl-3,3,3',3'-Tetramethylindodicarbocyanine perchlorate (DiD) was sourced from Gelman Sciences Inc., California, USA. Confocal plates and DMEM were procured from Rancho Technology Co., Ltd., Beijing, China. All other reagents and chemicals were of analytical reagent grade and were used without further purification. Animals BALB/c mice, male, aged 6–8 weeks and weighing 22–25 g (SPF grade), along with adult healthy female Sprague-Dawley rats, weighing between 200–250 g (SPF grade), were obtained from the Sichuan University Experimental Animal Center, Ltd., Chengdu, Sichuan, China. All animal experiments were conducted with the approval and under the supervision of the West China Hospital Animal Care and Use Committee, Sichuan University. The animals were housed in an environment maintained at 22 ± 1°C with a 12:12 hr light-dark cycle and a relative humidity of 55 ± 10%. Synthesis of Chol-PEG2000-Aβ11 Chol-PEG2000-Aβ11 was synthesized via a Michael addition reaction. Initially, 50 mg of Chol-PEG2000-Mal was dissolved in 5 mL of chloroform and subsequently transformed into a film through rotary evaporation. This film was then completely dissolved by hydrating with 3 mL of Milli-Q water for 30 minutes. In a separate procedure, 22 mg of thiodized Aβ11-Cys was dissolved in 2 mL of Milli-Q water and combined with the Chol-PEG2000-Mal suspension. Following this, 200 µL of EDTA (500 mM, pH 8.0) and 3 mL of 0.1 M phosphate buffer were added to the mixture. The reaction proceeded at room temperature for 48 hours. Unbound peptide and Chol-PEG2000-Mal were removed by dialysis (MW = 5 kDa) over a period of 72 hours, after which Chol-PEG2000-Aβ11 was obtained through freeze-drying. Formulation screening of PLGA nanoparticles To select the optimal polymer carrier material for encapsulating Tigecycline (TGC), we synthesized seven different formulations of PLGA nanoparticles (PLGA NPs), detailed in Table 1 . These PLGA NPs were prepared using an emulsification-solvent evaporation method. Briefly, PLGA was dissolved in a mixture of dichloromethane (DCM) and acetone to create a 2% (w/v) solution, serving as the organic phase. An aqueous solution of tigecycline was then gradually added dropwise to this organic phase and emulsified using an ultrasonic liquid processor (XinZhi, China) at 100 W power, forming an oil-in-water (O/W) emulsion. This O/W emulsion was subsequently dropped into a 1% polyvinyl alcohol (PVA) solution, and a secondary ultrasound process generated a multi emulsion (W/O/W). The resultant emulsion was then transferred to a 250 mL eggplant-shaped flask, and the organic solvent was evaporated under vacuum at 37°C, resulting in the formation of PLGA NPs. Using a similar preparation method, DiD was substituted for TGC to synthesize PLGA NPs/DiD. Table 1 Polymer material composition of each formulation. Formulation mPEG-PLGA (75/25) PLGA (50/50) PLGA (75/25) PLGA-PEG-PLGA (50/50) PLGA-PEG-PLGA (75/25) F1 20 mg - - - - F2 - 20 mg - - - F3 - - 20 mg - - F4 - - - 20 mg - F5 - - - - 20 mg F6 10 mg 10 mg - - - F7 10 mg - 10 mg - - Particle Size and ζ-Potential Measurement The particle size and ζ-potential of the nanoparticles were assessed using a Malvern particle size meter (Zetasizer NanoZS 90). Prior to measurement, the samples were diluted tenfold, and each sample underwent three separate measurements to ensure accuracy. TGC content and encapsulation efficiency determination High-Performance Liquid Chromatography (HPLC) was employed to detect the Tigecycline (TGC) content and to ascertain the encapsulation efficiency of the nanoparticles. A 200 µL aliquot of the nanoparticle solution was dissolved in 0.8 mL of methanol with ultrasonication to facilitate drug extraction, followed by dilution with 1 mL of water. Chromatographic separation was conducted on a C18 column (250 mm × 4.6 mm, 6 µm) using a mobile phase composed of ammonium phosphate dibasic-triethylamine-methanol (50:1:49, pH = 6.3), at a flow rate of 1.0 mL/min. The detection wavelength was set at 246 nm. The drug loading and encapsulation efficiency (%) of the nanoparticles were calculated using the following equation: Encapsulation efficiency = \(\frac{{M}_{1}-{M}_{2}}{{M}_{1}}\) ×100%, where M_1 represents the total weight of the drug and M_2 the weight of the drug (TGC) remaining in the liquid medium post-encapsulation. Preparation and characterization of the Aβ11/T80@css nanodrug delivery system Core-shell nanoparticles were synthesized through the thin-film hydration method, and the formulation with varying Aβ11 molar ratios is detailed in Table 2 . Phospholipid (PLS100), cholesterol (Chol), Chol-PEG2000-Aβ11, and Chol-PEG2000 were dissolved in 4 mL of chloroform. Subsequently, the organic solvent was evaporated using a rotary evaporator. The resultant lipid membrane was hydrated with a PLGA NPs solution at 37°C for 30 minutes, then sonicated at 80 W for 6 minutes to form lipid nanoparticles. These nanoparticles were collected in ultrafiltration tubes, centrifuged at 4000 rpm for 15 minutes, and washed thrice with Milli-Q water to remove unencapsulated drugs (Aβ11@CSs). Following a similar method, Tween 80 was added to the chloroform to synthesize Aβ11- and Tween 80-modified lipid nanoparticles (Aβ11/T80@CSs). Nanoparticles labeled with DiD or Cou6 were prepared by incorporating appropriate amounts of DiD or Cou6. Table 2 Formulations of Aβ11 delivery systems with different molar ratios. CSs 1%Aβ11 5%Aβ11 10%Aβ11 PLS100 60 60 60 60 Chol 30 30 30 30 PEG2000-Chol 10 9 5 0 Aβ11-PEG2000-Chol 0 1 5 10 The particle size and ζ-potential of the Aβ11/T80@CSs nanoparticles were measured using a Malvern particle size meter. The encapsulation efficiency (EE) was determined by High-Performance Liquid Chromatography (HPLC). For morphological analysis, transmission electron microscopy (TEM, HF-3300, Hitachi, Japan) was utilized to observe the nanoparticles. A 10 µL aliquot of the Aβ11/T80@CSs suspension was placed on copper grids and thoroughly freeze-dried before TEM examination. The structural characteristics of Aβ11/T80@CSs were then observed at an appropriate accelerating voltage. An in vitro drug release study was conducted employing the dialysis method, with phosphate-buffered saline (PBS, pH = 7.4) as the release medium. For this study, 2 mL aliquots of free Tigecycline (TGC), CSs, or Aβ11/T80@CSs (each containing 1 mg of TGC) were sealed in dialysis bags with a molecular weight cutoff of 3.5 kDa. These bags were then immersed in 30 mL of PBS and gently agitated at 37°C. At predetermined time intervals, 1.0 mL of PBS was sampled from outside each dialysis bag for HPLC analysis, and an equivalent volume of fresh PBS was replenished to maintain a constant volume in the release medium. Brain distribution imaging experiment BALB/c mice underwent a one-week acclimation period to their new environment. Subsequently, they were randomly assigned to different groups. The mice received injections of nanoparticles or free DiD (equivalent to 0.5 mg/kg DiD) via the tail vein. A blank control group, comprising three mice, was also established. Four hours post-injection, the mice were euthanized using isoflurane, and their brains were harvested for in vitro imaging. The imaging was performed using the IVIS imaging system (IVIS Lumina III, PerkinElmer, USA), with the excitation and emission wavelengths set at 720 nm and 740 nm, respectively. Cell uptake The uptake of Cou6-loaded nanoparticles by cells was investigated using bEnd.3 endothelial cells. bEnd.3 cells, seeded at a density of 1×10^5 cells/well, were cultured in 24-well plates for 24 hours until they reached full adherence. The cells were subsequently incubated with CSs-Cou6, Aβ11@CSs-Cou6, or Aβ11/T80@CSs-Cou6 in confocal dishes for four hours. Post-incubation, the cells were stained with DAPI for 20 minutes and imaged using a laser-scanning microscope (CLSM, LSM-880). Fluorescence intensity was quantified using ImageJ software (java8, NIH, USA). For flow cytometry analysis, the cells were incubated with CSs-Cou6, Aβ11@CSs-Cou6, or Aβ11/T80@CSs-Cou6 (each containing 80 ng of Cou6) for four hours in DMEM supplemented with 10% fetal bovine serum. After washing twice with PBS to remove any uninternalized nanoparticles, the cells were harvested and resuspended in 300 µL of PBS. Fluorescence intensity was measured using flow cytometry (2060R, NovoCyte, ACEA, USA). Transmembrane transport assay An in vitro blood-brain barrier (BBB) model was established using bEnd.3 cells to assess the penetration efficiency of different nanoparticles. For this model, 2.0×10^5 bEnd.3 cells were cultured in a 24-well Transwell chamber with 3 µm pores. Intercellular compactness was verified with a cell resistance meter (Millicell-ERS EVOM2, USA), and the BBB model was deemed successful when the transendothelial electrical resistance reached 200 Ω·cm^2. To evaluate nanoparticle penetration through the monolayer, Hank's Balanced Salt Solution (HBSS) replaced the standard medium, and free TGC, CSs-TGC, Aβ11@CSs-TGC, or Aβ11/T80@CSs-TGC was added to the apical side for co-incubation. At various time intervals, 200 µL samples of HBSS were collected from the basolateral side and replaced with fresh HBSS. The concentration of TGC in these samples was determined using HPLC. The cumulative permeation of TGC from the apical to the basolateral compartment and the apparent permeability coefficient (Papp) were calculated using the formula: $$\text{M}\text{n}={C}_{n}\times V+{\sum }_{i=1}^{n-1}{C}_{i}\times {V}_{i}$$ Papp= \(\frac{dQ}{dt}\) × \(\frac{1}{A\times {C}_{0}}\) ×100% where Mn represents the cumulative amount of TGC permeated at the nth time point, Cn is the concentration of TGC at the nth time point, V is the total volume of the basolateral solution, Ci is the concentration of TGC at the ith time point, and Vi is the volume of the sample collected at the ith time point. The Papp was calculated as dQ/dt×1/(A×C0)×100%, where dQ/dt is the rate of TGC transfer from the upper to the lower layer of the Transwell plate, C 0 is the initial concentration of TGC in the upper layer, and A is the surface area of the membrane ( cm2 ). Antimicrobial activity of Aβ11/T80@CSs in vitro and in CSF To assess the antibacterial activity of empty CSs, free Tigecycline (TGC), and Aβ11/T80@CSs-TGC against multidrug-resistant (MDR) A. baumannii , the minimum inhibitory concentration (MIC) was determined. Bacteria in the mid-logarithmic growth phase were diluted to a concentration of 1×10 5 CFU/mL. A 100 µL aliquot of this bacterial suspension was mixed with 100 µL of either free TGC or Aβ11/T80@CSs-TGC, with concentrations ranging from 0.125 to 16 µg/mL, and incubated in 96-well plates for 24 hours. The bacterial density at 600 nm was subsequently measured using a microplate reader (Biotek Synergy MX). In the rat intracranial infection model, MDR A. baumannii infection was induced by intracisternal injection of 20 µL of MDR A. baumannii (1×10 8 CFU/mL) into the cerebrospinal fluid (CSF) of healthy rats. To investigate the efficacy of TGC against MDR A. baumannii in CSF, rats infected with MDR A. baumannii received intrathecal injections of 20 µL of Aβ11/T80@CSs-TGC, CSs-TGC, or free TGC (equivalent to 10 µg TGC). After 24 hours, CSF was collected from the rats and cultured on solid media. Colony counts were recorded following a 24-hour incubation at 37°C. Pharmacokinetics of Aβ11/T80@CSs In the pharmacokinetic study, adult female Sprague-Dawley rats, weighing between 200 and 250 grams, were used. Prior to the experiment, the animals were fasted overnight with free access to water. Nine rats were randomly divided into three groups: free-TGC, CSs-TGC, and Aβ11/T80@CSs-TGC. Each group received an intravenous administration of TGC at a dose of 12.5 mg/kg via the tail vein. Blood samples were collected at predetermined time points (0.25, 0.5, 1, 2, 4, 6, and 8 hours), and then placed into 2 mL Eppendorf tubes. These samples were centrifuged at 10,000 rpm for 10 minutes at 4°C to separate the plasma. A portion of the plasma was mixed with methanol in a 1:4 volume ratio and further centrifuged at 13,000 rpm for 10 minutes at 4°C. The supernatant was collected for TGC concentration determination using HPLC. Pharmacokinetic parameters were subsequently calculated using the statistical analysis tool DAS2. Anti-infective efficacy of Aβ11/T80@CSs in vivo Rats with intracranial infections were randomly divided into four groups to evaluate the anti-infective efficacy of different treatments. These groups received saline, free Tigecycline (TGC), CSs-TGC, or Aβ11/T80@CSs-TGC (each with a TGC dose of 30 mg/kg) as treatments. The administrations were conducted intravenously at 0 hours, 6 hours, and 18 hours post-infection modeling. After 24 hours, cerebrospinal fluid (CSF) samples were collected from the rats, evenly spread onto solid culture media, and incubated at 37°C for 24 hours. The colony count for each group was then recorded. Hemolysis of Aβ11/T80@CSs The hemolytic activity of Aβ11/T80@CSs was assessed using erythrocytes from healthy rats. Blood samples were collected, and red blood cells were isolated through centrifugation, followed by suspension in normal saline to create a 2% erythrocyte solution. Two milliliters of this erythrocyte suspension were mixed with free TGC, CSs, or Aβ11/T80@CSs and incubated at 37°C for three hours. Post-incubation, the samples were centrifuged, and the absorbance of the supernatant was measured using spectrophotometry at 570 nm. Purified water and normal saline served as positive and negative controls, respectively. The percentage of hemolysis was calculated using the following formula: Hemolysis (%) = \(\frac{Asample- Anegative}{Apositive- Anegativ}\) ×100% Cell cytotoxicity assessment via MTT assay Cell cytotoxicity was evaluated using the MTT assay. Initially, 5×10^4 bEnd.3 cells were seeded in a 96-well plate and incubated overnight at 37°C to ensure complete adherence. Subsequently, the medium was replaced with fresh medium containing varying concentrations of Aβ11/T80@CSs-TGC, and the cells were incubated for an additional 24 hours in sets of three wells per concentration. Following this, 20 µL of MTT solution was added to each well, and the cells were incubated for another 4 hours at 37°C. The supernatant was then removed, and 150 µL of dimethyl sulfoxide was added to dissolve the dark blue formazan for approximately 30 minutes. The optical absorbance of each well was measured at 570 nm using a microplate reader (BioTek, USA). Cells treated with phosphate-buffered saline (PBS) served as the control group. In vivo biosafety assessment To further investigate the biosafety of the various formulations in vivo , blood samples were collected post-administration for biochemical analysis. After euthanizing the rats, their heart, liver, spleen, lung, and kidney tissues were harvested. These tissues underwent hematoxylin and eosin (H&E) staining and were subsequently imaged using a pathology slide scanner. Statistical analysis Each experimental condition was replicated in at least three parallel experiments. The results are presented as the mean ± standard deviation. GraphPad software was employed for all statistical analyses. RESULTS AND DISCUSSION Preparation of the Aβ11/T80@CSs nanodrug delivery system To optimize the formulation of poly(lactic-co-glycolic acid) nanoparticles (PLGA NPs), these nanoparticles were prepared using the emulsification-solvent evaporation method, employing PLGA series polymers as carrier materials (as illustrated in Fig. 1A ). The particle size, electric potential, and encapsulation efficiency (EE%) of the PLGA NPs were characterized using Malvern particle size analyzers and High-Performance Liquid Chromatography (HPLC). The seven nanoparticle formulations exhibited a particle size range of 100 to 200 nm and demonstrated uniform size distribution ( Fig. 1B ). All formulations displayed negative zeta potentials, with formulation F7 showing the lowest zeta potential ( Fig. 1C ), which contributed to enhanced nanoparticle stability and reduced aggregation. With a Tigecycline (TGC) content of 3 mg, the EE% of these nanoparticles varied from 40–80%. Notably, formulations F2 and F7 achieved higher EE%, approximately 80%, compared to the other five formulations ( Fig. 1D ). The particle sizes of F4 and F5 were smaller than those of the other groups, yet their encapsulation efficiencies were significantly lower, suggesting inadequate drug encapsulation and consequently smaller empty nanoparticles. In vivo studies were also conducted to assess variations in brain targeting among these formulations. As indicated in Fig. 1E , PLGA NPs demonstrated higher brain expression levels compared to free-DiD, implying enhanced drug delivery to the brain by the nanoparticles. The ability of the seven formulations to penetrate the blood-brain barrier (BBB) varied, with F7 exhibiting stronger fluorescence absorption than the other formulations. This variation in nanoparticle distribution could be attributed to the influence of the material composition on particle size and potential. PLGA polymers vary in lactic acid to glycolic acid (LA/GA) ratios, with a lower LA/GA ratio indicating increased hydrophilicity and higher zeta potential. Additionally, polyethylene glycol (PEG) modification of PLGA can further enhance its hydrophilicity, influencing nanoparticle size and encapsulation efficiency. Particle size is a critical attribute for nanoparticle characterization and a significant parameter in drug delivery systems, as it affects cellular and tissue uptake 27 . Smaller nanoparticles are generally more efficiently absorbed by cells. Recent studies have also suggested that endothelial cells preferentially uptake polymer nanoparticles with more negative charges 28 . Based on these results, F7 PLGA NPs were selected as the carrier material for preparing the core-shell nanoparticles (CSs) as a kernel. Next, thin film hydration was employed to prepare ligand-modified core-shell nanoparticles (CSs), as illustrated in Fig. 1F . Initially, Aβ11-modified CSs (Aβ11@CSs) were synthesized to screen the content of Chol-PEG2000-Aβ11 using IVIS imaging. As demonstrated in Fig. 1G, H , Aβ11@CSs displayed a higher fluorescence intensity in the brain compared to CSs alone, indicating Aβ11’s robust targeting ability. Notably, the brain’s fluorescence signal was significantly higher than in other groups when the molar ratio of Chol-PEG2000-Aβ11 was 5%. The fluorescence intensities for 1% and 10% Aβ11 in the brain did not exhibit a significant difference. Subsequently, the study investigated whether Tween 80 (T80) could enhance the penetration of Aβ11@CSs through the blood-brain barrier (BBB). As shown in Fig. 1I, J , the incorporation of T80 led to increased accumulation of nanoparticles in the brain compared to Aβ11@CSs. Interestingly, optimal distribution was observed with 0.5% T80 (v/v), and higher concentrations of T80 did not further enhance fluorescence intensity. This could be attributed to T80's ability to inhibit P-glycoprotein, thereby preventing nano efflux, and its potential competition with Aβ11 for binding to lipoproteins, which might reduce Aβ11's efficiency 24 , 29 . Based on these findings, a composition of 5% Chol-PEG2000-Aβ11 and 0.5% T80 was selected for modifying the nanoparticles (Aβ11/T80@CSs) in subsequent studies. Characterization of the Aβ11/T80@CSs nanodrug delivery system The physical, chemical properties, and stability of Aβ11/T80@CSs were characterized. The average particle size of Aβ11/T80@CSs-TGC was found to be 158 ± 3.1 nm, accompanied by a negative zeta potential of -11.7 ± 0.6 mV (Fig. 2 A, B). These findings indicated a uniform particle size distribution and a single-peak zeta potential distribution for Aβ11/T80@CSs. Notably, the particle size of Aβ11/T80@CSs was approximately 20 nm larger than that of the PLGA NPs, a difference that was not statistically significant. High-Performance Liquid Chromatography (HPLC) was utilized to ascertain the Tigecycline (TGC) content, revealing an encapsulation efficiency (EE%) of 84.2 ± 1.3% for Aβ11/T80@CSs-TGC. Under natural light, both Aβ11/T80@CSs-TGC and CSs-TGC solutions appeared clear, transparent, and light blue in color. Upon exposure to a laser pointer, aside from the control, Aβ11/T80@CSs-TGC and CSs-TGC exhibited a pronounced Tyndall effect (Fig. 2 C), demonstrating that the preparation was a homogeneous colloidal solution. Transmission Electron Microscopy (TEM) images revealed a homogeneous spherical structure with a core-shell configuration for Aβ11/T80@CSs-TGC (Fig. 2 D). The stability of Aβ11/T80@CSs-TGC was evaluated by storing the nanoparticles at 4°C for five days. As illustrated in Fig. 2 E, there were no significant changes in particle size and EE% during this storage period, suggesting excellent stability of the formulation. The dynamic dialysis method was employed to examine the in vitro drug release profile. As depicted in Fig. 2 F, approximately 50% of TGC was released from the nanoparticles within the first hour, followed by a sustained release over time. The cumulative drug release within 12 hours was 85 ± 2.3% for CSs-TGC and 80.5 ± 4.8% for Aβ11/T80@CSs-TGC, indicating that ligand modification did not significantly impact the release of TGC from the nanoparticles. The complete release of the free drug within three hours could be ascribed to the absence of a carrier material for encapsulation. Overall, these results demonstrated that Aβ11/T80@CSs was highly stable and could efficiently entrap and release TGC. Targeting efficiency of Aβ11/T80@CSs Effective drug delivery across the blood-brain barrier (BBB) is crucial in the treatment of intracranial infections, as it enables access to the infection site, enhances drug efficacy, minimizes side effects, prolongs drug delivery, and potentially overcomes resistance. Strategies and technologies of the Aβ11/T80@CSs nanodrug delivery system aimed at improving BBB penetration are pivotal for advancing treatment options for intracranial infections. We investigated the uptake of different nanoparticles at the 4-hour mark using confocal laser microscopy, employing bEnd.3 cells as a model system. As depicted in Fig. 3 A, CSs, Aβ11@CSs, and Aβ11/T80@CSs were internalized by bEnd.3 cells. Notably, Aβ11/T80@CSs demonstrated significantly higher cellular uptake, with fluorescence intensities 3.9 times and 1.65 times greater than those of CSs and Aβ11@CSs, respectively (Fig. 3 B). This finding was corroborated by flow cytometry results, which showed that the fluorescence intensity of Aβ11/T80@CSs was four times and 2.5 times higher than that of CSs and Aβ11@CSs, respectively, signifying that nanoparticles modified with Aβ11 and Tween 80 significantly augmented cellular uptake (Fig. 3 C, D). In this study, an in vitro BBB model was developed to examine the transport capacity of free Tigecycline (TGC), CSs, Aβ11@CSs, and Aβ11/T80@CSs across the endothelial barrier monolayer. As illustrated in Fig. 3 E, F, free TGC exhibited the lowest permeability in monolayer bEnd.3 cells and the weakest ability to traverse the BBB. The CSs-TGC group showed limited BBB permeability within the initial four hours, with a gradual increase over the subsequent three hours. However, the dual-ligand Aβ11/T80@CSs displayed enhanced transport capacity in the in vitro BBB model compared to untargeted CSs and single-ligand Aβ11@CSs, with transshipment progressively increasing over time. Investigating the distribution of formulations in a brain infection model provided insights into the nanoparticles' ability to penetrate the BBB post-infection onset. This approach enabled a more accurate and comprehensive assessment of nanoparticle penetration capabilities, as the model more closely reflected BBB properties. The results revealed that the fluorescence intensity of Aβ11/T80@CSs-DiD was 19 times that of free DiD and 8.6 times that of CSs-DiD (Fig. 3 G, H), a significant difference, indicating that the nano-delivery system possessed exceptional brain targeting capabilities. Pharmacokinetics and anti-infective efficacy of Aβ11/T80@CSs-TGC In recent years, the prevalence of multidrug-resistant (MDR) A. baumannii has increased. Currently, TGC and polymyxin drugs are among the few effective treatments against infections caused by MDR A. baumannii . Nano-delivery systems have emerged as a promising strategy to overcome drug resistance by enhancing drug concentration, cellular uptake, and targeted delivery. These systems can bypass resistance mechanisms, deliver combination therapies, and enable programmable drug release, thereby enhancing the efficacy of therapeutic agents and contributing to improved treatment outcomes in resistance-prone conditions. We assessed the antimicrobial activity of Aβ11/T80@CSs-TGC against MDR A. baumannii . In vitro antibacterial experiments demonstrated that neither PBS nor blank core-shell nanoparticles inhibited bacterial growth. Both free TGC and Aβ11/T80@CSs-TGC displayed potent antimicrobial activity with a minimum inhibitory concentration of 2 µg/mL (Fig. 4 A, B), indicating TGC’s effectiveness against MDR A. baumannii . Cerebrospinal fluid (CSF) is a clear, colorless body fluid found in the brain and spinal cord. Bacteria predominantly reside in the CSF. To explore the in vivo anti-infective efficacy of Aβ11/T80@CSs-TGC, intrathecal injections of various formulations were administered directly into the CSF, and the antibacterial efficacy of TGC was observed. As shown in Fig. 4C, D , Aβ11/T80@CSs-TGC achieved an antibacterial rate of 90% in the CSF, indicating its potent anti- A. baumannii activity both in vitro and in vivo . Additionally, the study quantified the blood drug concentration of TGC at various time points following intravenous administration of nanoparticles, with the related pharmacokinetic parameters presented in Table 3 . Notably, the peak concentrations of CSs and Aβ11/T80@CSs were significantly higher than those of the free TGC group (Fig. 4 E). CSs-TGC and Aβ11/T80@CSs-TGC exhibited similar pharmacokinetic profiles. The area under the curve (AUC_0–8 h) for Aβ11/T80@CSs-TGC was 21.62 ± 1.79 µg/mL*h, approximately 2.5 times that of free TGC. Furthermore, the clearance (CL) of TGC was significantly reduced in nanoparticle formulations compared to free TGC. The CL for CSs-TGC and Aβ11/T80@CSs-TGC decreased by factors of 2 and 2.76, respectively. These results suggest that nanoparticle usage could prolong the blood circulation time of TGC and enhance its bioavailability. Table 3 Pharmacokinetic parameters after intravenous injection in rats. Pharmacokinetic Unit Free-TGC CSs-TGC Aβ11/T80@CSs-TGC Cmax µg/mL 3.70 ± 0.62 8.09 ± 0.35** 10.72 ± 2.26*** Tmax h 0.25 0.25 0.25 AUC(0-t) µg/mL*h 8.48 ± 2.90 16.51 ± 0.09* 21.62 ± 1.79** T1/2 h 0.77 ± 0.24 0.91 ± 0.21 1.26 ± 0.21 MRT(0-t) h 2.6 ± 0.16 2.29 ± 0.10 2.39 ± 0.14 CL mL/h/kg 1199.97 ± 248.32 590.64 ± 33.91 433.43 ± 20.93 Note: (𝑥̅ ± SD, n = 3, compared with Free-TGC, * p <0.5, ** p <0.01, *** p <0.001) Encouraged by these findings, we proceeded to intravenously administer physiological saline, free TGC, CSs-TGC, and Aβ11/T80@CSs-TGC to rats. The results revealed that Aβ11/T80@CSs-TGC significantly inhibited the growth of multidrug-resistant (MDR) A. baumannii in the cerebrospinal fluid (CSF). The colony counts in the Aβ11/T80@CSs-TGC group were markedly lower than those in the other groups (Fig. 4 F-H). These outcomes suggested that the ligand-modified nanoparticles enhanced the distribution characteristics of TGC, facilitating its penetration through the blood-brain barrier (BBB) and thereby exerting effective antibacterial effects. Biosafety assessment of Aβ11/T80@CSs The biosafety of Aβ11/T80@CSs was assessed through the evaluation of blood biochemical indices and histopathological examination using hematoxylin and eosin (H&E) staining. As depicted in Fig. 5 A, the hemolysis rates for both nano-formulations and the free TGC group were under 5%, relative to the positive control. This finding indicates that the Aβ11/T80@CSs formulation is biocompatible, exhibiting negligible hemolytic activity on erythrocytes. Additionally, the cytotoxic effects of TGC, CSs-TGC, and Aβ11/T80@CSs-TGC on bEnd.3 cells were quantified utilizing the MTT assay. Notably, cell survival rates exceeded 80% across a range of TGC concentrations (Figs. 5 B-D). However, a decline in cell viability was observed at elevated TGC concentrations within the formulation groups, although the variance remained minimal. Furthermore, histological analysis of the heart, liver, spleen, lungs, and kidneys, stained with H&E, revealed no significant pathological alterations in the TGC, CSs-TGC, and Aβ11/T80@CSs-TGC groups in comparison to the normal control group (Fig. 5 E). These findings corroborate the hypothesis of the enhanced biosafety profile of Aβ11/T80@CSs-TGC both in vitro and in vivo . Consequently, these results advocate for the potential of Aβ11/T80@CSs as a clinically viable nanocarrier system for targeted brain delivery of TGC, offering therapeutic avenues for treating intracranial infections. CONCLUSION In summary, we successfully synthesized core-shell nanoparticles, modified with Aβ11 and Tween 80, for the delivery of Tigecycline (TGC) aimed at treating intracranial infections caused by multi-drug resistant (MDR) A. baumannii . The Aβ11/T80@CSs nanoparticles demonstrated an effective encapsulation of the water-soluble anti-infection drug TGC in vitro , and exhibited significant activity against MDR A. baumannii . Crucially, the Aβ11/T80@CSs-TGC formulation effectively inhibited the growth of MDR A. baumannii in cerebrospinal fluid (CSF). Consistently, these findings suggest that the Aβ11/T80@CSs nano-delivery system has considerable potential to enhance the efficacy and safety of treatments for brain diseases (as depicted in abstract graphic ). However, further research is imperative to evaluate the clinical applicability of this nano-delivery system and to explore its potential in the treatment of various brain disorders. Declarations Ethics approval and consent to participate All animal experiments in this study were approved by the Animal Ethics Committee of West China Hospital of Sichuan University. Consent for publication All the listed authors have read the manuscript and approved to submission. The manuscript is original, has not been previously published and has not been submitted for publication elsewhere while under consideration. Availability of data and materials Not applicable Competing interests The authors have no financial conflict of interest. Funding This work was supported by West China Nursing Discipline Development Special Fund Project, Sichuan University (No. HXHL20007), Open Research fund of State Key Laboratory of Drug Delivery and Pharmacokinetics, Tianjin Institute of Pharmaceutical Research (No. 010162002), the National Natural Science Foundation of China (No. 82300113), China Postdoctoral Science Foundation (No.2022M722269), Sichuan University Postdoctoral Interdisciplinary Innovation Fund (No. JCXK2204), Post Doctor Research Project, West China Hospital, Sichuan University (No. 2023HXBH015). Authors' information 1 Department of Critical Care Medicine, Department of Clinical Pharmacy, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy and Cancer Center, West China School of Nursing, West China Hospital, Sichuan University, Chengdu, China. 2 State Key Laboratory of Drug Delivery and Pharmacokinetics, Tianjin Institute of Pharmaceutical Research, Tianjin 300301, People’s Republic of China. 3 School of Pharmacy, Faculty of Medicine, Macau University of Science and Technology, Macau, China. 3 Shihezi University, Xinjiang, China. # L.X, S.Q, H.L and M.G contributed equally to this study. *Corresponding author Email: [email protected] (Xiangrong Song), [email protected] (Yongmei Xie), [email protected] (Yan Kang). Author contributions X. Lan, S. Qin, H. Liu and X. Song designed the research. X. Lan, S. Qin, H. Liu and M. Guo carried out the experiments and performed data analysis. Y. Zhang, X. Jin, X. Duan, M. Sun, Z. Liu, W. Wang, Q. Zheng, X. Liao, J Chen, Y. Kang, Y. Xie participated part of the experiments and provided experimental drugs and quality control. X. Lan, S. Qin, H. Liu, and X. Song wrote the manuscript. Y. Kang, Y. Xie and X. Song revised the manuscript. All of the authors have read and approved the final manuscript. References Harding, C. M.; Hennon, S. W.; Feldman, M. F. Nature reviews. Microbiology 2018, 16, (2), 91-102. Tsitsopoulos, P. P.; Iosifidis, E.; Antachopoulos, C.; Anestis, D. M.; Karantani, E.; Karyoti, A.; Papaevangelou, G.; Kyriazidis, E.; Roilides, E.; Tsonidis, C. Acta Neurochir (Wien) 2016, 158, (9), 1647-54. Kurdyumova, N. V.; Danilov, G. V.; Ershova, O. N.; Savin, I. A.; Sokolova, E. Y.; Aleksandrova, I. A.; Shifrin, M. A. Zh Vopr Neirokhir Im N N Burdenko 2015, 79, (3), 55-59. Antunes, L. C.; Visca, P.; Towner, K. J. Pathog Dis 2014, 71, (3), 292-301. Giammanco, A.; Calà, C.; Fasciana, T.; Dowzicky, M. J. mSphere 2017, 2, (1). Jarvis, J. N.; Lawrence, D. S.; Meya, D. B.; Kagimu, E.; Kasibante, J.; Mpoza, E.; Rutakingirwa, M. K.; Ssebambulidde, K.; Tugume, L.; Rhein, J.; Boulware, D. R.; Mwandumba, H. C.; Moyo, M.; Mzinganjira, H.; Kanyama, C.; Hosseinipour, M. C.; Chawinga, C.; Meintjes, G.; Schutz, C.; Comins, K.; Singh, A.; Muzoora, C.; Jjunju, S.; Nuwagira, E.; Mosepele, M.; Leeme, T.; Siamisang, K.; Ndhlovu, C. E.; Hlupeni, A.; Mutata, C.; van Widenfelt, E.; Chen, T.; Wang, D.; Hope, W.; Boyer-Chammard, T.; Loyse, A.; Molloy, S. F.; Youssouf, N.; Lortholary, O.; Lalloo, D. G.; Jaffar, S.; Harrison, T. S. N Engl J Med 2022, 386, (12), 1109-1120. Doi, Y. Clin Infect Dis 2019, 69, (Suppl 7), S565-s575. Jo, J.; Ko, K. S. Microbiol Spectr 2021, 9, (2), e0101021. Frampton, J. E.; Curran, M. P. Drugs 2005, 65, (18), 2623-35; discussion 2636-7. Pankey, G. A. J Antimicrob Chemother 2005, 56, (3), 470-80. Fang, L. X.; Chen, C.; Cui, C. Y.; Li, X. P.; Zhang, Y.; Liao, X. P.; Sun, J.; Liu, Y. H. Bioessays 2020, 42, (8), e2000014. Cai, Y.; Bai, N.; Liu, X.; Liang, B.; Wang, J.; Wang, R. Infect Dis (Lond) 2016, 48, (7), 491-502. Kaewpoowat, Q.; Ostrosky-Zeichner, L. Expert Opin Drug Saf 2015, 14, (2), 335-42. Eichler, A. F.; Chung, E.; Kodack, D. P.; Loeffler, J. S.; Fukumura, D.; Jain, R. K. Nat Rev Clin Oncol 2011, 8, (6), 344-56. Shao, K.; Zhang, Y.; Ding, N.; Huang, S.; Wu, J.; Li, J.; Yang, C.; Leng, Q.; Ye, L.; Lou, J.; Zhu, L.; Jiang, C. Adv Healthc Mater 2015, 4, (2), 291-300. Hong, W.; Zhang, Z.; Liu, L.; Zhao, Y.; Zhang, D.; Liu, M. Drug Deliv 2018, 25, (1), 1886-1897. Zhuo, Y.; Zhang, Y.; Wang, B.; Cheng, S.; Yuan, R.; Liu, S.; Zhao, M.; Xu, B.; Zhang, Y.; Wang, X. Applied Materials Today 2022, 27, 101453. Cramer, P. E.; Cirrito, J. R.; Wesson, D. W.; Lee, C. Y.; Karlo, J. C.; Zinn, A. E.; Casali, B. T.; Restivo, J. L.; Goebel, W. D.; James, M. J.; Brunden, K. R.; Wilson, D. A.; Landreth, G. E. Science 2012, 335, (6075), 1503-6. Merino-Zamorano, C.; Fernández-de Retana, S.; Montañola, A.; Batlle, A.; Saint-Pol, J.; Mysiorek, C.; Gosselet, F.; Montaner, J.; Hernández-Guillamon, M. J Alzheimers Dis 2016, 53, (2), 677-91. Wang, Y.; Qin, X.; Paudel, H. K. Neurobiol Dis 2017, 103, 78-88. D'Ezio, V.; Colasanti, M.; Persichini, T. Antioxidants (Basel) 2021, 10, (11). Varadarajan, S.; Kanski, J.; Aksenova, M.; Lauderback, C.; Butterfield, D. A. J Am Chem Soc 2001, 123, (24), 5625-31. Zhang, Z.; Guan, J.; Jiang, Z.; Yang, Y.; Liu, J.; Hua, W.; Mao, Y.; Li, C.; Lu, W.; Qian, J.; Zhan, C. Nat Commun 2019, 10, (1), 3561. Joseph, A.; Simo, G. M.; Gao, T.; Alhindi, N.; Xu, N.; Graham, D. J.; Gamble, L. J.; Nance, E. Biomaterials 2021, 277, 121086. Pandey, V.; Haider, T.; Chandak, A. R.; Chakraborty, A.; Banerjee, S.; Soni, V. Int J Biol Macromol 2020, 164, 2018-2027. Das, D.; Lin, S. J Pharm Sci 2005, 94, (6), 1343-53. Leyva-Gómez, G.; Cortés, H.; Magaña, J. J.; Leyva-García, N.; Quintanar-Guerrero, D.; Florán, B. Drug Discov Today 2015, 20, (7), 824-37. Kenry; Yeo, T.; Manghnani, P. N.; Middha, E.; Pan, Y.; Chen, H.; Lim, C. T.; Liu, B. ACS Nano 2020, 14, (4), 4509-4522. Wagner, S.; Zensi, A.; Wien, S. L.; Tschickardt, S. E.; Maier, W.; Vogel, T.; Worek, F.; Pietrzik, C. U.; Kreuter, J.; von Briesen, H. PLoS One 2012, 7, (3), e32568. Additional Declarations No competing interests reported. Supplementary Files Abstractgraphic.tif Abstract graphic. Preparation and mechanism of action of Aβ11/T80@CSs. The Aβ11/T80@CSs nanoparticles were synthesized utilizing the emulsification-film hydration method. Upon preparation, these nanoparticles demonstrated a specific binding affinity for low-density lipoproteins (LDL), facilitating their interaction with LDL receptor-related protein 1 (LRP1) on the surface of brain endothelial cells. This interaction enabled the Aβ11/T80@CSs nanoparticles to efficiently penetrate the blood-brain barrier (BBB). Following penetration, Tigecycline (TGC) was released from the Aβ11/T80@CSs, where it targeted and bound to the 30S ribosomal subunit of multidrug-resistant (MDR) A. baumannii . This binding inhibited protein translation within the bacterial cells, ultimately leading to their demise. Cite Share Download PDF Status: Published Journal Publication published 30 Mar, 2024 Read the published version in Journal of Nanobiotechnology → Version 1 posted Editorial decision: Revision requested 17 Jan, 2024 Reviews received at journal 16 Jan, 2024 Reviewers agreed at journal 05 Jan, 2024 Reviewers invited by journal 05 Jan, 2024 Editor assigned by journal 05 Jan, 2024 Submission checks completed at journal 05 Jan, 2024 First submitted to journal 26 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3807612","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265528467,"identity":"ac9fd6d5-26ea-40cc-aeea-462f033c229b","order_by":0,"name":"Xing Lan","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Xing","middleName":"","lastName":"Lan","suffix":""},{"id":265528468,"identity":"8cf66350-4f37-4772-88c8-0a0d503c9555","order_by":1,"name":"Shugang Qin","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Shugang","middleName":"","lastName":"Qin","suffix":""},{"id":265528469,"identity":"05ff7a02-f775-4344-8367-206552ed3ece","order_by":2,"name":"Huan Liu","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Liu","suffix":""},{"id":265528470,"identity":"fd04a597-fe68-4908-baf6-175f705f184e","order_by":3,"name":"Mengran Guo","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Mengran","middleName":"","lastName":"Guo","suffix":""},{"id":265528471,"identity":"f0d83402-c977-4f74-b6f0-1bb0836c4774","order_by":4,"name":"Yupei Zhang","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yupei","middleName":"","lastName":"Zhang","suffix":""},{"id":265528472,"identity":"ce1339ac-97a1-4d2e-b32e-e5efd245e2eb","order_by":5,"name":"Xinyang Jin","email":"","orcid":"","institution":"Tianjin Institute of Pharmaceutical Research (China)","correspondingAuthor":false,"prefix":"","firstName":"Xinyang","middleName":"","lastName":"Jin","suffix":""},{"id":265528473,"identity":"8c0c6afe-494b-4d9d-be77-9caddce7bcda","order_by":6,"name":"Xing Duan","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Xing","middleName":"","lastName":"Duan","suffix":""},{"id":265528474,"identity":"42afda10-1469-4f0d-8336-a8f372541665","order_by":7,"name":"Min Sun","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Sun","suffix":""},{"id":265528475,"identity":"9122ebcf-a175-4d0f-b017-9b4d065befa3","order_by":8,"name":"Zhenjun Liu","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Zhenjun","middleName":"","lastName":"Liu","suffix":""},{"id":265528476,"identity":"00ba5d73-1fdc-429a-a5f7-d33c9a444187","order_by":9,"name":"Wenyan Wang","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Wenyan","middleName":"","lastName":"Wang","suffix":""},{"id":265528477,"identity":"28ae8f1e-ec79-47b6-a3a5-1e2d9f5868d7","order_by":10,"name":"Qian Zheng","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Zheng","suffix":""},{"id":265528478,"identity":"e96322fc-4bda-43bf-951a-1cd31c6e7cdf","order_by":11,"name":"Xuelian Liao","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Xuelian","middleName":"","lastName":"Liao","suffix":""},{"id":265528479,"identity":"048a32fc-6811-4750-9713-2ba71a97cc85","order_by":12,"name":"Jinpeng Chen","email":"","orcid":"","institution":"Tianjin Institute of Pharmaceutical Research (China)","correspondingAuthor":false,"prefix":"","firstName":"Jinpeng","middleName":"","lastName":"Chen","suffix":""},{"id":265528480,"identity":"8372f96a-fe3a-448f-8a12-3c0b3e271f65","order_by":13,"name":"Yan Kang","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Kang","suffix":""},{"id":265528481,"identity":"d87fa1a1-771b-4c81-9baf-a2f9ded3bc7a","order_by":14,"name":"Yongmei Xie","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yongmei","middleName":"","lastName":"Xie","suffix":""},{"id":265528482,"identity":"3b179208-2fe0-4c4c-b6e7-8932f4b143c5","order_by":15,"name":"xiangrong Song","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYPACGwjFQ4KWNNK1HCZBi3x77+HXvHvO2/PPSGB88LaNQd6ckBaDM+fSLGc8u50440YCs+HcNgbDnQ2EtEjkmBl8OHA7wUAigU2at40hweAAIYfNAGpJOHDOHqiF/TdRWhhu5Bg/+HDgAOMGoC3MRGkxOHPGjHHGgeTEGWceNkvOOSdhuIGgw9p7jD/zHLCz529PPvjhTZmNPGGHMTCwSUBoxgYgIUFYPRAwfyBK2SgYBaNgFIxcAADbCj44yysYMwAAAABJRU5ErkJggg==","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"xiangrong","middleName":"","lastName":"Song","suffix":""}],"badges":[],"createdAt":"2023-12-26 10:29:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3807612/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3807612/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12951-024-02373-z","type":"published","date":"2024-03-30T15:01:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49328056,"identity":"57151fc2-5f8b-4022-bc7a-2398aac355be","added_by":"auto","created_at":"2024-01-08 17:54:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1956557,"visible":true,"origin":"","legend":"\u003cp\u003ePrescription Optimization of Aβ11/T80@CSs. (A) Schematic diagram illustrating the preparation of PLGA nanoparticles (NPs). This figure shows the particle size (B), zeta potential (C), encapsulation efficiency (D), and brain distribution (E) of PLGA NPs synthesized from various polymer materials. (F) Schematic diagram depicting the preparation process of Aβ11/T80@CSs. The brain distribution of core-shell nanoparticles modified with varying concentrations of Aβ11 was evaluated (G) and quantified (H). Similarly, the brain distribution of core-shell nanoparticles modified with different amounts of Tween 80 was assessed (I) and quantified (J). All data are expressed as the mean ± standard deviation (SD), with n=3 independent experiments. Statistical analysis was conducted using a t-test for panels E, H, and J, with significance levels indicated as follows: \u003cem\u003e*p＜0.1, **p＜0.01, ***p＜0.001, ****p＜0.0001\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3807612/v1/7b7d2e5f2d58c15a3b17a187.jpg"},{"id":49328302,"identity":"09253e56-b947-4ac4-a1e3-d1cd49a4bed2","added_by":"auto","created_at":"2024-01-08 18:02:05","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":440900,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of Aβ11/T80@CSs. (A) The size distribution of Aβ11/T80@CSs was analyzed. (B) Zeta potential measurements were conducted to assess the surface charge of Aβ11/T80@CSs. (C) The Tyndall effect was employed to characterize the appearance and colloidal nature of Aβ11/T80@CSs. (D) Transmission Electron Microscopy (TEM) was used to visualize the structural morphology of Aβ11/T80@CSs. (E) The storage stability of Aβ11/T80@CSs at 4°C was evaluated by measuring particle size and encapsulation efficiency on days 0, 1, 3, 5, and 7. (F) The release profile of Aβ11/T80@CSs in phosphate-buffered saline (PBS) was investigated using a dynamic dialysis method. All data are expressed as the mean ± standard deviation (SD), based on n=3 independent experiments.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3807612/v1/3882b8571ebacb581a718e03.jpeg"},{"id":49328539,"identity":"e33c9aac-2829-4c92-a95e-0e5c9f029901","added_by":"auto","created_at":"2024-01-08 18:10:05","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":863733,"visible":true,"origin":"","legend":"\u003cp\u003eEffective uptake and brain distribution of Aβ11/T80@CSs.\u003cstrong\u003e \u003c/strong\u003e(A) Uptake of CSs, Aβ11@CSs, and Aβ11/T80@CSs by bEnd.3 cells was visualized using laser confocal microscopy. (B) Quantification of fluorescence intensity from the uptake study. (C) PBS, CSs, Aβ11@CSs, and Aβ11/T80@CSs were incubated with bEnd.3 cells for 4 hours, followed by (D) analysis of fluorescence using flow cytometry. (E) The cumulative transport volume of nanoparticles across the blood-brain barrier (BBB) was assessed at 4 hours. (F) Calculation of the transcellular membrane apparent permeability coefficient (Papp)\u003cem\u003ein vitro\u003c/em\u003e. (G) Fluorescence imaging of brains from intracranially infected rats. (H) Quantitative analysis of brain fluorescence. All data are presented as the mean ± standard deviation (SD), based on n=3 independent experiments. Statistical significance was determined using a t-test in panels B, D, F, and H, with \u003cem\u003e**p＜0.01, ***p＜0.001, ****p＜0.0001\u003c/em\u003eindicating levels of significance.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3807612/v1/c8f3674caaab26eba0f1d595.jpeg"},{"id":49328060,"identity":"10ff932b-49ca-4fa7-a0b2-413a65e4044c","added_by":"auto","created_at":"2024-01-08 17:54:05","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":943422,"visible":true,"origin":"","legend":"\u003cp\u003eEnhanced antibacterial activity of TGC by Aβ11/T80@CSs. (A) Digital images and (B) Optical Density (OD) at 600 nm of Aβ11/T80@CSs, determined using the microbroth dilution method. (C) Digital images and (D) bacterial count statistics in rat cerebrospinal fluid (CSF) following intrathecal injection of free TGC, CSs, and Aβ11/T80@CSs. (E) Plasma concentration-time curves following intravenous administration of free TGC, CSs-TGC, and Aβ11/T80@CSs-TGC. (F) Experimental protocol for the infection and treatment of multidrug-resistant (MDR) \u003cem\u003eA. baumannii\u003c/em\u003e(G) Digital images and (H) bacterial count statistics in CSF of different groups after intravenous injection. Pharmacokinetic parameters including maximum concentration (Cmax), terminal elimination half-life (T1/2), area under the curve AUC(0-t), and clearance (CL) are presented. All data are expressed as the mean ± standard deviation (SD), based on n=3 independent experiments. Statistical significance in panels D and H was determined using a t-test, with \u003cem\u003e**p＜0.01, ***p＜0.001, ****p＜0.0001\u003c/em\u003eindicating levels of significance.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3807612/v1/7f81a9d7320a34af996f29ad.jpeg"},{"id":49328057,"identity":"bc07b512-7c8c-42c7-85e6-24330963fe35","added_by":"auto","created_at":"2024-01-08 17:54:05","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1644138,"visible":true,"origin":"","legend":"\u003cp\u003eBiosafety Assessment of Aβ11/T80@CSs.\u003cstrong\u003e \u003c/strong\u003eThis figure presents the results of our biosafety evaluation. (A) We conducted \u003cem\u003ein vitro\u003c/em\u003e hemolysis assays on various formulations, employing pure water as the positive control (PC) and saline as the negative control (NC). (B) The viability of bEnd.3 cells was examined following a 24-hour incubation with different concentrations of free TGC, CSs-TGC (C), and Aβ11/T80@CSs-TGC (D). Additionally, histopathological examinations of the heart, liver, spleen, lungs, and kidneys were performed across the different groups, two days post-treatment (Panel E). All data are expressed as the mean ± SD, n=3 independent experiments. Experiment E was repeated 3 times independently.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3807612/v1/f0c15549ddd1027bea411224.jpeg"},{"id":53870018,"identity":"f8e01c30-e29f-4a13-bbec-f8d67b43989b","added_by":"auto","created_at":"2024-04-01 15:12:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1311991,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3807612/v1/b9cba4be-5dfd-4032-81b6-190c62364c3d.pdf"},{"id":49328061,"identity":"eb8b78a4-b36d-475f-9376-a8fdc92d7f31","added_by":"auto","created_at":"2024-01-08 17:54:05","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1916966,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbstract graphic. \u003c/strong\u003ePreparation and mechanism of action of Aβ11/T80@CSs.\u003cstrong\u003e \u003c/strong\u003eThe Aβ11/T80@CSs nanoparticles were synthesized utilizing the emulsification-film hydration method. Upon preparation, these nanoparticles demonstrated a specific binding affinity for low-density lipoproteins (LDL), facilitating their interaction with LDL receptor-related protein 1 (LRP1) on the surface of brain endothelial cells. This interaction enabled the Aβ11/T80@CSs nanoparticles to efficiently penetrate the blood-brain barrier (BBB). Following penetration, Tigecycline (TGC) was released from the Aβ11/T80@CSs, where it targeted and bound to the 30S ribosomal subunit of multidrug-resistant (MDR)\u003cem\u003e A. baumannii\u003c/em\u003e. This binding inhibited protein translation within the bacterial cells, ultimately leading to their demise.\u003c/p\u003e","description":"","filename":"Abstractgraphic.tif","url":"https://assets-eu.researchsquare.com/files/rs-3807612/v1/541ddb2535fa8a892a2c578d.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dual-targeting tigecycline nanoparticles for treating intracranial infections caused by multidrug-resistant Acinetobacter baumannii","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003e \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (\u003cem\u003eA. baumannii\u003c/em\u003e), a notorious nosocomial pathogen, was identified as a primary cause of severe intracranial infections and associated complications \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Recent data indicated a rising trend in the incidence of postoperative intracranial infections attributable to \u003cem\u003eA. baumannii\u003c/em\u003e, accounting for 15.7%-24.2% of cases \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The proliferation of multidrug resistance (MDR) in \u003cem\u003eA. baumannii\u003c/em\u003e, fueled by antibiotic misuse, rendered the treatment of such infections exceedingly challenging \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Reports highlighted that MDR \u003cem\u003eA. baumannii\u003c/em\u003e showed resistance to multiple antibiotic classes, including β-lactams, cephalosporins, and carbapenems, with the MDR rate escalating from 23\u0026ndash;63%, a rate fourfold higher than that observed in other MDR Gram-negative bacteria like \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The World Health Organization identified carbapenem-resistant \u003cem\u003eA. baumannii\u003c/em\u003e as a critical threat to global health \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Alarmingly, limited pharmaceutical options were available for treating MDR \u003cem\u003eA. baumannii\u003c/em\u003e, primarily tigecycline and colistin \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTigecycline (TGC), a new-generation tetracycline antibiotic, emerged as the most potent treatment against intracranial infections caused by MDR \u003cem\u003eA. baumannii\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. TGC functioned by binding to the 30S ribosomal subunit, thereby inhibiting bacterial protein synthesis through prevention of tRNA binding at the ribosomal A site, ultimately stalling bacterial growth \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Notably, TGC retained efficacy against MDR strains by circumventing resistance mechanisms such as ribosomal protection and antibiotic efflux, a significant advantage over minocycline \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, TGC\u0026rsquo;s limited permeability through the blood-brain barrier (BBB) posed challenges in attaining adequate drug concentrations in the cerebrospinal fluid (CSF). Intraventricular injection, often employed for treating MDR \u003cem\u003eA. baumannii\u003c/em\u003e intracranial infections, carried a heightened risk of secondary infections \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Consequently, the development of a safe and effective TGC brain-targeted delivery system was deemed essential.\u003c/p\u003e \u003cp\u003eNano-delivery systems have demonstrated the capability to precisely target specific organs and cells, and to extend the duration of blood circulation, thereby enhancing the efficacy and safety of drugs. This approach offered an innovative strategy for transporting drugs across the blood-brain barrier (BBB), yet reports on targeted therapy for intracranial infections remained sparse. Recently, antibacterial peptides and itraconazole were formulated into brain-targeted delivery systems for intracranial infection treatment, although their preparation processes were complex \u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. β-Amyloid (Aβ1\u0026ndash;40), a peptide resulting from the proteolytic cleavage of the amyloid precursor protein, circulated in blood, cerebrospinal fluid (CSF), and interstitial fluid. Aβ1\u0026ndash;40 was capable of crossing the BBB by binding to low-density lipoproteins (LDL, such as ApoE and ApoA) and LDL receptor-related protein 1 (LRP1) \u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. A fragment of Aβ1\u0026ndash;40, Aβ25\u0026ndash;35 (Aβ11), exhibited similar functionality \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Studies indicated that Aβ11 could be safely modified onto the surface of nanocarriers for brain targeting \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Tween 80 (T80), a nonionic surfactant, was observed to enhance the accumulation of nanoparticles in brain endothelial cells of the BBB \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Moreover, nanoparticles modified with T80 were reported to adsorb LDL in blood and be uptaken by BBB endothelial cells via interaction with LRP1 \u003csup\u003e25\u003c/sup\u003e. Additionally, T80 was found to inhibit the active efflux of P-glycoprotein, increasing the brain uptake of nanoparticles \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. These findings suggested that the Aβ11 and T80 dual-modified nano-delivery system held significant potential for the brain-targeted delivery of Tigecycline (TGC) to treat intracranial infections.\u003c/p\u003e \u003cp\u003eIn this study, we introduced a pioneering method to prepare core-shell nanoparticles modified with Aβ11 and Tween 80 (Aβ11/T80@CSs) for delivering water-soluble TGC into the CSF by traversing the BBB. We discovered that the Aβ11/T80@CSs brain-targeting nano-delivery system could enhance the encapsulation efficiency of water-soluble drugs, prolong TGC's \u003cem\u003ein vivo\u003c/em\u003e circulation time, and improve its bioavailability. The Aβ11/T80@CSs system facilitated TGC distribution in the brain and augmented its efficacy against MDR \u003cem\u003eA. baumannii\u003c/em\u003e in a mouse model of intracranial infection. Our findings provided a foundational framework for further development of brain-targeting nano-delivery systems in the treatment of intracranial infections caused by MDR bacteria.\u003c/p\u003e"},{"header":"EXPERIMENTAL SECTION","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eTigecycline, with a purity exceeding 98%, was procured from Suo Laibao Biotechnology Co., Ltd. The Aβ11 peptide, featuring an additional cysteine at its C-terminus (Aβ11-Cys), was synthesized by Qiang Yao Biochem Ltd., Hubei, China. The C-terminal amidated Aβ11-Cys peptide sequence was NH2-CGSNKGAIIGLM-CONH2. Mal-PEG2000-Chol was acquired from Pengshuo Biotechnology Co. Ltd., Chengdu, China. Various forms of mPEG-PLGA, PLGA, and PLGA-PEG-PLGA, all with a molecular weight of 15 kDa and varying lactide to glycolide ratios, were purchased from Jinan Daigang Biomaterial Co., Ltd., Jinan, China. Poly (vinyl alcohol) (PVA) with a molecular weight range of 30\u0026ndash;70 kDa, Tween 80, and 3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide (MTT) were obtained from Chengdu Real Biotechnology Co., Ltd., Chengdu, China. 1,1'-Dioctadecyl-3,3,3',3'-Tetramethylindodicarbocyanine perchlorate (DiD) was sourced from Gelman Sciences Inc., California, USA. Confocal plates and DMEM were procured from Rancho Technology Co., Ltd., Beijing, China. All other reagents and chemicals were of analytical reagent grade and were used without further purification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003eBALB/c mice, male, aged 6\u0026ndash;8 weeks and weighing 22\u0026ndash;25 g (SPF grade), along with adult healthy female Sprague-Dawley rats, weighing between 200\u0026ndash;250 g (SPF grade), were obtained from the Sichuan University Experimental Animal Center, Ltd., Chengdu, Sichuan, China. All animal experiments were conducted with the approval and under the supervision of the West China Hospital Animal Care and Use Committee, Sichuan University. The animals were housed in an environment maintained at 22\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C with a 12:12 hr light-dark cycle and a relative humidity of 55\u0026thinsp;\u0026plusmn;\u0026thinsp;10%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis of Chol-PEG2000-Aβ11\u003c/h2\u003e \u003cp\u003eChol-PEG2000-Aβ11 was synthesized via a Michael addition reaction. Initially, 50 mg of Chol-PEG2000-Mal was dissolved in 5 mL of chloroform and subsequently transformed into a film through rotary evaporation. This film was then completely dissolved by hydrating with 3 mL of Milli-Q water for 30 minutes. In a separate procedure, 22 mg of thiodized Aβ11-Cys was dissolved in 2 mL of Milli-Q water and combined with the Chol-PEG2000-Mal suspension. Following this, 200 \u0026micro;L of EDTA (500 mM, pH 8.0) and 3 mL of 0.1 M phosphate buffer were added to the mixture. The reaction proceeded at room temperature for 48 hours. Unbound peptide and Chol-PEG2000-Mal were removed by dialysis (MW\u0026thinsp;=\u0026thinsp;5 kDa) over a period of 72 hours, after which Chol-PEG2000-Aβ11 was obtained through freeze-drying.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eFormulation screening of PLGA nanoparticles\u003c/h2\u003e \u003cp\u003eTo select the optimal polymer carrier material for encapsulating Tigecycline (TGC), we synthesized seven different formulations of PLGA nanoparticles (PLGA NPs), detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. These PLGA NPs were prepared using an emulsification-solvent evaporation method. Briefly, PLGA was dissolved in a mixture of dichloromethane (DCM) and acetone to create a 2% (w/v) solution, serving as the organic phase. An aqueous solution of tigecycline was then gradually added dropwise to this organic phase and emulsified using an ultrasonic liquid processor (XinZhi, China) at 100 W power, forming an oil-in-water (O/W) emulsion. This O/W emulsion was subsequently dropped into a 1% polyvinyl alcohol (PVA) solution, and a secondary ultrasound process generated a multi emulsion (W/O/W). The resultant emulsion was then transferred to a 250 mL eggplant-shaped flask, and the organic solvent was evaporated under vacuum at 37\u0026deg;C, resulting in the formation of PLGA NPs. Using a similar preparation method, DiD was substituted for TGC to synthesize PLGA NPs/DiD.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePolymer material composition of each formulation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003emPEG-PLGA\u003c/p\u003e \u003cp\u003e(75/25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePLGA\u003c/p\u003e \u003cp\u003e(50/50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePLGA\u003c/p\u003e \u003cp\u003e(75/25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePLGA-PEG-PLGA\u003c/p\u003e \u003cp\u003e(50/50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePLGA-PEG-PLGA\u003c/p\u003e \u003cp\u003e(75/25)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 mg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eParticle Size and ζ-Potential Measurement\u003c/h2\u003e \u003cp\u003eThe particle size and ζ-potential of the nanoparticles were assessed using a Malvern particle size meter (Zetasizer NanoZS 90). Prior to measurement, the samples were diluted tenfold, and each sample underwent three separate measurements to ensure accuracy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTGC content and encapsulation efficiency determination\u003c/h2\u003e \u003cp\u003eHigh-Performance Liquid Chromatography (HPLC) was employed to detect the Tigecycline (TGC) content and to ascertain the encapsulation efficiency of the nanoparticles. A 200 \u0026micro;L aliquot of the nanoparticle solution was dissolved in 0.8 mL of methanol with ultrasonication to facilitate drug extraction, followed by dilution with 1 mL of water. Chromatographic separation was conducted on a C18 column (250 mm \u0026times; 4.6 mm, 6 \u0026micro;m) using a mobile phase composed of ammonium phosphate dibasic-triethylamine-methanol (50:1:49, pH\u0026thinsp;=\u0026thinsp;6.3), at a flow rate of 1.0 mL/min. The detection wavelength was set at 246 nm. The drug loading and encapsulation efficiency (%) of the nanoparticles were calculated using the following equation: Encapsulation efficiency =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{M}_{1}-{M}_{2}}{{M}_{1}}\\)\u003c/span\u003e\u003c/span\u003e\u0026times;100%, where M_1 represents the total weight of the drug and M_2 the weight of the drug (TGC) remaining in the liquid medium post-encapsulation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePreparation and characterization of the Aβ11/T80@css nanodrug delivery system\u003c/h2\u003e \u003cp\u003eCore-shell nanoparticles were synthesized through the thin-film hydration method, and the formulation with varying Aβ11 molar ratios is detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Phospholipid (PLS100), cholesterol (Chol), Chol-PEG2000-Aβ11, and Chol-PEG2000 were dissolved in 4 mL of chloroform. Subsequently, the organic solvent was evaporated using a rotary evaporator. The resultant lipid membrane was hydrated with a PLGA NPs solution at 37\u0026deg;C for 30 minutes, then sonicated at 80 W for 6 minutes to form lipid nanoparticles. These nanoparticles were collected in ultrafiltration tubes, centrifuged at 4000 rpm for 15 minutes, and washed thrice with Milli-Q water to remove unencapsulated drugs (Aβ11@CSs). Following a similar method, Tween 80 was added to the chloroform to synthesize Aβ11- and Tween 80-modified lipid nanoparticles (Aβ11/T80@CSs). Nanoparticles labeled with DiD or Cou6 were prepared by incorporating appropriate amounts of DiD or Cou6.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulations of Aβ11 delivery systems with different molar ratios.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCSs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%Aβ11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5%Aβ11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10%Aβ11\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLS100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEG2000-Chol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAβ11-PEG2000-Chol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe particle size and ζ-potential of the Aβ11/T80@CSs nanoparticles were measured using a Malvern particle size meter. The encapsulation efficiency (EE) was determined by High-Performance Liquid Chromatography (HPLC). For morphological analysis, transmission electron microscopy (TEM, HF-3300, Hitachi, Japan) was utilized to observe the nanoparticles. A 10 \u0026micro;L aliquot of the Aβ11/T80@CSs suspension was placed on copper grids and thoroughly freeze-dried before TEM examination. The structural characteristics of Aβ11/T80@CSs were then observed at an appropriate accelerating voltage.\u003c/p\u003e \u003cp\u003eAn \u003cem\u003ein vitro\u003c/em\u003e drug release study was conducted employing the dialysis method, with phosphate-buffered saline (PBS, pH\u0026thinsp;=\u0026thinsp;7.4) as the release medium. For this study, 2 mL aliquots of free Tigecycline (TGC), CSs, or Aβ11/T80@CSs (each containing 1 mg of TGC) were sealed in dialysis bags with a molecular weight cutoff of 3.5 kDa. These bags were then immersed in 30 mL of PBS and gently agitated at 37\u0026deg;C. At predetermined time intervals, 1.0 mL of PBS was sampled from outside each dialysis bag for HPLC analysis, and an equivalent volume of fresh PBS was replenished to maintain a constant volume in the release medium.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBrain distribution imaging experiment\u003c/h2\u003e \u003cp\u003eBALB/c mice underwent a one-week acclimation period to their new environment. Subsequently, they were randomly assigned to different groups. The mice received injections of nanoparticles or free DiD (equivalent to 0.5 mg/kg DiD) via the tail vein. A blank control group, comprising three mice, was also established. Four hours post-injection, the mice were euthanized using isoflurane, and their brains were harvested for \u003cem\u003ein vitro\u003c/em\u003e imaging. The imaging was performed using the IVIS imaging system (IVIS Lumina III, PerkinElmer, USA), with the excitation and emission wavelengths set at 720 nm and 740 nm, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCell uptake\u003c/h2\u003e \u003cp\u003eThe uptake of Cou6-loaded nanoparticles by cells was investigated using bEnd.3 endothelial cells. bEnd.3 cells, seeded at a density of 1\u0026times;10^5 cells/well, were cultured in 24-well plates for 24 hours until they reached full adherence. The cells were subsequently incubated with CSs-Cou6, Aβ11@CSs-Cou6, or Aβ11/T80@CSs-Cou6 in confocal dishes for four hours. Post-incubation, the cells were stained with DAPI for 20 minutes and imaged using a laser-scanning microscope (CLSM, LSM-880). Fluorescence intensity was quantified using ImageJ software (java8, NIH, USA).\u003c/p\u003e \u003cp\u003eFor flow cytometry analysis, the cells were incubated with CSs-Cou6, Aβ11@CSs-Cou6, or Aβ11/T80@CSs-Cou6 (each containing 80 ng of Cou6) for four hours in DMEM supplemented with 10% fetal bovine serum. After washing twice with PBS to remove any uninternalized nanoparticles, the cells were harvested and resuspended in 300 \u0026micro;L of PBS. Fluorescence intensity was measured using flow cytometry (2060R, NovoCyte, ACEA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTransmembrane transport assay\u003c/h2\u003e \u003cp\u003eAn \u003cem\u003ein vitro\u003c/em\u003e blood-brain barrier (BBB) model was established using bEnd.3 cells to assess the penetration efficiency of different nanoparticles. For this model, 2.0\u0026times;10^5 bEnd.3 cells were cultured in a 24-well Transwell chamber with 3 \u0026micro;m pores. Intercellular compactness was verified with a cell resistance meter (Millicell-ERS EVOM2, USA), and the BBB model was deemed successful when the transendothelial electrical resistance reached 200 Ω\u0026middot;cm^2. To evaluate nanoparticle penetration through the monolayer, Hank's Balanced Salt Solution (HBSS) replaced the standard medium, and free TGC, CSs-TGC, Aβ11@CSs-TGC, or Aβ11/T80@CSs-TGC was added to the apical side for co-incubation. At various time intervals, 200 \u0026micro;L samples of HBSS were collected from the basolateral side and replaced with fresh HBSS. The concentration of TGC in these samples was determined using HPLC. The cumulative permeation of TGC from the apical to the basolateral compartment and the apparent permeability coefficient (Papp) were calculated using the formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\text{M}\\text{n}={C}_{n}\\times V+{\\sum }_{i=1}^{n-1}{C}_{i}\\times {V}_{i}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ePapp=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{dQ}{dt}\\)\u003c/span\u003e\u003c/span\u003e\u0026times;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{1}{A\\times {C}_{0}}\\)\u003c/span\u003e\u003c/span\u003e\u0026times;100%\u003c/p\u003e \u003cp\u003ewhere Mn represents the cumulative amount of TGC permeated at the nth time point, Cn is the concentration of TGC at the nth time point, V is the total volume of the basolateral solution, Ci is the concentration of TGC at the ith time point, and Vi is the volume of the sample collected at the ith time point. The Papp was calculated as dQ/dt\u0026times;1/(A\u0026times;C0)\u0026times;100%, where dQ/dt is the rate of TGC transfer from the upper to the lower layer of the Transwell plate, \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e is the initial concentration of TGC in the upper layer, and A is the surface area of the membrane (\u003cem\u003ecm2\u003c/em\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAntimicrobial activity of Aβ11/T80@CSs\u003c/b\u003e \u003cb\u003ein vitro\u003c/b\u003e \u003cb\u003eand in CSF\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo assess the antibacterial activity of empty CSs, free Tigecycline (TGC), and Aβ11/T80@CSs-TGC against multidrug-resistant (MDR) \u003cem\u003eA. baumannii\u003c/em\u003e, the minimum inhibitory concentration (MIC) was determined. Bacteria in the mid-logarithmic growth phase were diluted to a concentration of 1\u0026times;10\u003csup\u003e5\u003c/sup\u003e CFU/mL. A 100 \u0026micro;L aliquot of this bacterial suspension was mixed with 100 \u0026micro;L of either free TGC or Aβ11/T80@CSs-TGC, with concentrations ranging from 0.125 to 16 \u0026micro;g/mL, and incubated in 96-well plates for 24 hours. The bacterial density at 600 nm was subsequently measured using a microplate reader (Biotek Synergy MX). In the rat intracranial infection model, MDR \u003cem\u003eA. baumannii\u003c/em\u003e infection was induced by intracisternal injection of 20 \u0026micro;L of MDR \u003cem\u003eA. baumannii\u003c/em\u003e (1\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL) into the cerebrospinal fluid (CSF) of healthy rats. To investigate the efficacy of TGC against MDR \u003cem\u003eA. baumannii\u003c/em\u003e in CSF, rats infected with MDR \u003cem\u003eA. baumannii\u003c/em\u003e received intrathecal injections of 20 \u0026micro;L of Aβ11/T80@CSs-TGC, CSs-TGC, or free TGC (equivalent to 10 \u0026micro;g TGC). After 24 hours, CSF was collected from the rats and cultured on solid media. Colony counts were recorded following a 24-hour incubation at 37\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePharmacokinetics of Aβ11/T80@CSs\u003c/h2\u003e \u003cp\u003eIn the pharmacokinetic study, adult female Sprague-Dawley rats, weighing between 200 and 250 grams, were used. Prior to the experiment, the animals were fasted overnight with free access to water. Nine rats were randomly divided into three groups: free-TGC, CSs-TGC, and Aβ11/T80@CSs-TGC. Each group received an intravenous administration of TGC at a dose of 12.5 mg/kg via the tail vein. Blood samples were collected at predetermined time points (0.25, 0.5, 1, 2, 4, 6, and 8 hours), and then placed into 2 mL Eppendorf tubes. These samples were centrifuged at 10,000 rpm for 10 minutes at 4\u0026deg;C to separate the plasma. A portion of the plasma was mixed with methanol in a 1:4 volume ratio and further centrifuged at 13,000 rpm for 10 minutes at 4\u0026deg;C. The supernatant was collected for TGC concentration determination using HPLC. Pharmacokinetic parameters were subsequently calculated using the statistical analysis tool DAS2.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAnti-infective efficacy of Aβ11/T80@CSs\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e\u003c/p\u003e \u003cp\u003eRats with intracranial infections were randomly divided into four groups to evaluate the anti-infective efficacy of different treatments. These groups received saline, free Tigecycline (TGC), CSs-TGC, or Aβ11/T80@CSs-TGC (each with a TGC dose of 30 mg/kg) as treatments. The administrations were conducted intravenously at 0 hours, 6 hours, and 18 hours post-infection modeling. After 24 hours, cerebrospinal fluid (CSF) samples were collected from the rats, evenly spread onto solid culture media, and incubated at 37\u0026deg;C for 24 hours. The colony count for each group was then recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eHemolysis of Aβ11/T80@CSs\u003c/h2\u003e \u003cp\u003eThe hemolytic activity of Aβ11/T80@CSs was assessed using erythrocytes from healthy rats. Blood samples were collected, and red blood cells were isolated through centrifugation, followed by suspension in normal saline to create a 2% erythrocyte solution. Two milliliters of this erythrocyte suspension were mixed with free TGC, CSs, or Aβ11/T80@CSs and incubated at 37\u0026deg;C for three hours. Post-incubation, the samples were centrifuged, and the absorbance of the supernatant was measured using spectrophotometry at 570 nm. Purified water and normal saline served as positive and negative controls, respectively. The percentage of hemolysis was calculated using the following formula:\u003c/p\u003e \u003cp\u003eHemolysis (%) =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{Asample- Anegative}{Apositive- Anegativ}\\)\u003c/span\u003e\u003c/span\u003e\u0026times;100%\u003c/p\u003e \u003cp\u003e \u003cb\u003eCell cytotoxicity assessment\u003c/b\u003e \u003cb\u003evia\u003c/b\u003e \u003cb\u003eMTT assay\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCell cytotoxicity was evaluated using the MTT assay. Initially, 5\u0026times;10^4 bEnd.3 cells were seeded in a 96-well plate and incubated overnight at 37\u0026deg;C to ensure complete adherence. Subsequently, the medium was replaced with fresh medium containing varying concentrations of Aβ11/T80@CSs-TGC, and the cells were incubated for an additional 24 hours in sets of three wells per concentration. Following this, 20 \u0026micro;L of MTT solution was added to each well, and the cells were incubated for another 4 hours at 37\u0026deg;C. The supernatant was then removed, and 150 \u0026micro;L of dimethyl sulfoxide was added to dissolve the dark blue formazan for approximately 30 minutes. The optical absorbance of each well was measured at 570 nm using a microplate reader (BioTek, USA). Cells treated with phosphate-buffered saline (PBS) served as the control group.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIn vivo\u003c/b\u003e \u003cb\u003ebiosafety assessment\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo further investigate the biosafety of the various formulations \u003cem\u003ein vivo\u003c/em\u003e, blood samples were collected post-administration for biochemical analysis. After euthanizing the rats, their heart, liver, spleen, lung, and kidney tissues were harvested. These tissues underwent hematoxylin and eosin (H\u0026amp;E) staining and were subsequently imaged using a pathology slide scanner.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eEach experimental condition was replicated in at least three parallel experiments. The results are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. GraphPad software was employed for all statistical analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003ePreparation of the A\u0026beta;11/T80@CSs nanodrug delivery system\u003c/h2\u003e\n \u003cp\u003eTo optimize the formulation of poly(lactic-co-glycolic acid) nanoparticles (PLGA NPs), these nanoparticles were prepared using the emulsification-solvent evaporation method, employing PLGA series polymers as carrier materials (as illustrated in \u003cstrong\u003eFig.\u0026nbsp;1A\u003c/strong\u003e). The particle size, electric potential, and encapsulation efficiency (EE%) of the PLGA NPs were characterized using Malvern particle size analyzers and High-Performance Liquid Chromatography (HPLC). The seven nanoparticle formulations exhibited a particle size range of 100 to 200 nm and demonstrated uniform size distribution (\u003cstrong\u003eFig.\u0026nbsp;1B\u003c/strong\u003e). All formulations displayed negative zeta potentials, with formulation F7 showing the lowest zeta potential (\u003cstrong\u003eFig.\u0026nbsp;1C\u003c/strong\u003e), which contributed to enhanced nanoparticle stability and reduced aggregation. With a Tigecycline (TGC) content of 3 mg, the EE% of these nanoparticles varied from 40\u0026ndash;80%. Notably, formulations F2 and F7 achieved higher EE%, approximately 80%, compared to the other five formulations (\u003cstrong\u003eFig.\u0026nbsp;1D\u003c/strong\u003e). The particle sizes of F4 and F5 were smaller than those of the other groups, yet their encapsulation efficiencies were significantly lower, suggesting inadequate drug encapsulation and consequently smaller empty nanoparticles.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eIn vivo\u003c/em\u003e studies were also conducted to assess variations in brain targeting among these formulations. As indicated in \u003cstrong\u003eFig.\u0026nbsp;1E\u003c/strong\u003e, PLGA NPs demonstrated higher brain expression levels compared to free-DiD, implying enhanced drug delivery to the brain by the nanoparticles. The ability of the seven formulations to penetrate the blood-brain barrier (BBB) varied, with F7 exhibiting stronger fluorescence absorption than the other formulations. This variation in nanoparticle distribution could be attributed to the influence of the material composition on particle size and potential. PLGA polymers vary in lactic acid to glycolic acid (LA/GA) ratios, with a lower LA/GA ratio indicating increased hydrophilicity and higher zeta potential. Additionally, polyethylene glycol (PEG) modification of PLGA can further enhance its hydrophilicity, influencing nanoparticle size and encapsulation efficiency. Particle size is a critical attribute for nanoparticle characterization and a significant parameter in drug delivery systems, as it affects cellular and tissue uptake \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Smaller nanoparticles are generally more efficiently absorbed by cells. Recent studies have also suggested that endothelial cells preferentially uptake polymer nanoparticles with more negative charges \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Based on these results, F7 PLGA NPs were selected as the carrier material for preparing the core-shell nanoparticles (CSs) as a kernel.\u003c/p\u003e\n \u003cp\u003eNext, thin film hydration was employed to prepare ligand-modified core-shell nanoparticles (CSs), as illustrated in \u003cstrong\u003eFig.\u0026nbsp;1F\u003c/strong\u003e. Initially, A\u0026beta;11-modified CSs (A\u0026beta;11@CSs) were synthesized to screen the content of Chol-PEG2000-A\u0026beta;11 using IVIS imaging. As demonstrated in \u003cstrong\u003eFig.\u0026nbsp;1G, H\u003c/strong\u003e, A\u0026beta;11@CSs displayed a higher fluorescence intensity in the brain compared to CSs alone, indicating A\u0026beta;11\u0026rsquo;s robust targeting ability. Notably, the brain\u0026rsquo;s fluorescence signal was significantly higher than in other groups when the molar ratio of Chol-PEG2000-A\u0026beta;11 was 5%. The fluorescence intensities for 1% and 10% A\u0026beta;11 in the brain did not exhibit a significant difference. Subsequently, the study investigated whether Tween 80 (T80) could enhance the penetration of A\u0026beta;11@CSs through the blood-brain barrier (BBB). As shown in \u003cstrong\u003eFig.\u0026nbsp;1I, J\u003c/strong\u003e, the incorporation of T80 led to increased accumulation of nanoparticles in the brain compared to A\u0026beta;11@CSs. Interestingly, optimal distribution was observed with 0.5% T80 (v/v), and higher concentrations of T80 did not further enhance fluorescence intensity. This could be attributed to T80\u0026apos;s ability to inhibit P-glycoprotein, thereby preventing nano efflux, and its potential competition with A\u0026beta;11 for binding to lipoproteins, which might reduce A\u0026beta;11\u0026apos;s efficiency \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Based on these findings, a composition of 5% Chol-PEG2000-A\u0026beta;11 and 0.5% T80 was selected for modifying the nanoparticles (A\u0026beta;11/T80@CSs) in subsequent studies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eCharacterization of the A\u0026beta;11/T80@CSs nanodrug delivery system\u003c/h2\u003e\n \u003cp\u003eThe physical, chemical properties, and stability of A\u0026beta;11/T80@CSs were characterized. The average particle size of A\u0026beta;11/T80@CSs-TGC was found to be 158\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 nm, accompanied by a negative zeta potential of -11.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 mV (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, B). These findings indicated a uniform particle size distribution and a single-peak zeta potential distribution for A\u0026beta;11/T80@CSs. Notably, the particle size of A\u0026beta;11/T80@CSs was approximately 20 nm larger than that of the PLGA NPs, a difference that was not statistically significant. High-Performance Liquid Chromatography (HPLC) was utilized to ascertain the Tigecycline (TGC) content, revealing an encapsulation efficiency (EE%) of 84.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3% for A\u0026beta;11/T80@CSs-TGC. Under natural light, both A\u0026beta;11/T80@CSs-TGC and CSs-TGC solutions appeared clear, transparent, and light blue in color. Upon exposure to a laser pointer, aside from the control, A\u0026beta;11/T80@CSs-TGC and CSs-TGC exhibited a pronounced Tyndall effect (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC), demonstrating that the preparation was a homogeneous colloidal solution. Transmission Electron Microscopy (TEM) images revealed a homogeneous spherical structure with a core-shell configuration for A\u0026beta;11/T80@CSs-TGC (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\n \u003cp\u003eThe stability of A\u0026beta;11/T80@CSs-TGC was evaluated by storing the nanoparticles at 4\u0026deg;C for five days. As illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE, there were no significant changes in particle size and EE% during this storage period, suggesting excellent stability of the formulation. The dynamic dialysis method was employed to examine the \u003cem\u003ein vitro\u003c/em\u003e drug release profile. As depicted in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eF, approximately 50% of TGC was released from the nanoparticles within the first hour, followed by a sustained release over time. The cumulative drug release within 12 hours was 85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3% for CSs-TGC and 80.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8% for A\u0026beta;11/T80@CSs-TGC, indicating that ligand modification did not significantly impact the release of TGC from the nanoparticles. The complete release of the free drug within three hours could be ascribed to the absence of a carrier material for encapsulation. Overall, these results demonstrated that A\u0026beta;11/T80@CSs was highly stable and could efficiently entrap and release TGC.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eTargeting efficiency of A\u0026beta;11/T80@CSs\u003c/h2\u003e\n \u003cp\u003eEffective drug delivery across the blood-brain barrier (BBB) is crucial in the treatment of intracranial infections, as it enables access to the infection site, enhances drug efficacy, minimizes side effects, prolongs drug delivery, and potentially overcomes resistance. Strategies and technologies of the A\u0026beta;11/T80@CSs nanodrug delivery system aimed at improving BBB penetration are pivotal for advancing treatment options for intracranial infections. We investigated the uptake of different nanoparticles at the 4-hour mark using confocal laser microscopy, employing bEnd.3 cells as a model system. As depicted in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, CSs, A\u0026beta;11@CSs, and A\u0026beta;11/T80@CSs were internalized by bEnd.3 cells. Notably, A\u0026beta;11/T80@CSs demonstrated significantly higher cellular uptake, with fluorescence intensities 3.9 times and 1.65 times greater than those of CSs and A\u0026beta;11@CSs, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). This finding was corroborated by flow cytometry results, which showed that the fluorescence intensity of A\u0026beta;11/T80@CSs was four times and 2.5 times higher than that of CSs and A\u0026beta;11@CSs, respectively, signifying that nanoparticles modified with A\u0026beta;11 and Tween 80 significantly augmented cellular uptake (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC, D).\u003c/p\u003e\n \u003cp\u003eIn this study, an \u003cem\u003ein vitro\u003c/em\u003e BBB model was developed to examine the transport capacity of free Tigecycline (TGC), CSs, A\u0026beta;11@CSs, and A\u0026beta;11/T80@CSs across the endothelial barrier monolayer. As illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE, F, free TGC exhibited the lowest permeability in monolayer bEnd.3 cells and the weakest ability to traverse the BBB. The CSs-TGC group showed limited BBB permeability within the initial four hours, with a gradual increase over the subsequent three hours. However, the dual-ligand A\u0026beta;11/T80@CSs displayed enhanced transport capacity in the \u003cem\u003ein vitro\u003c/em\u003e BBB model compared to untargeted CSs and single-ligand A\u0026beta;11@CSs, with transshipment progressively increasing over time. Investigating the distribution of formulations in a brain infection model provided insights into the nanoparticles\u0026apos; ability to penetrate the BBB post-infection onset. This approach enabled a more accurate and comprehensive assessment of nanoparticle penetration capabilities, as the model more closely reflected BBB properties. The results revealed that the fluorescence intensity of A\u0026beta;11/T80@CSs-DiD was 19 times that of free DiD and 8.6 times that of CSs-DiD (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG, H), a significant difference, indicating that the nano-delivery system possessed exceptional brain targeting capabilities.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003ePharmacokinetics and anti-infective efficacy of A\u0026beta;11/T80@CSs-TGC\u003c/h2\u003e\n \u003cp\u003eIn recent years, the prevalence of multidrug-resistant (MDR) \u003cem\u003eA. baumannii\u003c/em\u003e has increased. Currently, TGC and polymyxin drugs are among the few effective treatments against infections caused by MDR \u003cem\u003eA. baumannii\u003c/em\u003e. Nano-delivery systems have emerged as a promising strategy to overcome drug resistance by enhancing drug concentration, cellular uptake, and targeted delivery. These systems can bypass resistance mechanisms, deliver combination therapies, and enable programmable drug release, thereby enhancing the efficacy of therapeutic agents and contributing to improved treatment outcomes in resistance-prone conditions. We assessed the antimicrobial activity of A\u0026beta;11/T80@CSs-TGC against MDR \u003cem\u003eA. baumannii\u003c/em\u003e. \u003cem\u003eIn vitro\u003c/em\u003e antibacterial experiments demonstrated that neither PBS nor blank core-shell nanoparticles inhibited bacterial growth. Both free TGC and A\u0026beta;11/T80@CSs-TGC displayed potent antimicrobial activity with a minimum inhibitory concentration of 2 \u0026micro;g/mL (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA, B), indicating TGC\u0026rsquo;s effectiveness against MDR \u003cem\u003eA. baumannii\u003c/em\u003e. Cerebrospinal fluid (CSF) is a clear, colorless body fluid found in the brain and spinal cord. Bacteria predominantly reside in the CSF. To explore the \u003cem\u003ein vivo\u003c/em\u003e anti-infective efficacy of A\u0026beta;11/T80@CSs-TGC, intrathecal injections of various formulations were administered directly into the CSF, and the antibacterial efficacy of TGC was observed. As shown in \u003cstrong\u003eFig.\u0026nbsp;4C, D\u003c/strong\u003e, A\u0026beta;11/T80@CSs-TGC achieved an antibacterial rate of 90% in the CSF, indicating its potent anti-\u003cem\u003eA. baumannii\u003c/em\u003e activity both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e\n \u003cp\u003eAdditionally, the study quantified the blood drug concentration of TGC at various time points following intravenous administration of nanoparticles, with the related pharmacokinetic parameters presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Notably, the peak concentrations of CSs and A\u0026beta;11/T80@CSs were significantly higher than those of the free TGC group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eE). CSs-TGC and A\u0026beta;11/T80@CSs-TGC exhibited similar pharmacokinetic profiles. The area under the curve (AUC_0\u0026ndash;8 h) for A\u0026beta;11/T80@CSs-TGC was 21.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79 \u0026micro;g/mL*h, approximately 2.5 times that of free TGC. Furthermore, the clearance (CL) of TGC was significantly reduced in nanoparticle formulations compared to free TGC. The CL for CSs-TGC and A\u0026beta;11/T80@CSs-TGC decreased by factors of 2 and 2.76, respectively. These results suggest that nanoparticle usage could prolong the blood circulation time of TGC and enhance its bioavailability.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePharmacokinetic parameters after intravenous injection in rats.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePharmacokinetic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnit\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFree-TGC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCSs-TGC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eA\u0026beta;11/T80@CSs-TGC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCmax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.72\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTmax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAUC(0-t)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026micro;g/mL*h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMRT(0-t)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emL/h/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1199.97\u0026thinsp;\u0026plusmn;\u0026thinsp;248.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e590.64\u0026thinsp;\u0026plusmn;\u0026thinsp;33.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e433.43\u0026thinsp;\u0026plusmn;\u0026thinsp;20.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote: (𝑥̅ \u0026plusmn; SD, n\u0026thinsp;=\u0026thinsp;3, compared with Free-TGC, \u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u003c0.5, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u003c0.01, \u003csup\u003e***\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u003c0.001)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eEncouraged by these findings, we proceeded to intravenously administer physiological saline, free TGC, CSs-TGC, and A\u0026beta;11/T80@CSs-TGC to rats. The results revealed that A\u0026beta;11/T80@CSs-TGC significantly inhibited the growth of multidrug-resistant (MDR) \u003cem\u003eA. baumannii\u003c/em\u003e in the cerebrospinal fluid (CSF). The colony counts in the A\u0026beta;11/T80@CSs-TGC group were markedly lower than those in the other groups (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eF-H). These outcomes suggested that the ligand-modified nanoparticles enhanced the distribution characteristics of TGC, facilitating its penetration through the blood-brain barrier (BBB) and thereby exerting effective antibacterial effects.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003eBiosafety assessment of A\u0026beta;11/T80@CSs\u003c/h2\u003e\n \u003cp\u003eThe biosafety of A\u0026beta;11/T80@CSs was assessed through the evaluation of blood biochemical indices and histopathological examination using hematoxylin and eosin (H\u0026amp;E) staining. As depicted in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA, the hemolysis rates for both nano-formulations and the free TGC group were under 5%, relative to the positive control. This finding indicates that the A\u0026beta;11/T80@CSs formulation is biocompatible, exhibiting negligible hemolytic activity on erythrocytes. Additionally, the cytotoxic effects of TGC, CSs-TGC, and A\u0026beta;11/T80@CSs-TGC on bEnd.3 cells were quantified utilizing the MTT assay. Notably, cell survival rates exceeded 80% across a range of TGC concentrations (Figs. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eB-D). However, a decline in cell viability was observed at elevated TGC concentrations within the formulation groups, although the variance remained minimal. Furthermore, histological analysis of the heart, liver, spleen, lungs, and kidneys, stained with H\u0026amp;E, revealed no significant pathological alterations in the TGC, CSs-TGC, and A\u0026beta;11/T80@CSs-TGC groups in comparison to the normal control group (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eE). These findings corroborate the hypothesis of the enhanced biosafety profile of A\u0026beta;11/T80@CSs-TGC both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. Consequently, these results advocate for the potential of A\u0026beta;11/T80@CSs as a clinically viable nanocarrier system for targeted brain delivery of TGC, offering therapeutic avenues for treating intracranial infections.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn summary, we successfully synthesized core-shell nanoparticles, modified with Aβ11 and Tween 80, for the delivery of Tigecycline (TGC) aimed at treating intracranial infections caused by multi-drug resistant (MDR) \u003cem\u003eA. baumannii\u003c/em\u003e. The Aβ11/T80@CSs nanoparticles demonstrated an effective encapsulation of the water-soluble anti-infection drug TGC \u003cem\u003ein vitro\u003c/em\u003e, and exhibited significant activity against MDR \u003cem\u003eA. baumannii\u003c/em\u003e. Crucially, the Aβ11/T80@CSs-TGC formulation effectively inhibited the growth of MDR \u003cem\u003eA. baumannii\u003c/em\u003e in cerebrospinal fluid (CSF). Consistently, these findings suggest that the Aβ11/T80@CSs nano-delivery system has considerable potential to enhance the efficacy and safety of treatments for brain diseases (as depicted in \u003cb\u003eabstract graphic\u003c/b\u003e). However, further research is imperative to evaluate the clinical applicability of this nano-delivery system and to explore its potential in the treatment of various brain disorders.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments in this study were approved by the Animal Ethics Committee of West China Hospital of Sichuan University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the listed authors have read the manuscript and approved to submission. The manuscript is original, has not been previously published and has not been submitted for publication elsewhere while under consideration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no financial conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by\u0026nbsp;West China Nursing Discipline Development Special Fund Project, Sichuan University (No. HXHL20007), Open Research fund of State Key Laboratory of Drug Delivery and Pharmacokinetics, Tianjin Institute of Pharmaceutical Research (No. 010162002), the National Natural Science Foundation of China (No. 82300113), China Postdoctoral Science Foundation (No.2022M722269), Sichuan University Postdoctoral Interdisciplinary Innovation Fund (No. JCXK2204), Post Doctor Research Project, West China Hospital, Sichuan University (No. 2023HXBH015).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Critical Care Medicine, Department of Clinical Pharmacy, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy and Cancer Center, West China School of Nursing, West China Hospital, Sichuan University, Chengdu, China.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eState Key Laboratory of Drug Delivery and Pharmacokinetics, Tianjin Institute of Pharmaceutical Research, Tianjin 300301, People\u0026rsquo;s Republic of China.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e School of Pharmacy, Faculty of Medicine, Macau University of Science and Technology, Macau, China.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Shihezi University, Xinjiang, China.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e#\u003c/sup\u003e L.X, S.Q, H.L and M.G contributed equally to this study.\u003c/p\u003e\n\u003cp\u003e*Corresponding author Email: [email protected] (Xiangrong Song), [email protected] (Yongmei Xie), [email protected] (Yan Kang).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX. Lan, S. Qin, H. Liu and X. Song designed the research. X. Lan, S. Qin, H. Liu and M. Guo carried out the experiments and performed data analysis. Y. Zhang, X. Jin, X. Duan, M. Sun, Z. Liu, W. Wang, Q. Zheng, X. Liao, J Chen, Y. Kang, Y. Xie participated part of the experiments and provided experimental drugs and quality control. X. Lan, S. Qin, H. Liu, and X. Song wrote the manuscript. Y. Kang, Y. Xie and X. Song revised the manuscript. All of the authors have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHarding, C. M.; Hennon, S. W.; Feldman, M. F. \u003cem\u003eNature reviews. Microbiology \u003c/em\u003e\u003cstrong\u003e2018,\u003c/strong\u003e 16, (2), 91-102.\u003c/li\u003e\n\u003cli\u003eTsitsopoulos, P. P.; Iosifidis, E.; Antachopoulos, C.; Anestis, D. M.; Karantani, E.; Karyoti, A.; Papaevangelou, G.; Kyriazidis, E.; Roilides, E.; Tsonidis, C. \u003cem\u003eActa Neurochir (Wien) \u003c/em\u003e\u003cstrong\u003e2016,\u003c/strong\u003e 158, (9), 1647-54.\u003c/li\u003e\n\u003cli\u003eKurdyumova, N. V.; Danilov, G. V.; Ershova, O. N.; Savin, I. A.; Sokolova, E. Y.; Aleksandrova, I. A.; Shifrin, M. A. \u003cem\u003eZh Vopr Neirokhir Im N N Burdenko \u003c/em\u003e\u003cstrong\u003e2015,\u003c/strong\u003e 79, (3), 55-59.\u003c/li\u003e\n\u003cli\u003eAntunes, L. C.; Visca, P.; Towner, K. J. \u003cem\u003ePathog Dis \u003c/em\u003e\u003cstrong\u003e2014,\u003c/strong\u003e 71, (3), 292-301.\u003c/li\u003e\n\u003cli\u003eGiammanco, A.; Cal\u0026agrave;, C.; Fasciana, T.; Dowzicky, M. J. \u003cem\u003emSphere \u003c/em\u003e\u003cstrong\u003e2017,\u003c/strong\u003e 2, (1).\u003c/li\u003e\n\u003cli\u003eJarvis, J. N.; Lawrence, D. S.; Meya, D. B.; Kagimu, E.; Kasibante, J.; Mpoza, E.; Rutakingirwa, M. K.; Ssebambulidde, K.; Tugume, L.; Rhein, J.; Boulware, D. R.; Mwandumba, H. C.; Moyo, M.; Mzinganjira, H.; Kanyama, C.; Hosseinipour, M. C.; Chawinga, C.; Meintjes, G.; Schutz, C.; Comins, K.; Singh, A.; Muzoora, C.; Jjunju, S.; Nuwagira, E.; Mosepele, M.; Leeme, T.; Siamisang, K.; Ndhlovu, C. E.; Hlupeni, A.; Mutata, C.; van Widenfelt, E.; Chen, T.; Wang, D.; Hope, W.; Boyer-Chammard, T.; Loyse, A.; Molloy, S. F.; Youssouf, N.; Lortholary, O.; Lalloo, D. G.; Jaffar, S.; Harrison, T. S. \u003cem\u003eN Engl J Med \u003c/em\u003e\u003cstrong\u003e2022,\u003c/strong\u003e 386, (12), 1109-1120.\u003c/li\u003e\n\u003cli\u003eDoi, Y. \u003cem\u003eClin Infect Dis \u003c/em\u003e\u003cstrong\u003e2019,\u003c/strong\u003e 69, (Suppl 7), S565-s575.\u003c/li\u003e\n\u003cli\u003eJo, J.; Ko, K. S. \u003cem\u003eMicrobiol Spectr \u003c/em\u003e\u003cstrong\u003e2021,\u003c/strong\u003e 9, (2), e0101021.\u003c/li\u003e\n\u003cli\u003eFrampton, J. E.; Curran, M. P. \u003cem\u003eDrugs \u003c/em\u003e\u003cstrong\u003e2005,\u003c/strong\u003e 65, (18), 2623-35; discussion 2636-7.\u003c/li\u003e\n\u003cli\u003ePankey, G. A. \u003cem\u003eJ Antimicrob Chemother \u003c/em\u003e\u003cstrong\u003e2005,\u003c/strong\u003e 56, (3), 470-80.\u003c/li\u003e\n\u003cli\u003eFang, L. X.; Chen, C.; Cui, C. Y.; Li, X. P.; Zhang, Y.; Liao, X. P.; Sun, J.; Liu, Y. H. \u003cem\u003eBioessays \u003c/em\u003e\u003cstrong\u003e2020,\u003c/strong\u003e 42, (8), e2000014.\u003c/li\u003e\n\u003cli\u003eCai, Y.; Bai, N.; Liu, X.; Liang, B.; Wang, J.; Wang, R. \u003cem\u003eInfect Dis (Lond) \u003c/em\u003e\u003cstrong\u003e2016,\u003c/strong\u003e 48, (7), 491-502.\u003c/li\u003e\n\u003cli\u003eKaewpoowat, Q.; Ostrosky-Zeichner, L. \u003cem\u003eExpert Opin Drug Saf \u003c/em\u003e\u003cstrong\u003e2015,\u003c/strong\u003e 14, (2), 335-42.\u003c/li\u003e\n\u003cli\u003eEichler, A. F.; Chung, E.; Kodack, D. P.; Loeffler, J. S.; Fukumura, D.; Jain, R. K. \u003cem\u003eNat Rev Clin Oncol \u003c/em\u003e\u003cstrong\u003e2011,\u003c/strong\u003e 8, (6), 344-56.\u003c/li\u003e\n\u003cli\u003eShao, K.; Zhang, Y.; Ding, N.; Huang, S.; Wu, J.; Li, J.; Yang, C.; Leng, Q.; Ye, L.; Lou, J.; Zhu, L.; Jiang, C. \u003cem\u003eAdv Healthc Mater \u003c/em\u003e\u003cstrong\u003e2015,\u003c/strong\u003e 4, (2), 291-300.\u003c/li\u003e\n\u003cli\u003eHong, W.; Zhang, Z.; Liu, L.; Zhao, Y.; Zhang, D.; Liu, M. \u003cem\u003eDrug Deliv \u003c/em\u003e\u003cstrong\u003e2018,\u003c/strong\u003e 25, (1), 1886-1897.\u003c/li\u003e\n\u003cli\u003eZhuo, Y.; Zhang, Y.; Wang, B.; Cheng, S.; Yuan, R.; Liu, S.; Zhao, M.; Xu, B.; Zhang, Y.; Wang, X. \u003cem\u003eApplied Materials Today \u003c/em\u003e\u003cstrong\u003e2022,\u003c/strong\u003e 27, 101453.\u003c/li\u003e\n\u003cli\u003eCramer, P. E.; Cirrito, J. R.; Wesson, D. W.; Lee, C. Y.; Karlo, J. C.; Zinn, A. E.; Casali, B. T.; Restivo, J. L.; Goebel, W. D.; James, M. J.; Brunden, K. R.; Wilson, D. A.; Landreth, G. E. \u003cem\u003eScience \u003c/em\u003e\u003cstrong\u003e2012,\u003c/strong\u003e 335, (6075), 1503-6.\u003c/li\u003e\n\u003cli\u003eMerino-Zamorano, C.; Fern\u0026aacute;ndez-de Retana, S.; Monta\u0026ntilde;ola, A.; Batlle, A.; Saint-Pol, J.; Mysiorek, C.; Gosselet, F.; Montaner, J.; Hern\u0026aacute;ndez-Guillamon, M. \u003cem\u003eJ Alzheimers Dis \u003c/em\u003e\u003cstrong\u003e2016,\u003c/strong\u003e 53, (2), 677-91.\u003c/li\u003e\n\u003cli\u003eWang, Y.; Qin, X.; Paudel, H. K. \u003cem\u003eNeurobiol Dis \u003c/em\u003e\u003cstrong\u003e2017,\u003c/strong\u003e 103, 78-88.\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Ezio, V.; Colasanti, M.; Persichini, T. \u003cem\u003eAntioxidants (Basel) \u003c/em\u003e\u003cstrong\u003e2021,\u003c/strong\u003e 10, (11).\u003c/li\u003e\n\u003cli\u003eVaradarajan, S.; Kanski, J.; Aksenova, M.; Lauderback, C.; Butterfield, D. A. \u003cem\u003eJ Am Chem Soc \u003c/em\u003e\u003cstrong\u003e2001,\u003c/strong\u003e 123, (24), 5625-31.\u003c/li\u003e\n\u003cli\u003eZhang, Z.; Guan, J.; Jiang, Z.; Yang, Y.; Liu, J.; Hua, W.; Mao, Y.; Li, C.; Lu, W.; Qian, J.; Zhan, C. \u003cem\u003eNat Commun \u003c/em\u003e\u003cstrong\u003e2019,\u003c/strong\u003e 10, (1), 3561.\u003c/li\u003e\n\u003cli\u003eJoseph, A.; Simo, G. M.; Gao, T.; Alhindi, N.; Xu, N.; Graham, D. J.; Gamble, L. J.; Nance, E. \u003cem\u003eBiomaterials \u003c/em\u003e\u003cstrong\u003e2021,\u003c/strong\u003e 277, 121086.\u003c/li\u003e\n\u003cli\u003ePandey, V.; Haider, T.; Chandak, A. R.; Chakraborty, A.; Banerjee, S.; Soni, V. \u003cem\u003eInt J Biol Macromol \u003c/em\u003e\u003cstrong\u003e2020,\u003c/strong\u003e 164, 2018-2027.\u003c/li\u003e\n\u003cli\u003eDas, D.; Lin, S. \u003cem\u003eJ Pharm Sci \u003c/em\u003e\u003cstrong\u003e2005,\u003c/strong\u003e 94, (6), 1343-53.\u003c/li\u003e\n\u003cli\u003eLeyva-G\u0026oacute;mez, G.; Cort\u0026eacute;s, H.; Maga\u0026ntilde;a, J. J.; Leyva-Garc\u0026iacute;a, N.; Quintanar-Guerrero, D.; Flor\u0026aacute;n, B. \u003cem\u003eDrug Discov Today \u003c/em\u003e\u003cstrong\u003e2015,\u003c/strong\u003e 20, (7), 824-37.\u003c/li\u003e\n\u003cli\u003eKenry; Yeo, T.; Manghnani, P. N.; Middha, E.; Pan, Y.; Chen, H.; Lim, C. T.; Liu, B. \u003cem\u003eACS Nano \u003c/em\u003e\u003cstrong\u003e2020,\u003c/strong\u003e 14, (4), 4509-4522.\u003c/li\u003e\n\u003cli\u003eWagner, S.; Zensi, A.; Wien, S. L.; Tschickardt, S. E.; Maier, W.; Vogel, T.; Worek, F.; Pietrzik, C. U.; Kreuter, J.; von Briesen, H. \u003cem\u003ePLoS One \u003c/em\u003e\u003cstrong\u003e2012,\u003c/strong\u003e 7, (3), e32568.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-nanobiotechnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jnan","sideBox":"Learn more about [Journal of Nanobiotechnology](http://jnanobiotechnology.biomedcentral.com)","snPcode":"12951","submissionUrl":"https://submission.nature.com/new-submission/12951/3","title":"Journal of Nanobiotechnology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"nanoparticles, blood-brain barrier, multidrug-resistant Acinetobacter baumannii, Tigecycline, intracranial infection","lastPublishedDoi":"10.21203/rs.3.rs-3807612/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3807612/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMultidrug-resistant (MDR) Acinetobacter baumannii (\u003cem\u003eA. baumannii\u003c/em\u003e) is a formidable pathogen responsible for severe intracranial infections post-craniotomy, exhibiting a mortality rate as high as 71%. Tigecycline (TGC), a broad-spectrum antibiotic, emerged as a potential therapeutic agent for MDR \u003cem\u003eA. baumannii\u003c/em\u003einfections. Nonetheless, its clinical application was hindered by a short \u003cem\u003ein vivo\u003c/em\u003e half-life and limited permeability through the blood-brain barrier (BBB). In this study, we developed a novel nanocarrier, integrating a dual-targeting peptide Aβ11 and Tween 80 modification (Aβ11/T80@CSs), specifically designed to enhance TGC delivery to the brain for treating \u003cem\u003eA. baumannii\u003c/em\u003e-induced intracranial infections. Our findings demonstrated that Aβ11/T80@CSs nanocarriers successfully traversed the BBB and effectively delivered TGC into the cerebrospinal fluid (CSF), leading to a significant therapeutic response in a model of MDR \u003cem\u003eA. baumannii \u003c/em\u003eintracranial infection. This study offers initial evidence and a platform for the application of brain-targeted nanocarrier delivery systems, showcasing their potential in administering water-soluble anti-infection drugs for intracranial infection treatments, and suggesting promising avenues for clinical translation.\u003c/p\u003e","manuscriptTitle":"Dual-targeting tigecycline nanoparticles for treating intracranial infections caused by multidrug-resistant Acinetobacter baumannii","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-08 17:54:00","doi":"10.21203/rs.3.rs-3807612/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-01-18T01:40:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-01-16T20:58:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"f288cbee-d04e-4eb5-8ac9-da9328f8932a","date":"2024-01-06T04:19:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-06T02:00:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-05T16:50:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-05T16:50:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Nanobiotechnology","date":"2023-12-26T10:27:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-nanobiotechnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jnan","sideBox":"Learn more about [Journal of Nanobiotechnology](http://jnanobiotechnology.biomedcentral.com)","snPcode":"12951","submissionUrl":"https://submission.nature.com/new-submission/12951/3","title":"Journal of Nanobiotechnology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"66898656-49e8-4c9f-aab8-6d3ce382db3e","owner":[],"postedDate":"January 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-01T15:10:43+00:00","versionOfRecord":{"articleIdentity":"rs-3807612","link":"https://doi.org/10.1186/s12951-024-02373-z","journal":{"identity":"journal-of-nanobiotechnology","isVorOnly":false,"title":"Journal of Nanobiotechnology"},"publishedOn":"2024-03-30 15:01:24","publishedOnDateReadable":"March 30th, 2024"},"versionCreatedAt":"2024-01-08 17:54:00","video":"","vorDoi":"10.1186/s12951-024-02373-z","vorDoiUrl":"https://doi.org/10.1186/s12951-024-02373-z","workflowStages":[]},"version":"v1","identity":"rs-3807612","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3807612","identity":"rs-3807612","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}