An Injectable,Bifunctional Hydrogel with Photothermal Effects for Tumor Therapy and Bone Regeneration

Significant attention has been focused on bone tumor therapy recently. At present, the treatment in clinic typically requires surgical intervention. However, a few tumor cells remain around bone defects after surgery and subsequently proliferate within several days. Thus, fabrication of biomaterials with dual functions of tumor therapy and bone regeneration is significant. Herein, the injectable hydrogel containing cisplatin (DDP) and polydopamine‐decorated nano‐hydroxyapatite is prepared via Schiff base reaction between the aldehyde groups on oxidized sodium alginate and amino groups on chitosan. The hydrogel exhibits sustained release properties for DDP due to the immobilization of DDP via abundant functional groups on polydopamine (PDA). Additionally, given the intense absorption of PDA in the near‐infrared region, the hydrogel exhibits excellent photothermal effects when exposed to the NIR laser (808 nm). Based on the properties, the hydrogel effectively ablates tumor cells (4T1 cells) in vitro and suppresses tumor growth in vivo. Furthermore, the hydrogel promotes the adhesion and proliferation of bone mesenchymal stem cells in vitro due to the abundant functional groups on PDA and further induces bone regeneration in vivo. Therefore, the study extends research on novel biomaterials with dual functions of tumor therapy and bone regeneration.     

Sliding mode control for a diffuse interface tumor growth model coupling a Cahn–Hilliard equation with a reaction–diffusion equation

We consider the sliding mode control (SMC) problem for a diffuse interface tumor growth model coupling a Cahn–Hilliard equation with a reaction–diffusion equation perturbed by a maximal monotone nonlinearity. We prove existence and regularity of strong solutions and, under further assumptions, a uniqueness result. Then, we show that the chosen SMC law forces the system to reach within finite time a sliding manifold that we chose in order that the tumor phase remains constant in time.     

Artificial nano‐pin as a temporal molecular glue for the targeting of acidic tumor cells

Highly precise control of molecular structure for developing efficient anticancer drug delivery is challenging. Our method reported herein can satisfy the need for building novel hybrid molecule; this molecule serves as a built‐in transformer that changes its molecular configuration from a pin‐shaped arrangement to a dog bone‐shaped arrangement. This approach led to a significant increase in the efficiency of tumor inhibition. Copyright © 2014 John Wiley & Sons, Ltd.     

Thermo‐triggered Release of CRISPR‐Cas9 System by Lipid‐Encapsulated Gold Nanoparticles for Tumor Therapy

CRISPR/Cas9 system is a powerful toolbox for gene editing. However, the low delivery efficiency is still a big hurdle impeding its applications. Herein, we report a strategy to deliver Cas9‐sgPlk‐1 plasmids (CP) by a multifunctional vehicle for tumor therapy. We condensed CPs on TAT peptide‐modified Au nanoparticles (AuNPs/CP, ACP) via electrostatic interactions, and coated lipids (DOTAP, DOPE, cholesterol, PEG2000‐DSPE) on the ACP to form lipid‐encapsulated, AuNPs‐condensed CP (LACP). LACP can enter tumor cells and release CP into the cytosol by laser‐triggered thermo‐effects of the AuNPs; the CP can enter nuclei by TAT guidance, enabling effective knock‐outs of target gene (Plk‐1) of tumor (melanoma) and inhibition of the tumor both in vitro and in vivo. This AuNPs‐condensed, lipid‐encapsulated, and laser‐controlled delivery system provides a versatile method for high efficiency CRISPR/Cas9 delivery and targeted gene editing for treatment of a wide spectrum of diseases.     

Microfluidic Screening of Circulating Tumor Biomarkers toward Liquid Biopsy

The development of early and personalized diagnostic protocol with rapid response and high accuracy is considered the most promising avenue to advance point-of-care testing for tumor diagnosis and therapy. Given the growing awareness of the limitations of conventional tissue biopsy for gathering tumor information, considerable interest has recently been aroused in liquid biopsy. Among a myriad of analytical approaches proposed for liquid biopsy, microfluidics-based separation and purification techniques possess merits of high throughput, low samples consumption, high flexibility, low cost, high sensitivity, automation capability and enhanced spatio-temporal control. These characteristics endow microfluidics to serve as an emerging and promising tool in tumor diagnosis and prognosis by identifying specific circulating tumor biomarkers. In this review, we will put our focus on three key categories of circulating tumor biomarkers, namely, circulating tumor cells (CTCs), circulating exosomes, and circulating nucleic acids (cNAs), and discuss the significant roles of microfluidics in the separation and analysis of circulating tumor biomarkers. Recent advances in microfluidic separation and analysis of CTCs, exosomes, and cNAs will be highlighted and tabulated. Finally, the current challenges and future niches of using microfluidic techniques in the separation and analysis of circulating tumor biomarkers will be discussed.     

Assessing and improving the stability of chemometric models in small sample size situations

Small sample sizes are very common in multivariate analysis. Sample sizes of 10–100 statistically independent objects (rejects from processes or loading dock analysis, or patients with a rare disease), each with hundreds of data points, cause unstable models with poor predictive quality. Model stability is assessed by comparing models that were built using slightly varying training data. Iterated k-fold cross-validation is used for this purpose. Aggregation stabilizes models. It is possible to assess the quality of the aggregated model without calculating further models. The validation and aggregation methods investigated in this study apply to regression as well as to classification. These techniques are useful for analyzing data with large numbers of variates, e.g., any spectral data like FT-IR, Raman, UV/VIS, fluorescence, AAS, and MS. FT-IR images of tumor tissue were used in this study. Some tissue types occur frequently, while some are very rare. They are classified using LDA. Initial models were severely unstable. Aggregation stabilizes the predictions. The hit rate increased from 67% to 82%.