In Vivo Biodistribution of Mixed Shell Micelles with Tunable Hydrophilic/Hydrophobic Surface

The miserable targeting performance of nanocarriers for cancer therapy arises largely from the rapid clearance from blood circulation and the major accumulation in the organs of the reticuloendothelial system (RES), leading to inefficient enhanced permeability and retention (EPR) effect after intravenous injection (i.v.). Herein, we reported an efficient method to prolong the blood circulation of nanoparticles and decrease their deposition in liver and spleen. In this work, we fabricated a series of mixed shell micelles (MSMs) with approximately the same size, charge and core composition but with varied hydrophilic/hydrophobic ratios in the shell through spontaneously self-assembly of block copolymers poly­(ethylene glycol)-<i>block</i>-poly­(l-lysine) (PEG-<i>b</i>-PLys) and poly­(<i>N</i>-isopropylacrylamide)-<i>block</i>-poly­(aspartic acid) (PNIPAM-<i>b</i>-PAsp) in aqueous medium. The effect of the surface heterogeneity on the in vivo biodistribution was systematically investigated through in vivo tracking of the ¹²⁵I-labeled MSMs determined by Gamma counter. Compared with single PEGylated micelles, some MSMs were proved to be significantly efficient with more than 3 times lower accumulation in liver and spleen and about 6 times higher concentration in blood at 1 h after i.v.. The results provide us a novel strategy for future development of long-circulating nanocarriers for efficient cancer therapy

Self-Regulated Multifunctional Collaboration of Targeted Nanocarriers for Enhanced Tumor Therapy

Exploring ideal nanocarriers for drug delivery systems has encountered unavoidable hurdles, especially the conflict between enhanced cellular uptake and prolonged blood circulation, which have determined the final efficacy of cancer therapy. Here, based on controlled self-assembly, surface structure variation in response to external environment was constructed toward overcoming the conflict. A novel micelle with mixed shell of hydrophilic poly­(ethylene glycol) PEG and pH responsive hydrophobic poly­(β-amino ester) (PAE) was designed through the self-assembly of diblock amphiphilic copolymers. To avoid the accelerated clearance from blood circulation caused by the surface exposed targeting group c­(RGDfK), here c­(RGDfK) was conjugated to the hydrophobic PAE and hidden in the shell of PEG at pH 7.4. At tumor pH, charge conversion occurred, and c­(RGDfK) stretched out of the shell, leading to facilitated cellular internalization according to the HepG2 cell uptake experiments. Meanwhile, the heterogeneous surface structure endowed the micelle with prolonged blood circulation. With the self-regulated multifunctional collaborated properties of enhanced cellular uptake and prolonged blood circulation, successful inhibition of tumor growth was achieved from the demonstration in a tumor-bearing mice model. This novel nanocarrier could be a promising candidate in future clinical experiments

Tuning the Proximity Effect through Interface Engineering in a Pb/Graphene/Pt Trilayer System

The fate of superconductivity of a nanoscale superconducting film/island relies on the environment; for example, the proximity effect from the substrate plays a crucial role when the film thicknesses is much less than the coherent length. Here, we demonstrate that atomic-scale tuning of the proximity effects can be achieved by one atomically thin graphene layer inserted between the nanoscale Pb islands and the supporting Pt(111) substrate. By using scanning tunneling microscopy and spectroscopy, we show that the coupling between the electron in a normal metal and the Cooper pair in an adjacent superconductor is dampened by 1 order of magnitude <i>via</i> transmission through a single-atom-thick graphene. More interestingly, the superconductivity of the Pb islands is greatly affected by the moiré patterns of graphene, showing the intriguing influence of the graphene–substrate coupling on the superconducting properties of the overlayer

Clinical and disease characteristics of patients with EGFR gene TKI-sensitive mutations and patients with a wild-type EGFR gene in the training group.

<p>Clinical and disease characteristics of patients with EGFR gene TKI-sensitive mutations and patients with a wild-type EGFR gene in the training group.</p

ClinProTools image showing the average intensity, in arbitrary units, of five peptides composing the classifier in patients with <i>EGFR</i> gene TKI-sensitive mutations and wild-type <i>EGFR</i> genes.

<p>ClinProTools image showing the average intensity, in arbitrary units, of five peptides composing the classifier in patients with <i>EGFR</i> gene TKI-sensitive mutations and wild-type <i>EGFR</i> genes.</p

Clinical and disease characteristics of patients enrolled in the analysis of EGFR-TKI therapeutic effects in the validation group.

<p>Clinical and disease characteristics of patients enrolled in the analysis of EGFR-TKI therapeutic effects in the validation group.</p

2D peak distribution of peptides with m/z 4092.4 (x-axis) and 4585.05 (y-axis) between patients with <i>EGFR</i> gene TKI-sensitive mutations (green circles) and patients with wild-type <i>EGFR</i> genes (red crosses).

<p>The discriminating features of the two selected peptides were generated by ClinProTools bioinformatics software. The values represent the peptide abundance ratio, and these values were significantly different between patients with <i>EGFR</i> gene TKI-sensitive mutations and patients with wild-type <i>EGFR</i> genes. The ellipses represent the standard deviation of the class average of the peak areas/intensities.</p

Methods used in selected previous reports to detect <i>EGFR</i> gene mutations in plasma and serum samples of lung cancer patients.

<p>n.a.: Sensitivity and specificity are not available because of a lack of correlation with the primary matched tumors.</p><p>^a: Before/after treatment.</p><p>Methods used in selected previous reports to detect <i>EGFR</i> gene mutations in plasma and serum samples of lung cancer patients.</p

Kaplan-Meier plots of PFS (A) and OS (B) for 81 patients treated with EGFR-TKIs in the validation group.

<p>(A) PFS between patients whose matched samples were labeled as “mutant” (n = 47) and patients whose matched samples were labeled as “wild” (n = 34). (B) OS between patients whose matched samples were labeled as “mutant” (n = 47) and “wild” (n = 34).</p

Clinical and disease characteristics of all patients.

<p>ADC = adenocarcinoma; SCC = squamous cell carcinoma; TKI = tyrosine kinase inhibitor; EGFR = epidermal growth factor receptor; ARMS = amplification refractory mutation system; <i>E19del</i> = <i>exon 19</i> deletion; <i>L858R</i> = <i>exon 21 (L858R)</i> mutation; <i>G719X</i> = <i>exon 18 (G719X)</i> mutation.</p><p>Clinical and disease characteristics of all patients.</p